Proceedings of the 3rd European Conference on Intellectual Capital

<strong>Proceedings</strong>
<strong>of</strong> <strong>the</strong>
<strong>3rd</strong> <strong>European</strong> <strong>Conference</strong>
on Intellectual Capital
University <strong>of</strong> Nicosia,
Cyprus
18-19 April 2011
Edited by
Ge<strong>of</strong>f Turner and Clemente Minnone

Copyright The Authors, 2011. All Rights Reserved.
No reproduction, copy or transmission may be made without written permission from <strong>the</strong> individual authors.
Papers have been double-blind peer reviewed before final submission to <strong>the</strong> conference. Initially, paper
abstracts were read and selected by <strong>the</strong> conference panel for submission as possible papers for <strong>the</strong>
conference.
Many thanks to <strong>the</strong> reviewers who helped ensure <strong>the</strong> quality <strong>of</strong> <strong>the</strong> full papers.
These <strong>Conference</strong> <strong>Proceedings</strong> have been submitted to Thomson ISI for indexing.
Fur<strong>the</strong>r copies <strong>of</strong> this book and previous year’s proceedings can be purchased from http://academicconferences.org/2-proceedings.htm
ISBN:97-1-906638-95-5 CD
Published by Academic Publishing International Limited
Reading
UK
44-118-972-4148
www.academic-publishing.org

Contents
Paper Title Author(s) Page
No.
Preface vi
Biographies <strong>of</strong> <strong>Conference</strong> Chairs, Programme Chair,
Keynote Speaker and Mini-track Chairs
Biographies <strong>of</strong> contributing authors viii
Keynote Presentations 1
Social Knowledge: Are You Ready? John Girard 3
Intellectual Capital Accounting – how to measure <strong>the</strong>
unmeasurable
Ludo Pyis
Academic Research Papers 15
Social Capital Management in Iranian Knowledge-Based
SMEs
Khodayar Abili and Mahyar Abili
Knowledge Transfer in Romanian Universities Simona Agoston, Ivona Orzea, Alina
Mihaela Dima and Simona Vasilache
A Modeling Approach to Intellectual Capital
Advancement
Transformational Leadership in Mergers and Acquisition
Transactions in Emerging Markets. A Case Study <strong>of</strong> <strong>the</strong>
Bere Mures Acquisition by Heineken Romania
Added Value to Organizational Knowledge by Managing
<strong>European</strong> Projects
Developing and Implementing Strategies to Enhance
Intellectual Capital in <strong>the</strong> Online Learning Environment
Intellectual Capital Dynamics within <strong>the</strong> Learning
Organization
Education and Training Practice Strategies in Small and
Medium Sized Enterprises
Relation Between Organizational Learning and
Organizational Commitment: Case Study <strong>of</strong> a Private
Bank in North Cyprus
Knowledge Dynamics Modeling Using Analytic Hierarchy
Process (AHP)
Eckhard Ammann
Sorin Anagnoste and Gabriela Dumitru
Gabriela Atanasiu and Florin Leon
Bob Barrett
Ruxandra Bejinaru and Stefan Iordache
Andrea Bencsik, Vendel Lőre and Andrea
Sólyom
Ayşen Berberoğlu and Emine Ünar
Constantin Bratianu, Adriana Agapie, and
Ivona Orzea
Knowledge Sharing Through Communities <strong>of</strong> Practice Sheryl Buckley and Apostolos
Giannakopoulos
The Mediating Effects <strong>of</strong> Sensemaking and
Measurement on <strong>the</strong> Intellectual Capital and
Performance Linkage
Is “If it Can’t be Measured it Can’t be Managed” Really
True?
Knowledge Utilization <strong>of</strong> Women as Intellectual Capital
in Iranian Research Institutes (a Multiple-Case Study)
Earnings Quality and O<strong>the</strong>r Factors Affecting Intellectual
Capital Performance in Banks: The UAE Case
i
Donley Carrington and Mike Tayles
John Dumay and Jim Rooney
Marziye Ehrami, Khodayar Abili,
Mohamad Daneshgar and Mehdi
Narimani
Magdi El-Bannany
College <strong>of</strong> Business
vii
13
17
24
32
41
53
62
70
78
87
94
103
113
123
131
136

Paper Title Author(s) Page
No.
The Relationship Between Intellectual Capital and
Process and Product Innovation in Banks: An
Exploratory Study
The Strategies and Tactics <strong>of</strong> Patent Management and
Their Importance for Competitive Advantage
Intangible Assets and Value Creation <strong>of</strong> a Company:
Russian and UK Evidence
Impact <strong>of</strong> Investment in Human Capital on <strong>the</strong> Business
Value
The Relationship between Gross Domestic Product
(GDP) and Hidden Wealth during <strong>the</strong> years 2000- 2009:
An International Study
Academic Satisfaction as an Amplifier <strong>of</strong> <strong>the</strong>
Organizational Intellectual Capital
Ahmed Elsetouhi and Ibrahim Elbeltagi
Albrecht Fritzsche and Rebecca Geiger
Tatiana Garanina and Yana Pavlova
Lidia García-Zambrano, Arturo
Rodríguez-Castellanos and José
Domingo García-Merino
Intellectual Capital and Corporate Performance Agnes Maciocha
The Influence <strong>of</strong> Human Capital in Achieving Corporate
Performance
Eliciting Tacit Knowledge From a Domain <strong>of</strong> Physical
Skill
Innovation Strategy and Management Control: The Link
Between Knowledge Management and Management
Control Systems
Intellectual Capital Management: Case Study Portugal
Versus Romania
Víctor Raúl López Ruiz, José Luis Alfaro
Navarro and Domingo Nevado Peña
Maria de Lourdes Machado and Odília
Gouveia
Anca Mândruleanu
Peter Marshall and Damian Gordon
Maurizio Massaro, Roland Bardy and
Filippo Zanin
Florinda Matos, Albino Lopes, Marta-
Christina Suciu and Alex Ghitiu
Intellectual Capital Management and Food Control Florinda Matos, Susana Rodrigues, Albino
Lopes, Rui Coutinho and Nuno Matos
Knowledge Management for Knowledge Workers Ludmila Mládková
Applying <strong>the</strong> VAIC Model to Russian Industrial
Enterprises
Perspectives on <strong>the</strong> Possibilities Companies Have to
Recognise and Measure Intellectual Capital
The Structural Model <strong>of</strong> Intellectual Capital in Higher
Education Institutions
Maria Molodchik and Anna Bykova
Maria Cristina Morariu
Fattah Nazem
Knowledge Dynamics in a Chaotic Environment Andrei Stefan Nestian
Increasing Knowledge Management Maturity in
Organisations: A Capabilities - Driven Model
Strategic Innovation and Knowledge Management: The
Logic <strong>of</strong> Creativity and Development Institutionalization,
Framing and Diffusion
The Quality <strong>of</strong> Knowledge Flows and its Impact on <strong>the</strong>
Intellectual Capital Development <strong>of</strong> a University
ii
Theodora Ngosi, Markus Helfert and
Ashley Braganza
Bongani Ngwenya
Corina Pelau, Irina Bena, Anca Daniela
Vladoi, Dan Cristian Dabija and Monica
Fufezan
147
157
165
176
187
199
206
216
222
231
240
251
260
268
278
286
295
302
313
322

Paper Title Author(s) Page
No.
Hierarchy and Tacit Knowledge in <strong>the</strong> Swedish Armed
Forces: An Organisational Approach
An Alternative to <strong>the</strong> Crystal Ball: Participatory
Approaches for Sustainable Management
Human Capital and Relational Capital Dynamics Within
a University
Ulrica Pettersson and James Nyce
Katja Pook and Campbell Warden
Nicolae Al. Pop, Adrian Tantau, Corina
Pelau and Irina Bena
Knowledge Cities: A Portuguese Case Katia Rodrigues and Eduardo Tomé 350
Governance <strong>of</strong> Networks <strong>of</strong> Small Enterprises: A
Knowledge Perspective - Some Case Studies in <strong>the</strong>
Mechanical Industry in Italy
Organizational Development Activities and Social Capital
Accumulation: Exploring Relationships in Canadian
Healthcare Organizations
Anna Romiti and Daria Sarti
Kent Rondeau and Terry Wagar
Intellectual Capital and a Firm‘s Innovativeness Helena Santos-Rodrigues, Pedro
Figueroa Dorrego and Carlos Maria
Jardon
Factors Influencing <strong>the</strong> Acquiring <strong>of</strong> Technological
Knowledge Among Technology Transfer Recipients – a
Perspective From a Radar Manufacturing Firm
Enhancing IC Formation by Evoking Hidden Potentials –
<strong>the</strong> Case <strong>of</strong> Smart Textiles
In Search <strong>of</strong> key Factors for Ideal Research and
Education Projects
Thanaletchumi Sathasivam, Zuraini Ismail
and Ahmad Rahman Songip
Klaus Bruno Schebesch
Karen Smits, Ilse van den Donker and
Josephine Lappia
Intellectual Capital and <strong>the</strong> Romanian Education System Marta-Christina Suciu, Luciana Picioruş,
Cosmin Imbrişcă, Alexandru Ghitiu
Bratescu and Foksha Vitaly
Information and Communication Technology in Bilingual
Societies in Finland
Personal Knowledge Management (PKM) and Personal
Employability Management (PEM) – Concepts Based on
Competences
World Atlas <strong>of</strong> Intellectual Capital: Concept and
Methodology
Relational Capital Management <strong>of</strong> new Ventures
Through Virtual Embeddedness and Social Media
ICBS Intellectual Capital Benchmarking System: A
Practical Methodology for Successful Strategy
Formulation in <strong>the</strong> Knowledge Economy
A Critical Review <strong>of</strong> Business Performance Models and
Frameworks and Their Application to Sales
Organisations
The Global Position <strong>of</strong> <strong>the</strong> <strong>European</strong> Patent Office
(EPO): Is Europe Capable <strong>of</strong> Protecting its Intellectual
Capital Effectively?
Jukka Surakka, Pertti Saariluoma, Pertti
Jokivuori, Marjo Silvennoinen, Helena
Suvinen and M T Hyyppä
Marzena Świgoń
Eduardo Tomé
Eleni Magdalini Vasileiadou, Magdalena
Missler-Behr and Sebastian Ullrich
José María Viedma Marti
Angelos Vouldis and Angelica Kokkinaki
Piotr Wisniewski
PhD Research papers 499
Intellectual Capital Disclosure Commitment: A Myth or
Reality?
iii
Deborah Branswijck and Patricia Everaert
328
333
343
359
369
378
388
400
410
417
426
432
439
447
461
475
486
501

Paper Title Author(s) Page
No.
The More Satisfaction, <strong>the</strong> Best Productivity: Examining
<strong>the</strong> Relationship Between Social Capital and job
Satisfaction Among Staff at an Iranian Company
Measure <strong>the</strong> Unmeasurable? Intangible Assets as <strong>the</strong>
Major Strategic Keys <strong>of</strong> Enterprises: Their Contribution,
Difficulties and Proposals for Reliable Financial
Statements
Integrating Intellectual Capital and Sustainability
Management: Perspectives for <strong>the</strong> Internal Management
and External Reporting in Small and Medium Sized
Enterprises
The Investment in Human Capital Development in Public
Administration in Latvia
Summary on Intellectual Capital Value Added (VAIC)
and Calculated Intangible Value (CIV) all Over <strong>the</strong>
World: Lessons to be Learnt
A Multi-Stakeholder Perspective on <strong>the</strong> Value Relevance
<strong>of</strong>, Human Capital; Practice <strong>of</strong> Human Capital
Accounting and Human Capital Disclosure: A Review <strong>of</strong>
Existing Literature
iv
Korosh Gholami, Behjat Yazdkhasti,
Rasool Rabbani and Abdoulbaghi
Roushani
Emmanouil Gkinoglou
Kai Mertins and Ronald Orth
Maria Simonova
Nellija Titova
Krishanthi Ganga Vithana, Riham Rizk
and Amir Michael
Non-Academic Papers 563
The Beehive: A Practitioner’s Metaphor for Knowledge
Markets
Philippe Leliaert
The Tobing Knowledge Management Architecture Paul Lumbantobing, Nelson Rikardo
Pasaribu and Juli Purwanti
Harmonization Process Between Individual Performance
Appraisal and Business Unit Performance Appraisal
Without Decreasing Employee Engagement
Yuli Purwanti, Nelson Rikardo Pasaribu
and Paul Lumbantobing
Work-in-Progress Papers 583
Theoretical and Practical Aspects <strong>of</strong> Implementation <strong>of</strong>
Intellectual Capital Approaches for Sustainable
Economic Development
Diagnostic Analysis <strong>of</strong> Human Capital in <strong>the</strong> University -
<strong>the</strong> Premise <strong>of</strong> Organizational Development
The Contribution <strong>of</strong> <strong>the</strong> Organizational Culture for <strong>the</strong>
Development <strong>of</strong> Human Capital in Non-Pr<strong>of</strong>it System
Building an IC Based Model for <strong>the</strong> Evaluation <strong>of</strong> <strong>the</strong>
Innovation Capacity <strong>of</strong> KIBS
Evaluating Intellectual Capital Using DEA Envelopment
Techniques
Nargiza Abdullaeva and Campbell
Warden
Andreea Feraru and Nicoleta Ciucescu
Roxana Mironescu
Paloma Sánchez and Oihana Basilio
Stelian Stancu and Anca Domnica Lupu
Intellectual Capital in a Seaport Context José Vale, João Ribeiro and Manuel
Branco
509
514
527
537
543
555
565
566
577
585
591
597
601
604
609

Preface
These proceedings represent <strong>the</strong> work <strong>of</strong> presenters at <strong>the</strong> <strong>3rd</strong> <strong>European</strong> <strong>Conference</strong> on Intellectual Capital
(ECIC 2011).
The <strong>Conference</strong> is hosted this year by <strong>the</strong> University <strong>of</strong> Nicosia in Cyprus. The <strong>Conference</strong> Chair is Ge<strong>of</strong>f
Turner from <strong>the</strong> University <strong>of</strong> Nicosia and <strong>the</strong> Programme Chair is Clemente Minonne from <strong>the</strong> School <strong>of</strong>
Management and Law, Zurich University <strong>of</strong> Applied Sciences, Winterthur, Switzerland.
The opening keynote address is given by John Girard from Minot State University in <strong>the</strong> USA. John will
address <strong>the</strong> question Social Knowledge: Are we ready for <strong>the</strong> future? The second day <strong>of</strong> <strong>the</strong> conference will
be opened by Ludo Pyis from AREOPA in Belgium who will consider Intellectual Capital Accounting: how to
measure <strong>the</strong> unmeasurable. We also look forward to a Knowledge Cafe on <strong>the</strong> topic <strong>of</strong> What intellectual
capital ideas and developments do you expect to live and see? facilitated by Helen Paige from The Paige
Group, South Australia.
A primary aim <strong>of</strong> this conference is to contribute to <strong>the</strong> fur<strong>the</strong>r advancement <strong>of</strong> intellectual capital <strong>the</strong>ory and
practice. The conference provides a platform for presenting findings and ideas for <strong>the</strong> intellectual capital
community and associated fields. The range <strong>of</strong> people, issues, and <strong>the</strong> mix <strong>of</strong> approaches followed will
ensure an interesting two days.
144 abstracts were received for this conference. After <strong>the</strong> double blind, peer review process <strong>the</strong>re are 53
academic papers, 7 PhD papers, 7 work-in-progress papers and 3 non-academic contributions published in
<strong>the</strong>se <strong>Conference</strong> <strong>Proceedings</strong>. These papers represent truly global research from some 28 different
countries, including Australia, Barbados, Belgium, Canada, Cyprus, Czech Republic, Finland, Germany,
Greece, Hungary, Iran, Indonesia, Ireland, Italy, Latvia, Malaysia, Poland, Portugal, Romania, Russia, South
Africa, Spain, Sweden, The Ne<strong>the</strong>rlands, United Arab Emirates, United Kingdom, USA and Zimbabwe.
We hope that you have an enjoyable conference.
Ge<strong>of</strong>f Turner, Univeristy <strong>of</strong> Nicosia, Cyprus
<strong>Conference</strong> Chair
and
Clemente Minonne, Zurich University <strong>of</strong> Applied Sciences, Winterthur, Switzerland
Programme Chair
April 2011
v

Biographies <strong>of</strong> <strong>Conference</strong> Chairs, Programme Chairs
and Keynote Speakers
<strong>Conference</strong> Chair
Dr Ge<strong>of</strong>f Turner lives in Cyprus and is <strong>the</strong> Executive Director <strong>of</strong> <strong>the</strong> <strong>European</strong>
Centre <strong>of</strong> Knowledge Management Research, which is hosted by <strong>the</strong> University <strong>of</strong>
Nicosia. He is an Associate Pr<strong>of</strong>essor at that University and for more than 20 years
has been researching, teaching, practicing and advising internationally in <strong>the</strong> fields
<strong>of</strong> accounting, financial management and performance measurement. His doctoral
<strong>the</strong>sis examined <strong>the</strong> need for accounting for human resources in <strong>the</strong> context <strong>of</strong>
intellectual capital management.
Programme Chair
Dr Clemente Minonne lives in Switzerland and is a Research Associate at <strong>the</strong>
<strong>European</strong> Centre <strong>of</strong> Knowledge Management Research, which is hosted by <strong>the</strong>
University <strong>of</strong> Nicosia. He is a researcher, teacher and management advisor in <strong>the</strong>
fields <strong>of</strong> information, innovation, knowledge and strategic management. For <strong>the</strong>
last 19 years he has served in senior business and project management positions
for various multinational companies and is presently a member <strong>of</strong> faculty at <strong>the</strong>
Zurich University <strong>of</strong> Applied Sciences. Knowledge Management was <strong>the</strong> topic <strong>of</strong>
his doctoral dissertation.
Keynote Speakers Dr John Girard is Pr<strong>of</strong>essor <strong>of</strong> Management at Minot State University where he
is actively engaged in academic research. He has written more than thirty articles
and chapters for peer-reviewed or trade journals and books. John’s first book was
an edited volume entitled Building Organizational Memories: Will you know what
you knew? Published by IGI Global in 2009. He is <strong>the</strong> coauthor <strong>of</strong> A Leader’s
Guide to Knowledge Management: Drawing on <strong>the</strong> past to Enhance Future
Performance, published by Business Expert Press in 2009. John speaks
regularly on <strong>the</strong> subjects <strong>of</strong> knowledge management, transformation and
innovation at events such as KM World, APQC’s Knowledge Management
<strong>Conference</strong>, <strong>the</strong> World Congress on Intellectual Capital, KM Australia, KM Asia,
and InfoVision (India).
Ludo Pyis is <strong>the</strong> founder <strong>of</strong> AREOPA, a management consulting group specialising
in change management, intellectual capital accounting, and learning and knowledge
management. He speaks regularly on <strong>the</strong>se topics, especially intellectual capital
accounting. Ludo was a member <strong>of</strong> <strong>the</strong> <strong>European</strong> Commission Expert Group on <strong>the</strong>
Valuation <strong>of</strong> Intangible Assets, which produced <strong>the</strong> Ricadis Report in 2006 and is a
visiting Pr<strong>of</strong>essor at several international universities.
Knowledge Cafe Leader
Dr Helen Paige is <strong>the</strong> Founder and Director <strong>of</strong> The Paige Group, Adelaide,
Australia. She holds an EdD from <strong>the</strong> Flinders University in South Australia. She
was <strong>the</strong> Academic Director <strong>of</strong> <strong>the</strong> Master <strong>of</strong> Entrepreneurship at <strong>the</strong> University <strong>of</strong>
Adelaide, and has lectured at <strong>the</strong> three South Australian universities in a variety
<strong>of</strong> topics including Leadership, HRM and Management. With more than 20 years
in corporate education, Helen has her own consultancy business, Advance
Knowledge Networks, and consults in applied knowledge management,
facilitation <strong>of</strong> World Knowledge Cafes, strategic business management, change
management, and independent chairing and facilitation. She is also <strong>the</strong> Founder
<strong>of</strong> a creative business – Fun.Food.Focus – which combines learning, training and
vi

educating through ‘hands on’ cooking. Helen’s research interests encompass a wide range <strong>of</strong> topics
including – leadership, values and ethics; <strong>the</strong> knowledge-based economy and evaluating executive coaching
as an executive learning tool. She is an internationally published author and a regular contributor to The
Advertiser newspaper on business strategy. She is a Deputy Chair and Executive member <strong>of</strong> a number <strong>of</strong>
organisations, and also holds a Master’s Degree in Policy and Administration; and degrees in law and social
science. She frequently facilitates World Knowledge Cafes internationally, nationally and locally.
Biographies <strong>of</strong> contributing authors (in alphabetical order)
Khodayar Abili. PhD, University <strong>of</strong> Michigan, Postdoctoral fellow, UCLA / Woodrow Wilson Fellow and
Associate Pr<strong>of</strong>essor at <strong>the</strong> University <strong>of</strong> Tehran. He is an Affiliate Pr<strong>of</strong>essor at LUT in Sweden, a Guest
Pr<strong>of</strong>essor at IMI, Iran. Wurzburg University, Iran-Germany Chamber <strong>of</strong> Commerce / Winneba University,
Ghana . Bordeaux-Nice-IMI joint DBA, Iran.
Nargiza Abdullaeva is a Senior Lecturer at <strong>the</strong> University <strong>of</strong> World Economy and Diplomacy (2004-2010),
MBA, PhD in Economics (2007). She worked as a Deputy Dean at <strong>the</strong> University <strong>of</strong> World Economy and
Diplomacy (2008-2009), and is co-author <strong>of</strong> several scientific projects. She is a member <strong>of</strong> External Advisory
Board on RIFI project.
Adriana Agapie is lecturer <strong>of</strong> Quantitative Methods in Business Research and Decision Making Processes
at <strong>the</strong> Academy <strong>of</strong> Economic Studies <strong>of</strong> Bucharest, UNESCO Department for Business Administration, and a
member <strong>of</strong> <strong>the</strong> Research Center for Intellectual Capital. Her main research interests are in <strong>the</strong> fields <strong>of</strong>
research methods in business and economics, and ma<strong>the</strong>matical <strong>the</strong>ory <strong>of</strong> decision processes.
Eckhard Ammann is a Pr<strong>of</strong>essor for computer science at <strong>the</strong> Reutlingen University, Germany, since 1992.
Before that, he spent 8 years with <strong>the</strong> IBM company doing research and development in parallel systems
and system structures. His research interests include knowledge management,intellectual capital, business
process modeling, distributed systems, and virtual organisations.
Sorin Anagnoste is a PhD student at <strong>the</strong> Academy <strong>of</strong> Economic Studies Bucharest. Sorin has been working
for <strong>the</strong> last three years for companies like ABN Amro Bank, PriceWaterhouseCoopers and is now working at
Heineken Romania. Before considering doing a PhD on leadership Sorin has been a volunteer for <strong>the</strong> last 6
years in different NGOs.
Gabriela Atanasiu is a Pr<strong>of</strong>essor <strong>of</strong> Structural Dynamics at <strong>the</strong> Faculty <strong>of</strong> Civil Engineering and Architecture
in <strong>the</strong> Technical University “Gheorghe Asachi” <strong>of</strong> Iasi, Romania since 1995, and PhD Supervisor since 1999.
From 2002 she is serving as <strong>the</strong> Director <strong>of</strong> <strong>the</strong> Multidisciplinary Center <strong>of</strong> Structural Engineering and Risk
Management, MCSERM and her main research areas are: modeling and simulations, performance-based
earthquake engineering and efficient project management.
Bob Barrett is a Pr<strong>of</strong>essor in <strong>the</strong> School <strong>of</strong> Business at <strong>the</strong> American Public University in Charles Town,
West Virginia, USA. In addition to teaching, he trains new instructors transitioning from face-to-face (F2F)
teaching to <strong>the</strong> growing field <strong>of</strong> online learning.
Oihana Basilio is a PhD Candidate and teaching assistant <strong>of</strong> External Sector at <strong>the</strong> Department <strong>of</strong>
Economic Structure and Economy <strong>of</strong> Development, at <strong>the</strong> Autonomous University <strong>of</strong> Madrid (UAM). She
holds a Masters in Economics and Management <strong>of</strong> Innovation and a Masters from <strong>the</strong> <strong>European</strong> Inter-
University Association on Society, Science and Technology (ESST).
Ruxandra Bejinaru is a Junior Teaching Assistant for Management specializations within <strong>the</strong> Management
and Business Administration Department at “Stefan cel Mare” University in Suceava County, Romania. She
is currently a second year - PhD Student studying Business Administration, at <strong>the</strong> Academy <strong>of</strong> Economics, in
Bucharest.
Iren Bena is an assistant pr<strong>of</strong>essor at <strong>the</strong> UNESCO Chair for Business Administration. Irina is a graduate <strong>of</strong>
<strong>the</strong> Academy <strong>of</strong> Economic Studies Bucharest and a former scholarship holder <strong>of</strong> <strong>the</strong> German Academic
Exchange Service. Her teaching activities focus on Customer Relationship Management (in English) and
Human Resource Management (in German). Her research work is on Customer Relationship Management
within <strong>the</strong> banking area.
Andrea Bencsik is an associate pr<strong>of</strong>essor at Széchenyi István University in Győr, and she also teaches as a
visiting pr<strong>of</strong>essor at <strong>the</strong> University J. Selyeho Komarno in Slovakia. She teaches and does research in <strong>the</strong>
vii

fields <strong>of</strong> change management, knowledge management, organizational behaviour, etc. She is a member <strong>of</strong>
some scientific committees.
Aysen Berberoglu received her Bachelor <strong>of</strong> Business Administration degree from Cyprus International
University in 2007 and earned an MBA degree in <strong>the</strong> same institution in 2009. Currently she is working in <strong>the</strong>
Cyprus International University as a research assistant and she is a PhD student as well.
Deborah Branswijck is a Phd student at Ghent University. Her main research fields are in accounting,
namely international accounting standards and corporate disclosure. In addition to her research assignments
she also gives a course on International Accounting Standards and Corporate Accounting at Ghent
University College.
Constantin Bratianu is a pr<strong>of</strong>essor <strong>of</strong> Strategic Management and Knowledge Management at <strong>the</strong> Academy
<strong>of</strong> Economic Studies <strong>of</strong> Bucharest, Romania. He is currently <strong>the</strong> Head <strong>of</strong> <strong>the</strong> UNESCO Department for
Business Administration, and Director <strong>of</strong> <strong>the</strong> Research Centre for Intellectual Capital, within <strong>the</strong> same
university. His research interests are in <strong>the</strong> fields <strong>of</strong> strategic management, knowledge management,
intellectual capital and university management.
Sheryl Buckley is Deputy Head <strong>of</strong> Department in <strong>the</strong> Department <strong>of</strong> Business Information Technology (BIT)
at <strong>the</strong> University <strong>of</strong> Johannesburg (UJ). Her passion lies in <strong>the</strong> Information Science discipline. She is a
committee member <strong>of</strong> a number <strong>of</strong> international organisations as well as an active peer reviewer. She has
presented and published papers locally and internationally.
Anna Bykova is researcher <strong>of</strong> <strong>the</strong> Laboratory <strong>of</strong> Investment Analysis at <strong>the</strong> State University Higher School
<strong>of</strong> Economics (Russia, Perm) and also PhD student in Economy and Management at this <strong>of</strong> university. Her
current research field is focused on intellectual capital, collaborative networks, relationship between firm
competitiveness and innovation clusters.
Donley Carrington is a lecturer in Accounting at <strong>the</strong> University <strong>of</strong> <strong>the</strong> West Indies (UWI) Cave Hill Barbados
Campus. He has been researching and teaching in <strong>the</strong> fields <strong>of</strong> accounting, intellectual capital and
performance measurement. He read for this PhD at <strong>the</strong> University <strong>of</strong> Hull in <strong>the</strong> UK where his doctoral <strong>the</strong>sis
examined intellectual capital in <strong>the</strong> hospitality industry in <strong>the</strong> Caribbean.
Nicoleta Ciucescu is a doctorate student in Management is working as a assistant, in <strong>the</strong> “Vasile
Alecsandri” University <strong>of</strong> Bacau, Faculty <strong>of</strong> Economics. His areas <strong>of</strong> interest in teaching and res3earch are:
management, organizational culture, projects and business plans, small and medium enterprises
management, tourism marketing.
Mihaela Alina Dima is associate pr<strong>of</strong>essor at <strong>the</strong> Bucharest Academy <strong>of</strong> Economic Studies, School <strong>of</strong>
Business Administration. She has held a PhD. in Economics since 2007. Her specialization is International
Business and Economics. Her main fields <strong>of</strong> interest include International Business, Competition Policy,
<strong>European</strong> integration and Higher Education. She has presented various papers at international conferences
in Europe and USA.
John Dumay,MBA AGSM,MA MGSM,PhD (Economics) Sydney is currently a Lecturer in Accounting at
Sydney University after spending 15 years as an independent consultant specialising in management
Accounting. His PhD won <strong>the</strong> prestigious Emerald/EFMD Outstanding Doctoral Research Award 2008 in
Knowledge Management category. His research/consulting focuses on <strong>the</strong> use <strong>of</strong> narrative as a
management tool for organisations. He has presented at numerous international conferences and published
in international academic journals.
Marziye Ehrami is an expert in human resource management and works in IIES in Iran. Marziye has a MA in
public administration and 4 years experience in research about human recourse management. Marziye is
also a member <strong>of</strong> research team <strong>of</strong> strategic studies <strong>of</strong> human resource in <strong>the</strong> oil industry.
Magdi El-Bannany is an Assistant Pr<strong>of</strong>essor at University <strong>of</strong> Sharjah in UAE and Ain Shams University in
Egypt. He is Research Fellow at Liverpool Business School, LJMU. He is a Pr<strong>of</strong>essional Accountant and
Auditor in UK and Egypt. His teaching and research interests include Auditing, Financial Accounting,
Intellectual Capital, Social Responsibility, Bank Pr<strong>of</strong>itability and Governmental Accounting.
viii

Ibrahim Elbeltagi is a Senior lecturer <strong>of</strong> Information and Knowledge Management in Plymouth Business
School, Plymouth University. His Publications relate to electronic commerce, adoption <strong>of</strong> ICT, information
systems in developing countries, social networking and knowledge management. He acts as a member <strong>of</strong>
<strong>the</strong> review board for many journals
Andreea Feraru is a doctoral student in Business Administration and is working as a assistant in <strong>the</strong> “Vasile
Alecsandri” University <strong>of</strong> Bacau in <strong>the</strong> Faculty <strong>of</strong> Economics. His areas <strong>of</strong> interest in teaching and research
include management, intellectual capital, projects and business plans and human resources.
Albrecht Fritzsche has a Master's degree in ma<strong>the</strong>matics and a Master's degree in educational science. He
is a vehicle scheduling expert in <strong>the</strong> IT Management department <strong>of</strong> Daimer, A.G., Stuttgart. His doctoral
dissertation is on industrial economics on heuristic search in complex environments, doctoral dissertation in
philosophy on indeterminacy in technical systems. Interdisciplinary research on innovation at TU Darmstadt.
Tatiana Garanina is Director <strong>of</strong> <strong>the</strong> Masters in Management Programs at St Petersburg State University.
Since 2005 she has been a senior Lecturer in <strong>the</strong> Department <strong>of</strong> Finance and Accounting, Graduate School
<strong>of</strong> Management. She gained her Ph.D., at <strong>the</strong> Graduate School <strong>of</strong> Management in 2009. Her research
interests include Intellectual Capital and Intangible Assets Evaluation and Value-Based Management.
Jose Domingo García-Merino is a lecturer in Financial Economics at The University <strong>of</strong> <strong>the</strong> Basque Country.
He Researches in <strong>the</strong> areas <strong>of</strong> international financial management, financial valuation <strong>of</strong> intangibles and elearning.
He is also an author <strong>of</strong> numerous articles in scientific magazines. He is a member <strong>of</strong> <strong>the</strong> Research
Group in Financial Valuation <strong>of</strong> Intangibles and he participates in e-learning practices developed by
University <strong>of</strong> <strong>the</strong> Basque Country.
Lidia García-Zambrano is a researcher in Financial Economics at The University <strong>of</strong> <strong>the</strong> Basque Country.
Her research activities are oriented towards <strong>the</strong> fields <strong>of</strong> <strong>the</strong> knowledge management: assessment and
financial valuation <strong>of</strong> intangibles. She is co-author <strong>of</strong> various articles in international scientific magazines.
She is working on her <strong>the</strong>sis about financial valuation <strong>of</strong> intangibles.
Rebecca Geiger is degreed economist at <strong>the</strong> Eberhard Karls University Tübingen and at <strong>the</strong> École de
Management de Strasbour. Her research fokusses knowledge management, in particual management and
accounting <strong>of</strong> intellectual property rights issues. She belongs to <strong>the</strong> research staff <strong>of</strong> <strong>the</strong> International
Performance Research Institute gem. GmbH since 2008.
Korosh Gholami Kotenaee is a PHD student in <strong>the</strong> sociology <strong>of</strong> development at Isfahan University. Korosh
is interested in working on social capital and network analysis.
Manolis Gkinoglou is a PhD Candidate in <strong>the</strong> Department <strong>of</strong> Accounting and Finance at <strong>the</strong> University <strong>of</strong>
Macedonia, Thessaloniki, Greece. He holds a MSc and MBA in Accounting and Financial Management and
now he is a PhD Candidate researching in <strong>the</strong> field <strong>of</strong> Accounting for Intangible Assets. He works as a
pr<strong>of</strong>essional accountant and tax consultant with his own enterprise. He has presented working papers from
his PhD at several Academic <strong>Conference</strong>s.
Philippe Leliaert is an independent management consultant, specialising in organisational development &
change, and in <strong>the</strong> management and governance <strong>of</strong> organisational knowledge. He is a regular presenter at
conferences and seminars on <strong>the</strong> identification, measurement and management <strong>of</strong> Intellectual Capital, and a
visiting lecturer at several business schools in Europe, Asia-Pacific, and Latin America.
Florin Leon is a Lecturer with <strong>the</strong> Department <strong>of</strong> Computer Science and Engineering <strong>of</strong> <strong>the</strong> Technical
University <strong>of</strong> Iasi, Romania. His main research interests include artificial intelligence, simulations using
intelligent agents and data mining. He has been involved in interdisciplinary collaborations regarding <strong>the</strong>
application <strong>of</strong> artificial intelligence techniques to civil engineering and chemistry problems.
Víctor López holds a Ph.D. in Econometrics (2002). He researches at <strong>the</strong> University <strong>of</strong> Castilla-La Mancha.
His research interests are Intellectual Capital Measurement, Regional Economy and Models Applied to
Management. He is author <strong>of</strong> diverse papers, books and documents on <strong>the</strong>se topics. He has given
international courses on Intellectual Capital, and obtained several investigation prizes.
Paul Lumbantobing is <strong>the</strong> author <strong>of</strong> two books on knowledge management in <strong>the</strong> Indonesian language on
<strong>the</strong> topics <strong>of</strong> Knowledge Management: Concepts, Architecture and Implementation (2007) and Management
ix

<strong>of</strong> Knowledge Sharing for Community-Based (2011). He is currently attending a doctoral program in
management science at <strong>the</strong> University <strong>of</strong> Padjadjaran Indonesia.
Agnes Maciocha graduated from University <strong>of</strong> Lodz, (master degree) and Warsaw University <strong>of</strong> Technology
(Ph.D), Poland. She was working as Assistant Lecturer and <strong>the</strong>n Research Fellow at Dublin Institute <strong>of</strong>
Technology. Currently she is an Assistant Lecturer at <strong>the</strong> Institute <strong>of</strong> Art Design and Technology, Dublin,
Ireland. Her research interests evolve around Intellectual Capital measurement, quantitative research
methods and Rough Sets.
Peter Marshall is a Student at <strong>the</strong> Dublin Institute <strong>of</strong> Technology in Ireland. The work presented in this paper
was conducted as part <strong>of</strong> his Masters <strong>of</strong> Science Degree in Computing for Knowledge Management and was
inspired by a life long passion in acquiring skills in <strong>the</strong> field <strong>of</strong> Martial Arts.
Maurizio Massaro, Ph.D.is aggregate pr<strong>of</strong>essor at Udine University since 2008, having worked as lecturer
at Udine University since 2001. He was a visiting scholar at <strong>the</strong> Florida Gulf Coast University, Florida, USA,
in 2010. His academic interests are primarily in <strong>the</strong> field <strong>of</strong> <strong>the</strong> measurement <strong>of</strong> business performance,
intangible assets and entrepreneurship. He has written several publications on <strong>the</strong>se topics, and has some
more forthcoming.
Florinda Matos is a Ph.D. student at ISCTE, Lisbon University Institute. Her Doctoral research focuses on
intellectual Capital Management. She is a researcher at UNIDE and at Dinâmia, Lisbon University Institute.
She lectures management and marketing courses in master degree programmes. Currently, she is leading
<strong>the</strong> development <strong>of</strong> ICAA – Intellectual Capital Accreditation Association.
Kai Mertins is Director <strong>of</strong> <strong>the</strong> Division Corporate Management at <strong>the</strong> Fraunh<strong>of</strong>er-Institute for Production
Systems and Design Technology (IPK), Berlin/Germany since 1988. He studies Control Theory in Hamburg
and Economy toge<strong>the</strong>r with Production Management at <strong>the</strong> Technical University <strong>of</strong> Berlin. Since 1998 he is
Pr<strong>of</strong>essor for Global Production Management at <strong>the</strong> Technical University <strong>of</strong> Berlin.
Roxana Mironescu has a doctorate in Management and is currently working as a Senior lecturer in <strong>the</strong> “
Vasile Alecsandri” University <strong>of</strong> Bacau, Faculty <strong>of</strong> Economics. Her areas <strong>of</strong> interests are in teaching and
research, management, human resources management, organizational behaviour, communication and
negotiation. She also collaborates with some educational pr<strong>of</strong>essional institutions in Bacau and Sibiu,
Romania.
Ludmila Mládková works as an associate pr<strong>of</strong>essor at <strong>the</strong> University <strong>of</strong> Economics Prague, Faculty <strong>of</strong>
Business Administration, and Department <strong>of</strong> Management. She specializes in knowledge management,
management <strong>of</strong> knowledge workers and managerial leadership. Her activities involve lecturing, writing and
working with Ph.D. students.
Anatolievna Molodchik Mariya works as an associate pr<strong>of</strong>essor in <strong>the</strong> economic <strong>the</strong>ory department at <strong>the</strong>
State University – High School <strong>of</strong> Economics (Perm). Key scientific interests are knowledge management
and measurement <strong>of</strong> intellectual capital in developing economies. The research results are published in
various academic journals. In 2004 she was invited as visiting pr<strong>of</strong>essor in <strong>the</strong> Austrian Karl-Franzens-
University.
Cristina Morariu is a lecturer at <strong>the</strong> Academy <strong>of</strong> Economic Studies (ASE) - Bucharest and is currently
finalising her PhD at <strong>the</strong> same institution. Her current research interests relate to <strong>the</strong> measurement and
disclosure <strong>of</strong> intellectual capital. Her writing on <strong>the</strong> topic <strong>of</strong> intellectual capital has been published in
academic journals and presented at international conferences.
Fattah Nazem is an Associate Pr<strong>of</strong>essor. He has been vice-president <strong>of</strong> <strong>the</strong> research department for <strong>the</strong> last
five years and has been head <strong>of</strong> <strong>the</strong> department <strong>of</strong> education sciences for <strong>the</strong> past 18 months. He has
written two books and a large number <strong>of</strong> articles. He is Chief Executive <strong>of</strong> <strong>the</strong> Quarterly Journal <strong>of</strong>
Educational Science
Andrei Stefan Nestian is an associate pr<strong>of</strong>essor at <strong>the</strong> Alexandru Ioan Cuza University in Iasi, Romania, in
<strong>the</strong> Faculty <strong>of</strong> Economics and Business Administration. He lectures in Management, HRM and TQM in
bachelor studies and Knowledge Management and Organizational performance at masters level. In 2009 he
completed <strong>the</strong> International Management Teachers Academy (IMTA) program organized by CEEMAN.
x

Theodora Ngosi has a PhD in Computer Science from City University London. She is a researcher studying
<strong>the</strong> IT-CMF with <strong>the</strong> Innovation Value Institute <strong>of</strong> <strong>the</strong> National University <strong>of</strong> Ireland Maynooth. Prior to this,
she was a leading Project Manager in international IT standards covering projects such as Multimedia,
Hypermedia and S<strong>of</strong>tware Development.
Bongani Ngwenya is a Lecturer, MBA programme director and Masters <strong>the</strong>sis supervisor at Solusi
University, in Zimbabwe.. She is currently studying for a PhD in Business Management and Administration,
with specialization in Strategic Management (A Grounded Theory Research), with North West University,
Mafeking Campus in South Africa. Her research interests are mainly in <strong>the</strong> areas <strong>of</strong> Organisational Decision-
Making Research and in Business in general.
Ronald Orth holds a MBA degree from <strong>the</strong> Free University <strong>of</strong> Berlin. Since 2003 he has worked as a senior
researcher for <strong>the</strong> Competence Centre <strong>of</strong> Knowledge Management in <strong>the</strong> Corporate Management Division <strong>of</strong>
Fraunh<strong>of</strong>er IPK, Berlin. His specific focus and area <strong>of</strong> research is in intellectual capital management and
business process-oriented knowledge management as well as sustainability management.
Corina Pelau is a university assistant at <strong>the</strong> Academy <strong>of</strong> Economic Studies, Bucharest Romania, UNESCO
Chair for Business Administration. Within <strong>the</strong> Faculty for Business Administration, in foreign languages, she
holds courses and seminars on marketing, customer relationship management and organiztional and
consumer behavior in German and English language. Her main reseach interests are marketing-controlling,
customer relationship management and consumer behavior.
Juli Purwanti graduated in Ma<strong>the</strong>matical Science from <strong>the</strong> University <strong>of</strong> GadjahMada Yogyakarta. Juli
gained a Master <strong>of</strong> Business Administration from <strong>the</strong> Institute <strong>of</strong> Technology Bandung. Juli works for PT
Telekomunikasi Indonesia, Tbk. Where <strong>the</strong> main responsibility is managing HR communication. Juli has
experience in developing performance management policy and facing <strong>the</strong> problem in it's implementation.
Ulrica Pettersson has been employed by <strong>the</strong> Swedish Armed Forces since 2000, as an engineer and
project leader. She is also a PhD student at Lund University in Sweden. Her dissertation is concerned with
lessons learned and organizational learning (focus on military international missions).
Katja Pook is an independent consultant for intangibles and has a PhD in psychology. Katja is also a
Certified Systemic Consultant (SG), facilitator for Intellectual Capital Reporting (Wissensbilanz-Moderator).
Her Areas <strong>of</strong> expertise are Knowledge Management, Intellectual Capital Management, Human Resources
and Organisational Development, Business Process Management and Systemic Consulting. She also has
experience in <strong>the</strong> public and private sector.
Katia Rodrigues graduated in Economic and Management Sciences in 2010 at Universidade Lusíada. She
is currently studying for a Masters in Banking and Monetary Economics at Univeridade do Minho.
Arturo Rodríguez-Castellanos is a Plain Pr<strong>of</strong>essor in Financial Economics, Dean <strong>of</strong> <strong>the</strong> Faculty <strong>of</strong>
Economics and Business at <strong>the</strong> University <strong>of</strong> <strong>the</strong> Basque Country. Arturo is also <strong>the</strong> Coordinator <strong>of</strong> <strong>the</strong>
Research Group on Firm’s Intangibles Valuation (VALINTE). Their research activities are oriented towards <strong>the</strong>
fields <strong>of</strong> financial management, knowledge management and its relation with finance, and <strong>the</strong> financial valuation
<strong>of</strong> intangibles.
Anna Romiti is an Assistant Pr<strong>of</strong>essor <strong>of</strong> Management at <strong>the</strong> Department <strong>of</strong> Public Health, Faculty <strong>of</strong>
Medicine, University <strong>of</strong> Florence. Her teaching activity covers <strong>the</strong> following subjects: general management
and sport tourism management. Her main research interests are <strong>the</strong> following: Governance mechanisms <strong>of</strong>
small firms, Small firm development, Entrepreneurial network, Strategic Management, Sport Tourism
Management.
Kent Rondeau is an associate pr<strong>of</strong>essor in <strong>the</strong> School <strong>of</strong> Public Health at <strong>the</strong> University <strong>of</strong> Alberta in
Edmonton, Alberta Canada. He teaches graduate courses in health care management and design and in
health human resources management. Kent has an active research program focusing on human resources
development and <strong>the</strong> strategic management <strong>of</strong> human resources in healthcare settings.
Bejinaru Ruxandra is a Junior Teaching Assistant for Management specializations within <strong>the</strong> Management
and Business Administration Department at “Stefan cel Mare” University in Suceava County, Romania.
Presently Bejinaru is a second year PhD Student on Business Administration, at <strong>the</strong> Academy <strong>of</strong> Economics,
in Bucharest.
xi

Dolores Sánchez Bengoa (Med. PhD. cand.) is a university lecturer in cross-cultural management in Austria
and Liechtenstein. Recently, she was <strong>the</strong> research coordinator at Intercollege, Cyprus. She is finalizing her
PhD in <strong>the</strong> area <strong>of</strong> intercultural knowledge transfer process between Eastern and Western Europe Cooperations.
Helena Santos Rodrigues Is <strong>the</strong> 2011 Winner <strong>of</strong> <strong>the</strong> Extraordinary PhD Award from Vigo University for <strong>the</strong>
excellence <strong>of</strong> <strong>the</strong> PhD Investigation and in 2010 Won <strong>the</strong> Investigation award "Catedra da Universidade de
Vigo" (Spain). She has a PhD from <strong>the</strong> Vigo University (Spain). She is now at <strong>the</strong> Viana do Castelo
Polytechnic Institute Portugal, were she teaches Marketing, Organization and Strategy.
Thanaletchumi Sathasivam is a Project Consulting Manager with IRIS Corporation Berhad. She is currently
pursuing an Engineering Doctorate with <strong>the</strong> University Technology Malaysia on a part time basis. She
completed her MSc in Information Technology in Business with University <strong>of</strong> Lincoln in 2002 and was given a
Book Award for <strong>the</strong> research conducted. She has vast experience in managing government based projects,
system integrations and providing technical solutions.
Klaus Bruno Schebesch is Pr<strong>of</strong>essor <strong>of</strong> Marketing Research and responsible for international relations at
<strong>the</strong> business incubator ITA-Goldtech, both at <strong>the</strong> Vasile Goldiş West University, Arad, Romania. He holds a
PhD and a post-doctoral degree from Bremen University.
Maria Simonova is a doctoral student at <strong>the</strong> University <strong>of</strong> Latvia in <strong>the</strong>“Public Administration” program and
her dissertation topic is “Human Capital development in Public Administration in Latvia”. She works at <strong>the</strong>
Latvian Employee’s Confederation.
Karen Smits, MSc is a researcher at The Rotterdam University <strong>of</strong> Applied Sciences where she started
working on a PhD research project on <strong>the</strong> optimalization <strong>of</strong> <strong>the</strong> relationship between research, pr<strong>of</strong>essional
development and curriculum innovation. She has previously worked as Manager in Human Resource
Management in higher education and health care organizations. She holds a Master’s Degree in Social
Science.
Stelian Stancu – teaching courses as: Microeconomics, Quantitative Economics, Methods and techniques
for project predicition, Processus and business modelling. Working with last year students for <strong>the</strong>ir diploma.
Working in research as director or member <strong>of</strong> difference research projects. Member <strong>of</strong> <strong>the</strong> Scientific Committ
from <strong>the</strong> Economic cybernetic Department and Vice Head <strong>of</strong> <strong>the</strong> Department
Marta-Christina Suciu has a Phd in Economics. She graduated from <strong>the</strong> Cybernetics Faculty, Academy <strong>of</strong>
Economic Studies Bucharest (ASE) in 1981. She is a research fellow at <strong>the</strong> National Institute for Economic
Research, Romanian Academy.Since 1993 she has been involved in teaching and research at ASE. She is
now full pr<strong>of</strong>essor and PhD supervisor in Economics, ASE. Her areas <strong>of</strong> interest include <strong>the</strong> knowledgebased
society, intellectual capital, creative economies, investing in people and skills.
Jukka Surakka, PhD, is Head <strong>of</strong> Research at Arcada – University <strong>of</strong> Applied Sciences, His expertise and
scientific interests lie in <strong>the</strong> areas <strong>of</strong> Social Capital, Intellectual Capital, Knowledge Management, Social
Media and communication, Leadership and Organizational solutions.
Marzena Świgoń is an Assistant Pr<strong>of</strong>essor at <strong>the</strong> University <strong>of</strong> Warmia and Mazury in Olsztyn, Poland,
Department <strong>of</strong> Archive studies, Library and Information Science. She received her PhD in Information
Science from University <strong>of</strong> Wrocław, Poland. She also finished postgraduate studies in economics at
Olsztyn. Her research interests include knowledge management, knowledge sharing, information barriers,
information user studies.
Nellija Titova is <strong>the</strong> Deputy Head <strong>of</strong> EU funds, project management and Control in <strong>the</strong> department <strong>of</strong> State
Education Developent Agency. She works with EU funds in Education and Science and is a PhD student at
<strong>the</strong> University <strong>of</strong> Latvia. Her fields <strong>of</strong> interest include Intellectual capital evaluation issues and <strong>the</strong> impact on
financial ratios on <strong>the</strong> enterprise.
Eduardo Tomé has a PhD in Economics from ISEG in Lisbon. Currently he teaches at Universidade Lusiada
in Portugal. He has presented at some 40 conferences and published 20 papers since 2001. In 2009 and
2011 he organized MSKE. His main interests are Knowledge Management, Human Resource Economics,
Social Policy and Economic Integration.
xii

José Vale is an invited assistant pr<strong>of</strong>essor at <strong>the</strong> Aveiro University and at <strong>the</strong> Porto polytechnic in <strong>the</strong> areas
<strong>of</strong> management, strategy and accounting. Presently he is doing a PhD in Accounting and Management
Control in <strong>the</strong> faculty <strong>of</strong> economics at Porto University, studying Intellectual Capital in a seaport context.
Eleni Magdalini Vasileiadou holds a pr<strong>of</strong>essional degree in Architecture and a postgraduate degree in
Business Studies, awarded by <strong>the</strong> Brandenburg University <strong>of</strong> Technology – Cottbus. She currently lectures
Strategic and Operative Management <strong>of</strong> Technology and Innovation. Her Doctoral research comprises
knowledge dynamics, web technologies, intellectual capital and <strong>the</strong> implementation <strong>of</strong> methods for ITS
evaluation and management.
José Maria Viedma Martí is a Doctor <strong>of</strong> Industrial Engineering, a Graduate in Economics and Pr<strong>of</strong>essor <strong>of</strong>
Business Administration, at <strong>the</strong> U.P.C., Polytechnic University <strong>of</strong> Catalonia in Barcelona, Spain. He teaches
and researches on <strong>the</strong> subject <strong>of</strong> knowledge management and intellectual capital. He is a regular speaker in
international conferences on Knowledge Management and Intellectual Capital.
Krishanthi Vithana is a Lecturer from <strong>the</strong> Department <strong>of</strong> Agribusiness Management <strong>of</strong> Sabaragamuwa
University <strong>of</strong> Sri Lanka. Krishanthi is currently studying for PhD in Accounting and Finance at Durham
Business School and is researching in <strong>the</strong> area <strong>of</strong> human capital accounting and disclosure from 2009.
Angelos Vouldis is a aassistant Sales & Marketing Director, Mercedes - Benz Cyprus, and a Lecturer at <strong>the</strong>
University <strong>of</strong> Nicosia. Middlesex University, Doctorate in Pr<strong>of</strong>essional Studies. “Development and
Implementation Issues for Managing Sales Performance”.
Campbell Warden is an accountant, translator and international research administrator. He received an
MBA from <strong>the</strong> Open University Business School, UK in 2002. He served as <strong>the</strong> President <strong>of</strong> <strong>the</strong> <strong>European</strong>
Association <strong>of</strong> Research Managers and Administrators (2000-2002). He was a detached National Expert (on
behalf <strong>of</strong> Spain) in <strong>the</strong> <strong>European</strong> Commission (at DG RTD) between 1998 and 2001. He is an advisor on EU
Research Infrastructure policyand an external expert, evaluator and trainer to UNESCO, UNIDO, DG-RTD &
DG-ENTR.
Piotr Wisniewski is Associate Pr<strong>of</strong>essor <strong>of</strong> Corporate Finance at <strong>the</strong> Warsaw School <strong>of</strong> Economics and has
authored a doctoral dissertation on venture capitalism in Central Europe. Piotr holds a Visiting Pr<strong>of</strong>essorship
in Economics, Finance and Quantitative Methods at <strong>the</strong> International University <strong>of</strong> Monaco. His research and
teaching interests revolve around intellectual capital, capital markets, creative accounting, behavioural
finance and international taxation.
Filippo Zanin, Ph. D.is aggregate pr<strong>of</strong>essor at Udine University since 2008. He is external pr<strong>of</strong>essor at <strong>the</strong>
“Ca’ Foscari” Venice University. His academic interests are primarily in <strong>the</strong> field <strong>of</strong> knowledge management,
performance measurement and strategic planning. He wrote several publications on <strong>the</strong>se topics, and has
some more forthcoming.
xiii

Keynote
Presentations
1

Social Knowledge: Are you Ready? 1
John Girard
College <strong>of</strong> Business, Minot State University, USA
Abstract: For <strong>the</strong> past two decades, public and private sector executives have struggled to develop effective
ways <strong>of</strong> sharing what <strong>the</strong>ir organizations know. Driven by concerns such as downsizing, <strong>the</strong> impending retirement
<strong>of</strong> baby boomers, terrorism, <strong>the</strong> troubling economy, and a host <strong>of</strong> o<strong>the</strong>r organizational challenges, many leaders
have sought ways to share knowledge with both internal and external stakeholders. Despite <strong>the</strong> best efforts <strong>of</strong>
many innovative leaders, few organizations have achieved <strong>the</strong> desired level <strong>of</strong> knowledge sharing. This is
certainly not due to a lack <strong>of</strong> energy, enthusiasm, or excitement on <strong>the</strong> part <strong>of</strong> executives. Today, ample
resources exist for <strong>the</strong> leaders who wish to manage <strong>the</strong>ir organizational intellectual property - many proven tools
and techniques exist to manage today’s knowledge assets. However, what about <strong>the</strong> future? Will today’s babyboomer
based practices pass <strong>the</strong> test <strong>of</strong> time? Are our current processes <strong>the</strong> most relevant ones for <strong>the</strong> next
generation <strong>of</strong> organizational leaders? We are seeing some very promising results from third-generation
knowledge projects, which focus on connecting people and facilitating collaboration. Many organizations are now
reaping <strong>the</strong> benefits <strong>of</strong> using social media such as wikis for collaboration and social networking tools for
connecting people. These emerging tools and techniques provide flexible, agile, and intuitive solutions for
connecting people with people and facilitating coordination, communication, and collaboration. This paper will
focuses on what we should be doing now (or soon) to ensure <strong>the</strong> next generation <strong>of</strong> organizational leaders know
what we knew. In o<strong>the</strong>r words, are we creating organizational memories today, which will be useful to <strong>the</strong> leaders
who follow us?
1. Just <strong>the</strong> facts, please
How many times have you heard an executive say I just want <strong>the</strong> facts. But do <strong>the</strong>se very busy
executive really want just <strong>the</strong> facts? To start our exploration, consider <strong>the</strong> following definition, “data is
a set <strong>of</strong> discrete, objective facts about events” (Davenport & Prusak, 1998, p. 2). From a management
perspective two features are worthy <strong>of</strong> note. First, data is <strong>the</strong> lowest level in <strong>the</strong> value chain and by
itself is not very beneficial. Second, too much data exists and until or unless managers transform this
data into information, it is simply occupying valuable space.
So why is it that executives crave data? If <strong>the</strong>y buy into <strong>the</strong> concepts <strong>of</strong> knowledge management <strong>the</strong>n
one would think that <strong>the</strong>y should prefer having access to processed data, which many people call
information or maybe even knowledge. Recall Peter Drucker’s description, “Information is data
endowed with relevance and purpose,” (1988, p. 46) which seems to imply that senior managers
would wish this relevant entity (information) ra<strong>the</strong>r that <strong>the</strong> raw form (data). However, no matter how
many times <strong>the</strong>y remind <strong>the</strong>mselves <strong>of</strong> this concept, <strong>the</strong> executives continue to say, “I want <strong>the</strong> facts.”
Well maybe <strong>the</strong> answer is to give <strong>the</strong>m facts, but in a way that can make a difference.
What executives need, and need now, is whatever nugget will help <strong>the</strong>m make a decision. What is
data to one person may be knowledge to ano<strong>the</strong>r. At <strong>the</strong> end <strong>of</strong> <strong>the</strong> day executives crave whatever is
needed to make a decision, <strong>the</strong>y do not worry about <strong>the</strong> nomenclature. Verna Allee, author <strong>of</strong> several
excellent knowledge management books, reminds us that fuzzy boundaries create innovation (Allee,
2003, p. 4). This phase was <strong>the</strong> catalyst for a new model to describe <strong>the</strong> relationship between data
management, information management and knowledge management. Ra<strong>the</strong>r than focus on whe<strong>the</strong>r a
particular tool, tactic, or technique should be labeled as a data management, information
management or knowledge management, <strong>the</strong> model suggests that a continuum exists. By eliminating
strict boundaries, which are <strong>of</strong>ten difficult to define, <strong>the</strong> model focuses on outputs ra<strong>the</strong>r than
preconceived categorizations.
Data Mining is an excellent example <strong>of</strong> this concept in action. Some would argue that data mining is
data dependent and <strong>the</strong>refore a data management tool. O<strong>the</strong>rs argue that data mining was not
possible until powerful information technology systems were available to take deep dives into <strong>the</strong> vast
stores <strong>of</strong> data and <strong>the</strong>refore it must be an information management tool. Still o<strong>the</strong>rs contend that data
mining is clearly knowledge management. At <strong>the</strong> end <strong>of</strong> <strong>the</strong> day, <strong>the</strong> executive who makes a vital
decision because <strong>of</strong> a particular process is more concerned with <strong>the</strong> result than <strong>the</strong> label.
1 Adapted from A Leader’s Guide to Knowledge Management: Drawing on <strong>the</strong> Past to Enhance Future Performance, published
by Business Expert Press, used with permission. (Girard & Girard, 2009)
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John Girard
Consider <strong>the</strong> following example <strong>of</strong> data mining in action. According to NCR Corporation, one <strong>of</strong> its
divisions (Teradata) “pioneered <strong>the</strong> field <strong>of</strong> data mining by looking at sales data from a retailer and
discovering that in <strong>the</strong> evening hours, beer and diapers are <strong>of</strong>ten purchased toge<strong>the</strong>r. This
relationship, called a data mining affinity, captured <strong>the</strong> imagination <strong>of</strong> industry watchers, spawning a
legend that has been recounted hundreds <strong>of</strong> times and is frequently cited as <strong>the</strong> textbook example <strong>of</strong>
data mining.”(Michael, 2002) Much has been written about this example <strong>of</strong> data mining in action.
Many <strong>of</strong> <strong>the</strong> articles describe <strong>the</strong> technology used to discover this relationship while o<strong>the</strong>rs describe
<strong>the</strong> ma<strong>the</strong>matics used to develop <strong>the</strong> algorithms.
However, <strong>the</strong> aspect <strong>of</strong> most interest is what <strong>the</strong> retailer did with this valuable information. Imagine
that you are at <strong>the</strong> helm <strong>of</strong> a large retail operation and you are presented with <strong>the</strong> findings <strong>of</strong> this
experimental research. At an executive meeting <strong>the</strong> Vice President <strong>of</strong> Sales, supported by <strong>the</strong> Chief
Information Officer, describe <strong>the</strong>ir findings. They tell a story that every Friday evening most people
that purchase beer also purchase diapers. They have <strong>the</strong> data to prove it, each and every Friday
<strong>the</strong>re is a very clear relationship between beer sales and diapers sales.
The question is, what do you do armed with this knowledge? Most executives would consider how
<strong>the</strong>y could use this knowledge to create a competitive advantage. They would realize <strong>the</strong> value <strong>of</strong> this
knowledge is time limited. In o<strong>the</strong>r words, once <strong>the</strong>ir competitors discover <strong>the</strong> relationship, <strong>the</strong> value
<strong>of</strong> <strong>the</strong> knowledge will be diminished. Before answering <strong>the</strong> question, how many executives would stop
to ask this question, am I dealing with data, information, or knowledge? None. Well no executive that
wants to remain competitive. The reality is executives are not concerned with <strong>the</strong> nomenclature, but
ra<strong>the</strong>r with <strong>the</strong> results.
So what really happened? What did <strong>the</strong> retailer do? Well this is where <strong>the</strong> urban myth part <strong>of</strong> <strong>the</strong> story
starts. Many tales have been told about <strong>the</strong> unnamed retailer, so many so, that many skeptics
suggest <strong>the</strong> whole event may not have existed. Like many great stories, <strong>the</strong> most important thing is
<strong>the</strong> story must be believable; it does not have to be true, but it does have to be believable. The most
important point in this story is that <strong>the</strong> CEO had <strong>the</strong> data, information, or knowledge (whatever you
wish to call it) that she needed to make <strong>the</strong> decision. We can debate <strong>the</strong> decision but at <strong>the</strong> end <strong>of</strong> <strong>the</strong>
day, <strong>the</strong> most important issue is that <strong>the</strong> CEO had what she needed to make an important corporate
decision. Knowledge management is about making sure that senior executives know what <strong>the</strong>y need
to know to make <strong>the</strong> decisions that <strong>the</strong>y must make.
2. Unknown unknowns – gibberish or wisdom?
The Plain English Campaign is a United Kingdom-based organization that describes itself as “an
independent pressure group fighting for public information to be written in plain English.”("Plain
English Campaign,") Annually, <strong>the</strong> Plain English Campaign presents a variety <strong>of</strong> awards focusing on
<strong>the</strong> use <strong>of</strong> English. One <strong>of</strong> <strong>the</strong>ir awards is entitled <strong>the</strong> Foot in Mouth, which <strong>the</strong>y present to a public
figure for a baffling quote. In 2003, <strong>the</strong> recipient <strong>of</strong> <strong>the</strong> Foot in Mouth award was former US Defense
Secretary Donald Rumsfeld for saying <strong>the</strong> following during a Pentagon press conference on February
12 th , 2002:
. . . as we know, <strong>the</strong>re are known knowns; <strong>the</strong>re are things we know we know. We also
know <strong>the</strong>re are known unknowns; that is to say we know <strong>the</strong>re are some things we do not
know. But <strong>the</strong>re are also unknown unknowns -- <strong>the</strong> ones we don't know we don't know.
And if one looks throughout <strong>the</strong> history <strong>of</strong> our country and o<strong>the</strong>r free countries, it is <strong>the</strong>
latter category that tend to be <strong>the</strong> difficult ones.("DoD News Briefing - Secretary
Rumsfeld and Gen. Myers," 2002)
Say what? What do you mean <strong>the</strong>re are known knowns, known unknowns, and unknown unknowns?
This sounds like gibberish at best or perhaps just pure nonsense. Many journalist poked fun at Donald
Rumsfeld and a series <strong>of</strong> Internet sites emerged to document <strong>the</strong> poetry <strong>of</strong> Rumsfeld. Surely, <strong>the</strong>
Secretary misspoke or was misquoted. In fact, nothing could be fur<strong>the</strong>r from <strong>the</strong> truth as Donald
Rumsfeld very concisely described a major complex management challenge. The challenge is best
illustrated using a 2 x 2 matrix:
The point that Secretary Rumsfeld so eloquently articulated in just 20 seconds has since been <strong>the</strong>
subject <strong>of</strong> a variety <strong>of</strong> articles and book chapters. Take for example Alex & David Bennet’s chapter
entitled Exploring <strong>the</strong> Unknown in <strong>the</strong>ir book Organizational Survival in <strong>the</strong> New World: The Intelligent
Complex Adaptive System. This chapter focuses on “how do we identify things that we don’t know we
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John Girard
don’t know.” (Bennet & Bennet, 2004) This is exactly what Rumsfeld was suggesting. If we know that
we do not know something <strong>the</strong>n we can develop a plan to find out more. Likewise, if we do not know
that we know something <strong>the</strong>n again we can develop a plan to find <strong>the</strong> missing link. Both <strong>of</strong> <strong>the</strong>se
issues are dealt with during external and internal scanning, competitive intelligence, and <strong>the</strong> like.
Unknown
Knowns
Known
Knowns
Unknown
Unknowns
Known
Unknowns
Figure 1: Rumsfeld’s unknown unknowns
The 2 X 2 matrix is a useful way to categorize <strong>the</strong> challenges confronting many originations.
Unfortunately, most leaders focus on <strong>the</strong> easy bits: things <strong>the</strong>y know and things that <strong>the</strong>y know that
<strong>the</strong>y do not know. Many organizations ignore <strong>the</strong> upper right-hand quadrant – <strong>the</strong> unknown unknowns
– because it is just too difficult. Perhaps some ignore this quadrant because <strong>the</strong>y do not know what to
do. A very good example <strong>of</strong> a time-tested tool to conquer this quadrant is data mining as discussed
earlier in this paper. That said, to some degree <strong>the</strong> avoidance <strong>of</strong> <strong>the</strong> upper right-hand quadrant is a
symptom <strong>of</strong> <strong>the</strong> not on my watch syndrome. Many leaders do not wish to dig too deep into <strong>the</strong>
unknown unknowns because it is uncharted territory. Equally concerning is <strong>the</strong> fear that discovering
unknown unknowns will expose a corporate Achilles heel . . . Then what would we do?
The o<strong>the</strong>r quadrant that <strong>of</strong>ten creates anxiety is <strong>the</strong> upper left or unknowns knowns quadrant. One <strong>of</strong>
my favorite stories about this quadrant features a large technology company. The story is loosely
based on a real company, but given I embellished a few parts to make my point, I must declare it is a
fictional company – let’s call <strong>the</strong>m IQ. IQ is a well-known brand that for many years operated with a
divisional organization structure. Once a year, each <strong>of</strong> <strong>the</strong> divisional vice presidents were afforded <strong>the</strong>
opportunity to brief <strong>the</strong> Board <strong>of</strong> Directors on <strong>the</strong>ir plans for <strong>the</strong> future. This rare occasion was seen to
be a time when senior executives could describe <strong>the</strong> next big thing that would provide IQ with a
competitive advantage.
One year, <strong>the</strong> printer division’s vice president was extremely excited about his time with <strong>the</strong> Board. He
was sure <strong>the</strong> directors would agree that his new idea, a printer that could also scan, would be a
history-making innovative product, a must have for many small businesses. The R&D arm <strong>of</strong> <strong>the</strong>
printer division had been working secretly on <strong>the</strong> project for some time. After investing considerable
resources, <strong>the</strong>ir prototype was ready to be showcased to <strong>the</strong> Board. They were very proud <strong>of</strong> <strong>the</strong>ir
clandestine operation; it was quite a coup that none <strong>of</strong> <strong>the</strong> technology press had picked up on <strong>the</strong>ir
work.
Finally, <strong>the</strong> big day arrived. The vice president was waiting patiently in <strong>the</strong> anteroom reviewing his
presentation. Suddenly, an unprecedented level <strong>of</strong> applause from inside <strong>the</strong> Board Room interrupted
his thoughts. Shortly afterwards <strong>the</strong> vice president <strong>of</strong> <strong>the</strong> scanner division emerged, smiling, and
clearly happy with her performance in <strong>the</strong> room. The printer executive politely asked his colleague
why <strong>the</strong> Board erupted into applause. After a short pause, she replied, “I just showed <strong>the</strong> Board our
prototype for <strong>the</strong> next big thing . . . a scanner that can also print.” Needless to say, <strong>the</strong> printer
executive was no longer excited about briefing <strong>the</strong> Board.
The moral <strong>of</strong> <strong>the</strong> story is that a need to know culture, which is commonplace in many technology
companies, does not facilitate knowledge sharing. Here is a case where senior executives did not
share, let alone, collaborate on <strong>the</strong> project. Imagine if <strong>the</strong> two divisions shared resources and
knowledge to design <strong>the</strong> printer scanner. Regrettably, many organizations fall victim to <strong>the</strong> unknown
knowns because <strong>the</strong>y do not foster a collaborative environment with a need to share philosophy.
3. We have a problem!
The nightmare scenario for many executives is a call in <strong>the</strong> night that begins with <strong>the</strong> words “We have
a problem!” Almost certainly one <strong>of</strong> <strong>the</strong> most famous problems was in April 1970 when astronaut Jack
Swigert, aboard Apollo 13, radioed Houston and said <strong>the</strong> famous, but <strong>of</strong>t misquoted, phrase “Houston,
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we’ve had a problem!” Fortunately, most management decisions are not life and death as was <strong>the</strong>
case with Apollo 13.
Never<strong>the</strong>less, organizations must be prepared for crisis decision making. It is too late when crises
present <strong>the</strong>mselves to consider what values are important to an organization. The recent and
spectacular failures <strong>of</strong> large corporations seem to indicate that many corporate leaders are ill
prepared or unwilling to deal with unanticipated tribulations. However, <strong>the</strong>re are a few great examples
<strong>of</strong> organizations whose management teams internalize core values in quiet times so that <strong>the</strong>y are
prepared for catastrophic events.
In 1943, when General Robert Wood Johnson penned “Our Credo” for Johnson & Johnson, he had no
idea just how important this short passage would become. He had no idea how his carefully crafted
words would help <strong>the</strong> leaders <strong>of</strong> <strong>the</strong> next generation. The Credo has been changed, ever so slightly
since 1943; however, most <strong>of</strong> <strong>the</strong> changes have been in language and not in substance or spirit. The
Credo begins by stating, “We believe our first responsibility is to <strong>the</strong> doctors, nurses and patients, to
mo<strong>the</strong>rs and fa<strong>the</strong>rs and all o<strong>the</strong>rs who use our products and services. In meeting <strong>the</strong>ir needs
everything we do must be <strong>of</strong> high quality.” The Credo continues with some guiding principles and <strong>the</strong>n
concludes by stating, “When we operate according to <strong>the</strong>se principles, <strong>the</strong> stockholders should realize
a fair return.” (Johnson) 2
The Credo proved its worth when some malefactors infected some TYLENOL® with cyanide in 1982.
According Lawrence G. Foster, Vice President <strong>of</strong> Public Relations for Johnson & Johnson “The Credo
served <strong>the</strong> company better than any crisis management plan could have.”(Foster, 1983) Based on <strong>the</strong>
Credo, <strong>the</strong> Johnson & Johnson managers knew what to do. However, how can a 40-year-old onepage
document help managers make decisions? The answer is that everyone in Johnson & Johnson
is aware <strong>of</strong> <strong>the</strong> Credo and its importance. It is more than words on a paper. It is more than just some
poster hanging in conference rooms. It has become synonymous with Johnson & Johnson and all
managers know what it means.
All too <strong>of</strong>ten executives go through <strong>the</strong> motions <strong>of</strong> developing a mission, vision, and values so that
<strong>the</strong>y may be proudly displayed in <strong>of</strong>fices. To many this is a paper exercise that does not really change
<strong>the</strong> price <strong>of</strong> fish. Johnson & Johnson’s Credo is NOT simply a paper exercise. Johnson & Johnson’s
Credo is a guiding document that has passed <strong>the</strong> test <strong>of</strong> time and it is an excellent example <strong>of</strong> what
Nonaka termed Internalization.
4. A day to remember
For many August 14 th 2003 is a date <strong>the</strong>y will remember. That was <strong>the</strong> day that some 50 million
Americans and Canadians witnessed a blackout across <strong>the</strong> Nor<strong>the</strong>ast portion <strong>of</strong> <strong>the</strong> North American
continent. On that hot August day, I was living in Ottawa, Canada’s capital. Brownouts are relatively
common in Ontario during <strong>the</strong> summer and although local blackouts are not unheard <strong>of</strong>, <strong>the</strong>y are quite
rare. The “usual suspect” in <strong>the</strong>se cases is high summer temperatures, which in turn cause people to
crank up <strong>the</strong>ir air conditioners. Invariably this puts a strain on <strong>the</strong> power grid and sometimes <strong>the</strong> result
is a brownout or very occasionally a blackout.
I knew this day was different when I received a telephone call from our daughter, Terri-Lynn. At <strong>the</strong>
time, she was a Human Resource Associate at Wal-Mart in Ottawa. I was not surprised when she told
us that her store was using emergency power as our house was without electricity and it was only
about two miles from her <strong>of</strong>fice. What really surprised me was when she said that she had just spoken
to a Toronto store and it too was experiencing a blackout. Her colleague stated that <strong>the</strong> entire
metropolitan Toronto area was in <strong>the</strong> dark. All <strong>of</strong> a sudden, <strong>the</strong> situation changed. How could Ottawa
(population 800,000) and Toronto (population 2,500,000) be without electricity?
I turned on a battery-powered radio to discover that New York and Detroit were also without power. If
<strong>the</strong> news reports were true, <strong>the</strong>n at least 15 million people were in <strong>the</strong> dark, maybe even more. How
could this be? Not surprisingly, <strong>the</strong>re was talk <strong>of</strong> malicious attacks. This seemed plausible. Now what?
Well in hindsight we now know that this was not caused by a targeted attacked on <strong>the</strong> North American
infrastructure but ra<strong>the</strong>r an unfortunate, though predictable, shut down designed to protect <strong>the</strong> grid.
2 See http://tinyurl.com/c7rtfa for <strong>the</strong> complete text <strong>of</strong> <strong>the</strong> one-page Credo
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The real question becomes what should we do to ensure this never happens again. One way is to
conduct an After Action Review or AAR, which considers four questions:
1. What was supposed to happen?
2. What happened?
3. What is <strong>the</strong> difference?
4. What should we do to improve?
The US Army designed <strong>the</strong> AAR process more than two decades ago. The premise is simple – how
can we learn from our mistakes to ensure we do not repeat <strong>the</strong> same mistakes. I like to think about it
as a scheme that encourages making “new” mistakes ra<strong>the</strong>r than <strong>the</strong> same old ones. Of course, for
<strong>the</strong> US Army it is much more serious than avoiding old mistakes because an avoidable mistake may
be dyer – it may involve <strong>the</strong> loss <strong>of</strong> life <strong>of</strong> a brave American soldier and this must be avoided at all
costs.
Today many organizations are benefiting from <strong>the</strong> outstanding work <strong>of</strong> <strong>the</strong> US Army. Today
organizations across <strong>the</strong> US and around <strong>the</strong> world have implemented AARs to ensure <strong>the</strong>y make new
mistakes. AARs are a powerful concept for creating and transferring organizational knowledge;
however, like many management processes <strong>the</strong>y must be implemented with care.
Often it is a good idea to have a trained facilitator help organizations learn <strong>the</strong> craft <strong>of</strong> AARs. Once
AARs become commonplace <strong>the</strong>y should be conducted by internal managers. Remember AARs are
not about assigning or implying blame, but ra<strong>the</strong>r, AARs are about making sure that organizations do
not repeat <strong>the</strong> same mistakes. AAR sessions should be short and positive. Do NOT allow <strong>the</strong>
sessions to turn into a witch-hunt or a figure-pointing exercise. AAR’s are a very good example <strong>of</strong>
what Nonaka termed Externalization. By <strong>the</strong> way, it turns out <strong>the</strong> cause <strong>of</strong> <strong>the</strong> Blackout <strong>of</strong> 2003 was
likely due to trees not being trimmed as <strong>the</strong>y should have been.
Many executives crave data, or at least <strong>the</strong>y believe <strong>the</strong>y crave data. Regrettable this constant desire
for data creates an environment in which leaders are drowning in data and let starving for knowledge.
Often <strong>the</strong>re is much more value created by processing data into information or knowledge, which is
generally more useful to decision makers. In this paper, we explored a number <strong>of</strong> examples <strong>of</strong> how
organizations may complete this task. Many <strong>of</strong> <strong>the</strong>se tools and techniques are simple ideas that work
in complex environments go some way to enlightening organizational leaders.
5. The future is just a day away
For <strong>the</strong> past two decades, public and private sector executives and managers have struggled to
develop effective ways <strong>of</strong> sharing what <strong>the</strong>ir organizations know. Driven by concerns such as
downsizing, <strong>the</strong> impending retirement <strong>of</strong> baby boomers, terrorism, <strong>the</strong> troubling economy, and a host
<strong>of</strong> o<strong>the</strong>r organizational challenges, many leaders have sought ways to share knowledge with both
internal and external stakeholders. For <strong>the</strong> past decade, much <strong>of</strong> <strong>the</strong>ir work was built on <strong>the</strong> solid
foundation provided by several seminal works including Working Knowledge (Davenport & Prusak,
1998), If Only We Knew What We Know (O’Dell & Grayson, 1998), and The Knowledge Creating
Company (Nonaka & Takeuchi, 1995).
Despite <strong>the</strong> best efforts <strong>of</strong> many innovative leaders, few organizations have achieved <strong>the</strong> desired level
<strong>of</strong> knowledge sharing. This is certainly not due to a lack <strong>of</strong> energy, enthusiasm, or excitement on <strong>the</strong>
part <strong>of</strong> executives, but ra<strong>the</strong>r <strong>the</strong> result <strong>of</strong> technology-focused, complicated, and expensive tools,
techniques, and technologies. Equally, a culture based on a need-to-know ra<strong>the</strong>r than one based on a
need-to-share basis prevented <strong>the</strong> transparency necessary to achieve organizational knowledge
goals.
Our review suggests that many first-generation knowledge management projects were based on
collecting and classifying information. The belief seemed to be that if we developed huge, centralized,
IT-based repositories <strong>of</strong> artifacts, <strong>the</strong>n stakeholders would serve <strong>the</strong>mselves. Unfortunately, this
approach never delivered <strong>the</strong> promised user-friendly access but ra<strong>the</strong>r resulted in many very
expensive partial databases <strong>of</strong> little value.
Second-generation knowledge management projects shifted <strong>the</strong> focus to codifying tacit knowledge
and combining explicit knowledge to create new knowledge. This approach seemed plausible in
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John Girard
<strong>the</strong>ory; however, quickly it became apparent that codifying tacit knowledge was difficult and very
expensive, both in terms <strong>of</strong> time and money. Fur<strong>the</strong>r exacerbating <strong>the</strong> challenge was <strong>the</strong> issue <strong>of</strong>
information overload that resulted from <strong>the</strong> combination efforts.
Today we are seeing some very promising results from third-generation knowledge projects, which
focus on connecting people and facilitating collaboration. Some organizations are now reaping <strong>the</strong>
benefits <strong>of</strong> using social media tools such as wikis for collaboration and knowledge-sharing and
commercial social networking tools, such as Facebook, LinkedIn, Socialcast, or Twitter for connecting
people. These emerging tools and techniques provide flexible, agile, and intuitive solutions for
connecting people with people and facilitating coordination, communication, and collaboration.
A word <strong>of</strong> warning is necessary, as most <strong>of</strong> <strong>the</strong> tools, tactics, and techniques that we will discuss in
this paper are relatively immature. Indeed, this is a domain in which practitioners are leading and
academics are lagging. As a result, <strong>the</strong>re is little empirical research to support many <strong>of</strong> <strong>the</strong> claims
articulated by <strong>the</strong> proponents. Unlike <strong>the</strong> ideas we covered in previous chapters, <strong>the</strong> ideas presented
here are likely more suited to early adopters. We believe that each <strong>of</strong> <strong>the</strong> emerging concepts are
worthy <strong>of</strong> consideration; however, caveat emptor—let <strong>the</strong> buyer (or user) beware!
6. Sagology
The more we analyze <strong>the</strong> first and second-generation knowledge management projects, <strong>the</strong> more we
believe that we got exactly what we asked. In o<strong>the</strong>r words, it seems likely that collectively we were
confused about what we really wanted. Let us use <strong>the</strong> concept <strong>of</strong> Expertise Location Systems (ELS)
as an example. There are many great examples <strong>of</strong> ELS in action; however, <strong>the</strong>re are few examples <strong>of</strong>
ELS being institutionalize in large organizations. Most examples <strong>of</strong> successful ELS implementations
are relatively small scale—small islands <strong>of</strong> knowledge management in a larger sea <strong>of</strong> chaos.
We believe that many projects relied too much on process ra<strong>the</strong>r than <strong>the</strong> enablers <strong>of</strong> technology,
leadership, and culture. Returning to ELS, what we find is that <strong>the</strong> process works fine in <strong>the</strong>ory.
Simply develop a process where we can record everyone’s expertise and <strong>the</strong>n knowledge seekers will
be able to, magically, connect with <strong>the</strong>se knowledge providers. Unfortunately, this approach viewed
knowledge production as a very mechanical process. In practice, many <strong>of</strong> <strong>the</strong> knowledge providers
were too busy to bo<strong>the</strong>r with <strong>the</strong> system or were guilty <strong>of</strong> knowledge hoarding. In o<strong>the</strong>r words, we
ignored <strong>the</strong> cultural component <strong>of</strong> knowledge management. Clearly, in <strong>the</strong> future we must consider
<strong>the</strong> enablers, especially as <strong>the</strong>y apply to our organization.
We also believe that sometimes leaders may have missed <strong>the</strong> point <strong>of</strong> <strong>the</strong> whole exercise. Earlier in
<strong>the</strong> book, we <strong>of</strong>fered Davenport and Prusak’s definition <strong>of</strong> knowledge:
a fluid mix <strong>of</strong> framed experience, values, contextual information, expert insight that
provides a framework for evaluating and incorporating new experiences and information.
It originates and is applied in <strong>the</strong> minds <strong>of</strong> knowers. In organizations, it <strong>of</strong>ten becomes
embedded not only in documents or repositories but also in organizational routines,
processes, practices, and norms. (Davenport & Prusak, 1998, p. 5)
The elevator version <strong>of</strong> this definition might be “concepts, experience, and insight that provide a
framework for creating, evaluating and using information” (Laudon & Laudon, 2005, p. 373). We like
this concise definition as it supports <strong>the</strong> concept <strong>of</strong> <strong>the</strong> cognitive hierarchy by suggesting that
knowledge is about evaluating and using information. Despite <strong>the</strong> pleasing nature <strong>of</strong> this definition, we
sometimes wonder if evaluating and using information is really <strong>the</strong> desired end state. Is that all
executives need, evaluating and using information?
The same authors who eloquently penned our elevator definition <strong>of</strong> knowledge are proponents <strong>of</strong> <strong>the</strong>
notion that <strong>the</strong> cognitive hierarchy extends beyond knowledge. In Essentials <strong>of</strong> Management
Information Systems: Managing <strong>the</strong> Digital Firm, <strong>the</strong> authors, Kenneth and Jane Laudon, provided a
clear, concise, and accurate definition for <strong>the</strong> apex <strong>of</strong> <strong>the</strong> knowledge pyramid. They defi ne wisdom as
“<strong>the</strong> collective and individual experiences <strong>of</strong> applying knowledge to <strong>the</strong> solution <strong>of</strong> problems” (Laudon
& Laudon, 2005, p. 373). We like this definition because it brings two important ideas to <strong>the</strong> table.
First is <strong>the</strong> notion that wisdom is derived from both individual and collective experiences, which
reminds us that this is probably a team sport and not an individual effort. Equally important is <strong>the</strong>
phase “applying knowledge to <strong>the</strong> solution <strong>of</strong> <strong>the</strong> problem.” This concept is paramount as it reinforces
8

John Girard
our belief that many leaders will only embark on this knowledge journey to solve organizational
challenges, present or future.
We <strong>of</strong>ten refer to this expanded hierarchy as <strong>the</strong> Knowledge Edge, which is <strong>the</strong> domain <strong>of</strong> senior
leaders. Compare this element to Knowledge Creation, which is <strong>of</strong>ten <strong>the</strong> area <strong>of</strong> expertise for middle
managers or executive staff. Remember earlier that we described <strong>the</strong> methods for creating
knowledge. We suggested <strong>the</strong>re are five major ways to transform data into information. First, one may
put <strong>the</strong> data into context by communicating <strong>the</strong> reason for ga<strong>the</strong>ring <strong>the</strong> data. Second, one may
categorize <strong>the</strong> data by describing <strong>the</strong> breakdown or <strong>the</strong> essential components <strong>of</strong> <strong>the</strong> data. Third, one
may ma<strong>the</strong>matically or statistically calculate <strong>the</strong> data. Fourth, one may correct errors in previously
reported data. Finally, one may condense <strong>the</strong> data by providing a summary instead <strong>of</strong> <strong>the</strong> entire
collection <strong>of</strong> data. Equally, we argued <strong>the</strong>re are four activities that transform information into <strong>the</strong>
knowledge. First, one may compare information with previous information, primarily to determine what
has changed in a particular situation. Second, one may determine <strong>the</strong> consequences or
repercussions <strong>of</strong> this information on decisions. Third, one may consider how this information connects
or correlates to o<strong>the</strong>r information. Finally, through conversation one may conclude what people think
about <strong>the</strong> information (Davenport & Prusak, 1998).
Without wishing to dwell on definitions, we think it is important to realize that <strong>the</strong>re is much more to
knowledge management than <strong>the</strong> ra<strong>the</strong>r mechanical production <strong>of</strong> knowledge. Knowledge
management, which many agree is a ra<strong>the</strong>r unfortunate term, is much more; it really is about senior
leaders combining <strong>the</strong>ir organizational knowledge with experience to solve challenges. To emphasize
<strong>the</strong> difference, we have adopted a different term for this essential executive function. We use <strong>the</strong> term
sagology to describe our work, which we define as <strong>the</strong> study <strong>of</strong> organizational wisdom in all its forms,
especially with reference to technology, leadership, culture, process, and measurement. The
remainder <strong>of</strong> this chapter focuses on sagology and how leaders may apply <strong>the</strong> idea to <strong>the</strong>ir future
needs.
7. The power <strong>of</strong> <strong>the</strong> people
By far <strong>the</strong> most watched phenomenon <strong>of</strong> <strong>the</strong> 21 st
century surrounds <strong>the</strong> power <strong>of</strong> everyday people.
Executives across <strong>the</strong> board seem surprised by <strong>the</strong> sudden, and sometimes unwanted, knowledge
and resultant power <strong>of</strong> <strong>the</strong> people. In <strong>the</strong>ir book Groundswell: Winning in a World Transformed by
Social Technologies, Forrester analysts Charlene Li and Josh Bern<strong>of</strong>f describe part <strong>of</strong> this
phenomenon as a groundswell, which <strong>the</strong>y define as “a social trend in which people use technologies
to get <strong>the</strong> things <strong>the</strong>y need from each o<strong>the</strong>r, ra<strong>the</strong>r than from traditional institutions like corporations”
(Li & Bern<strong>of</strong>f, 2008, p. 9).
In a 2006 Wired magazine article, Jeff Howe coined <strong>the</strong> term crowd-sourcing to describe “everyday
people using <strong>the</strong>ir spare cycles to create content, solve problems, even do corporate R & D” (Howe,
2006). In his book, Crowdsourcing: Why <strong>the</strong> Power <strong>of</strong> <strong>the</strong> Crowd Is Driving <strong>the</strong> Future <strong>of</strong> Business,
Howe defined crowdsourcing as “<strong>the</strong> act <strong>of</strong> taking a job traditionally performed by a designated agent
(usually an employee) and outsourcing it to an undefined, generally large group <strong>of</strong> people in <strong>the</strong> form
<strong>of</strong> an open call” (Howe, 2008). Howe wrote, “The amount <strong>of</strong> knowledge and talent dispersed among
<strong>the</strong> human race has always outstripped our capacity to harness it. Crowdsourcing corrects that—but
in doing so, it also unleashes <strong>the</strong> forces <strong>of</strong> creative destruction” (Howe, 2008).
Both terms, groundswell and crowdsourcing, are neologisms and as a result many academics may
dismiss <strong>the</strong>m as hype designed to sell books. However, we would caution against a hasty dismissal.
Of course, time will be <strong>the</strong> real test <strong>of</strong> <strong>the</strong>ir relevance. In <strong>the</strong> meantime, we suggest that leaders
should learn about <strong>the</strong> opportunities and threats <strong>of</strong> <strong>the</strong> social revolution. We are most concerned
about <strong>the</strong>se ideas from a knowledge point <strong>of</strong> view and <strong>the</strong>refore we will not consider, in any great
detail, <strong>the</strong> related marketing, public relations, or economic issues.
8. The social revolution
But what has changed to empower <strong>the</strong>se communities with such power? Surely, groups <strong>of</strong> passionate
people have long yearned for <strong>the</strong> opportunity to influence or perhaps even hijack issues. Of course,
<strong>the</strong>re have been many times in history when large groups congregated to spark change. However, <strong>the</strong>
logistics with massing large groups can be very cumbersome, expensive, and difficult to
communicate.
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John Girard
Enter Web 2.0—a World Wide Web based on collaboration ra<strong>the</strong>r than content—and suddenly all <strong>of</strong>
<strong>the</strong>se obstacles evaporate, at least for virtual groups. In <strong>the</strong>ir book Wikinomics: How Mass
Collaboration Changes Everything, authors Dan Tapscott and Anthony Williams describe how a lowcost
collaborative infrastructure is empowering <strong>the</strong> many—<strong>the</strong>y term <strong>the</strong>se “<strong>the</strong> weapons <strong>of</strong> mass
collaboration” (Tapscott & Williams, 2006, p. 11). Tapscott and Williams warn <strong>the</strong>se weapons support
a new level <strong>of</strong> collaboration that will turn <strong>the</strong> economy upside down and may well facilitate <strong>the</strong>
destruction <strong>of</strong> organizations who fail to adjust.
To understand <strong>the</strong> power <strong>of</strong> <strong>the</strong>se new collaborative tools, consider <strong>the</strong> transformation <strong>of</strong> <strong>the</strong> travel
industry. A travel pr<strong>of</strong>essional’s business was all about knowledge and access to information, much <strong>of</strong>
which she paid to access. Over time, <strong>the</strong>y developed a clientele who knew <strong>the</strong>m and trusted <strong>the</strong>ir
judgment. They knew that she had incredible knowledge <strong>of</strong> many destinations and she had access to
information, like wholesale prices, that was only available to <strong>the</strong> industry insiders. Today that has
changed as most mere mortals now have more access to higher fidelity information, usually at no
cost, than <strong>the</strong> pr<strong>of</strong>essionals <strong>of</strong> just a couple <strong>of</strong> years ago. Through sites such as Tripadvisor.com,
SeatGuru. com, Wikitravel.com, and Orbitz.com, to name just a few, we are now able to gain <strong>the</strong>
valuable knowledge we need to make travel decisions.
Consider <strong>the</strong> following example from our recent trip to speak at an International Knowledge
Management conference in Cape Town, South Africa. Whenever we travel to a new destination for
business, we try to build in a little time to learn about <strong>the</strong> host country. We decided to arrive in Cape
Town a few days early to tour <strong>the</strong> city and surrounding area. Our first real question was where to stay.
A quick search on Tripadvisor.com revealed one particular guesthouse, An African Villa, received rave
reviews from many people. In fact, virtually everyone who had stayed <strong>the</strong>re rated <strong>the</strong> hotel as five
stars, resulting in An African Villa being rated as <strong>the</strong> best hotel in Cape Town. In addition to <strong>the</strong> high
quantitative scores <strong>the</strong> qualitative comments were glowing—most reviewers took <strong>the</strong> time to describe
in detail just how happy <strong>the</strong>y were with <strong>the</strong> property and <strong>the</strong> staff. Finally, we reviewed <strong>the</strong> photos
provided by <strong>the</strong> many happy visitors. We thought this would be a great place to stay and decided to
book. We made this decision because we trusted <strong>the</strong> 100 or so people who had provided feedback to
Tripadvisor.com.
Our next challenge was to decide what to do before <strong>the</strong> conference. We only had a couple <strong>of</strong> days to
see <strong>the</strong> sights so we decided it would be best to hire a guide for our visit. We searched several travel
sites but did not find any guides that seemed to meet our needs. We decided to contact An African
Villa and ask <strong>the</strong>ir advice. Suddenly we were treating An African Villa as a trusted authority as we
assumed that <strong>the</strong>y would not recommend anyone who might negatively influence our experience and
ultimately our rating <strong>of</strong> <strong>the</strong> hotel. Within a day, we had an eMail recommending a couple who were
certified guides. One more eMail and we were set. As it turns out, we could not have been happier
with ei<strong>the</strong>r <strong>the</strong> property or our guide. This is an example <strong>of</strong> <strong>the</strong> power <strong>of</strong> collaboration and knowledge
sharing. Through <strong>the</strong> collective knowledge <strong>of</strong> many Tripadvisor.com contributors, none <strong>of</strong> whom is
paid for <strong>the</strong>ir services, we gained invaluable insight to make our decision. Frankly, it would be virtually
impossible for a pr<strong>of</strong>essional travel consultant in our home city to be able to provide this service.
9. Social media knowledge-sharing tools
There are many examples <strong>of</strong> how organizations are using <strong>the</strong> collaborative forces <strong>of</strong> <strong>the</strong> Internet to
create and exchange knowledge. The question is, What are you doing in your organization to exploit
<strong>the</strong> weapons <strong>of</strong> mass collaboration? Virtually every day, new Web tools are being developed <strong>of</strong>fering
new ways to foster collaboration and knowledge sharing. Our aim is not to endorse particular tools,
but ra<strong>the</strong>r to encourage leaders to think about how <strong>the</strong>se tools will help <strong>the</strong>m achieve a competitive
advantage. Below is a brief summary <strong>of</strong> three tools worthy <strong>of</strong> notice—please remember this list was
current as <strong>of</strong> early 2009, and almost certainly <strong>the</strong>re will be new entrants very soon. We encourage you
to learn about social media and decide what tools are best suited to your needs.
Earlier we provided Howe’s definition <strong>of</strong> crowdsourcing: “<strong>the</strong> act <strong>of</strong> taking a job traditionally performed
by a designated agent (usually an employee) and outsourcing it to an undefined, generally large
group <strong>of</strong> people in <strong>the</strong> form <strong>of</strong> an open call” (Howe, 2008). One great example <strong>of</strong> this idea in practice
is <strong>the</strong> InnoCenter (see http://www.innocenter.com), which aims to connect “companies, academic
institutions, public sector and non-pr<strong>of</strong>it organizations, all hungry for breakthrough innovation, with a
global network <strong>of</strong> more than 160,000 <strong>of</strong> <strong>the</strong> world’s brightest mind” (“InnoCenter About Us,” 2009). By
connecting knowledge seekers with knowledge solvers, crowdsourcing may be a way for
10

John Girard
organizations to gain knowledge from outside sources that would be very expensive to develop inhouse.
Could this help you solve organizational challenges?
The single largest cultural-technological innovation <strong>of</strong> <strong>the</strong> 21st century is <strong>the</strong> social networking Web
site. These sites help people connect with o<strong>the</strong>r people to collaborate in an online environment. Some
are designed for connecting friends and family (e.g., Facebook or MySpace), while o<strong>the</strong>rs facilitate
pr<strong>of</strong>essional connection (e.g., LinkedIn). Here we are, just a few years into <strong>the</strong> new millennium, and it
is hard to remember what <strong>the</strong> world was like before Facebook (founded 2004), MySpace (founded
2003), or LinkedIn (founded 2003). How can you use social networking?
Wikis are <strong>the</strong> epitome <strong>of</strong> what many people think <strong>of</strong> Web 2.0—a collaborative Web page that is quick
and easy to edit. In fact, <strong>the</strong> name “Wiki” is a Hawaiian word meaning fast. By far <strong>the</strong> best known
example <strong>of</strong> a wiki is <strong>the</strong> infamous Wikipedia, <strong>the</strong> self-proclaimed free encyclopedia. During a recent
fund-raising campaign, Wikipedia founder Jimmy Wales wrote,
Wikipedia is driven by a global community <strong>of</strong> more than 150,000 volunteers—all
dedicated to sharing knowledge freely. Over almost eight years, <strong>the</strong>se volunteers have
contributed more than 11 million articles in 265 languages. More than 275 million people
come to our website every month to access information, free <strong>of</strong> charge and free <strong>of</strong>
advertising. But Wikipedia is more than a website. We share a common cause: Imagine
a world in which every single person on <strong>the</strong> planet is given free access to <strong>the</strong> sum
<strong>of</strong> all human knowledge. That’s our commitment. (Wales, 2008, p. 1)
Consider <strong>the</strong> impact <strong>of</strong> Wales’s second to last sentence at <strong>the</strong> micro level; imagine how this might
work in your organization. Perhaps your vision might be Imagine an organization in which every single
person on <strong>the</strong> team is given free access to <strong>the</strong> sum <strong>of</strong> all organizational knowledge. A wiki might be a
very low-cost, high-return tool for collaboration and knowledge sharing in your organization.
10. Conclusion
For <strong>the</strong> past two decades, public and private sector executives have struggled to develop effective
ways <strong>of</strong> sharing what <strong>the</strong>ir organizations know. Driven by concerns such as downsizing, <strong>the</strong>
impending retirement <strong>of</strong> baby boomers, terrorism, <strong>the</strong> troubling economy, and a host <strong>of</strong> o<strong>the</strong>r
organizational challenges, many leaders have sought ways to share knowledge with both internal and
external stakeholders. Despite <strong>the</strong> best efforts <strong>of</strong> many innovative leaders, few organizations have
achieved <strong>the</strong> desired level <strong>of</strong> knowledge sharing. This is certainly not due to a lack <strong>of</strong> energy,
enthusiasm, or excitement on <strong>the</strong> part <strong>of</strong> executives.
Today, ample resources exist for <strong>the</strong> leaders who wish to manage <strong>the</strong>ir organizational intellectual
property - many proven tools and techniques exist to manage today’s knowledge assets. However,
what about <strong>the</strong> future? Will today’s baby-boomer based practices pass <strong>the</strong> test <strong>of</strong> time? Are our
current processes <strong>the</strong> most relevant ones for <strong>the</strong> next generation <strong>of</strong> organizational leaders? We are
seeing some very promising results from third-generation knowledge projects, which focus on
connecting people and facilitating collaboration. Many organizations are now reaping <strong>the</strong> benefits <strong>of</strong>
using social media such as wikis for collaboration and social networking tools for connecting people.
These emerging tools and techniques provide flexible, agile, and intuitive solutions for connecting
people with people and facilitating coordination, communication, and collaboration.
This paper focused on what we should be doing now (or soon) to ensure <strong>the</strong> next generation <strong>of</strong>
organizational leaders know what we knew. In o<strong>the</strong>r words, are we creating organizational memories
today, which will be useful to <strong>the</strong> leaders who follow us?
References
Allee, V. (2003). The future <strong>of</strong> knowledge : increasing prosperity through value networks. Amsterdam ; Boston:
Butterworth-Heinemann.
Bennet, A., & Bennet, D. (2004). Organizational survival in <strong>the</strong> new world : <strong>the</strong> intelligent complex adaptive
system. Amsterdam ; Boston: Butterworth-Heinemann.
Davenport, T. H., & Prusak, L. (1998). Working knowledge : how organizations manage what <strong>the</strong>y know. Boston,
Mass: Harvard Business School Press.
DoD News Briefing - Secretary Rumsfeld and Gen. Myers. (2002, 12 February). Retrieved 6 July, 2006, from
http://www.defenselink.mil/transcripts/2002/t02122002_t212sdv2.html
Drucker, P. F. (1988). The coming <strong>of</strong> <strong>the</strong> new organization. Harvard Business Review, 66(1), 45.
Foster, L. G. (1983). The Johnson & Johnson Credo and <strong>the</strong> Tylenol Crisis. New Jersey Bell Journal, 6(1), 6.
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Girard, J. P., & Girard, J. L. (2009). A Leader’s Guide to Knowledge Management: Drawing on <strong>the</strong> Past to
Enhance Future Performance. New York: Business Expert Press.
Howe, J. (2006). The rise <strong>of</strong> crowdsourcing. Wired, 14(6). Retrieved January 15, 2009, from
http://www.wired.com/wired/archive/14.06/crowds.html
Howe, J. (2008). Crowdsourcing: Why <strong>the</strong> power <strong>of</strong> <strong>the</strong> crowd is driving <strong>the</strong> future <strong>of</strong> business (1st ed.). New
York: Crown Business.
InnoCenter about us. (2009). Retrieved January 15, 2009, from http://innocentive .com/about-us-openinnovation.php
Johnson, J. Our Credo. Retrieved 6 July, 2006, from http://www.jnj.com/our_company/our_credo/index.htm
Laudon, K. C., & Laudon, J. P. (2005). Essentials <strong>of</strong> management information systems: Managing <strong>the</strong> digital fi rm
(6th ed.). Upper Saddle River, NJ: Prentice Hall.
Li, C., & Bern<strong>of</strong>f, J. (2008). Groundswell: Winning in a world transformed by social technologies. Boston: Harvard
Business Press.
Michael, H. (2002). Teradata Takes Data Mining Beyond Beer and Diapers. Dayton, Ohio: NCR Corporation.
Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create <strong>the</strong>
dynamics <strong>of</strong> innovation. New York: Oxford University Press.
O’Dell, C., & Grayson, C. J. (1998). If only we knew what we know: Identification and transfer <strong>of</strong> internal best
practices. California Management Review, 40(3), 154–174.
Plain English Campaign. Retrieved 6 July, 2006, from www.plainenglish.co.uk
Tapscott, D., & Williams, A. D. (2006). Wikinomics: How mass collaboration changes everything. New York:
Portfolio.
Wales, J. (2008). An appeal from Wikipedia founder. Retrieved December 24, 2008, from
http://wikimediafoundation.org/wiki/Donate/Letter/en?utm_source=2008_jimmy_letter&utm_medium=sitenoti
ce&utm_campaign=fund raiser2008#appeal
12

Intellectual Capital Accounting – How to Measure <strong>the</strong>
Unmeasurable
Ludo Pyis
AREOPA, Belgium
Intellectual capital building blocks, elements, variables and indicators
Studies have managed to reach a consensus around <strong>the</strong> building blocks <strong>of</strong> intellectual capital. There
seems to be some agreement that human capital and structural capital are two <strong>of</strong> <strong>the</strong> corner stones,
although <strong>the</strong> term organisational capital is <strong>of</strong>ten used for <strong>the</strong> latter. However, talk about relational
capital and ideas seem to become a little more confused: customer capital is certainly one <strong>of</strong> <strong>the</strong>
aspects here although in some publications this classification comprises alliance and partner capital.
In trying to capture <strong>the</strong> entire picture, social capital and even cultural capital may be added to <strong>the</strong> list.
Never<strong>the</strong>less, once <strong>the</strong> main blocks are defined, specialists descend one step fur<strong>the</strong>r into <strong>the</strong> depths
<strong>of</strong> intellectual capital secrets looking to sum up all <strong>the</strong> elements that are part <strong>of</strong> <strong>the</strong> inventory <strong>of</strong> each
major sphere. The ideas become more dispersed here but careful harvesting yields a list <strong>of</strong> 100 to
150 elements.
The next development concentrates on <strong>the</strong> attributes, variables and parameters that are linked to or
characteristic <strong>of</strong> <strong>the</strong> element at stake. And that is where it stops. Intellectual capital reporting is
primarily limited to indicators, which leads to <strong>the</strong> pertinent question…"What’s <strong>the</strong> use <strong>of</strong> all this?"
Some managers who are confronted with <strong>the</strong> (sales) talk from intellectual capital accounting
promoters are lured into starting an exercise, which is <strong>of</strong>ten called: <strong>the</strong> putting toge<strong>the</strong>r <strong>of</strong> an
Intellectual Capital Balance Sheet (Wissensbilanz in Germany and Austria). All <strong>of</strong> <strong>the</strong>se projects start
with <strong>the</strong> listing <strong>of</strong> chapters and elements and generate or calculate indicators at best. In many cases
<strong>the</strong>se Intellectual Capital Balance Sheets are <strong>the</strong>n used for internal and/or external communications,
i.e. as propaganda to show <strong>the</strong> innovative spirit <strong>of</strong> management. And <strong>the</strong>n <strong>the</strong>re is silence…
1. What is missing? The answer is simple and tw<strong>of</strong>old:
The value <strong>of</strong> intellectual capital assets needs to be expressed in ONE, and <strong>the</strong> same, common
denominator so that values can be added up and compared, i.e. money, <strong>the</strong> only measure known and
understood by everyone;
The report format needs to be clear, known and understood by <strong>the</strong> average manager. Maybe a
classical (financial) balance sheet format might fulfil this requirement.
Designing a report in balance sheet format is simple. Everybody talks about intellectual capital assets,
which requires ordering <strong>the</strong>se assets in a similar manner to <strong>the</strong> financial assets on a conventional
balance sheet. This task is relatively easy. Financial assets are financed with equity (shareholders'
capital) and external funds (banks, financial institutions, suppliers, creditors, etc.). The 'financing' <strong>of</strong>
intellectual capital assets may be approached in exactly <strong>the</strong> same way. These assets are ei<strong>the</strong>r
owned by <strong>the</strong> company (explicit) or are 'borrowed' by <strong>the</strong> company (tacit). Understanding this leads to
<strong>the</strong> construction <strong>of</strong> <strong>the</strong> liabilities side <strong>of</strong> <strong>the</strong> Intellectual Capital Balance Sheet.
2. Intellectual Capital Accounting
If <strong>the</strong> Intellectual Capital Balance Sheet is what we want, <strong>the</strong>n we have to decide what we need to do
in order to get this report. Applying <strong>the</strong> basic accounting rules seems to get us quite far:
Designing an Intellectual Capital Chart <strong>of</strong> Accounts is not complicated because <strong>the</strong> asset list is pretty
clear and complete;
Intellectual capital accounting rules are a bit more complicated. We start by looking for <strong>the</strong> 'events'
that drive intellectual capital value in much <strong>the</strong> same way as we do for 'events' that drive general
accounting. Things such as incoming invoices and bank statements, for example, should help us
<strong>the</strong>re;
13

Ludo Pyis
Intellectual capital valuation rules are <strong>the</strong> core <strong>of</strong> <strong>the</strong> matter. In general accounting rules have been
defined to calculate <strong>the</strong> value <strong>of</strong> stock, estimate <strong>the</strong> amount <strong>of</strong> bad debts, convert items expressed in
foreign currencies, and depreciate fixed assets. Financial accounting prepares a picture <strong>of</strong> <strong>the</strong> past.
Intellectual capital accounting looks to <strong>the</strong> future.
The main challenge is to come up with a valuation system which is transparent, auditable, repeatable
(objective), and…simple. This basic principle is based on two components:
A component covering <strong>the</strong> book value <strong>of</strong> <strong>the</strong> element, based on items such as acquisition or
construction costs, depreciation and amortisation;
A component covering <strong>the</strong> future potential value <strong>of</strong> <strong>the</strong> element, probably <strong>the</strong> net present value <strong>of</strong>
future cash streams.
The former follows <strong>the</strong> same principles used for tangible assets, e.g. <strong>the</strong> building <strong>of</strong> a new plant
(which is comparable to building knowledge in a staff member). The latter requires more complex
econometrical formulas based on parameters and variables typical for each element.
3. Double Counting
One <strong>of</strong> <strong>the</strong> main points <strong>of</strong> concern in intellectual capital accounting is <strong>the</strong> question <strong>of</strong> avoiding double
counting. Human Capital is needed to realise Customer Capital. Adding up both values may result in
double counting <strong>of</strong> <strong>the</strong> same potential. The 4-leaf model helps in visualising this phenomenon.
3.1 Is Human Capital Euro equal to Structural Capital Euro?
Ano<strong>the</strong>r major concern is <strong>the</strong> equality <strong>of</strong> <strong>the</strong> unit <strong>of</strong> measurement used, i.e. <strong>the</strong> monetary unit <strong>of</strong> all <strong>the</strong>
asset values. Expressing all values in Euro for example does not mean that all <strong>the</strong>se values are <strong>of</strong> <strong>the</strong>
same nature. Special care has to be taken to assure comparability.
4. Conclusion
A lot has been done, but much remains to be done. Unless we are able to translate and present
intellectual capital into a language and format that managers understand, interest in this area will
remain primarily academic. Auditors will have to be convinced that intellectual capital valuations are
based on sound rules that are transparent, objective and auditable. Equally, auditors will have to
'open up' to <strong>the</strong> need <strong>of</strong> <strong>the</strong> knowledge economy where <strong>the</strong> majority <strong>of</strong> <strong>the</strong> assets utilised in a
company are not presently found on <strong>the</strong> balance sheet.
14

Academic
Research
Papers
15

Social Capital Management in Iranian Knowledge-Based
SMEs
Khodayar Abili 1 and Mahyar Abili 2
1
University <strong>of</strong> Tehran, Iran
2
Badi’a Consulting Firm, Tehran, Iran
abili@ut.ac.ir
abili_hrm@yahoo.com
mahyar.abili@gmail.com
Abstract: The role <strong>of</strong> knowledge-based SMEs, particularly high tech SMEs, in <strong>the</strong> development <strong>of</strong> <strong>the</strong> society
and <strong>the</strong>ir surrounding environment requires <strong>the</strong>m to develop an organizational social capital that can help <strong>the</strong>m to
gain more potential market opportunities and to achieve and sustain <strong>the</strong>ir competitive advantage. The importance
<strong>of</strong> social capital and its effective management approach in organizations, particularly knowledge-based
organizations, for assuring <strong>the</strong>ir ongoing and sustainable development and competitive advantage has been a
matter <strong>of</strong> serious discussion in recent years. Considering <strong>the</strong> recent expansion and growth <strong>of</strong> knowledge-based
SMEs in Iran and <strong>the</strong> role and importance <strong>of</strong> <strong>the</strong>ir social capital in fur<strong>the</strong>r development <strong>of</strong> Iranian society, an
effective system <strong>of</strong> management <strong>of</strong> social capital <strong>of</strong> <strong>the</strong>se enterprises is a matter <strong>of</strong> concern <strong>of</strong> <strong>the</strong>ir top
managers. Therefore, a blend (quantitative and qualitative) multiple case study was conducted with a selected
number <strong>of</strong> SMEs to assess <strong>the</strong>ir existing social capital, to identify factors which might have positive or negative
impacts on <strong>the</strong> promotion <strong>of</strong> <strong>the</strong>ir social capital and to propose an effective approach for its management. To
conduct <strong>the</strong> study, a purposive sample <strong>of</strong> sixteen R&D, consulting and training SMEs was selected. To collect <strong>the</strong>
data, a stratified random sample <strong>of</strong> 192 staff members (knowledge workers) and managers <strong>of</strong> <strong>the</strong> selected SMEs
were given a 24-item questionnaire which was designed based on three dimensions (structural, relational and
cognitive) <strong>of</strong> Organizational Social Capital Model used by Nahapiet and Ghoshal in <strong>the</strong>ir study. This was followed
by semi-structured interviews with a selected number <strong>of</strong> research participants for completion and fur<strong>the</strong>r
clarification <strong>of</strong> collected data. Findings indicated that <strong>the</strong> selected knowledge-based SMEs are not benefiting from
a desirable social capital and, <strong>the</strong>refore, some measures need to be taken to improve <strong>the</strong> situation. Based on <strong>the</strong>
findings <strong>of</strong> this study, suggestions were provided for <strong>the</strong> promotion <strong>of</strong> <strong>the</strong>ir social capitals and <strong>the</strong>ir more effective
management.
Keywords: social capital, organizational social capital, knowledge-based SME, structural capital, relational
capital, cognitive capital
1. Introduction
In more developed societies, knowledge-based SMEs, with <strong>the</strong>ir high flexibility and fast-responsive
nature and high ability in coping with market needs, form a large and vital part <strong>of</strong> modern societies
and are gaining a larger share and playing a more effective role in <strong>the</strong>ir market (Abili and Movaffaghi,
2008). These knowledge-based enterprises are developing a social capital that can help <strong>the</strong>m
achieve <strong>the</strong>ir sustainable competitive advantage. On contrary, in less developed societies, until
recently, social capital has not been regarded as an important factor that can contribute to
performance improvement, growth and success <strong>of</strong> organizations.
2. What is organizational social capital?
Social capital is a concept which has been accepted as a valuable asset for protection and safety <strong>of</strong>
society, empowerment <strong>of</strong> organizations, and likelihood <strong>of</strong> civil society (Timberlake, 2005). It plays an
important role in meeting organizations’ needs and contributing to <strong>the</strong>ir successful survival in today’s
world <strong>of</strong> competition. It acts as a management tool for fulfilling organizations’ goals more effectively
and with less cost. In o<strong>the</strong>r words, social capital facilitates knowledge sharing, value creation,
competitive advantage, better and faster performance, and fur<strong>the</strong>r development <strong>of</strong> organizations (Abili
and Faraji, 2009). It includes norms, values, orientations, networks and social relations governing
behaviors and interactions among individuals. It also facilitates individuals’ mutual cooperation and
coordination for shared interests and enables <strong>the</strong>m to act collectively.
Social capital does exist in three levels. At micro level, it is formed wherever human relations exist. At
middle level, it is formed among members <strong>of</strong> a group. Relations created as a result <strong>of</strong> group
membership and belongingness can provide opportunities for development <strong>of</strong> social capital. At macro
level, social capital exists in larger social environments and includes formal relations and structures,
such as rules and regulations and legal frameworks (Akdere, 2008).
17

Khodayar Abili and Mahyar Abili
There are two types <strong>of</strong> internal and external social capital. Internal social capital refers to structure
and content <strong>of</strong> relations among employees as well as organizational units. According to Nahapiet and
Ghoshal (1998), this type <strong>of</strong> organizational social capital has three dimensions <strong>of</strong> structural, relational
and cognitive. External social capital exits in mutual relations between <strong>the</strong> company and its external
stakeholders and increases organizational predicting capability in interacting with environment and
provides opportunities for management.
According to Nahapiet and Ghoshal (1998), organizational social capital (OSC) is a collection <strong>of</strong>
existing and potential sources resulted from relational network which belongs to individual or a social
unit. As a basis for trust and cooperation among individuals, it helps to lead social relations and
improves organizational performance.
Organizational social capital exists in structures and processes <strong>of</strong> social exchange and it is <strong>the</strong> only
factor which provides sustainable organizational advantage. It reflects quality <strong>of</strong> relations in
organization and measures interrelatedness among its members (Pastoriza, 2009).
Organizational social capital is a source which reflects <strong>the</strong> nature <strong>of</strong> social relations in an
organization. It is identified through desire for collective goal and shared trust among members <strong>of</strong> an
organization. According to Leana and Van Buren, social capital is an asset which gives benefit to both
individual and organization. The importance <strong>of</strong> organizational social capital is that it causes ga<strong>the</strong>ring
<strong>of</strong> individuals as team members who work toge<strong>the</strong>r to succeed. It also causes <strong>the</strong> integrity <strong>of</strong> staff and
management (Leana and Van Buren, 1999).
Quality <strong>of</strong> organization from social capital perspective is assessed based on <strong>the</strong> characteristics <strong>of</strong>
existing social relations in which employees (a) learn about organizational values and try to gain
<strong>the</strong>m, (b) trust and help each o<strong>the</strong>r and (c) learn about and understand each o<strong>the</strong>r (pastoriza, 2009).
Due to different approaches used in studies on organizational social capital concept and its multidimensional
nature, several models have been developed, including studies by Coleman Model
(1988), Nahapiet and Ghoshal (1998). Leana and Van Buren (1999), Bolino (2002). However, <strong>the</strong>
model developed by Nahapiet and Ghoshal was used as a <strong>the</strong>oretical framework in this study. In this
model, social capital includes relations, orientations, values and norms which enable individuals to act
and behave collectively. It refers to shared goals and values, mutual trust and sympathy, and social
interaction among employees. According to this model, organizational social capital has three
dimensions (Figure 1):
Structural
Dimension
Social
Interaction
Organizational Social Capital
Relational
Dimension
- Trust
- Sympathy
Cognitive
Dimension
Shared goals
Figure 1: Theoretical framework <strong>of</strong> research (based on Nohapiet and Ghoshal model)
Structural dimension which refers to non-personal links between individuals or units. It shows who
ands how employees have access to and how employees interact in order to learn, share and
exchange information, ideas and knowledge.
18

Khodayar Abili and Mahyar Abili
Relational dimension which refers to interpersonal relations among individuals. It focuses on
special relations, such as respect and friendship which influence employees' behavior. It shows
how much trust exists among employees, how much <strong>the</strong>y help each o<strong>the</strong>r when needed, how
honest <strong>the</strong>y are with each o<strong>the</strong>r and how much <strong>the</strong>y share <strong>the</strong>ir feelings and respect each o<strong>the</strong>r.
Contrary to structural capital which emphasizes quantity <strong>of</strong> relations, relational capital focuses on
quality <strong>of</strong> relations in organizations.
Cognitive dimension which refers to sources which provide shared interpretations and concepts
among individuals. It shows how much employees have clear understanding and perception <strong>of</strong>
organizational goals and values; and how much <strong>the</strong>y accept and are committed to <strong>the</strong>m.
3. Problem statement
In Iran, <strong>the</strong> number <strong>of</strong> SMEs is growing rapidly. Although <strong>the</strong>y vary widely in terms <strong>of</strong> <strong>the</strong>ir nature, size
and region, most <strong>of</strong> <strong>the</strong>se SMEs are private/family-owned or cooperative mainly high tech and
knowledge-based manufacturing or service-providing firms with little knowledge <strong>of</strong> social capital
concept and unaware <strong>of</strong> its importance and necessity for <strong>the</strong>ir fur<strong>the</strong>r development and success.
Considering <strong>the</strong> role and importance <strong>of</strong> knowledge-based SMEs in fur<strong>the</strong>r development <strong>of</strong> Iranian
society and due to <strong>the</strong> importance <strong>of</strong> social capital in <strong>the</strong>se organizations, an attempt was made to
conduct a study to assess <strong>the</strong> current situation <strong>of</strong> Iranian knowledge-based SMEs regarding <strong>the</strong>ir
social capital in order to provide <strong>the</strong>m with strategies for promoting <strong>the</strong>ir social capital and managing it
more effectively. It is believed that such a study can not only promote <strong>the</strong>ir managers’ understanding
<strong>of</strong> <strong>the</strong>ir social capital, but also help <strong>the</strong>m to identify <strong>the</strong>ir social capital-related strengths and
weaknesses and to take actions needed to improve <strong>the</strong> situation. It is also believed that improving
social capital in <strong>the</strong>se enterprises can help <strong>the</strong>m to create more potential market opportunities and to
contribute toward sustainable economic development <strong>of</strong> <strong>the</strong>ir surrounding environment.
To conduct this study, <strong>the</strong> following questions were addressed:
1. What is <strong>the</strong> current situation <strong>of</strong> social capital (structural, relational and cognitive) in Iranian
knowledge-based SMEs?
2. What can be done to promote social capital and to manage it more effectively in Iranian
knowledge-based SMEs?
4. Research methodology
A two-phase (explorative and actual), mixed (qualitative and quantitative) and multiple case study was
conducted to assess <strong>the</strong> social capital <strong>of</strong> a selected number <strong>of</strong> Iranian knowledge-based SMEs.
In <strong>the</strong> first phase, following a brief review <strong>of</strong> related literature on SMEs and Knowledge-based
organizations, different social capital models were also reviewed and analyzed in order to select <strong>the</strong>
one to be used as a <strong>the</strong>oretical framework for data collection in <strong>the</strong> next phase (Nahapiet and
Ghoshal Model).
In <strong>the</strong> second phase (data collection stage), a stratified random sample <strong>of</strong> 192 knowledge workers
from different genders, educational backgrounds, ages, occupational types and length <strong>of</strong> <strong>the</strong>ir work
experience, 16 top managers and 16 HR managers <strong>of</strong> participating SMEs were selected to participate
in this study (Table 1):
Table 1: Sample size
Type <strong>of</strong> SMEs # <strong>of</strong> firms
#<strong>of</strong> top
managers
# <strong>of</strong> HR managers
# <strong>of</strong> Knowledge
workers
- R&D centers
5 5 5 55
- Consulting firms
5 5 5 62
- Training institutes
6 6 6 75
Total
16 16 16 192
To collect data, a 24-item questionnaire (appendix 1) was used which was designed based on three
dimensions <strong>of</strong> organizational social capital model (structural, relational and cognitive) developed by
19

Khodayar Abili and Mahyar Abili
Nahapiet and Ghoshal (1998). This instrument included items used more frequently in previouslydeveloped
instruments. The questionnaire had three parts: Part one (structural dimension) includes
seven questions related to interaction <strong>of</strong> personnel for learning and sharing information. Part two
(relational dimension) includes eleven questions related to trust (counting on each o<strong>the</strong>r regarding
<strong>the</strong>ir needs and sensitive and important issues) and sympathy (sharing feelings and emotional
support for each o<strong>the</strong>r) <strong>of</strong> personnel. Part three (cognitive dimension) includes six questions dealing
with personnel’s agreement on and committed to shared missions, values, vision and goals.
Validity <strong>of</strong> <strong>the</strong> instrument was approved by assessing <strong>the</strong> degree to which its questions were related
to <strong>the</strong> subject under study. Reliability <strong>of</strong> <strong>the</strong> instrument was tested and approved statistically (table 2):
Table 2: Reliability <strong>of</strong> questionnaire
Indicators Questions Cronbach's alpha
Social capital dimensions 1-24 0.9744
- Cognitive 1,5,10,15,18,22 0.8971
- Relational 2,4,6,7,8,11,13,14,17,23,24 0.9558
- Structural 3,9,12,16,19,20,21 0.8996
For completion and fur<strong>the</strong>r clarification <strong>of</strong> collected data, semi-structured interviews were conducted
with a selected number <strong>of</strong> research participants (20 knowledge workers, five top managers and five
HR managers).
5. Findings and conclusions
5.1 Current situation <strong>of</strong> social capital in selected SMEs
Based on <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> data collected though administering questionnaires and conducting
interviews, research findings indicate that <strong>the</strong> current situation <strong>of</strong> social capital in Iranian knowledgebased
SMEs is not that desirable. This is due to <strong>the</strong> fact that in many <strong>of</strong> <strong>the</strong>se enterprises,
technology-related issues are paid more attention compared to social capital-related concerns.
Therefore, human resource managers are constantly challenging with accepting more responsibility
toward improving organizational social capital and using opportunities more effectively to have more
impact on <strong>the</strong>ir senior manager’ social capital-related decisions. However, as indicated in table 3, <strong>the</strong>
average score in all three dimensions <strong>of</strong> social capital (cognitive, relational and structural) is higher in
R&D centers compared to consulting firms and training institutes. Therefore it can be concluded that
<strong>the</strong> current situation <strong>of</strong> social capital is more desirable in R&D centers:
Table 2: Current situation <strong>of</strong> social capital in selected Iranian SMEs
Social
Capital
Dimension
Average
R&D centers Consulting firms Training centers
Standard
deviation
Average
Standard
deviation
Average
Standard
deviation
Cognitive 5.56 0.48 5.24 0.36 4.63 1.07
Relational 5.86 0.48 5.41 0.48 4.62 1.05
Structural 5.57 0.54 5.19 0.61 4.23 0.99
5.2 Solutions for improving social capital in selected SMEs
Measures (solutions) <strong>of</strong>fered by research participants for developing and fur<strong>the</strong>r improving social
capital in Iranian SMEs are divided in three categories:
5.2.1 Individual measures
There was a strong belief among research participants that individual measures, such as mutual
support for and learning about each o<strong>the</strong>r and no hostility and jealousness toward each o<strong>the</strong>r, can
develop and fur<strong>the</strong>r improve organizational social capital in Iranian SMEs:
20

5.2.2 Managerial measures
Khodayar Abili and Mahyar Abili
Research participants believed that through a responsible management and taking <strong>the</strong> following
measures, social capital can be improved in Iranian SMEs:
Paying attention to employees’ interests and experiences and improving <strong>the</strong>ir morale
Developing trust and informal relations among employees through organizing friendly ga<strong>the</strong>rings
for easing <strong>the</strong>ir work-related issues and tensions
Informing employees about <strong>the</strong> organizational goals and values
Increasing employee motivation through reducing feeling <strong>of</strong> discrimination and promoting honesty
and fairness
Developing and empowering employees and providing <strong>the</strong>m with pr<strong>of</strong>essional and job security
Getting employees involved in management decisions and creating an open environment for
presenting <strong>the</strong>ir personal views more freely
5.2.3 Organizational measures
Research participants believed that <strong>the</strong> following organizational measures do have an effective role in
improving social capital in Iranian SMEs:
Promoting a culture <strong>of</strong> meritocracy among employees
Providing employees with organizational support
Reducing hypocrisy among employees
Regarding employees as human beings ra<strong>the</strong>r than working tools
6. Recommendations
Prior to <strong>of</strong>fering any suggestion, it should be pointed out that any activity or measure for
developing and improving social capital in an organization should give employees <strong>the</strong> feeling that
management considers <strong>the</strong>m and <strong>the</strong>ir needs important and <strong>the</strong>y are not regarded as tools. This
will encourage <strong>the</strong>m to internalize organizational values and to build a trust-based relation with
o<strong>the</strong>rs. Of course, top management has a key role in creating this feeling among employees.
Social capital is strongly related to ethics. Therefore, management should be committed to and
behave according to ethics. This will cause employees’ more trust toward management.
Social capital can be fur<strong>the</strong>r developed by creating feeling <strong>of</strong> organizational belongingness in
employees through management sensitivity toward <strong>the</strong>ir pr<strong>of</strong>essional and job-related needs, such
as job security and stability.
Clarity <strong>of</strong> expectations from employees and giving <strong>the</strong>m frank and honest feedback about <strong>the</strong>ir
performance and behavior can lead to increase <strong>of</strong> social capital in organizations.
Social capital can be improved through involving and engaging employees, particularly knowledge
workers, in group and organizational decisions. This will streng<strong>the</strong>n <strong>the</strong>ir social identity and fulfill
<strong>the</strong>ir need for team-working.
References
Abili, K. and Faraji, H., (2009). “A comparative study on organizational social capital in faculties <strong>of</strong> Humanities,
Social and Behavioral Sciences at University <strong>of</strong> Tehran”, Tehran, Iran
Abili, K. and Movaffaghi, H., (2008), Management New Concepts with an Emphasis on Human Resource
Management (in Farsi), 2nd edition, Sargol Publications, Tehran, Iran
Akdere, M. and Roberts, P.B., (2008) “Economics <strong>of</strong> social capital: implications for organizational performance”,
Advances in Developing Human Resources, Vol. 10, No. 6, pp 802-816
Bolino, M.C.; Turnley, W.H. and Bloodgood, J. M., (2002), “Citizenship behavior and creation <strong>of</strong> social capital in
organizations”, Academy <strong>of</strong> Management Review”, Vol. 27, No. 4, pp 505-522
Leana, C.R. and Van Buren, H.J., (1999), Organizational social capital and employment practices”, The Academy
<strong>of</strong> Management Review, Vol. 24, No. 3, pp 538-555
Nahapiet, J. and Ghoshal, S., (1998), “Social capital, intellectual capital and organizational advantage”, The
Academy <strong>of</strong> Management Review, Vol. 23, No. 2, pp 242-266
Pastoriza, D.; Arino, M.A. and Ricart, J.E. (2009), Creating an ethical work context: A pathway to generate social
capital in a firm”, Journal <strong>of</strong> Business ethics, No. 88, pp 477-489
21

Khodayar Abili and Mahyar Abili
Timberlake, S., (2005), “Social capital and gender in workplace”, Journal <strong>of</strong> Management Development, Vol. 24,
No. 1, pp 34-44
7. Appendix 1: Organizational social capital assessment questionnaire
Dear Participant:
This is a questionnaire used for a survey on “Assessing organizational social capital <strong>of</strong> knowledgebased
SMEs in Iran”. This study is aimed to measure <strong>the</strong> extent to which trust, sympathy, cooperation
and shared values exist in selected Iranian SMEs. Your cooperation with this study will help
researcher to collect <strong>the</strong> data needed for answering research questions and to come up with some
recommendations on how to improve social capital in Iranian SMEs. In advance, I appreciate your
participation and sincere responses.
Best wishes,
Khodayar Abili, PhD
Associate Pr<strong>of</strong>essor <strong>of</strong> Higher Education
Faculty <strong>of</strong> Psychology and Education
The University <strong>of</strong> Tehran
abili@ut.ac.ir
abili_hrm@yahoo.com
Organizational information Respondent information
Name <strong>of</strong> organization: Length <strong>of</strong> employment:
Type <strong>of</strong> production/service: Educational background:
Gender:
In this organization:
Number
statements
1 There are shared goals and values among
employees
.
2 Employees can trust <strong>the</strong>ir colleagues when needed
.
3 Employees combine information, ideas and o<strong>the</strong>r
sources to perform <strong>the</strong>ir duties.
4 Employees consider <strong>the</strong>mselves as members <strong>of</strong> a
shared and large family.
5 Employees follow organizational goals and missions
very willingly.
6 There is team-work morale among employees.
7 Employees respect each o<strong>the</strong>r’s feelings.
8 Employees trust each o<strong>the</strong>r.
9 Employees criticize each o<strong>the</strong>r in a healthy and
constructive way.
22
Position:
disagree
somewhat
disagree
somewhat
agree
agree

Khodayar Abili and Mahyar Abili
statements
Number
10 There is a similarity and conformity between
employees’ personal values and organizational goals
and values.
11 Employees can be trusted
.
12 When problems arise, employees discuss issues in
healthy and useful ways.
13 Employees behave sincerely.
14 Employees share <strong>the</strong>ir work-related problems with
o<strong>the</strong>rs freely.
15 Employees agree with what is important for <strong>the</strong>
organization.
16 Employees usually exchange information and views
for making decisions.
17 Employees support each o<strong>the</strong>r emotionally.
18 Employees are committed to organizational goals.
19 Employees usually help <strong>the</strong>ir colleagues.
20 Employees share information willingly and voluntarily.
21 Employees inform each o<strong>the</strong>r about organizational
affairs.
22 Employees have a clear perception <strong>of</strong> organizational
goals and missions.
23 Employees share feelings with each o<strong>the</strong>r.
24 Employees believe that <strong>the</strong>ir organization has good
intentions and goals.
disagree
somewhat
disagree
somewhat
agree
agree
In your opinion, what can be done to develop warm, friendly and positive relations and to increase
trust, cooperation and sympathy among employees? Please explain:
23

Knowledge Transfer in Romanian Universities
Simona Agoston, Ivona Orzea, Alina Mihaela Dima and Simona Vasilache
Academy <strong>of</strong> Economic Studies <strong>of</strong> Bucharest, Romania
Simona.agoston@ase.ro
Ivona.orzea@gmail.com
alinamihaeladima@yahoo.com
simona.vasilache@gmail.com
Abstract: Following <strong>the</strong> sharpening competition in <strong>the</strong> education market and <strong>the</strong> dynamics <strong>of</strong> social, economic
and political changes, educational institutions in general and universities in particular face new challenges
regarding <strong>the</strong> marketisation <strong>of</strong> <strong>the</strong>ir programs and attainment <strong>of</strong> a number <strong>of</strong> candidates, which is able to ensure
<strong>the</strong> sustainable development <strong>of</strong> <strong>the</strong> respective institution. The present paper aims at investigating from different
perspectives <strong>the</strong> knowledge transfer activities in universities and <strong>the</strong> relation between <strong>the</strong> number <strong>of</strong> applications
at a university and <strong>the</strong> knowledge transfer between <strong>the</strong> university and its stakeholders. In general knowledge
transfer activities provide <strong>the</strong> university with positive publicity which consequently leads to a higher candidates’
awareness <strong>of</strong> <strong>the</strong> university and finally to a larger number <strong>of</strong> applications. Knowledge transfer activities can occur
in form <strong>of</strong> knowledge inflow and knowledge outflow. In <strong>the</strong> present paper, both streams have been taken into
consideration in <strong>the</strong> conceptual part as well as in <strong>the</strong> empirical one. From <strong>the</strong> perspective <strong>of</strong> <strong>the</strong> university, <strong>the</strong>re
have been identified four categories <strong>of</strong> transfer partners: business environment, public bodies (universities,
international institutions etc.), current students and o<strong>the</strong>r third parties (alumni, society etc). Considering <strong>the</strong>se
categories, different types <strong>of</strong> knowledge transfer activities are ascertained and analyzed according to different
criteria, such as: periodicity, impact, results etc. After <strong>the</strong> <strong>the</strong>oretical framework is established, <strong>the</strong> second part <strong>of</strong>
<strong>the</strong> study addresses mainly <strong>the</strong> relation between knowledge transfer activities and <strong>the</strong>ir influence on <strong>the</strong> number
<strong>of</strong> applications in a university. The empirical approach relies on <strong>the</strong> findings resulted from <strong>the</strong> <strong>the</strong>oretical research
which was conducted previously. Making use <strong>of</strong> several qualitative and quantitative statistical tools, <strong>the</strong> empirical
study related to <strong>the</strong> aforementioned issue is carried out within <strong>the</strong> Academy <strong>of</strong> Economic Studies <strong>of</strong> Bucharest.
The methods used, in SPSS 19, include regression analysis, to highlight <strong>the</strong> relationship between <strong>the</strong> identified
types <strong>of</strong> knowledge transfer and <strong>the</strong> multi-annual evolution <strong>of</strong> <strong>the</strong> number <strong>of</strong> candidates in <strong>the</strong> entry examination.
The results reveal a unreckoned correlation between <strong>the</strong> dynamics <strong>of</strong> certain knowledge transfer areas and <strong>the</strong>
dynamics <strong>of</strong> <strong>the</strong> university attractiveness on <strong>the</strong> academic market. The main limitations refer to choosing only one
university, and having a restrained time span <strong>of</strong> analysis. The conclusions will allow for an extension <strong>of</strong> <strong>the</strong> study
in a comparative perspective, in similar universities, and on a larger time scale. Also <strong>the</strong>re have been identified
o<strong>the</strong>r highly important external factors such as demographic change, emigration etc., which should be considered
in a fur<strong>the</strong>r study, while trying to establish a relation between knowledge transfer in a university and <strong>the</strong> number
<strong>of</strong> candidates at that university.
Keywords: knowledge transfer, university, transfer partners, academy <strong>of</strong> economic studies <strong>of</strong> Bucharest
1. Introduction
In <strong>the</strong> last few decades <strong>the</strong> economies <strong>of</strong> <strong>the</strong> developed countries became knowledge dependent.
Knowledge turned into <strong>the</strong> key driver <strong>of</strong> sustainable economic growth and productivity. Therefore
economies <strong>of</strong> <strong>the</strong> Western world are becoming increasingly dependent on knowledge producers. An
important amount <strong>of</strong> knowledge is created and provided by universities and research centers. In order
to benefit from this knowledge and to use it to increase <strong>the</strong> common welfare <strong>of</strong> citizens, <strong>the</strong> results <strong>of</strong>
research need to be transferred from <strong>the</strong> university to its stakeholders (Vinig and Rijsbergen, 2008).
This process is known as knowledge transfer. Some authors use <strong>the</strong> terms “Knowledge Sharing” and
“Knowledge Exchange” as synonyms for “Knowledge Transfer”.
Several authors (Argote and Ingram, 2000; Duan et al., 2010; Hubig and Jonen, 2006) define <strong>the</strong>
knowledge transfer as a process by which one individual or organization transmits its experience to
ano<strong>the</strong>r and systematically organized information and skills are exchanged between entities. Authors
argue that <strong>the</strong>re are some factors which facilitate and some o<strong>the</strong>r factors which might hinder
knowledge transfer. In <strong>the</strong> category <strong>of</strong> facilitators can be included determinants such as: commercial
resources <strong>of</strong> a university, research and teaching experience, <strong>the</strong> stock <strong>of</strong> technology, whe<strong>the</strong>r it is
private or public university, <strong>the</strong> personnel’s background, organizational culture, effectiveness <strong>of</strong> <strong>the</strong>
public relations activity, <strong>the</strong> presence <strong>of</strong> a business incubator and science park, agreements with
o<strong>the</strong>r universities, NGOs and private enterprises, membership in social networks, social
connectedness, etc. (Santoro and Bierly, 2006; Santoro and Gopalakrishnan, 2000; Vinig and
Rijsbergen, 2008). Among <strong>the</strong> hindrances we can mention <strong>the</strong> emotional issues, “academical
arrogance” (scientists’ attitude towards business partners, who are “too practice oriented” and
<strong>the</strong>refore might impair <strong>the</strong> quality <strong>of</strong> research results), uncertainty <strong>of</strong> <strong>the</strong> scientific outcome, a poor
24

Simona Agoston et al.
marketing <strong>of</strong> <strong>the</strong> university, bad reputation <strong>of</strong> <strong>the</strong> partner, short term orientation, communication
problems, too strong <strong>the</strong>oretical orientation (Goldfarb and Henrekson, 2003; Hubig and Jonen, 2006;
Ndonzuau et al., 2002).
Knowledge transfer is classified according to different criteria. We can differentiate between personal
and technology transfer (Geuna and Muscio, 2008; Hubig and Jonen, 2006) The first group
summarizes <strong>the</strong> transfer <strong>of</strong> knowledge in form <strong>of</strong> well educated graduates to <strong>the</strong> labour market, in
forms <strong>of</strong> practitioners delivering presentations within academic courses, in form <strong>of</strong> scholarships
granted by organizations to students, prizes and awards for outstanding results, training programs
<strong>of</strong>fered by pr<strong>of</strong>essors to employees etc. In <strong>the</strong> category <strong>of</strong> technology transfer fall joint research
programs with <strong>the</strong> private sector, o<strong>the</strong>r public institutions and NGOs, publishing research results,
consulting services etc. Next we can differentiate between knowledge outflow and knowledge inflow.
Knowledge produced by <strong>the</strong> university and transferred to its stakeholders represents <strong>the</strong> outflow,
while knowledge captured by universities from o<strong>the</strong>r entities represents <strong>the</strong> knowledge inflow.
Considering <strong>the</strong> role played by universities in <strong>the</strong> development <strong>of</strong> <strong>the</strong> society it should exist a balance
between <strong>the</strong> outflow and inflow <strong>of</strong> knowledge. Knowledge can be transferred through formal and
informal channels (Agrawal, 2001; Link et al., 2007). The researchers note a shift from <strong>the</strong> informal
processes to formal ones, once <strong>the</strong> importance <strong>of</strong> knowledge transfer increased in universities and
<strong>the</strong>re were established specialized departments in order to manage this task.
Especially in <strong>the</strong> last ten years it can be observed <strong>the</strong> emergence <strong>of</strong> a large number <strong>of</strong> papers which
examine knowledge transfer activities between universities and industry (business sector) (Agrawal,
2001; Geuna and Muscio, 2008; Hubig and Jonen, 2006; Santoro and Gopalakrishnan, 2000; Yusuf,
2008). Less attention was paid to knowledge transfer between universities and o<strong>the</strong>r important
stakeholders such as students, alumni, society, public institutions etc. Duan et al. (2010) argue that
<strong>the</strong>re are four levels <strong>of</strong> knowledge transfer: <strong>the</strong> individual level, <strong>the</strong> intra-organisational level, <strong>the</strong> interorganisational
level and <strong>the</strong> multinational level. The present paper will focus on <strong>the</strong> knowledge
transfer at inter-organisational level, namely between universities and its stakeholders. From <strong>the</strong>
perspective <strong>of</strong> <strong>the</strong> university, <strong>the</strong>re have been identified four main categories <strong>of</strong> transfer partners:
business environment, public bodies (universities, international associations, high schools etc.),
students and third parties (alumni, society, non-governmental organizations etc.).
2. Knowledge transfer activities within Romanian universities
The knowledge transfer activities between university and its partners were structured in four
categories, each <strong>of</strong> <strong>the</strong>m corresponding to one category <strong>of</strong> stakeholders: knowledge transfer activities
with business environment, knowledge transfer activities with public bodies, knowledge transfer
activities with students, knowledge transfer activities with third parties. The aforementioned
knowledge transfer activities were analyzed on <strong>the</strong> concrete example <strong>of</strong> <strong>the</strong> Academy <strong>of</strong> Economic
Studies <strong>of</strong> Bucharest. To each category <strong>of</strong> knowledge transfer activities <strong>the</strong>re were assigned several
performance indicators, as presented in <strong>the</strong> table (Table 1). These indicators facilitate <strong>the</strong> assessment
<strong>of</strong> <strong>the</strong> overall knowledge transfer activity in <strong>the</strong> University, as illustrated within <strong>the</strong> next chapter <strong>of</strong>
research methodology.
Knowledge transfer between academic institutions and <strong>the</strong> business sector is understood as “any
activities aimed at transferring knowledge or technology that may help ei<strong>the</strong>r <strong>the</strong> company or <strong>the</strong>
academic institute – depending on <strong>the</strong> direction <strong>of</strong> transfer – to fur<strong>the</strong>r pursue its activities” (Arvanitis
et al., 2008, p.1866). The interaction between business sector and science represents a main concern
for economic policy makers, since in <strong>the</strong> knowledge economy science exerts a major influence on
innovation, which is one <strong>of</strong> <strong>the</strong> main sources <strong>of</strong> competitive advantage. Still, <strong>the</strong>re are voices stating
that, in order to counterbalance <strong>the</strong> public underfinancing many universities show <strong>the</strong> tendency <strong>of</strong>
commercialization <strong>of</strong> <strong>the</strong> research results and this might jeopardize <strong>the</strong> fundamental long-term
research and teaching objectives <strong>of</strong> a university and negatively impact on scientific quality (Stephan,
2001; Tijssen, 2004). On <strong>the</strong> o<strong>the</strong>r hand, in <strong>the</strong> USA <strong>the</strong>re is evidence that projects conducted by
universities and financed by private enterprises can meet <strong>the</strong> needs <strong>of</strong> both parties, if a long term
perspective is adopted by both entities. Never<strong>the</strong>less <strong>European</strong> universities are lagging behind in this
aspect (Arvanitis et al., 2008). This might be traced back to <strong>the</strong> time when universities were isolated in
<strong>the</strong>ir ivory tower, being disconnected from practice and to <strong>the</strong> traditional <strong>European</strong> paradigm <strong>of</strong>
university’s scope and mission in society, as opposed to <strong>the</strong> concept <strong>of</strong> entrepreneurial university
(Bratianu, 2001).
25

Simona Agoston et al.
Table 1: Knowledge transfer activities and indicators
Knowledge Transfer Activity Indicators
Joint- research projects financed by business environment
Students internship in companies
Visiting lecturers from business environment
Knowledge transfer with business
environment
Knowledge transfer with public
bodies (universities, international
associations, high schools etc.)
Knowledge transfer with students
Knowledge transfer with third parties
(alumni, society, non-governmental
organizations etc.)
Grants from business environment towards university
Projects financed by business environment conducted within <strong>the</strong>
university
Post-graduate courses for employees
Scholarships granted by business environment to students with
outstanding results
Agreements concluded with foreign universities
Membership in international academic networks
Joint projects with Romanian high schools
Research projects financed by Romanian public institutions
Research projects financed by International public institutions
Scientific output
International exchange programs for students
Facilities in <strong>the</strong> students campus
Joint projects with students organizations
Scholarships granted by university
Project contests for students within <strong>the</strong> university
Summer schools organized by <strong>the</strong> university
Pr<strong>of</strong>essional and social networks for alumni
Social and cultural projects
Ecological initiatives
Joint projects with non-governmental organizations
TOTAL: 4 23
In <strong>the</strong> specialized literature knowledge transfer between universities and business environment has
been researched mainly from <strong>the</strong> perspective <strong>of</strong> joint research projects. We want to broaden this area
<strong>of</strong> transfer by introducing in our analysis several o<strong>the</strong>r activities such as: training <strong>of</strong>fered by university
experts to employees by means <strong>of</strong> post-graduate courses (<strong>the</strong>se might be tailored in order to meet
<strong>the</strong> specific training needs <strong>of</strong> a company), various educational activities (guest speakers from
companies, scholarship programs for students with outstanding results and jointly supervised master
<strong>the</strong>sis and PhDs, internship programs), joint use <strong>of</strong> technical infrastructure, consulting services etc.
An important role within <strong>the</strong> knowledge transfer process is assigned to collaboration with o<strong>the</strong>r public
bodies, like foreign universities, international associations, high schools. This collaboration might
occur in form <strong>of</strong> agreements and joined projects with o<strong>the</strong>r universities, joint research and publishing
activity with o<strong>the</strong>r research institutes (e.g. in Romania Ministry <strong>of</strong> Education and Research, Romanian
Academy, CNCSIS), projects carried out with high schools teachers and pupils etc.
Despite <strong>the</strong> fact that students are <strong>the</strong> main beneficiaries <strong>of</strong> educational services, one can note <strong>the</strong>
lack <strong>of</strong> research regarding <strong>the</strong> knowledge transfer activities between universities and students.
Anyway, <strong>the</strong> reduced amount <strong>of</strong> papers which approach this topic evidence a lack <strong>of</strong> costumer focus
in universities regarding <strong>the</strong> transfer <strong>of</strong> knowledge (Johannesson, 2006). We have identified several
indicators used to ascertain <strong>the</strong> intensity <strong>of</strong> <strong>the</strong> transfer: joint projects with students’ organizations,
summer schools, conferences and o<strong>the</strong>r kinds <strong>of</strong> projects organized for students in <strong>the</strong> institutional
framework <strong>of</strong> a university, access to scientific databases and libraries etc. Whereas <strong>the</strong> transfer <strong>of</strong>
knowledge towards and from students stands for <strong>the</strong> core function <strong>of</strong> a university, <strong>the</strong> delivery <strong>of</strong>
knowledge to society aims mainly at cultural exchange (Hubig and Jonen, 2006) and is embedded in
various collaborations on cultural, ecological and social topics, as depicted in <strong>the</strong> next paragraph.
The role that universities play goes beyond <strong>the</strong> mere impact <strong>the</strong>y have on <strong>the</strong> economic environment.
Universities significantly affect <strong>the</strong> local community (Wright et al., 2008) and <strong>the</strong> society through social
and cultural projects (arts exhibition, movies gala, charity activities, concerts and presentations),
ecological initiatives (recycling projects, promoting alternatives means <strong>of</strong> transportation, organizing
ecological programs and trainings etc.), joint projects with non-governmental organizations and
alumni associations.
26

3. Research methodology
Simona Agoston et al.
Fundamental to <strong>the</strong> strategy <strong>of</strong> science is <strong>the</strong> formulation and testing <strong>of</strong> hypo<strong>the</strong>ses about populations
or <strong>the</strong> effects <strong>of</strong> experimental conditions on criterion variables (Ho, 2006). For that reason <strong>the</strong> first
step <strong>of</strong> <strong>the</strong> research was <strong>the</strong> identification <strong>of</strong> <strong>the</strong> research hypo<strong>the</strong>sis and <strong>the</strong> null hypo<strong>the</strong>sis. Thus:
H1: Knowledge transfer is positively correlated with <strong>the</strong> number <strong>of</strong> candidates for <strong>the</strong> programs <strong>of</strong> <strong>the</strong>
university.
H0: Knowledge transfer is negatively correlated with <strong>the</strong> number <strong>of</strong> candidates for <strong>the</strong> programs <strong>of</strong> <strong>the</strong>
university.
In order to measure <strong>the</strong> knowledge transfer <strong>of</strong> <strong>the</strong> university we used <strong>the</strong> index <strong>of</strong> knowledge transfer
calculated as per <strong>the</strong> following formula:
IKT=∑xi*IKTi (1)
where: IKT – index <strong>of</strong> knowledge transfer <strong>of</strong> <strong>the</strong> university, xi – <strong>the</strong> weight <strong>of</strong> each sub-index in <strong>the</strong>
index <strong>of</strong> knowledge transfer and IKTi – <strong>the</strong> index calculated for each sub category identified for <strong>the</strong>
processes <strong>of</strong> knowledge transfer within <strong>the</strong> university. The weight <strong>of</strong> each sub-index in <strong>the</strong> index <strong>of</strong>
knowledge transfer was identified as a result <strong>of</strong> <strong>the</strong> focus groups organized with 7 experts in <strong>the</strong> field
<strong>of</strong> intellectual capital, members <strong>of</strong> <strong>the</strong> Research Center for Intellectual Capital, held throughout
October 2010. Therefore, based on <strong>the</strong> data ga<strong>the</strong>red from <strong>the</strong> Academy <strong>of</strong> Economic Studies <strong>of</strong>
Bucharest <strong>the</strong> experts were able to identify for each <strong>of</strong> <strong>the</strong> sub categories <strong>of</strong> knowledge transfer
processes within <strong>the</strong> university <strong>the</strong> weight <strong>of</strong> importance. Thus formula (1) becomes:
rd
IKT = 0.30*IKTBusiness + 0.2*IKTPublicBodies + 0.4*IKTStudents+ 0.1*IKT3 Parties (2)
Also, for each <strong>of</strong> <strong>the</strong> sub categories <strong>of</strong> knowledge transfer processes were calculated indexes as <strong>the</strong>
average <strong>of</strong> <strong>the</strong> weights identified in <strong>the</strong> focus groups. For each <strong>of</strong> <strong>the</strong> four categories <strong>of</strong> knowledge
transfer <strong>the</strong> members <strong>of</strong> <strong>the</strong> focus group gave marks to identify <strong>the</strong> growth or <strong>the</strong> decrease <strong>of</strong> <strong>the</strong>
actions identifies in <strong>the</strong> sub categories as compared with <strong>the</strong> previous years. The marking system
used was from 1 = very poor performance to 5 = very good performance. The value <strong>of</strong> <strong>the</strong> indexes for
<strong>the</strong> sub categories and <strong>the</strong> value <strong>of</strong> <strong>the</strong> index <strong>of</strong> knowledge transfer calculated as per formula (2) are
presented in table 2. The data was analyzed using SPSS 19.
Table 2: Index <strong>of</strong> knowledge transfer
Name 2005 2006 2007 2008 2009
Index <strong>of</strong> knowledge transfer with business environment 2.69 2.83 2.98 3 3.28
Index <strong>of</strong> knowledge transfer with public bodies
(universities, international associations, high schools etc.)
1.89 2.78 2.82 2.83 3.5
Index <strong>of</strong> knowledge transfer with students 2.3 2.65 2.76 2.83 3.5
Index <strong>of</strong> knowledge transfer with third parties (alumni,
society, non-governmental organizations etc.)
1.79 2.27 2.64 3 3.75
Index <strong>of</strong> knowledge transfer 2.28 2.69 2.82 2.9 3.46
4. Results and discussions
Correlation is primarily concerned with finding out whe<strong>the</strong>r a relationship exists and with determining
its magnitude and direction. When two variables vary toge<strong>the</strong>r <strong>the</strong>y are said to be correlated.
Accordingly, correlational studies are attempts to find <strong>the</strong> extent to which two or more variables are
related (Field, 2005; Ho, 2006). To quantitatively express <strong>the</strong> extent to which two variables are
related, it is necessary to calculate a correlation coefficient. The correlation coefficients calculated for
our case <strong>of</strong> correlation between <strong>the</strong> index <strong>of</strong> knowledge transfer and <strong>the</strong> numbers <strong>of</strong> candidates for
<strong>the</strong> university are Pearson and Spearman correlation coefficients. In order to test <strong>the</strong> assumptions <strong>of</strong>
<strong>the</strong> two correlation tests a scatterplot diagram was employed (Figure 1).
As can be depicted from figure, <strong>the</strong>re is a linear relationship between <strong>the</strong> variables <strong>of</strong> index <strong>of</strong>
knowledge transfer and number <strong>of</strong> candidates, such that as <strong>the</strong> value <strong>of</strong> <strong>the</strong> index <strong>of</strong> knowledge
transfer increases, <strong>the</strong> number <strong>of</strong> candidates decreases. The figure also shows that <strong>the</strong>
27

Simona Agoston et al.
homoscedasticity assumption is met. Therefore <strong>the</strong> next step in <strong>the</strong> analysis is <strong>the</strong> calculation <strong>of</strong> <strong>the</strong>
two correlation coefficients (Table 2, 3).
Figure 1: Scatterplot diagram
Table 2: Pearson correlation coefficient
Knowledge transfer Index
Number <strong>of</strong> candidates
Table 3: Spearman correlation coefficient
Spearman's rho
index_ranked
stud_ranked
Knowledge transfer
Index Number <strong>of</strong> candidates
Pearson Correlation 1 -.918
Sig. (2-tailed) .028
N 5 5
Pearson Correlation -.918 1
Sig. (2-tailed) .028
N 5 5
index_ranked stud_ranked
Correlation Coefficient 1.000 -.900
Sig. (2-tailed) .037
N 5 5
Correlation Coefficient -.900 1.000
Sig. (2-tailed) .037 .
N 5 5
The correlation between <strong>the</strong> index <strong>of</strong> knowledge transfer and <strong>the</strong> number <strong>of</strong> candidates for <strong>the</strong>
programs <strong>of</strong> <strong>the</strong> university in terms <strong>of</strong> <strong>the</strong> Pearson correlation coefficient is negative and statistically
significant (r = -0.918, p< .005). This means that as <strong>the</strong> value <strong>of</strong> <strong>the</strong> index <strong>of</strong> knowledge transfer
increases, <strong>the</strong> number <strong>of</strong> students for <strong>the</strong> programs <strong>of</strong> <strong>the</strong> university decreases. It is highly important
to note that this interpretation in no way implies causality — that increases in value <strong>of</strong> knowledge
transfer index caused decreases in <strong>the</strong> number <strong>of</strong> candidates for <strong>the</strong> programs <strong>of</strong> <strong>the</strong> university. The
significant relationship merely indicates that <strong>the</strong> two variables covary.
The obtained Spearman rank-order coefficient (rho = -0.90, p < .005) is highly similar in magnitude
and direction to that in <strong>the</strong> Pearson correlation table (Table 2). Thus, similar to <strong>the</strong> Pearson
coefficient, <strong>the</strong> Spearman coefficient indicates that as <strong>the</strong> value <strong>of</strong> <strong>the</strong> knowledge transfer index
increases <strong>the</strong> number <strong>of</strong> candidates for <strong>the</strong> programs <strong>of</strong> <strong>the</strong> university decreases.
28

Simona Agoston et al.
Regression and correlation are closely related. Both techniques involve <strong>the</strong> relationship between two
variables, and <strong>the</strong>y both utilize <strong>the</strong> same set <strong>of</strong> paired scores taken from <strong>the</strong> same subjects. However,
whereas correlation is concerned with <strong>the</strong> magnitude and direction <strong>of</strong> <strong>the</strong> relationship, regression
focuses on using <strong>the</strong> relationship for prediction (Ho, 2006). The results <strong>of</strong> <strong>the</strong> linear regression are
presented in table 4, 5, 6.
Table 4: Model summary
Model
R
R Square
Adjusted R Square
Std. Error <strong>of</strong> <strong>the</strong> Estimate
1 .918 a .843 .790 453.58973
Table 5: ANOVA
1
Model
Sum <strong>of</strong> Squares
Df
Mean Square
Regression 3303101.858 1 3303101.858 16.054 .028 a
Residual 617230.942 3 205743.647
Total 3920332.800 4
a. Predictors: (Constant), Knowledge transfer Index
Table 6: Coefficients table
Unstandardized Coefficients
Standardized
Coefficients
Model B Std. Error Beta t Sig.
1
(Constant) 12175.947 1522.199 7.999 .004
Knowledge transfer Index -2135.953 533.082 -.918 -4.007 .028
The prediction equation is:
Y' = A + B * X (3)
where: Y' = <strong>the</strong> predicted dependent variable, A = Constant, B = unstandardized regression
coefficient, and X =value <strong>of</strong> <strong>the</strong> predictor variable. Using <strong>the</strong> constant and unstandardized coefficient
values, <strong>the</strong> prediction equation (3) would become:
Predicted Number <strong>of</strong> candidates = 12175.947 + (-2135.95) * Knowledge transfer index (4)
A measure <strong>of</strong> <strong>the</strong> strength <strong>of</strong> <strong>the</strong> computed equation is R-square, or coefficient <strong>of</strong> determination. Rsquare
represents <strong>the</strong> proportion <strong>of</strong> variance accounted for in <strong>the</strong> dependent variable (Number <strong>of</strong>
candidates) by <strong>the</strong> predictor variable (Index <strong>of</strong> knowledge transfer).
The ANOVA table presents results from <strong>the</strong> test <strong>of</strong> <strong>the</strong> null hypo<strong>the</strong>sis that R-square is zero which
would indicate no linear relationship between <strong>the</strong> predictor and dependent variable. The table shows
that <strong>the</strong> computed F statistic is 16.05, with an observed significance level <strong>of</strong> less than 0.05. Thus, <strong>the</strong>
hypo<strong>the</strong>sis that <strong>the</strong>re is no linear relationship between <strong>the</strong> predictor and dependent variable is
rejected.
Taken into consideration <strong>the</strong> test concluded (Pearson correlation coefficient, Spearman correlation
coefficient and <strong>the</strong> linear regression) we can deduce that <strong>the</strong> research hypo<strong>the</strong>sis (H1) is rejected and
accept <strong>the</strong> null hypo<strong>the</strong>sis (H0). Thus, <strong>the</strong> statistical test conducted proved <strong>the</strong> existence <strong>of</strong> a negative
correlation between <strong>the</strong> index <strong>of</strong> knowledge transfer <strong>of</strong> universities and <strong>the</strong> number <strong>of</strong> candidates for
<strong>the</strong> programs proposed.
Moreover, due to <strong>the</strong> fact that this study was a pilot study, conducted only on one university from <strong>the</strong>
area <strong>of</strong> Bucharest <strong>the</strong> relevance <strong>of</strong> <strong>the</strong> results has to be fur<strong>the</strong>r analyzed and more factors have to be
29
F
Sig.

Simona Agoston et al.
included in <strong>the</strong> analysis, such as <strong>the</strong> budget <strong>of</strong> <strong>the</strong> candidates, number <strong>of</strong> competitors, demographics
and so on.
5. Conclusions
Although <strong>the</strong> present research conducted on <strong>the</strong> example <strong>of</strong> <strong>the</strong> most prestigious Romanian university
in <strong>the</strong> field <strong>of</strong> economics and business does not reveal <strong>the</strong> expected positive correlation between
knowledge transfer activities and university prestige and indirectly number <strong>of</strong> candidates, university
leaders should still foster knowledge transfer activities and advertise <strong>the</strong>m properly in order to
increase <strong>the</strong> competitiveness <strong>of</strong> <strong>the</strong> universities in <strong>the</strong> global education market and establish <strong>the</strong>
framework for sustainable development. We must underline <strong>the</strong> fact that <strong>the</strong> negative correlation
between knowledge transfer and <strong>the</strong> number <strong>of</strong> candidates at <strong>the</strong> entry examination should not be
confounded or overlapped with a possible causal relation between <strong>the</strong> two variables. This correlation
represents ra<strong>the</strong>r a result <strong>of</strong> a poor advertisement <strong>of</strong> <strong>the</strong> knowledge transfer activities: prospect
students are not aware <strong>of</strong> <strong>the</strong>se activities due to <strong>the</strong> lack <strong>of</strong> promotional and marketing instruments
and <strong>the</strong>refore <strong>the</strong>se do not influence <strong>the</strong>ir university selection process.
The negative correlation between knowledge transfer activities and number <strong>of</strong> candidates and <strong>the</strong>
reduced impact exerted by knowledge transfer on academic reputation and consequently on <strong>the</strong>
number <strong>of</strong> students might have been caused also by <strong>the</strong> fact that important factors such as
demographic challenges, competition, emigration, globalization <strong>of</strong> educational market have not been
taken into consideration within this analysis. These factors might play a much more relevant role
regarding <strong>the</strong> “shrinkage <strong>of</strong> candidates” at <strong>the</strong> Academy <strong>of</strong> Economic Studies <strong>of</strong> Bucharest than <strong>the</strong>
knowledge transfer activities. The globalization <strong>of</strong> <strong>the</strong> educational market toge<strong>the</strong>r with <strong>the</strong> effort to
create a common <strong>European</strong> Area for Higher Education expose Romanian universities to a severe
competition and facilitates <strong>the</strong> access <strong>of</strong> Romanian high school graduates to foreign universities. A
second important factor is represented by <strong>the</strong> demographic changes (<strong>the</strong> reduction <strong>of</strong> birth rate and
consequently <strong>of</strong> <strong>the</strong> potential candidates) along with <strong>the</strong> high rate <strong>of</strong> emigration from Romania abroad,
mostly to o<strong>the</strong>r countries <strong>of</strong> <strong>the</strong> <strong>European</strong> Union. Last but not least, <strong>the</strong> criteria based on <strong>the</strong> level <strong>of</strong>
tuition fee and <strong>the</strong> entry examination might influence <strong>the</strong> high school pupils. The tuition fees for <strong>the</strong>
students who are not financed from <strong>the</strong> public budget are higher than <strong>the</strong> taxes claimed by private
universities. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> Academy <strong>of</strong> Economic Studies <strong>of</strong> Bucharest organized a written
examination based on a multiple choice test, while most <strong>of</strong> <strong>the</strong> private universities rely within <strong>the</strong>
selection process exclusively on <strong>the</strong> results from <strong>the</strong> final secondary-school examinations, reducing
<strong>the</strong>refore <strong>the</strong> entry barriers.
The new elements that this paper ads to empirical literature are <strong>the</strong> analysis at <strong>the</strong> level <strong>of</strong> a
Romanian University <strong>of</strong> a wide spectrum <strong>of</strong> knowledge transfer activities, covering not only research
agreements between companies and universities, but also o<strong>the</strong>r types <strong>of</strong> knowledge transfer activities
which are performed not only with business environment, but also with o<strong>the</strong>r interested parties as
students, o<strong>the</strong>r public institutions, alumni, society etc., which have been severely underestimated so
far in research papers.
In order to overcome <strong>the</strong> challenges posed by globalization, an increasingly complex business world
and <strong>the</strong> transition to <strong>the</strong> knowledge based economy, both academia and practitioners reinforced <strong>the</strong>
importance <strong>of</strong> knowledge transfer activities between public units, represented within this knowledge
transfer process mainly by universities and research institutes and o<strong>the</strong>r stakeholders. As businesses,
economy and society in general become more global and as <strong>the</strong> pace <strong>of</strong> change increases, <strong>the</strong>y
become more dependent on science and technology, which are provided partialy by universities
through knowledge transfer activities (Harvard Business School, 2009).
Acknowledgements
This work was supported by CNCSIS-UEFISCSU, project PN II-RU-TE_351/2010 and project PN II-
ID_1812/2008.
This article is a result <strong>of</strong> <strong>the</strong> project „Doctoral Program and PhD Students in <strong>the</strong> education research
and innovation triangle”. This project is co funded by <strong>European</strong> Social Fund through The Sectorial
Operational Programme for Human Resources Development 2007-2013, coordinated by The
Bucharest Academy <strong>of</strong> Economic Studies.
30

References
Simona Agoston et al.
Agrawal, A. (2001) “University-to-industry knowledge transfer: literature review and unanswered questions”
International Journal <strong>of</strong> Management Reviews, Vol.3, No.4, pp.285-302.
Argote, L., Ingram, P. (2000) “Knowledge transfer: a basis for competitive advantage in firms”, Organizational
Behavior and Human Decision Processes, Vol 82, No.1, pp. 150–169.
Arvanitis, S., Kubli, U., Woerter, M. (2008) “University-industry knowledge and technology transfer in Switzerland:
What university scientists think about co-operation with private enterprises”, Research Policy, No.37, pp.
1865–1883.
Brătianu, C., Lefter, V. (2001) Management strategic universitar, Editura Rao, Bucureşti
Duan, Y., Nie, W., Coakes, E. (2010) „Identifying key factors affecting transnational knowledge transfer”,
Information& Management, doi:10.1016/j.im.2010.08.003 (article in press).
Field, A. (2005) Discovering Statistics Using SPSS - 2nd edition, Sage Publications.
Geuna, A.; Muscio,A. (2008) “The Governance <strong>of</strong> University Knowledge Transfer” SPRU Electronic Working
Paper Series, Paper no. 173.
Goldfarb, B., Henrekson, M. (2003) “Bottom-up versus top-down policies towards <strong>the</strong> commercialization <strong>of</strong>
university intellectual property”, Research Policy, Vol.4, No.32, pp.639-658.
Ho, R. (2006) Handbook <strong>of</strong> univariate and multivariate data analysis and interpretation with SPSS, Taylor &
Francis Group.
Hubig, L., Jonen, A. (2006) „Hindrances, Benefits and Measurement <strong>of</strong> Knowledge Transfer in Universities -
Should Be Done More in <strong>the</strong> Light <strong>of</strong> Corporate Social Responsibility?” Available at SSRN:
http://ssrn.com/abstract=939390, retrieved 25.10.2010.
Johannesson, C. (2006) “University strategies for knowledge transfer and commercialization- An overview based
on peer reviews at 24 Swedish universities 2006” Vinnova Report, No. 17.
Link, A., Siegel, D., Bozeman, B. (2007) “An empirical analysis <strong>of</strong> <strong>the</strong> propensity <strong>of</strong> academics to engage in
informal university technology transfer”, Industrial and corporate change, Vol. 4, No.16, pp. 641-655.
Ndonzuau, F., Pirnay, F., Surlemont, B. (2002) “A stage model <strong>of</strong> academic spin-<strong>of</strong>f creation” Technovation, No.
22, pp. 281–289.
Santoro, M., Bierly, P.E. (2006) “Facilitators <strong>of</strong> Knowledge Transfer in University-Industry Collaborations: A
Knowledge-Based Perspective” IEEE Transactions on Engineering Management, Vol. 53, No. 4, pp.495-
507.
Santoro, M., Gopalakrishnan, S. (2000) “The institutionalization <strong>of</strong> knowledge transfer activities within industry–
university collaborative ventures” Journal <strong>of</strong> Engineering and Technology Management, No.17, pp.299–319.
Stephan, P.E. (2001) “Educational implications <strong>of</strong> university-industry technology transfer”, Journal <strong>of</strong> Technology
Transfer, No. 26, pp. 199–205.
Tijssen, R.J.W. (2004) “Is <strong>the</strong> commercialization <strong>of</strong> scientific research affecting <strong>the</strong> production <strong>of</strong> public
knowledge? Global trends in <strong>the</strong> output <strong>of</strong> corporate research articles” Research Policy, No.33, pp.709–733.
Vinig, T., Rijsbergen, P. (2008) “Determinants <strong>of</strong> university technology transfer - Comparative study <strong>of</strong> US,
Europe and Australian universities” available at SSRN: http://ssrn.com/abstract=1324601, retrieved
01.11.2010.
Wright, M., Clarysse, B., Lockett, A., Knockaert, M. (2008) “Mid-range universities’ linkages with industry:
Knowledge types and <strong>the</strong> role <strong>of</strong> intermediaries” Research Policy, No.37, pp.1205–1223.
Yusuf, S. (2008) “Intermediating knowledge exchange between universities and businesses” Research Policy No.
37, pp.1167–1174.
***Harvard Business School (2009) Annual Report 2009, Available at
http://www.hbs.edu/about/annualreport/2009/download2009/annual-2009.pdf, retrieved 20.10.2010.
31

A Modeling Approach to Intellectual Capital Advancement
Eckhard Ammann
Reutlingen University, Germany
Eckhard.Ammann@Reutlingen-University.de
Abstract: Current intellectual capital approaches normally provide an overall picture <strong>of</strong> an organization. This is
<strong>the</strong> case especially in <strong>the</strong> human capital domain, where statistical numbers like <strong>the</strong> percentage <strong>of</strong> employees
having carried out continuous training courses are given as indicators for aptitudes. The same applies to <strong>the</strong>
structural domain, where <strong>the</strong> number <strong>of</strong> innovation processes may be counted. While this may suffice for a static
intellectual capital statement <strong>of</strong> an organization, it clearly does not help for <strong>the</strong> dynamic perspective <strong>of</strong> intellectual
capital advancement. In order to improve <strong>the</strong> non-physical and non-monetary capital <strong>of</strong> a company, you have to
go into <strong>the</strong> details. That means, to enable personal development and knowledge adaption <strong>of</strong> individual
employees, to optimize single business processes and to establish new or improved customer relations – just to
name a few. In this paper, we introduce three operators, which help to model intellectual capital advancement on
each level <strong>of</strong> granularity: refinement, scope restriction, and individualization. Toge<strong>the</strong>r <strong>the</strong>y work along <strong>the</strong> three
dimensions <strong>of</strong> <strong>the</strong> intellectual capital space (IC space), which spans <strong>the</strong> whole <strong>of</strong> intellectual capital viewpoints.
These three operators can be concatenated. It is a meaningful scenario, to first restrict to a working unit and <strong>the</strong>n
individualize to single employees. In effect, repeated applications <strong>of</strong> any <strong>of</strong> <strong>the</strong> three operators lead to changed
viewpoint <strong>of</strong> observation and investigation: from <strong>the</strong> more strategic and resource-oriented view <strong>of</strong> intellectual
capital development to a more operational view <strong>of</strong> knowledge development. This means, that <strong>the</strong> task <strong>of</strong>
intellectual capital advancement is broken down to <strong>the</strong> task <strong>of</strong> knowledge development in <strong>the</strong> company through
<strong>the</strong> application <strong>of</strong> appropriate combinations and sequences <strong>of</strong> <strong>the</strong>se three operators. A suitable conception <strong>of</strong>
knowledge and knowledge dynamics, which supports this operational level task, has already been introduced
before and is shortly recapped in this paper. In addition, three fur<strong>the</strong>r operators, inverse to <strong>the</strong> three already
mentioned, are introduced: coarsing, enlargement and generalization. Applying <strong>the</strong>m in a second phase <strong>of</strong>
intellectual capital advancement helps to regain <strong>the</strong> improved overall picture <strong>of</strong> <strong>the</strong> intellectual capital <strong>of</strong> <strong>the</strong>
organization. To indicate <strong>the</strong> validity <strong>of</strong> <strong>the</strong> approach and in order to be able to give concrete modeling examples,
<strong>the</strong> “Intellectus Model” for <strong>the</strong> measurement and management <strong>of</strong> <strong>the</strong> intellectual capital is chosen as reference
model, to which <strong>the</strong> three operators and <strong>the</strong>ir inverses are applied. Several example scenarios are given in <strong>the</strong>
paper, which show different combinations <strong>of</strong> <strong>the</strong> application <strong>of</strong> <strong>the</strong> operators. These scenarios are shown as
closed paths in <strong>the</strong> IC space.
Keywords: intellectual capital advancement, IC space, IC viewpoint operators, advancement scenarios,
knowledge dynamics
1. Introduction
Intellectual capital <strong>of</strong> a company is defined as all non-monetary and non-physical resources that are
fully or partly controlled by <strong>the</strong> organisation and that contribute to <strong>the</strong> value creation <strong>of</strong> <strong>the</strong>
organisation (Roos 2005). Several domains <strong>of</strong> intellectual capital are normally distinguished. One
<strong>of</strong>ten used distinction is between three domains, namely relational structure (as <strong>the</strong> family <strong>of</strong>
intangible relationships with customers and suppliers), internal structure (including patents, concepts,
models, IT systems and processes) and human competence <strong>of</strong> <strong>the</strong> employees (see Andriessen 2004,
Sveiby 2001, and Roos 2005). The Intellectus Model (IADE_CIC 2005, Bueno et al. 2006) fur<strong>the</strong>r
divides relational structure (into a business and a social component) and internal structure (into an
organizational and a technological component). The model in (Sánchez-Canizares et al. 2007)
especially focuses on organizational culture as additional domain. In Europe, <strong>the</strong> Intellectual Capital
Statement (InCaS, see <strong>European</strong> Commission 2008) allows organizations to establish <strong>the</strong>ir intangible
balance sheet. In Germany finally, <strong>the</strong> so-called “Wissensbilanz” is a structural and procedural model,
that enables SMEs to state <strong>the</strong>ir intellectual capital assets (see Alwert et al. 2008). Those concepts <strong>of</strong>
intellectual capital help to let intangible resources <strong>of</strong> a company be measured, communicated and
interpreted. Economic value creation <strong>of</strong> a company is based on intangible resources to a high and
increasing degree. Advancement <strong>of</strong> intellectual capital <strong>of</strong> a company <strong>the</strong>refore is a key activity for
value creation.
Current intellectual capital approaches normally provide an overall picture <strong>of</strong> an organization. This is
<strong>the</strong> case especially in <strong>the</strong> human capital domain, where statistical numbers like <strong>the</strong> percentage <strong>of</strong>
employees having carried out continuous training courses are given as indicators for aptitudes. The
same applies to <strong>the</strong> structural domain, where <strong>the</strong> number <strong>of</strong> innovation processes may be counted.
While this may suffice for a static intellectual capital statement <strong>of</strong> an organization, it clearly does not
help for <strong>the</strong> dynamic perspective <strong>of</strong> intellectual capital advancement. See also (Mertins et al. 2010) for
32

Eckhard Ammann
an argument along this line. In order to improve <strong>the</strong> non-physical and non-monetary capital <strong>of</strong> a
company, you have to go into <strong>the</strong> details. That means, to enable personal development and
knowledge adaption <strong>of</strong> individual employees, to optimize single business processes and to establish
new or improved customer relations – just to name a few.
In this paper, we introduce three operators, which help to model intellectual capital advancement on
each level <strong>of</strong> granularity: refinement, scope restriction, and individualization. Toge<strong>the</strong>r <strong>the</strong>y work along
<strong>the</strong> three dimensions <strong>of</strong> <strong>the</strong> IC space, which spans <strong>the</strong> whole <strong>of</strong> intellectual capital viewpoints. Firstly,
refinement leads to a more detailed observation <strong>of</strong> <strong>the</strong> examined issue. For example, aptitude in <strong>the</strong>
human capital domain is refined to formal education, specialized training, experience and so on.
Again formal education can be fur<strong>the</strong>r refined into its constituents. Secondly, scope restriction
operates on <strong>the</strong> entirety <strong>of</strong> <strong>the</strong> organisation and restricts it to units, activities or teams inside <strong>the</strong>
company. Finally, individualization describes <strong>the</strong> changeover from <strong>the</strong> whole or groups <strong>of</strong> observed
employees, processes or items to <strong>the</strong> individual employee, <strong>the</strong> single process or item.
These three operators can be concatenated. It is a meaningful scenario, to first restrict to a working
unit and <strong>the</strong>n individualize to single employees. In effect, repeated applications <strong>of</strong> any <strong>of</strong> <strong>the</strong> three
operators lead to changed viewpoint <strong>of</strong> observation and investigation: from <strong>the</strong> more strategic and
resource-oriented view <strong>of</strong> intellectual capital development to a more operational view <strong>of</strong> knowledge
development. This means, that <strong>the</strong> task <strong>of</strong> intellectual capital advancement is broken down to <strong>the</strong> task
<strong>of</strong> knowledge development in <strong>the</strong> company through <strong>the</strong> application <strong>of</strong> appropriate combinations and
sequences <strong>of</strong> <strong>the</strong>se three operators. A suitable conception <strong>of</strong> knowledge and knowledge dynamics,
which supports this operational level task, has already been introduced before (Ammann 2010) and is
shortly recapped in this paper.
In addition, three fur<strong>the</strong>r operators, inverse to <strong>the</strong> three already mentioned, are introduced: coarsing,
enlargement and generalization. Applying <strong>the</strong>m in a second phase <strong>of</strong> intellectual capital advancement
helps to regain <strong>the</strong> improved overall picture <strong>of</strong> <strong>the</strong> intellectual capital <strong>of</strong> <strong>the</strong> organization.
To indicate <strong>the</strong> validity <strong>of</strong> <strong>the</strong> approach and in order to be able to give concrete modeling examples,
<strong>the</strong> “Intellectus Model” for <strong>the</strong> measurement and management <strong>of</strong> <strong>the</strong> intellectual capital is chosen as
reference model, to which <strong>the</strong> three operators and <strong>the</strong>ir inverses are applied. Several example
scenarios are given in <strong>the</strong> paper, which show different combinations <strong>of</strong> <strong>the</strong> application <strong>of</strong> <strong>the</strong>
operators. These scenarios are shown as closed paths in <strong>the</strong> IC space.
The structure <strong>of</strong> <strong>the</strong> paper is as follows. After <strong>the</strong> introduction, Section 2 shortly describes <strong>the</strong>
Intellectus Model as reference model for our IC advancement approach. Also a knowledge and
knowledge development concept is recapped as operational model. Section 3 introduces <strong>the</strong>
modeling concept for intellectual capital advancement, while <strong>the</strong> subsequent Section 4 provides
scenarios for <strong>the</strong> model application. A summary concludes <strong>the</strong> paper.
2. Reference models
In this section two reference models are shortly outlined, which serve as base model for <strong>the</strong>
intellectual capital advancement approach and as operational model for knowledge dynamics,
respectively. Note however, that <strong>the</strong> IC advancement approach as presented in Section 3 does not
depend on <strong>the</strong>se specific reference models, but can also followed with o<strong>the</strong>r models for IC and
knowledge development.
2.1 The Intellectus model as IC reference model
The Intellectus model is designed for measurement and management <strong>of</strong> intangible values, which
compose <strong>the</strong> concept <strong>of</strong> Intellectual Capital (IADE-CIC 2003). It comes with a hierarchical structure to
clarify <strong>the</strong> relationships between <strong>the</strong> different intangible assets <strong>of</strong> <strong>the</strong> organization. See Figure 1 for
<strong>the</strong> overall structure <strong>of</strong> <strong>the</strong> model. Five components expand <strong>the</strong> three well-known domains (Human,
Structural and Relational capital) into Human, Organizational, Technological, Business and Social
Capital. Organizational Capital is <strong>the</strong> combination <strong>of</strong> intangibles that structure and develop <strong>the</strong>
organizational activity, while Technological Capital refers to intangibles linked to <strong>the</strong> activities and
functions <strong>of</strong> <strong>the</strong> technical system <strong>of</strong> operations <strong>of</strong> <strong>the</strong> organization. Both sum up to <strong>the</strong> Structural
Capital domain. The Relational Capital domain is divided into <strong>the</strong> Business Capital component
(referring to <strong>the</strong> value <strong>of</strong> relationships with <strong>the</strong> main agents <strong>of</strong> <strong>the</strong> business) and Social Capital
33

Eckhard Ammann
(referring to <strong>the</strong> relationships with social agents in its surroundings). They group intangible assets
according <strong>the</strong>ir nature. Each component splits into elements, which again integrate variables.
Indicators for variables help for <strong>the</strong> valuation <strong>of</strong> intangible assets.
Figure 1: The Intellectus model
To give an example, <strong>the</strong> human capital component contains an element “aptitudes”, which again
contains four variables (formal education, specialised training, experience, and personal
development). Three indicators are given for “personal development”, one <strong>of</strong> <strong>the</strong>m is “percentage <strong>of</strong>
people with socio-cultural activities outside <strong>the</strong>ir pr<strong>of</strong>essional life”. Ano<strong>the</strong>r example from <strong>the</strong>
Organizational Capital component is <strong>the</strong> element “processes”, which itself is fur<strong>the</strong>r refined to three
variables: processes directed towards internal customers, external customers and towards <strong>the</strong>
suppliers. An indicator for <strong>the</strong> latter variable is “number <strong>of</strong> supplier risk management processes”.
Alternative IC reference models include <strong>the</strong> 3-domain model by Sveiby (Sveiby 2001) and <strong>the</strong>
approach using a resource distinction tree (see Roos, Pike, Fernström 2005).
2.2 The conception <strong>of</strong> knowledge and knowledge dynamics
In this section, we shortly recap <strong>the</strong> conception <strong>of</strong> knowledge and knowledge dynamics in a company
as already introduced in (Ammann 2009 and Ammann 2010).
Three main dimensions <strong>of</strong> knowledge, namely type, kind and quality, are introduced. The type
dimension categorizes knowledge according to its presence and availability. The conception for <strong>the</strong>
type dimension <strong>of</strong> knowledge follows a distinction between <strong>the</strong> internal and external knowledge types,
seen from <strong>the</strong> perspective <strong>of</strong> <strong>the</strong> human being. As third and intermediary type, explicit knowledge is
seen as an interface for human interaction and for <strong>the</strong> purpose <strong>of</strong> knowledge externalisation, <strong>the</strong> latter
one ending up in external knowledge. Internal (or implicit) knowledge is bound to <strong>the</strong> human being. It
is all that, what a person has “in its brain” due to experience, history, activities and learning. It can be
fur<strong>the</strong>r divided into tacit, latent and conscious knowledge. Explicit knowledge is “made explicit” to <strong>the</strong>
outside world e.g. through spoken language, but is still bound to <strong>the</strong> human being. External
knowledge finally is detached from <strong>the</strong> human being and may be kept in appropriate storage media as
part <strong>of</strong> <strong>the</strong> organisational memory. In <strong>the</strong> second dimension <strong>of</strong> knowledge, four kinds <strong>of</strong> knowledge
are distinguished: propositional, procedural and strategic knowledge, and familiarity. Finally, <strong>the</strong>
quality dimension introduces five characteristics <strong>of</strong> knowledge with an appropriate qualifying: level,
structure, automation, modality and generality. Knowledge qualities apply to each knowledge asset.
Knowledge dynamics is about acquisition, conversion, transfer, development and usage <strong>of</strong>
knowledge, in an enterprise. Its conception is based on knowledge conversions, i.e. transitions
between <strong>the</strong> different knowledge types, kind and qualities, which are responsible to a high degree for
knowledge development in an organisation. Five basic knowledge conversions in <strong>the</strong> type dimension
are distinguished here: Socialization, explicitation, externalization, internalization and combination.
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Eckhard Ammann
They convert exactly one source knowledge asset into exactly one destination knowledge asset. This
is an generalization <strong>of</strong> <strong>the</strong> well-known SECI-model (Nonaka/Takeuchi 1995). More complex
conversions may be easily gained by building on this set. They will consist <strong>of</strong> n-to-m-conversions and
include information assets in addition. General knowledge conversions are modeled converting
several source assets (possibly <strong>of</strong> different types, kinds and quality) to several destination assets
(also possibly different in <strong>the</strong>ir knowledge dimensions). In addition, information assets are considered
as possible contributing or generated parts <strong>of</strong> general knowledge conversions.
With <strong>the</strong> help <strong>of</strong> general nets <strong>of</strong> knowledge conversions, knowledge development activities in a
company can be modeled. This includes as well asset-oriented as process-oriented activities and also
allows for human-to-human interactions for knowledge advancement.
3. A modeling concept <strong>of</strong> intellectual capital advancement
For a dynamic perspective <strong>of</strong> intellectual capital advancement we need to break down <strong>the</strong> overall
picture <strong>of</strong> <strong>the</strong> intellectual capital <strong>of</strong> a company to a finer granularity in order to be able to apply
advancement measures. Again this means a change from summarized statements on human capital
to personal development and knowledge adaption <strong>of</strong> individual employees, to give just one example.
In sub-section 3.1., we follow this line and introduce <strong>the</strong> IC space (intellectual capital space) toge<strong>the</strong>r
with three operators (plus three inverse operators), which work along <strong>the</strong> dimensions <strong>of</strong> this IC space.
Sub-section 3.2. introduces concatenated applications <strong>of</strong> <strong>the</strong>se operators and indentifies important
classes <strong>of</strong> <strong>the</strong>se concatenations.
3.1 IC space and <strong>the</strong> operators <strong>of</strong> <strong>the</strong> model
The IC space (short for intellectual capital space) <strong>of</strong> a company is a three-dimensional space, which
spans <strong>the</strong> whole <strong>of</strong> intellectual capital viewpoints <strong>of</strong> this company. Viewpoints include <strong>the</strong> overall IC
statement <strong>of</strong> company as one extreme (<strong>the</strong> so-called IC origin) and individual statements on personal
aptitudes <strong>of</strong> an employee or single business processes at <strong>the</strong> o<strong>the</strong>r extreme (<strong>the</strong> so-called knowledge
management base, KM base). In between each level <strong>of</strong> detail regarding parts <strong>of</strong> <strong>the</strong> company or
detailed views <strong>of</strong> IC assets is represented in <strong>the</strong> IC space.
Three operators are introduced, which help to model intellectual capital advancement on each level <strong>of</strong>
granularity: refinement, scope restriction, and individualization. They work along <strong>the</strong> three dimensions
<strong>of</strong> <strong>the</strong> IC space, in <strong>the</strong> downward direction from IC origin to KM base. Firstly, refinement leads to a
more detailed observation <strong>of</strong> <strong>the</strong> examined issue. For example, aptitude in <strong>the</strong> human capital domain
is refined to formal education, specialized training, experience and so on. Again formal education can
be fur<strong>the</strong>r refined into its constituents. In effect, refinement works down <strong>the</strong> hierarchy <strong>of</strong> <strong>the</strong> Intellectus
Model, if this is taken as reference IC model. Secondly, scope restriction starts at <strong>the</strong> entirety <strong>of</strong> <strong>the</strong>
organisation and restricts <strong>the</strong> viewpoint to units, activities or teams inside <strong>the</strong> company. Finally,
individualization describes <strong>the</strong> changeover from <strong>the</strong> whole or groups <strong>of</strong> observed employees,
processes or items to <strong>the</strong> individual employee, <strong>the</strong> single process or item.
Note, that refinement and restriction can work piecewise through <strong>the</strong> IC space. For example, a first
application <strong>of</strong> restriction can change <strong>the</strong> viewpoint from <strong>the</strong> company-wide to a business-unit view,
while a second application can fur<strong>the</strong>r change this to a working unit level. Individualization is an
operator mapping combined viewpoints to individualized viewpoints. This can start from IC origin (e.g.
from <strong>the</strong> overall statement on human capital) or at a deeper level (e.g. <strong>the</strong> human capital <strong>of</strong> a
business unit). In any case, an application <strong>of</strong> <strong>the</strong> individualization operator will lead to <strong>the</strong> individual
employee, <strong>the</strong> single item or business process, all at KM base <strong>of</strong> <strong>the</strong> IC space.
In addition, three fur<strong>the</strong>r operators, being effective in <strong>the</strong> inverse (upward) direction to <strong>the</strong> three
already mentioned, are introduced: coarsing, enlargement and generalization. Applying <strong>the</strong>m in a
second phase <strong>of</strong> intellectual capital advancement helps to regain <strong>the</strong> improved overall picture <strong>of</strong> <strong>the</strong>
intellectual capital <strong>of</strong> <strong>the</strong> organization.
Figure 2 displays <strong>the</strong> IC space with its three dimensions, which again are worked on by <strong>the</strong> three
operators refinement, scope restriction and individualization (<strong>the</strong> three “downward” operators). They
start working on <strong>the</strong> overall IC viewpoint <strong>of</strong> <strong>the</strong> company, <strong>the</strong> IC origin, and break down in direction <strong>of</strong>
<strong>the</strong> KM base <strong>of</strong> <strong>the</strong> IC space. The three inverse operators (<strong>the</strong> “upward” operators) would work in <strong>the</strong>
opposite direction, from KM base in direction <strong>of</strong> <strong>the</strong> IC origin.
35

Eckhard Ammann
Figure 2: The IC space with <strong>the</strong> three (downward) operators
To state it more formally, let V be <strong>the</strong> set <strong>of</strong> all possible IC viewpoints <strong>of</strong> a company. V will include as
well IC origin as KM Base as elements. Fur<strong>the</strong>r elements <strong>of</strong> V would be, just to give some examples:
<strong>the</strong> IC statement <strong>of</strong> a subsidiary company <strong>of</strong> <strong>the</strong> company, <strong>the</strong> viewpoint <strong>of</strong> <strong>the</strong> human capital <strong>of</strong> a
business unit or <strong>the</strong> set <strong>of</strong> all business processes <strong>of</strong> <strong>the</strong> company, which are directed to suppliers.
Then <strong>the</strong> six operators are functions from V to V:
x: V -> V, where x is one <strong>of</strong> <strong>the</strong> set { Ind, Res, Ref, Gen, Enl, Coa }.
Here <strong>the</strong> abbreviations are Ind for individualization, Res for (scope) restriction, Ref for refinement,
Gen for generalization, Enl for enlargement and Coa for coarsing.
If x: V -> V is an operator out <strong>of</strong> <strong>the</strong> set { Ind, Res, Ref, Gen, Enl, Coa }, <strong>the</strong>n by x -1 we denote <strong>the</strong>
corresponding inverse operator. That means for example, that if x is a restriction Res, <strong>the</strong>n x -1 is <strong>the</strong>
specific enlargement operator Enl with <strong>the</strong> property, that a subsequent application <strong>of</strong> first Res and
<strong>the</strong>n Enl would mean <strong>the</strong> identity in <strong>the</strong> IC space (by <strong>the</strong> way, this also works <strong>the</strong> o<strong>the</strong>r way around:
first Enl and <strong>the</strong>n Res). The same way, corresponding pairs (Ref, Coa) and (Ind, Gen) can be seen.
3.2 Concatenation <strong>of</strong> operators
The operators on <strong>the</strong> IC space can be concatenated, i.e. applied one after <strong>the</strong> o<strong>the</strong>r. It is a meaningful
scenario, to first restrict to a working unit and <strong>the</strong>n individualize to single employees. In effect,
repeated applications <strong>of</strong> any <strong>of</strong> <strong>the</strong> three downward operators lead to changed viewpoint <strong>of</strong>
observation and investigation: from <strong>the</strong> more strategic and resource-oriented view <strong>of</strong> intellectual
capital development to a more operational view <strong>of</strong> knowledge development. This means, that <strong>the</strong> task
<strong>of</strong> intellectual capital advancement is broken down to <strong>the</strong> task <strong>of</strong> knowledge development in <strong>the</strong>
company through <strong>the</strong> application <strong>of</strong> appropriate combinations and sequences <strong>of</strong> <strong>the</strong>se three
operators. A suitable conception <strong>of</strong> knowledge and knowledge dynamics, which supports this
operational level task, has already been introduced before (Ammann 2009 and 2010) and shortly
recapped in section 2. Applying concatenated upward operators will lead towards IC origin, i.e. in
direction <strong>of</strong> <strong>the</strong> overall IC statement <strong>of</strong> <strong>the</strong> company.
While in principle each possible sequence <strong>of</strong> operators is possible in a concatenation, not all <strong>of</strong> <strong>the</strong>m
are meaningful. Meaningful concatenations mostly consist <strong>of</strong> pure sequences <strong>of</strong> downward or upward
operators, or <strong>of</strong> sequences <strong>of</strong> a number <strong>of</strong> downward operators directly following by a number <strong>of</strong>
upward operators. Important patterns <strong>of</strong> concatenation are hierarchical, symmetric and roundtrip
concatenations, which are explained in <strong>the</strong> following three sub-sections. Formally a concatenation <strong>of</strong>
operators again is a function from V to V. As notation for concatenated operators, we will use <strong>the</strong>
following arrow notation, working from left to right. That means for example, that in “Ref -> Res -> Ind”
first a refinement operator is applied, <strong>the</strong> result restricted by a scope restriction, and finally
36

Eckhard Ammann
individualization is applied to give <strong>the</strong> result <strong>of</strong> <strong>the</strong> concatenated operators. With this notation, <strong>the</strong>
concept <strong>of</strong> inverse operators introduced in <strong>the</strong> previous sub-section can be stated as
x -> x -1 == id == x -1 -> x, where x, id: V -> V and id is <strong>the</strong> identity operator on <strong>the</strong> IC space.
3.2.1 Hierarchical concatenations
The first important class <strong>of</strong> concatenations <strong>of</strong> operators are hierarchical concatenations. They consist
<strong>of</strong> sequences <strong>of</strong> <strong>the</strong> same operator applied one after <strong>the</strong> o<strong>the</strong>r, i.e. <strong>the</strong>y come in <strong>the</strong> form
x -> x -> … -> x, where x: V -> V and x is one <strong>of</strong> <strong>the</strong> set { Ind, Res, Ref, Gen, Enl, Coa }.
This is important for <strong>the</strong> downward operator refinement and restriction, where a meaningful procedure
for IC advancement is <strong>the</strong> repeated refinement from high level components to elements and variables
or <strong>the</strong> repeated restriction from <strong>the</strong> company-wide viewpoint to parts <strong>of</strong> <strong>the</strong> company. The case <strong>of</strong> <strong>the</strong>
individualization operator is not important here, because a single application <strong>of</strong> it already leads to <strong>the</strong>
full detail <strong>of</strong> individuals and single items or processes.
Using hierarchical concatenations with upward operators describe <strong>the</strong> repeated consolidation <strong>of</strong>
detailed statements into higher level viewpoints with growing overall perspective in <strong>the</strong> company.
3.2.2 Symmetric concatenations
Symmetric concatenations are defined as concatenations <strong>of</strong> <strong>the</strong> form
-1 -1 -1
x1 -> x2 -> … -> xn -> xn -> … -> x2 -> x1 == id, where xi: V -> V and i = 1,2, …,n.
They always effect in identity in <strong>the</strong> IC space. By far <strong>the</strong> most important ones in this class, and we
want to restrict our definition to <strong>the</strong>se cases, are those, where <strong>the</strong> x1, …,xn are all downward
operators. With <strong>the</strong> help <strong>of</strong> <strong>the</strong>m, you break down your IC viewpoint with <strong>the</strong> help <strong>of</strong> several (possibly
different) downward operators to <strong>the</strong> point <strong>of</strong> detail in <strong>the</strong> IC space you want <strong>the</strong> see and develop with
knowledge development measures, and <strong>the</strong>n proceed upwards on <strong>the</strong> same path in reverse order,
until <strong>the</strong> starting point <strong>of</strong> <strong>the</strong> procedure is reached again. An example scenario with a symmetric
concatenation path is visually depicted in Figure 3 in <strong>the</strong> next section 4 on model application
scenarios.
Important subclasses <strong>of</strong> symmetric concatenations are those, where <strong>the</strong> xi’s in <strong>the</strong> previous definition
are all ei<strong>the</strong>r refinements or restrictions. Then we have homogeneous refinement or restriction
followed by homogeneous coarsing or enlargement, respectively.
3.2.3 Roundtrip concatenations
Roundtrip concatenations are defined as concatenations <strong>of</strong> <strong>the</strong> form
x1 -> x2 -> … -> xn == id, where xi: V -> V and i = 1,2, …,n.
They always effect in identity in <strong>the</strong> IC space. By far <strong>the</strong> most important ones in this class, and we
want to restrict our definition to <strong>the</strong>se cases, are those, where <strong>the</strong> first x1, …,xi are all downward
operators and <strong>the</strong> last xi+1, …,xn are all upward operators (1

Eckhard Ammann
section 2. They are visualized in <strong>the</strong> IC space. The kind <strong>of</strong> visualization in both cases is inspired by
<strong>the</strong> visualization <strong>of</strong> social learning cycles in <strong>the</strong> so-called Information Space by Boisot (see Boisot
1999).
4.1 Scenario <strong>of</strong> a symmetric concatenation
As explained in section 3.2.2 symmetric concatenations lead to closed paths through <strong>the</strong> IC Space in
a way, that a first phase <strong>of</strong> breaking down consists <strong>of</strong> <strong>the</strong> subsequent application <strong>of</strong> downward
operators and a second phase reverts this path by appropriate application <strong>of</strong> <strong>the</strong> inverse upward
operators.
Our scenario will be <strong>the</strong> following: The level <strong>of</strong> communication (exchange <strong>of</strong> knowledge) should be
improved among <strong>the</strong> employees <strong>of</strong> a certain business unit within <strong>the</strong> company. This improvement can
be done on <strong>the</strong> operational level with <strong>the</strong> help <strong>of</strong> appropriate knowledge management activities.
Having performed <strong>the</strong>se activities, <strong>the</strong> company would like to see an observable improvement in its
overall intellectual capital statement (more specific, in <strong>the</strong> human capital domain part <strong>of</strong> this
statement). We can model this scenario with <strong>the</strong> symmetric concatenation
Ref -> Res -> Ind -> Gen -> Enl -> Coa ( == id).
A visualization <strong>of</strong> this symmetric path through <strong>the</strong> IC space is given in Figure 3. It starts and ends at
<strong>the</strong> IC origin.
Figure 3: A symmetric path
Applying <strong>the</strong> first operator in this concatenation, we refine our viewpoint from <strong>the</strong> IC origin to <strong>the</strong>
variable “Communication (exchange <strong>of</strong> knowledge) in <strong>the</strong> element “Capacities” <strong>of</strong> <strong>the</strong> human capital
domain. Here <strong>the</strong> concepts <strong>of</strong> domains, elements and variables are taken from our IC reference
model, <strong>the</strong> Intellectus Model. The subsequent restriction focuses on <strong>the</strong> business unit <strong>of</strong> interest
within <strong>the</strong> company, while <strong>the</strong> following individualization views at <strong>the</strong> exchange <strong>of</strong> knowledge
behaviour <strong>of</strong> <strong>the</strong> single employees in this business unit. Having improved <strong>the</strong>se behaviours through
application <strong>of</strong> knowledge management activities, we step up <strong>the</strong> path again by first generalize to <strong>the</strong>
group <strong>of</strong> employees in this business unit, <strong>the</strong>n enlarge to <strong>the</strong> company-wide viewpoint <strong>of</strong> human
capital and finally coarse to <strong>the</strong> improved and developed new intellectual capital statement <strong>of</strong> <strong>the</strong>
whole company.
38

4.2 Scenario <strong>of</strong> a roundtrip concatenation
Eckhard Ammann
Roundtrip concatenations are closed paths <strong>of</strong> operator application as introduced in section 3.2.3. An
important subclass <strong>of</strong> those roundtrips, where a first phase <strong>of</strong> downward operator application is
followed by a second, but not necessarily inverse, phase <strong>of</strong> upward movement in <strong>the</strong> IC space
towards IC origin.
In our scenario, we step down <strong>the</strong> IC space with <strong>the</strong> sequence Ind -> Res -> Ref first, to individually
view <strong>the</strong> “Satisfaction” variable <strong>of</strong> <strong>the</strong> “Values and attitudes” element in <strong>the</strong> human capital domain in a
certain business unit. Having worked on <strong>the</strong> variable (e.g. by improving <strong>the</strong> individual indicator
“Benefit by Employee”), we first enlarge <strong>the</strong> viewpoint to regard all employees in <strong>the</strong> company, <strong>the</strong>n
generalize (consolidate) to an overall “Satisfaction” view within this business unit, before finally we
coarse to gain <strong>the</strong> overall company-wide viewpoint. Again we use <strong>the</strong> concepts <strong>of</strong> <strong>the</strong> Intellectus
Model in this scenario. We can model this scenario with <strong>the</strong> roundtrip concatenation
Ind -> Res -> Ref -> Enl -> Gen -> Coa ( == id).
A visualization <strong>of</strong> <strong>the</strong> roundtrip path through <strong>the</strong> IC space is given in Figure 4.
Figure 4: A roundtrip path
5. Summary and conclusion
A modeling approach for intellectual capital advancement is given, which is based on a set <strong>of</strong>
operators in <strong>the</strong> Intellectual Capital space. Applying <strong>the</strong> operators provides suitable perspectives <strong>of</strong>
granularity in an organization (modeled as points in <strong>the</strong> IC space), where advancement measures can
be taken. On <strong>the</strong> operational level, this comes down to knowledge development. Using <strong>the</strong> inverse
operators in a second phase leads to <strong>the</strong> advanced overall IC statement <strong>of</strong> <strong>the</strong> organization.
The modeling approach is based on <strong>the</strong> Intellectus Model (while does not depend on this choice).
Several scenarios are provided, which indicate <strong>the</strong> applicability <strong>of</strong> this approach, among <strong>the</strong>se
hierarchical, symmetric, and roundtrip paths in <strong>the</strong> IC space, toge<strong>the</strong>r with <strong>the</strong>ir interpretations in <strong>the</strong>
organizational context.
This modeling approach provides a structured view <strong>of</strong> all possible IC viewpoints <strong>of</strong> a company, from
<strong>the</strong> overall perspective to very specific considerations <strong>of</strong> single assets. The model allows for a
systematic localization <strong>of</strong> viewpoints as well as for a well-defined path towards it. There, development
activities can be started, improving <strong>the</strong> situation at this viewpoint.
39

Eckhard Ammann
From an overall perspective, this modelling approach shows as well characteristics <strong>of</strong> <strong>the</strong> ostensive
research approach to IC as those <strong>of</strong> <strong>the</strong> performative approach. An ostensive approach is related to
knowledge and value objects and objectives in a more or less fixed model. In <strong>the</strong> performative
approach, IC is seen as part <strong>of</strong> actively-undertaken knowledge management and is utilized to develop
organizational conditions. See (Mouritsen 2006) for a detailed discussion on <strong>the</strong>se two approaches. In
few words, our modeling approach follows <strong>the</strong> ostensive way through path finding in <strong>the</strong> IC space and
motivates <strong>the</strong> performative way, when improvement activities are to be done at <strong>the</strong> viewpoint level <strong>of</strong>
<strong>the</strong> IC space.
References
Alwert, K., Bornemann, M., Will, M. (2008) Wissensbilanz – Made in Germany. Leitfaden 2.0 zur Erstellung einer
Wissensbilanz, Guideline Published by <strong>the</strong> Federal Ministry for Economics and Technology, Berlin.
Ammann, E. (2009) “The Knowledge Cube and Knowledge Conversions”, in: Proc. <strong>of</strong> <strong>the</strong> World Congress <strong>of</strong>
Engineering, International <strong>Conference</strong> on Data Mining and Knowledge Engineering (ICDMKE), London, UK,
pp. 319-324.
Ammann, E. (2010) “Intellectual Capital Development by Means <strong>of</strong> Knowledge Conversions”, in: Proc. <strong>of</strong> <strong>the</strong> 2 nd
<strong>European</strong> <strong>Conference</strong> on Intellectual Capital 2010 (ECIC 2010), Lissabon, Portugal, 29-30 March, 2010, pp.
44-53.
Andriessen, D. (2004) Making Sense <strong>of</strong> Intellectual Capital, Elsevier.
Boisot, M.H. (1998) Knowledge Assets – Securing Competitive Advantage in <strong>the</strong> Information Economy, Oxford
University Press, Oxford.
Bratianu, C. (2009) “The Frontier <strong>of</strong> Linearity in <strong>the</strong> Intellectal Capital Metaphor”, Electronic Journal <strong>of</strong> Knowledge
Management, Vol.7, Issue 4, pp. 415-424.
Bueno, E., Salmador, M., Rodriguez, O., De Castro, G.M. (2006) “Internal Logic <strong>of</strong> Intellectual Capital: A
Biological Approach”, Journal <strong>of</strong> Intellectual Capital, Vol.7, No.3, pp. 394-405.
<strong>European</strong> Commission (2008) InCaS – Intellectual Capital Statement – Made in Europe, <strong>European</strong> ICS
Guideline, [online] www.incas-europe.org.
IADE-CIC (2003) “Model for <strong>the</strong> measurement and management <strong>of</strong> intellectual capital: Intellectus Model”,
Documentos Intellectus 5, Universidad Autónoma de Madrid, Madrid.
Mertins, K., Will, M., Meyer, C. (2010) “Analysing and Enhancing IC in Business Networks: Results From a
Recent Study”, Proc. <strong>of</strong> <strong>the</strong> 2 nd <strong>European</strong> <strong>Conference</strong> on Intellectual Capital (ECIC 2010), Lisbon Portugal,
pp. 450-456.
Mouritsen, J. (2006) “Problematising intellectual capital research: ostensive versus performative IC”, Accouning,
Auditíng & Accountability Journal, Vol.19, No.6, pp. 820-841.
Nonaka, I., Takeuchi, H. (1995) The Knowledge-Creating Company – How Japanese Companies Foster
Creativity and Innovation for Competitive Advantage , Oxford University Press, London.
Roos, G., Pike, St., Fernström, L. (2005) Managing Intellectual Capital in Practice, Elsevier.
Sánchez-Canizares, S.M., Ayuso Munoz, M.Á., López-Guzmán, T. (2007) “Organizational culture and intellectual
capital: a new model”, Journal <strong>of</strong> Intellectual Capital, Vol.8, No.3, pp. 409-430.
Sveiby, K.-E. (2001) “A Knowledge-Based Theory <strong>of</strong> <strong>the</strong> Firm to guide Strategy Formulation”, Journal <strong>of</strong>
Intellectual Capital, Vol.2, No.4, pp. 344-358.
40

Transformational Leadership in Mergers and Acquisitions
Transactions in Emerging Markets. Case Study <strong>of</strong> <strong>the</strong> Bere
Mures Acquisition by Heineken Romania
Sorin Anagnoste 1 and Gabriela Dumitru 2
1
The Academy <strong>of</strong> Economic Studies, Bucharest, Romania
2
AT Kearney, Bucharest, Romania
Sorin.anagnoste@gmail.com
Gabriela.dumitru@atkearney.com
Abstract: Mergers and acquisition have become attractive options in <strong>the</strong> last years in emerging markets being
driven not only by a financial attractiveness point <strong>of</strong> view but also seen as a strategic investment movement.
However, leadership styles are key determinants <strong>of</strong> <strong>the</strong> success or failure <strong>of</strong> such transactions. Leadership, a hot
topic with impact in day-to-day business life, is usually taken for granted, and despite <strong>the</strong> fact that most <strong>of</strong> <strong>the</strong>
times <strong>the</strong> general principles are applied, <strong>the</strong> key cultural dimension is <strong>of</strong>ten forgotten. The aim <strong>of</strong> this paper is to
report <strong>the</strong> findings <strong>of</strong> an empirical study exploring <strong>the</strong> existence and relationship between seven variables <strong>of</strong>
transformational leadership (values, vision, optimism, innovation and change, trust, motivation and emotional
intelligence) and to lay out <strong>the</strong> strategy <strong>of</strong> a company to gain competitive edge by means <strong>of</strong> an acquisition case
study in beer industry. Companies need <strong>the</strong> appropriate levers if <strong>the</strong>y are to maintain <strong>the</strong>ir positions in <strong>the</strong>
market, should imply as much as possible <strong>the</strong> local resources, should adapt to <strong>the</strong> customs and traditions <strong>of</strong> that
country or region and one <strong>of</strong> <strong>the</strong> most important findings is that leaders create leaders.
Keywords: transformational leadership, mergers, acquisitions, emerging markets
1. Introduction
Nowadays we see leadership in everything around us, from family members to businesses and
brands (Northouse, 2007) and that is why we decided to take a look <strong>of</strong> <strong>the</strong> transformational leadership
perspective into mergers and acquisitions in beer market in an emergent economy to see, both, <strong>the</strong>
usage <strong>of</strong> leadership and <strong>the</strong> way a merger and acquisition is a model <strong>of</strong> success through it.
The beer market is Romania is evaluated at 1 billion EURO and <strong>the</strong> main four players (SAB Miller,
Heineken, INBEV AG, Carslberg) have 95% <strong>of</strong> <strong>the</strong> market share.
We wanted to find out if <strong>the</strong> main transaction in <strong>the</strong> Romanian beer market was an acquisition
planned or forced by <strong>the</strong> competitors and see <strong>the</strong> importance <strong>of</strong> <strong>the</strong> transformational leadership in <strong>the</strong>
people involved in this transaction. When it comes to leadership it is very important to stress out that
leadership has a nonlinear nature and is an integrator much more powerful than technologies or its
associated processes being a generic and flexible integrator <strong>of</strong> intellectual capital (Bratianu el al.,
2007).
2. The basics <strong>of</strong> mergers and acquisition
Companies never stop searching for sources <strong>of</strong> pr<strong>of</strong>itable growth, whe<strong>the</strong>r organic (hiring additional
salespeople, developing new products) or inorganic (firm acquisition). M&A can provide a stimulus to
growth, enable market dominance in a slow growth market, enlarge geographical/product/domain
footprint or also provide opportunities for enhancing <strong>the</strong> bottom line through better synergies and
reduced overheads. The drivers <strong>of</strong> mergers and acquisitions can be very different depending upon <strong>the</strong>
industry and firm specific factors; however, growth is <strong>the</strong> dominant driver <strong>of</strong> M&A:
Acquirers usually pursue a merger to cut costs and create growth opportunities. The aim is to
establish or broaden <strong>the</strong>ir presence in high-growth markets, so <strong>the</strong>y are constantly on <strong>the</strong> lookout for
acquisitions with growth prospects. Ano<strong>the</strong>r reason could be to gain access to production and new
technology. This strategy pushes expansion plans by broadening <strong>the</strong> customer base and increasing
market share (Ro<strong>the</strong>nbuecher and Hoyningen-Huene, 2008).
Throughout <strong>the</strong> process <strong>of</strong> merger and acquisition negotiation <strong>the</strong>re are a set <strong>of</strong> instruments and
activities that are performed: while <strong>the</strong> company willing to expand is developing a short list <strong>of</strong> potential
candidates, on <strong>the</strong> o<strong>the</strong>r side <strong>the</strong> targeted company is performing a market screening to have an idea
about what could be <strong>the</strong> market potential. The next step is defined as an understanding point from
41

Sorin Anagnoste and Gabriela Dumitru
both sides <strong>of</strong> <strong>the</strong> risks involved, potential attractiveness. This is normally done via due diligence
reports and management presentations. In <strong>the</strong> end <strong>the</strong> process as such is managed through <strong>of</strong>fer
evaluation, structuring <strong>the</strong> deal, negotiating <strong>the</strong> agreement and in <strong>the</strong> end signing and closing <strong>the</strong>
process.
Figure 1: Main drivers <strong>of</strong> mergers and acquisition
Source: Ro<strong>the</strong>nbuecher, J. and von Hoyningen-Huene, J. (2008) The rise <strong>of</strong> Emerging Markets in
Mergers and Acquisitions, A.T. Kearney
There are different parts involved in an M&A process like auditors, banks, legal advisors,
management <strong>of</strong> <strong>the</strong> two parties involved and consultants whose role is mainly in developing <strong>the</strong>
commercial due diligence process that results in a due diligence report based on an in-depth analysis
<strong>of</strong> <strong>the</strong> market and competition, strategy and business plan.
Due diligence is a key activity in mergers and acquisitions because it is <strong>the</strong> point at which both <strong>the</strong>
potential for value creation and <strong>the</strong> purchase price are determined. To fully assess <strong>the</strong> value creation
potential acquires perform different types <strong>of</strong> due diligence reports (Niewiem and Ro<strong>the</strong>nbucher,
2008):
Figure 2: Types <strong>of</strong> due diligence reports
Source: Perry, S.J. and Herd, J.T. (2004) Mergers and acquisitions: Reducing M&A risk through
improved due diligence, A.T. Kearney, Vol. 32 No.2
42

Sorin Anagnoste and Gabriela Dumitru
A successful merger is certainly not all about speed or applying sophisticated tools for managing <strong>the</strong>
process. Instead, today’s successful integration managers use a different, more nuanced approach by
establishing clear structures – skillfully combining leadership with execution and placing greater
emphasis on achieving growth.
Leadership has a pivotal role in any merger integration, where a certain degree <strong>of</strong> chaos and
confusion is unavoidable. Two companies shed <strong>the</strong>ir separate identities to form a new, combined
organization – and without <strong>the</strong> familiar structures to hold things toge<strong>the</strong>r, <strong>the</strong>re is a tendency to pull in
different and sometimes, conflicting directions. Such situation requires strong leadership to ensure
that <strong>the</strong> merger is on <strong>the</strong> right track and all necessary tasks are being executed. (Ro<strong>the</strong>nbucher and
Declerq, 2008)
Most mergers fail. That’s a fact. After <strong>the</strong> merger, many companies cannot sustain <strong>the</strong>ir growth
momentum. A.T. Kearney finds that <strong>the</strong> major cause for post-merger financial slow-downs is treating
all mergers alike. In a study <strong>of</strong> 175 mergers, seven types <strong>of</strong> mergers were identified. Each type has its
own challenges and opportunities. Companies that tailor <strong>the</strong> merger approach to <strong>the</strong> merger type will
increase merger success and <strong>the</strong> value <strong>of</strong> <strong>the</strong> new company. Altoge<strong>the</strong>r, <strong>the</strong>re are seven merger
types (please see figure below).
Figure 3: The seven types <strong>of</strong> mergers
Source: Cole, Rebel A., Ferris, Kenneth R. and Melnik, Arie L. (2010) The Cost <strong>of</strong> Advice in Merger &
Acquisition Transactions, AT Kearney
According to an A.T. Kearney study <strong>of</strong> 175 mergers, <strong>the</strong> key challenge <strong>of</strong> a merger is not achieving
<strong>the</strong> cost synergies as such but ra<strong>the</strong>r to sustain <strong>the</strong> growth <strong>of</strong> <strong>the</strong> new company. The research
43

Sorin Anagnoste and Gabriela Dumitru
revealed that <strong>the</strong> most critical factors in today’s merger process are providing leadership and
direction, and putting <strong>the</strong> new organization and management in place (please see figure below)
Figure 4: Success factors for a M&A transaction, study results
Source: Ro<strong>the</strong>nbucher, J. and Declerq, S. (2008) Three years after <strong>the</strong> marriage, AT Kearney
In <strong>the</strong> entire process <strong>the</strong> complexity <strong>of</strong> activities and efforts needed to be invested vary along <strong>the</strong>
timeline <strong>of</strong> <strong>the</strong> M&A process. A recent article wrote in 2010 by <strong>the</strong> DePaul University and Arizona
state university, “The cost <strong>of</strong> advice in merger & acquisition transactions”, shows that mergers &
acquisitions are significant resource-consuming activities for businesses. The underlying idea is that
real spending commitments (e.g. cost <strong>of</strong> merging advisory) are done by a potential acquirer even
before any announcement <strong>of</strong> proposed transaction and most <strong>of</strong> <strong>the</strong> times <strong>the</strong>se costs if <strong>the</strong>
transaction does not succeed will never be recuperated. The costs size is directly correlated with <strong>the</strong>
complexity <strong>of</strong> <strong>the</strong> deal and <strong>the</strong> financial size <strong>of</strong> <strong>the</strong> deal.
The conclusion and hypo<strong>the</strong>sis <strong>of</strong> <strong>the</strong> article would be that it is this cost <strong>of</strong> pre-merger advice that
explains a large share <strong>of</strong> <strong>the</strong> decline in acquiring-firm shareholder wealth that is frequently observed
in such transactions (Cole, Ferris and Melnik, 2010). In <strong>the</strong> context <strong>of</strong> our study, <strong>the</strong> conclusion is
valid as it reveals increased effort and due-diligence from <strong>the</strong> acquirer side not to fall into this trap,
fact evidenced by <strong>the</strong> successful increase in shareholder value after <strong>the</strong> M&A process took place.
3. Mergers and acquisitions in emerging markets
In order to maintain <strong>the</strong>ir position on <strong>the</strong> market, companies need <strong>the</strong> appropriate levers and <strong>the</strong>
increase in <strong>the</strong> number <strong>of</strong> M&A transactions is adding pressure on <strong>the</strong> companies in developing
world.
Acquirers in developed countries usually pursue a merger to cut costs and create growth
opportunities. The aim is to establish or broaden <strong>the</strong>ir presence in high-growth markets, so <strong>the</strong>y are
constantly on <strong>the</strong> lookout for acquisitions with growth prospects. These companies also focus on lowcost
environments for manufacturing and sourcing. Well aware <strong>of</strong> <strong>the</strong> growing threat from emerging
rivals, <strong>the</strong>y want to streng<strong>the</strong>n <strong>the</strong>ir competitive positions.
In contrast acquirers from developing countries focus on gaining access to production and new
technology. These firms are also entering established markets to maximize <strong>the</strong> advantages <strong>of</strong> <strong>the</strong>ir
low-cost structure against traditional competitors. This strategy pushes expansion plans by
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Sorin Anagnoste and Gabriela Dumitru
broadening <strong>the</strong> customer base and increasing market share in developed countries. It relies on a new,
more educated class <strong>of</strong> executives driven to expand <strong>the</strong> scope <strong>of</strong> <strong>the</strong>ir business activities.
Consider <strong>the</strong> motives behind Tata Motor’s pursuit <strong>of</strong> <strong>the</strong> traditional British brands Jaguar and Land
Rover. So far, Tata has produced only simple, cheap cars and it is now trying to expand into Western
markets. Acquiring <strong>the</strong> Jaguar and Land Rover brands <strong>of</strong>fers Tata access to production technology
and distribution channels. It also changes <strong>the</strong> perceived quality <strong>of</strong> Tata products in <strong>the</strong> established
world. While this brand-buying met well result in a positive spillover for <strong>the</strong> Tata brand, it could also
harm <strong>the</strong> established brands as <strong>the</strong> spillover effect works both ways.
Acquirers from developing countries are pursuing spectacular majority acquisitions. For example,
petrochemical giant Saudi Basic Industries Corporation (SABIC) acquired GE Plastics for $12 billion.
This transaction gave SABIC, already in <strong>the</strong> top 10 petrochemical companies globally, strategic
access to markets in <strong>the</strong> United States and Europe and improved competitiveness.
Huge deals are never<strong>the</strong>less not one-way events. Transactions by developed countries into emerging
markets still represent <strong>the</strong> majority <strong>of</strong> deals, as evidence by transactions such as Vodafone’s
purchase <strong>of</strong> Hutchison Essar in India that secured its position as a global market leader and gained a
foothold in <strong>the</strong> fastest-growing and second-biggest mobile market in <strong>the</strong> world. Transactions involving
companies from countries at different stages <strong>of</strong> economic development pose unique challenges for
acquirers and require specific skills. (Ro<strong>the</strong>nbuecher and von Hoyningen-Huene, A.T. Kearney 2008).
4. Case study – Bere-Mures acquisition by Heineken Romania, M&A driven by
strategic market movement
The beer market followed a strong consolidation process in <strong>the</strong> recent years while <strong>the</strong> big producers
were fighting for a top position through acquiring as much local producers as possible. There is a
natural tendency <strong>of</strong> industries towards consolidation (please see figure below) and <strong>the</strong> domestic beer
market was no exception.
Figure 5: Natural trend <strong>of</strong> industries consolidation
Source: Perry, S.J. and Herd, J.T. (2004) Mergers and acquisitions: Reducing M&A risk through
improved due diligence, A.T. Kearney, Vol. 32 No.2
45

Sorin Anagnoste and Gabriela Dumitru
This might be reason why <strong>the</strong> domestic beer market is one <strong>of</strong> <strong>the</strong> regional market with <strong>the</strong> most local
competitiveness dominated mainly by world producers. Thus 95% <strong>of</strong> <strong>the</strong> beer market is controlled by
5 players (Ursus Breweries, Heineken, Bergenbier, Tuborg and Romaqua) and small producers
account for only 5% <strong>of</strong> <strong>the</strong> market, while o<strong>the</strong>r regional markets like Czech Republic, Poland and
Hungary are dominated by <strong>the</strong> same producers, but with less market share and an important number
<strong>of</strong> small beer producers.
In this context, <strong>the</strong> two main players are forced to play <strong>the</strong> game <strong>of</strong> market leaders, as an alternative
to organic growth, and any strategic movement like and merger and acquisition is key determinant in
<strong>the</strong>ir market positioning. Thus, I can drive <strong>the</strong> conclusion that <strong>the</strong> particular case <strong>of</strong> Bere acquisition
was not necessarily a desired acquisition but ra<strong>the</strong>r a reactive movement to <strong>the</strong> market tendencies.
Going fur<strong>the</strong>r analyzing <strong>the</strong> typical merger and acquisition process we will be able to conclude
whe<strong>the</strong>r or not <strong>the</strong> acquisition process <strong>of</strong> Bere-Mures by Heineken was a reactive or proactive
process, probably due to <strong>the</strong> fact that Bere-Mures was <strong>the</strong> last opportunity for a significant market
share gain by acquisition.
Bere-Mures shareholders sold <strong>the</strong> company simply because it was <strong>the</strong> best moment <strong>of</strong> exiting <strong>the</strong>
market, at <strong>the</strong> beginning <strong>of</strong> 2008 <strong>the</strong> beer market being still in one <strong>of</strong> <strong>the</strong> best evolution moments,
afterwards <strong>the</strong> beer market decrease by 13% in 2009 compared to 2008 (Romanian Beer Association,
2010). On <strong>the</strong> o<strong>the</strong>r side, because <strong>of</strong> <strong>the</strong> market consolidation characteristics, <strong>the</strong> main players Ursus
and Heineken, fighting for <strong>the</strong> first position were forced to get involved in <strong>the</strong> process and make a
decision.
Heineken paid much attention on <strong>the</strong> market position <strong>of</strong> <strong>the</strong> brands recent acquired by maintain only
<strong>the</strong> main brand, Neumarkt, to avoid cannibalization through investments in too many economic
brands. Ano<strong>the</strong>r important decision was to not maintain <strong>the</strong> core beer activity and not to focus on <strong>the</strong>
water and hotel industry that Bere-Mures was also developing, and recently after acquisition <strong>the</strong> water
division and hotel both were sold.
At <strong>the</strong> moment <strong>of</strong> <strong>the</strong> acquisition <strong>the</strong> market share difference between Heineken and its main
competitor SAB Miller was <strong>of</strong> only 1% thus <strong>the</strong> fight <strong>of</strong> getting Bere-Mures that accounted for 6% <strong>of</strong>
<strong>the</strong> market was very tight with both player negotiating in parallel with Bere-Mures.
Heineken turned potential threat into an opportunity by acting depending on its relative positioning on
<strong>the</strong> market, if Heineken would have not acquired Bere-Mures, its main competitor Ursus Breweries
would have done that, Heineken would have missed growth opportunity.
Improve competitive position is one <strong>of</strong> <strong>the</strong> main drivers <strong>of</strong> M&A transactions and this was also one <strong>of</strong>
<strong>the</strong> main reasons for Bere-Mures acquisition
5. Methodology
The research method is defined in three parts, which contains a <strong>the</strong>oretical point <strong>of</strong> view, using <strong>the</strong>
macro economical description, and also a methodological research based on a quantitative research
and a quantitative research.
Interviewing and recording <strong>the</strong> key people in <strong>the</strong> transaction did <strong>the</strong> quantitative research and <strong>the</strong>
quantitative research was conducted during October and November 2010 through on-line
questionnaires for all <strong>the</strong> managers and seniors.
For <strong>the</strong> qualitative research we interviews with <strong>the</strong> most important people from Heineken Romania at
that time, Flavius Adrian Cimpian (Legal Manager) and Vasile Ciurba (Heineken Administer) and it
lasted 30 minutes each meeting. We wanted to find out every aspect <strong>of</strong> <strong>the</strong> negotiation from <strong>the</strong> point
it started to <strong>the</strong> point <strong>the</strong> transaction was complete and also we wanted to find out <strong>the</strong> openness <strong>of</strong>
<strong>the</strong> Romanian managers regarding transformational leadership.
In <strong>the</strong> Appendix 1 can be observed <strong>the</strong> results <strong>of</strong> <strong>the</strong> questionnaire after an analysis <strong>of</strong> SPSS, a
statistical program. To have a better image <strong>of</strong> what <strong>the</strong> results we have obtained also data regarding
<strong>the</strong>ir gender, level <strong>of</strong> education and age. We obtained data from 135 out <strong>of</strong> 148 employees who have
46

Sorin Anagnoste and Gabriela Dumitru
at least senior in his position and have a team. The percentage resulted from <strong>the</strong> study is 91%, which
is a very good rate <strong>of</strong> response.
As we know, <strong>the</strong> leadership styles <strong>the</strong> managers use has focused in some researches on gender or
level <strong>of</strong> education, or on <strong>the</strong> hierarchy and its impact on leadership (Stordeur, Vandenberghe &
D’hoore, 2000). We believe that a better approach is to examine both personal and organization
dimensions regarding transformational leadership (Reader et all,2008) through <strong>the</strong> sever factors we
have enumerated at <strong>the</strong> beginning are also to try to differentiate from <strong>the</strong> very general items
described by Bass (2002) in his book.
The conclusions are divided in two parts: findings and unexpected findings.
5.1 Qualitative research
We wanted to see “how” and “why” was <strong>the</strong> acquisition a success for Heineken Romania, and not only
“what”, “where”, “when”. During <strong>the</strong> research we had interview session with <strong>the</strong> negotiation team also,
made by Mr. Vasile Ciurba, member <strong>of</strong> Board <strong>of</strong> Administration member, and Mr Flavius Cimpian,
Legal Manager. In <strong>the</strong> interview with Mr. Ciurba we found out <strong>the</strong> very though position he was during
<strong>the</strong> negotiations and after this, restructuring <strong>the</strong> business. “The process started right away”, as he
mentioned, “and it was necessarily to align all <strong>the</strong> processes <strong>of</strong> Bere-Mures with those <strong>of</strong> Heineken
Romania”. We identified that during this process <strong>the</strong>y used <strong>the</strong> system called Total Product
Management, which is very similar with Six Sigma concept, where Sig Sigma can enact as an enabler
for cultural change (Draghici, Petcu;2010). Ano<strong>the</strong>r aspect that we considered important was “<strong>the</strong>
leadership style <strong>of</strong> <strong>the</strong> Romanian management <strong>of</strong> Bere-Mures, which was a direct leadership style,
<strong>the</strong> decisions were taken much faster compared to Heineken Romania”, as Mr Ciurba stated.
Our aim was also to ga<strong>the</strong>r a better an in-depth understanding <strong>of</strong> what <strong>the</strong>ir leadership traits are and
to observe if <strong>the</strong>ir answers to <strong>the</strong> questionnaire were reflecting <strong>the</strong>ir opinions.
Although <strong>the</strong> negotiations between Heineken and Romania started after those between <strong>the</strong>
negotiations <strong>of</strong> Ursus and Bere-Mures, <strong>the</strong> negotiation team made by Flavius Cimpiam and Vasile
Ciurba, believed position <strong>of</strong> <strong>the</strong>ir success due to diplomacy, respect, trust and leadership showed in
front <strong>of</strong> <strong>the</strong> Board <strong>of</strong> Administration <strong>of</strong> Bere-Mures (Naidoo and Lord, 2008). It was felt during <strong>the</strong>
discussion with Mr Cimpian and Mr Ciurba that Ursus might have ignored <strong>the</strong>ir presence at
negotiations and conform <strong>the</strong> negotiation manual this can be attributed to <strong>the</strong> “delays tactics” that
organizations use in this kind o activity. The success <strong>of</strong> <strong>the</strong> negotiation team was <strong>the</strong> success <strong>of</strong> all
<strong>the</strong> Heineken’s departments and third parties exemplary collaboration due to a great leadership.
5.2 Quantitative research: Sample and procedures
A questionnaire survey was made by us following a brainstorming and contains 28 questions, divided
on seven areas: values, vision, optimism, innovation and change, trust, motivation and emotional
intelligence. The questionnaire was conducted on 148 managers or seniors who have at least two
people under guidance. We used Lotus Notes, which is <strong>the</strong> internal electronic communication system
within Heineken Romania, to send <strong>the</strong> questionnaire. The questionnaires covered managers and
seniors from all <strong>the</strong> regions <strong>of</strong> <strong>the</strong> country in which were breweries or local <strong>of</strong>fices.
The e-mail was accompanied by a descriptive letter, which contained <strong>the</strong> subject <strong>of</strong> <strong>the</strong> research, <strong>the</strong>
importance <strong>of</strong> everyone in order to complete <strong>the</strong> research, <strong>the</strong> confidentiality <strong>of</strong> <strong>the</strong>ir answers and <strong>the</strong>
availability <strong>of</strong> <strong>the</strong> article when will be made public. A total <strong>of</strong> 135 questionnaires were completed and
returned and we obtained a 91% response rate after we have made a phone call to everybody as a
reminder. We observed that <strong>the</strong> higher in hierarchy, <strong>the</strong> harder was for us to obtain a completed
questionnaire, though this can be explained by <strong>the</strong> lack <strong>of</strong> free time, pressure and o<strong>the</strong>r problems that
<strong>the</strong>y face in daily. Also, <strong>the</strong> difference to 100% completed surveys can be explained to <strong>the</strong> fact that
some <strong>of</strong> <strong>the</strong>m don’t fill in unsolicited surveys (House, Woycke & Fodor,2001).
The questionnaire requested to respondents to indicate <strong>the</strong> ways <strong>the</strong>y deal in <strong>the</strong>ir daily activities
regarding our seven items we defined for transformational leadership. The were also asked to indicate
<strong>the</strong>ir age among 5 age groups specified in <strong>the</strong> survey, namely: 1) up to 30, 2) 31-40, 3) 41-50, 4) 51-
60, 5) >61. The leadership styles which managers adopt has changed radically over <strong>the</strong> last 60 years
(Gill, 2003) and we started to see that is less use <strong>of</strong> directive leadership in favor <strong>of</strong> transactional and
47

Sorin Anagnoste and Gabriela Dumitru
transformational leadership, which we will go into more details later in <strong>the</strong> paper. The top and middle
management started to be younger and younger, and this research can be <strong>the</strong> start <strong>of</strong> a second part
in <strong>the</strong> near future due to <strong>the</strong> rapid transformation <strong>of</strong> <strong>the</strong> markets, especially when important events
occur more <strong>of</strong>ten than ever. The research can be an answer to <strong>the</strong> suggestion <strong>of</strong> Kabac<strong>of</strong>f (2002)
regarding <strong>the</strong> personal characteristics, such age, education, etc that have a significant impact on
leadership. For example, <strong>the</strong> youngest manager within Heineken Romania is under 30 years old and
this can be an answer to a lot <strong>of</strong> questions, especially when you want to improve <strong>the</strong> management <strong>of</strong>
<strong>the</strong> human resources.
Therefore, <strong>the</strong> present work attempts a comprehensive research <strong>of</strong> transformational leadership <strong>of</strong>
managers from two perspectives, personal and organizational dimensions, to describe new both <strong>the</strong>
individual and also <strong>the</strong> impact <strong>of</strong> <strong>the</strong>se variables on leadership practice.
Also, <strong>the</strong> respondents were also asked to indicate <strong>the</strong>ir last form <strong>of</strong> education completed: 1) Highschool,
2) University, 3) Master, 4) PhD, 5) MBA
The rating scale adopted was Likert-type scale from 1 (Strongly Disagree), 2 (Partially Disagree), 3
(Uncertain), 4 (Partially Agree), 5 (Strongly agree). Some authors, like Hogan and Hogan (2001) are
not in favor <strong>of</strong> self-report data used in leadership research, because <strong>the</strong>y consider that “leadership is
a social influence process and thus, should be determined by manager’ s staff/direct reports”. (Hogan,
2005,p.3). Moreover, while Gill (2003) accepts that self-reports are open to criticism, he argued that
<strong>the</strong>y could be valid and very important in certain circumstances. Bass (2002) has demonstrated how
“self-report personality scales show predictable, significant and substantial correlations with criteria <strong>of</strong>
management job success”.
6. SPSS interpretation
The first step <strong>of</strong> <strong>the</strong> analysis is to determine whe<strong>the</strong>r <strong>the</strong> twenty-eight statements represent
identifiable factors. The method used for this objective is factor analysis. The analysis was initiated
with <strong>the</strong> assumption that all variables are correlated to some extent. Therefore, those variables that
share similar underlying dimensions should be highly correlated, and those variables that measure
dissimilar dimensions should yield low correlations. The adequacy <strong>of</strong> <strong>the</strong> correlation matrix is
measured with <strong>the</strong> help <strong>of</strong> <strong>the</strong> KMO (0.76, which is over 0.6; KMO measures <strong>the</strong> sampling adequacy
which should be greater than 0.6 for a satisfactory factor analysis to proceed) and Bartlett test that
yield a valued <strong>of</strong> 913.522 and an associated level <strong>of</strong> significance smaller than 0.001. Thus, <strong>the</strong>
correlation matrix has significant correlations among at least some <strong>of</strong> <strong>the</strong> variables.
Once applied <strong>the</strong> factor analysis with main component extraction through varimax orthogonal rotation
were obtained 7 factors that represent 61.3 percent <strong>of</strong> <strong>the</strong> information contained in <strong>the</strong> original data.
Applying an oblimin rotation also shows <strong>the</strong> same results. Table 2 presents <strong>the</strong> percentage <strong>of</strong> each
factor accounted in total variance.
Component
Total
Initial Eigenvalues
% <strong>of</strong> Variance Cumulative %
1 7.444 26.584 26.584
2 2.062 7.366 33.950
3 1.797 6.417 40.367
4 1.705 6.091 46.458
5 1.511 5.397 51.855
6 1.343 4.797 56.652
7 1.302 4.649 61.301
Figure 6: Total variance explained
After a first analysis <strong>of</strong> <strong>the</strong> factors extracted in <strong>the</strong> varimax rotation we have decided to rerun <strong>the</strong>
analysis and impose <strong>the</strong> condition to have a fixed number <strong>of</strong> five factors extracted because <strong>the</strong>
difference between <strong>the</strong> fifth and sixth is considerable. The initial rotated factor structure showed a
number <strong>of</strong> cross-loaded items. Deletion <strong>of</strong> cross-loaded items serves to clarify <strong>the</strong> factors and makes
<strong>the</strong>ir interpretation easier.
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Sorin Anagnoste and Gabriela Dumitru
The first factor extracted from <strong>the</strong> second rotation explained 26.58 percent <strong>of</strong> <strong>the</strong> total variance.
Among <strong>the</strong> items included in this factor are: You emphasize in front <strong>of</strong> your team <strong>the</strong> importance <strong>of</strong> a
common mission aligned with organization's vision, you communicate your organization's vision to
your team, you make decisions based on your organization's values, you identify improvement
opportunities for <strong>the</strong> product/services you <strong>of</strong>fer or <strong>the</strong> opportunity to introduce new/innovative ones,
You integrate current market evolution in your own field <strong>of</strong> activity in <strong>the</strong> proposals you make, You
explain <strong>the</strong> path to reach your organization long term objectives, You are constantly seeking new
ways to increase <strong>the</strong> involvement <strong>of</strong> those under your supervision. Thus, analyzing <strong>the</strong> content <strong>of</strong> <strong>the</strong>
sentences included in <strong>the</strong> first factor extracted we can conclude that an important factor in
transformational leadership is <strong>the</strong> vision <strong>the</strong> leader has and his/her identification as a change agent
within <strong>the</strong> organization. The second factor that can be identified from <strong>the</strong> analysis includes items such
as: You identify misunderstandings and you make sure <strong>the</strong>y are diminished, You see delegation as a
sign <strong>of</strong> trust, The members <strong>of</strong> your team have <strong>the</strong> courage to express a point <strong>of</strong> view which is different
than yours, You encourage your team/colleagues to come up with new solutions or ways <strong>of</strong> working.
The statements included in <strong>the</strong> second factor analyzed reveal <strong>the</strong> importance <strong>of</strong> <strong>the</strong> relationship that
<strong>the</strong> leader has with <strong>the</strong> group. Factor 3 includes statements that clearly demonstrate <strong>the</strong> importance
<strong>of</strong> trust among <strong>the</strong> team players and <strong>the</strong> leader <strong>of</strong> <strong>the</strong> group (Through your actions you inspire <strong>the</strong>
o<strong>the</strong>rs to outperform <strong>the</strong>mselves, You use symbols, stories, rituals to create <strong>the</strong> trust and identity <strong>of</strong> a
team, You inspire power and pride in your team, You demonstrate to <strong>the</strong> members <strong>of</strong> your team that
<strong>the</strong>y need to take into account <strong>the</strong> feelings and needs <strong>of</strong> o<strong>the</strong>rs). Factor 3 is in close connection with
<strong>the</strong> fourth factor identified from <strong>the</strong> analysis. The latter includes statements that demonstrate <strong>the</strong> need
<strong>of</strong> <strong>the</strong> leaders to take decision which are in accordance with <strong>the</strong> moral and ethical principles, involving
employees in <strong>the</strong> decision making process (e.g. You always take in consideration <strong>the</strong> moral and
ethical consequences <strong>of</strong> your decisions, You encourage your team to participate in decision making
and you try to implement <strong>the</strong>ir ideas and suggestions). Whereas, <strong>the</strong> fifth factor identified reveals <strong>the</strong>
importance <strong>of</strong> optimism, as a trait <strong>of</strong> <strong>the</strong> perfect leader (e.g. You think <strong>of</strong> yourself as a lucky person).
The sixth factor is motivation (e.g. You act upon <strong>the</strong> opportunities you have identified, The members
<strong>of</strong> your team have <strong>the</strong> courage to express o point <strong>of</strong> view which is different from yours), which it
seems that is not so important compared to <strong>the</strong> factors we have described above. We think that is a
cultural aspect regarding this factor.
The last factor is represented by emotional intelligence (e.g. Emotional intelligence is more important
than intelligence quotient) obtained a response that it was so impressive and this we might correlate
<strong>of</strong> 45 years spent in communism by <strong>the</strong> country.
The reliability <strong>of</strong> a measuring represents <strong>the</strong> consistency <strong>of</strong> <strong>the</strong> factors determined and <strong>the</strong> internal
consistency <strong>of</strong> <strong>the</strong> factors should be tested to ensure <strong>the</strong> reliability <strong>of</strong> <strong>the</strong> factors. Cronbach's Alpha is
0.86 which is higher than 0.7 for all <strong>of</strong> <strong>the</strong> seven factors, which indicates high overall internal
consistency among <strong>the</strong> items representing <strong>the</strong> factors. Regarding reliability we also used
communalities, which demonstrated also that all <strong>the</strong> factors were above 0,5.
We used ANOVA test, which is <strong>the</strong> simplest test <strong>of</strong> whe<strong>the</strong>r or not <strong>the</strong> means <strong>of</strong> our four groups <strong>of</strong>
people, divided by age, are all equal. The advantage <strong>of</strong> ANOVA over t-test is that doing two-sample ttests
would result in an increased chance <strong>of</strong> committing a type L error. We obtained <strong>the</strong> highest mean
for <strong>the</strong> group 41-50, followed by <strong>the</strong> group under 30 and <strong>the</strong> last group by <strong>the</strong> mean is <strong>the</strong> group with
ages between 51 and 60. We can conclude that regarding <strong>the</strong> seventh factor, emotional intelligence, it
is requested a deep research on this topic due to <strong>the</strong> characteristics and influence <strong>of</strong> economic and
social background during <strong>the</strong> last half <strong>of</strong> 20 th century in Europe.
7. Conclusions
Historically, half <strong>of</strong> <strong>the</strong> M&A activities have failed to create lasting shareholder value. Findings in a
ten-year A.T. Kearney study on stock performance after mergers reveals that since 1990, in two years
after <strong>the</strong>ir deal closed, nearly 50% <strong>of</strong> <strong>the</strong> biggest mergers and acquisitions failed to produce total
shareholders returns greater than <strong>the</strong>ir industry peers. Only 30% outperformed <strong>the</strong>ir industry peers
(by 15% or more) and had earned a penny more in pr<strong>of</strong>itability two years later. After 5 years, 70% <strong>of</strong>
<strong>the</strong> survivors were still chronic under performers in <strong>the</strong>ir industry (Perry and Herd, 2004).
Studies repeatedly confirm that half <strong>of</strong> all business “marriages” fail. Yet when M&A works <strong>the</strong>y create
significant value <strong>the</strong> secret to <strong>the</strong>ir success is a strong leadership combined with pr<strong>of</strong>essional
execution and <strong>the</strong> pursuit <strong>of</strong> growth, right from <strong>the</strong> start.
49

Sorin Anagnoste and Gabriela Dumitru
However, Bere-Mures acquisition by Heineken proved to be <strong>the</strong> right decision at <strong>the</strong> right time. A
follow-up <strong>of</strong> <strong>the</strong> transactions shows a significant improvement in both companies’ activities after <strong>the</strong>
merger.
One limitation <strong>of</strong> <strong>the</strong> study is <strong>the</strong> nature <strong>of</strong> <strong>the</strong> sample. All <strong>the</strong> subjects came from brewery sector. It is
Heineken Romania with its specialties regarding its history, its culture, philosophy, managerial
practices and values. It is a family owned business and it would be interested comparing with o<strong>the</strong>r
competitors like AB Inbev, SAB Miller, etc.
We obtained and interpreted results using questions, which define transformational leadership, but it
will be interesting to interpret <strong>the</strong> answers <strong>of</strong> questionnaires related to o<strong>the</strong>r styles <strong>of</strong> leadership or to
do a 360-degree transformational leadership interpretation.
Findings
During <strong>the</strong> negotiation process <strong>the</strong> Heineken team was very humble and had an attitude <strong>of</strong> selfdeterminacy
and strong confidence, which was very important when <strong>the</strong> shareholders <strong>of</strong> Bere-
Mures took <strong>the</strong> decision; this is also known as tacit knowledge (Orzea, Agoston;2009) which was
represented by having worked in that culture and using <strong>the</strong> using tacit knowledge is very hard for
outsiders to imitate it, and <strong>the</strong>refore, to be transferred;
Due to <strong>the</strong> fact that <strong>the</strong> negotiation team was from <strong>the</strong> same region with <strong>the</strong> shareholders seems
to be an advantage;
We believe that <strong>the</strong> Ursus team made its presentations in English, its negotiations in English and
<strong>the</strong> documentation presented to shareholders in English. These issues, whilst not influencing in
<strong>the</strong> cash value <strong>of</strong> <strong>the</strong>ir <strong>of</strong>fer, seems to have been significant in <strong>the</strong> decision which <strong>of</strong>fer to accept;
We think that <strong>the</strong> lost was pr<strong>of</strong>ound for Ursus, because on <strong>the</strong> medium and long term producing
beer in a big city and respecting environment legislation is not <strong>the</strong> best thing you can do; when we
are writing this article in <strong>the</strong> Financial newspaper appeared <strong>the</strong> news that Ursus is closing <strong>the</strong>
brewery from Cluj;
The leadership (top management) <strong>of</strong> Heineken is changing every 3-4 years from country to
country and this is an example <strong>of</strong> reaching that maturity, development and ability to lead for every
management member, which was translated in <strong>the</strong> end in a perfect collaboration to achieve <strong>the</strong>
goal: acquiring Bere-Mures (Kelloway and Barling, J. 2009);
The CEO <strong>of</strong> Heineken at that time delegated <strong>the</strong> negotiation process to people from that region
compared to Ursus who sent <strong>the</strong> experts from London. By doing this <strong>the</strong> CEO proved an example
<strong>of</strong> Level 5 leadership by setting up his successors for even greater success in <strong>the</strong> next
generation; a Level 5 leaders embody a mix between personal humility and pr<strong>of</strong>essional will. The
egos <strong>of</strong> most CEOs contributed to demise or mediocrity;
It is said that we work for our self interest, but we do not work for our self interest all <strong>the</strong> time
because emotions change our way <strong>of</strong> thinking (Anagnoste et al, 2009);
Unexpected findings
All Heineken’s CEOs came from inside;
In <strong>the</strong> discussion with <strong>the</strong> negotiation team we observed that <strong>the</strong> good luck was an attribute <strong>of</strong>ten
presented for <strong>the</strong> success, ra<strong>the</strong>r than personal greatness;
We were not looking for transformational leaders in our research, but <strong>the</strong> data ga<strong>the</strong>ring was
convincing. It was an empirical, not an ideological, finding;
People formed in Heineken Romania became leaders in o<strong>the</strong>r industries, which results that
leaders create leaders;
8. Appendix 1
Factor analysis results for Transformational Analysis
50

Note: Values below 0.3 are suppressed
References
Sorin Anagnoste and Gabriela Dumitru
Anagnoste, S., Agoston,S. & Puia (2010), R. Transformational leadership as a tool <strong>of</strong> knowledge dynamics,
<strong>European</strong> <strong>Conference</strong> on Intellectual Capital, 2 nd edition, Lisbon
Bass, B.M. and Riggio, R.E. (2002), Transformational leadership, 2nd edition, Lawrence Wrlbaum Associates,
London
Bratianu, C., Jianu, I., Vasilache, S. (2007) Integrators for organizational intellectual capital, IC-Congress 2007,
INHOLLAND University <strong>of</strong> pr<strong>of</strong>essional education, Haarlem, The Ne<strong>the</strong>rlands, 3-4 May 2007
Cole, Rebel A., Ferris, Kenneth R. and Melnik, Arie L. (2010) The Cost <strong>of</strong> Advice in Merger & Acquisition
Transactions, AT Kearney
Drăghici, M., Petcu, A.J. (2010) TQM and Six Sigma - <strong>the</strong> role and impact on service organization. „Risk and
opportunities on <strong>the</strong> emerging markets”, <strong>Conference</strong> (ASE Bucharest). The Romanian Economic Journal.
Gill, R. (2003), Towards an Integrative Model <strong>of</strong> Leadership, Queen’s University <strong>of</strong> Belfast, School <strong>of</strong>
Management and Economics, December
Hogan, R., and Hogan, J. (2001). Assessing Leadership: A View from The Dark Side, International Journal <strong>of</strong>
Selection and Assessment, 9, 40-51
Kelloway, E.K. and Barling, J. (2009), What we have learned about developing transformational leaders,
Leadership & Organization Development Journal, Vol. 21 No. 7, pp. 355-62.
House R.J., Woycke J., & Fodor E.M. (1986), Charismatic Leadership in US Presidential Office, paper presented
at <strong>the</strong> annual Academy <strong>of</strong> Management Meetings, San Diego, California
51

Sorin Anagnoste and Gabriela Dumitru
Kabac<strong>of</strong>f, R.I. (2002). Leadership: What Has Age Got to do With It?, Research Release, New York: Management
Research Group
Naidoo, L.J. and Lord, R.G. (2008), Speech imagery and perceptions <strong>of</strong> charisma: <strong>the</strong> mediating role <strong>of</strong> positive
affect, Leadership Quarterly, Vol. 19 No. 3, pp. 283-96.
Niewiem, S. and Ro<strong>the</strong>nbucher, J. (2008), Due Dilligence: Think operational, Discovering “quick win” value in
mergers and acquisitions, A.T. Kearney
Northouse, P.G. (2007) Leadership – <strong>the</strong>ory and practice forth edition. Sage Publications, London
Orzea,I and Agoston, S, (2010) Sharing and integrating tacit knowledge, Business Excellence <strong>Conference</strong>,
Brasov
Perry, S.J. and Herd, J.T. (2004) Mergers and acquisitions: Reducing M&A risk through improved due diligence,
A.T. Kearney, Vol. 32 No.2
Reader, S. M., Bruce, M. J. & Rebers, S. (2008). Social learning <strong>of</strong> route preferences in adult humans. Biology
Letters, 4, 37-40
Ro<strong>the</strong>nbuecher, J. and von Hoyningen-Huene, J. (2008) The rise <strong>of</strong> Emerging Markets in Mergers and
Acquisitions, A.T. Kearney
Ro<strong>the</strong>nbucher, J. and Declerq, S. (2008) Three years after <strong>the</strong> marriage, AT Kearney
Stordeur, S., Vandenberghe, C., and D’hoore, W. (2000). Leadership Styles across Hierarchical Levels in
Nursing Departments. Nursing Research, 49, 37-43
52

Added Value to Organizational Knowledge by Managing
<strong>European</strong> Projects
Gabriela Atanasiu and Florin Leon
Technical University Gheorghe Asachi <strong>of</strong> Iaşi, Romania
gabriela.atanasiu@gmail.com,
atanasiu@ce.tuiasi.ro
florinleon@gmail.com,
fleon@cs.tuiasi.ro
Abstract: Due to <strong>the</strong> fact that project management has become an important tool for organizations acting in
different areas <strong>of</strong> society, including academic organizations, <strong>the</strong> implementation <strong>of</strong> small and large projects within
Research Frame Programme FP7 or/and in o<strong>the</strong>r specific <strong>European</strong> Programmes could play an important role to
enhance organizational knowledge, adding value, not only for <strong>the</strong> project team <strong>of</strong> beneficiary organizations, but
also for <strong>the</strong> organization itself. The excellent opportunities open for Romanian organizations, since 2007, when
Romania became a member <strong>of</strong> <strong>the</strong> <strong>European</strong> Union, have led to an increase in <strong>the</strong> competition for new projects
for universities and research institutions, <strong>the</strong> success rate in gaining projects <strong>of</strong> <strong>European</strong> dimension being
directly related to <strong>the</strong> level <strong>of</strong> organizational culture. A good exemplification <strong>of</strong> <strong>the</strong> growth <strong>of</strong> knowledge in <strong>the</strong>
management <strong>of</strong> <strong>European</strong> projects is illustrated by <strong>the</strong> formation and evolution <strong>of</strong> an interdisciplinary team <strong>of</strong> <strong>the</strong>
Multidisciplinary Centre <strong>of</strong> Structural Engineering & Risk Management (MCSERM) acting within <strong>the</strong> academic
environment <strong>of</strong> <strong>the</strong> Technical University “Gheorghe Asachi” <strong>of</strong> Iaşi, Romania. The continuous evolution <strong>of</strong> project
management culture began with <strong>the</strong> implementation <strong>of</strong> <strong>the</strong> MATRA/PSO project on quality assurance in
Romanian universities (2000-2003), followed by <strong>the</strong> EUA Quality Culture project (2005-2006), which represented
learned lessons <strong>of</strong> effectively dealing with projects and improving <strong>the</strong> team skills for planning a project, managing
<strong>the</strong> project, minimizing <strong>the</strong> risk, and maintaining <strong>the</strong> control <strong>of</strong> <strong>the</strong> project. Based on <strong>the</strong> individual and social
knowledge created within <strong>the</strong> above-mentioned <strong>European</strong> context, <strong>the</strong> existing research centre has been
successfully integrated in <strong>the</strong> recently gained FP7 projects, in execution until 2013. A case study based on <strong>the</strong>
use <strong>of</strong> new instruments <strong>of</strong> FP7, leading to <strong>the</strong> improvement <strong>of</strong> knowledge within <strong>the</strong> interdisciplinary research
centre is discussed and documented by <strong>the</strong> accumulated experience at an individual and institutional level.
Keywords: organizational knowledge, project management, <strong>European</strong> projects
1. Introduction
Knowledge transfer is a dominant subject within <strong>the</strong> present society based on globalisation and on a
tremendous development <strong>of</strong> informational technology. The present paper presents some new trends
in Project Management, applicable to knowledge transfer projects. Along with <strong>the</strong>se new trends, <strong>the</strong>
paper highlights <strong>the</strong> lessons learned in a special knowledge transfer project within MATRA/PSO
programme <strong>of</strong> Romania’s pre-accession efforts to <strong>the</strong> <strong>European</strong> Union, as well as <strong>the</strong> participation as
network coordinator in EUA Quality Culture Project. They deal with a sensitive issue <strong>of</strong> Quality
Assurance implementation in Romanian universities based on <strong>the</strong> best practice from <strong>the</strong> <strong>European</strong>
universities. The projects showed <strong>the</strong> importance <strong>of</strong> transnational knowledge and know-how transfer,
in parallel with streng<strong>the</strong>ning <strong>the</strong> institutional capacity <strong>of</strong> processing this kind <strong>of</strong> new inputs.
Both before and after Romania’s accession to <strong>the</strong> EU, initiating, obtaining and implementing projects
for knowledge transfer were important issues in project management, as an essential issue in <strong>the</strong>
present knowledge society. The case studies presented in section 5 contain an analysis <strong>of</strong> <strong>the</strong> results
obtained within <strong>the</strong> concept <strong>of</strong> “learning by doing”, for knowledge transfer projects in higher education
quality assurance implemented in Romania.
2. Project management – a source for knowledge enhancement
At <strong>the</strong> end <strong>of</strong> <strong>the</strong> 2 nd millennium and especially at <strong>the</strong> beginning <strong>of</strong> <strong>the</strong> 3 rd millennium, project
management became more <strong>of</strong> a business standard, both for private sector and for public sector, with
increasingly diverse fields <strong>of</strong> application, as well as increasingly sophisticated patterns and
development forms. One can notice that <strong>the</strong> statement “project management era”, used to
characterize <strong>the</strong> current period is used more and more by <strong>the</strong> managers and experts from almost all
sectors <strong>of</strong> economic, social and political life (Gray & Larson, 2003). The compression/reduction <strong>of</strong>
product lifecycle, due to <strong>the</strong> development <strong>of</strong> high-end fabrication techniques represents one <strong>of</strong> <strong>the</strong>
major driving forces <strong>of</strong> project management progress. If 30 years ago a 10-year lifecycle <strong>of</strong> a product
was considered unusually short, now we witness <strong>the</strong> development <strong>of</strong> products with average lifecycles
<strong>of</strong> 1.5 to 3 years.
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Gabriela Atanasiu and Florin Leon
The global competition increases <strong>the</strong> importance <strong>of</strong> project management in <strong>the</strong> organizations that
produce goods and services, in general. The actual market requirements involve increasingly cheaper
products and services, but also increasingly better ones. This imposes a need for certification, through
<strong>the</strong> ISO 9000 family <strong>of</strong> management and quality assurance standards for products all over <strong>the</strong> world.
The development <strong>of</strong> quality management also assumes <strong>the</strong> development <strong>of</strong> project management, to
allow <strong>the</strong> application <strong>of</strong> principles, methodologies, and procedures specific to quality assurance. The
informational revolution has led to <strong>the</strong> increase <strong>of</strong> project complexity in any field <strong>of</strong> reference.
Organizational reengineering, characterised by dramatic changes, presupposed <strong>the</strong> implementation <strong>of</strong>
change projects, as well as change management in order to increase efficiency and competitiveness.
The orientation towards customer requirements within a global competition leads organizations to
pursue customer satisfaction. At <strong>the</strong> same time, clients manifest a preference towards customized
products to <strong>the</strong>ir specific needs. This tendency assumes an intensification <strong>of</strong> <strong>the</strong> dialogue and direct
relation between <strong>the</strong> producer and <strong>the</strong> client. After <strong>the</strong> year 2000, in <strong>the</strong> curricula <strong>of</strong> prestigious
universities especially in <strong>the</strong> USA and Western Europe, <strong>the</strong> Project Management subject can be <strong>of</strong>ten
found. This subject was introduced both in Bachelor programmes, and in Master programmes, both
economical and engineering, and also in <strong>the</strong> fields <strong>of</strong> science, letters, arts, etc.
Project management can be characterised by two essential dimensions:
The technical dimension, including planning, scheduling, and project control. This dimension is
formal, purely logical and develops on <strong>the</strong> basis <strong>of</strong> <strong>the</strong> available information about <strong>the</strong> system.
The project involves a clear statement <strong>of</strong> project mission and objectives, aiming at <strong>the</strong> relation
between <strong>the</strong> project and its client;
The socio-cultural dimension, referring to <strong>the</strong> environment in which <strong>the</strong> project develops. This
dimension involves <strong>the</strong> temporary social system, <strong>the</strong> political environment, client expectations
toge<strong>the</strong>r with aspects related to leadership, to <strong>the</strong> competencies and abilities <strong>of</strong> THE project team,
to <strong>the</strong> wisdom and experience <strong>of</strong> <strong>the</strong> project manager to create all means to achieve <strong>the</strong> project
objectives, <strong>of</strong>ten in a difficult, contradictory setting, from <strong>the</strong> material or spiritual point <strong>of</strong> view. This
dimension plays an especially important role in knowledge transfer projects. The project manager
has <strong>the</strong> mission to create a temporary social system within <strong>the</strong> wider organizational environment,
a favourable context to <strong>the</strong> implementation <strong>of</strong> <strong>the</strong> project, based on a strong motivation <strong>of</strong> THE
team members, which can allow <strong>the</strong> identification and solving OF THE problems. This dimension
also imposes <strong>the</strong> evaluation and <strong>the</strong> management <strong>of</strong> <strong>the</strong> interfaces between <strong>the</strong> internal and
external environments <strong>of</strong> <strong>the</strong> project.
3. The Impact <strong>of</strong> projects on <strong>the</strong> organizational enhancement <strong>of</strong> culture
New ideas are only useful if <strong>the</strong>y result in changed practices. However, <strong>the</strong> diffusion <strong>of</strong> knowledge
and ideas is difficult. From <strong>the</strong> knowledge perspective, <strong>the</strong> idea that knowledge itself is power
provides a barrier to organizational endorsement <strong>of</strong> knowledge and ideas. Knowledge can be
considered an entity, <strong>the</strong>refore it can be captured and transferred (Tsoukas, 1996) and it can be
possessed (Blackler, 1995). Critics <strong>of</strong> this approach (Lam, 2000) emphasize <strong>the</strong> fact that knowledge
should be understood as an ongoing process, ra<strong>the</strong>r than something that someone possesses. It
means that knowledge needs to be fitted to practice and practiced, and thus it becomes part <strong>of</strong>
actions and beliefs (Lave & Wenger, 1991). In this way, <strong>the</strong> individuals <strong>of</strong> an organization feel that <strong>the</strong>
decisions and actions are <strong>the</strong>irs and not just an application <strong>of</strong> o<strong>the</strong>rs’ knowledge.
Knowing in action provides a sense <strong>of</strong> control, and implies that an agent can act and make decisions
from a range <strong>of</strong> possibilities based on <strong>the</strong> individual’s perception <strong>of</strong> what could be an appropriate
reaction in a given situation. This differs from <strong>the</strong> common view <strong>of</strong> learning and competence
development as simple adaptations to environmental changes (Andersen & Vaagaasar, 2009).
3.1 The interaction <strong>of</strong> cultural, leadership, project, management, and behavioural
factors on project outcomes
Badger et al. (2010) make a distinction between management and leadership. The former deals with
establishing order and structure by devising models that reflect <strong>the</strong> current reality and shape a desired
future. The latter is concerned with <strong>the</strong> vision, human motivation, decision making capabilities, and
relationships among different people whose actions ultimately determine <strong>the</strong> success or failure <strong>of</strong> a
project. National culture can be defined as <strong>the</strong> values and belief systems held by a group <strong>of</strong>
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Gabriela Atanasiu and Florin Leon
individuals, learned early in life, and difficult to change (H<strong>of</strong>stede, 1997). Given <strong>the</strong> international
character <strong>of</strong> many present projects, project management must acknowledge <strong>the</strong> influence <strong>of</strong> national
culture on <strong>the</strong> management <strong>of</strong> projects (Shore & Cross, 2005; Wang & Liu, 2007). These relationships
between culture, leadership, project management, and behavioural factors are summarized in figure
1, adapted after Shore (2008).
Figure 1: The relationships between <strong>the</strong> factors that influence a project’s outcome
Organizational culture develops within <strong>the</strong> context <strong>of</strong> national culture and executive leadership, and
can be defined as <strong>the</strong> shared perceptions <strong>of</strong> organizational work practices within organizational units
(H<strong>of</strong>stede, 1999). While executive leadership shapes <strong>the</strong> culture <strong>of</strong> <strong>the</strong> organization, project
leadership shapes project culture (Turner & Müller, 2006). Therefore, project culture represents <strong>the</strong>
shared perceptions <strong>of</strong> project work practices, influenced by both <strong>the</strong> project leader and organizational
culture, and is characterized by <strong>the</strong> way in which project planning, execution, and control are
exercised.
4. Success and perceived performance
In <strong>the</strong> contemporary competence-based society (Castells, 1996), it is very important for organizations
to develop <strong>the</strong>ir competences in order to stay competitive. Since value creation is increasingly a
matter <strong>of</strong> implementing projects, <strong>the</strong> organizations need to constantly improve <strong>the</strong>ir capacity for
managing projects (Davies & Brady, 2000).
An analysis concerned with studying <strong>the</strong> value <strong>of</strong> project management discovered <strong>the</strong> perception <strong>of</strong>
positive effects <strong>of</strong> <strong>the</strong> improvement attempts. According to Andersen and Vaagaasar (2009) <strong>the</strong>se
effects:
Provide a common base for communication and introduce common concepts;
Raise <strong>the</strong> competencies on project management;
Create a shared understanding <strong>of</strong> project management throughout <strong>the</strong> organization, including
administration and top management, as well as understanding <strong>of</strong> project management across
divisions;
Help <strong>the</strong> people answer <strong>the</strong> questions <strong>the</strong>y have to answer;
Create an understanding <strong>of</strong> <strong>the</strong> importance <strong>of</strong> projects and project management as a pr<strong>of</strong>ession
equal to o<strong>the</strong>r pr<strong>of</strong>essions;
Introduce a uniform way <strong>of</strong> doing and thinking <strong>of</strong> things;
Bring about a positive culture development;
Establish a broader base to recruit people for different projects - improved resource allocation;
Contribute to employee satisfaction - employees feel pr<strong>of</strong>essional;
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Gabriela Atanasiu and Florin Leon
Make employees feel prouder and actually be more competent;
Contribute to more learning in <strong>the</strong> organization;
Result in resource efficiency due to a more holistic view.
Project Management Maturity and organizational culture are expected to influence organizational
performance, and <strong>the</strong> resulting internal and external business performances <strong>of</strong> <strong>the</strong> organization, as
shown in figure 2, adapted after Yazici (2009).
Figure 2: Organizational factors and <strong>the</strong> perceived performance
Organizational perceived performance is measured by two dimensions: project performance and
business performance:
Project Performance. Traditionally, project success was measured as project completion on
time, within budget, and according to specifications. Because client satisfaction became
important, meeting customer expectations was added to <strong>the</strong>se measures (Mullaly, 2006). As
projects are accomplished by teams, one <strong>of</strong> <strong>the</strong> measures <strong>of</strong> success is how much <strong>the</strong> work team
was satisfied in working toge<strong>the</strong>r (Doolen, Hacker & Van Aken, 2003). Project performance is
measured by: project efficiency (meeting time and budget targets), and project effectiveness
(meeting customer expectations, and team satisfaction);
Business Performance. Business performance measures can measure an organization’s
performance by sales growth, return on investment, market-share gain, and overall competitive
position (Nahm, Vonderembse & Koufteros, 2004). Fur<strong>the</strong>r measures for project success can be
used, such as whe<strong>the</strong>r a project resulted in a new line <strong>of</strong> products or services (Dvir, Sadeh &
Malch-Pines, 2006): internal organization success factors (e.g. savings benefits <strong>of</strong> projects,
projects resulting in sales growth, and overall business performance compared with <strong>the</strong> previous
year), and external organization success factors (e.g. increased market share, whe<strong>the</strong>r <strong>the</strong>
organization improved its competitive position, and organization performance compared with <strong>the</strong>
best worldwide competition).
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Gabriela Atanasiu and Florin Leon
5. Learning by doing in <strong>the</strong> pre-accession phase
5.1 MATRA/PSO programme
The period 1998-1999, which preceded <strong>the</strong> signing <strong>of</strong> <strong>the</strong> Bologna Declaration in 1999, coincided with
<strong>the</strong> development <strong>of</strong> <strong>the</strong> MATRA/PSO Programme, regarding <strong>the</strong> bilateral cooperation between <strong>the</strong>
Kingdom <strong>of</strong> <strong>the</strong> Ne<strong>the</strong>rlands and Romania, dedicated to <strong>the</strong> countries involved in <strong>the</strong> pre-accession
phase to <strong>the</strong> EU (Atanasiu, 2001).
Romania was on <strong>the</strong> list <strong>of</strong> <strong>the</strong> 29 countries which signed <strong>the</strong> declaration regarding <strong>the</strong> formation <strong>of</strong>
<strong>the</strong> <strong>European</strong> Higher Education Area (EHEA), and this led to <strong>the</strong> initiation <strong>of</strong> actions to implement
quality management in this field, as an external and internal requirement to ensure a minimal
standard for quality in higher education. The idea to propose such a <strong>the</strong>me was immediately
acknowledged by <strong>the</strong> management factors in <strong>the</strong> MATRA/PSO programme <strong>of</strong> <strong>the</strong> Ne<strong>the</strong>rlands, and it
was one <strong>of</strong> <strong>the</strong> top selected projects in early 1999 in <strong>the</strong> pre-accession phase <strong>of</strong> Romania (Brătianu &
Atanasiu, 2000). The main objective <strong>of</strong> this project was to transfer knowledge and expertise in <strong>the</strong>
field <strong>of</strong> quality management <strong>of</strong> higher education in Romania, on national and institutional level <strong>of</strong>
universities, following <strong>the</strong> concept adopted by <strong>the</strong> <strong>European</strong> Commission since 1992 (Brătianu, 2002).
The whole project designed within <strong>the</strong> logical matrix created by <strong>the</strong> Dutch consortium formed <strong>of</strong> <strong>the</strong>
Royal Dutch Institute, CHEPS from <strong>the</strong> University <strong>of</strong> Twente, University <strong>of</strong> Utrecht and VSNU
(Engelkamp, 2003) was based on a “learning by doing” scheme, in terms <strong>of</strong> both project activities and
forming <strong>the</strong> group <strong>of</strong> participants in <strong>the</strong> field <strong>of</strong> quality in higher education. The concept <strong>of</strong> quality in
higher education was based on <strong>the</strong> model <strong>of</strong> quality elaborated by <strong>the</strong> <strong>European</strong> Foundation for
Quality Management presented in figure 3 (Atanasiu & Brătianu, 2005) and led to a first drop in
adding value to <strong>the</strong> individual team and organisational level <strong>of</strong> MCSERM.
Figure 3: Quality model
The flexibility <strong>of</strong> <strong>the</strong> managerial approach during <strong>the</strong> project lifecycle, which ultimately led to <strong>the</strong>
successful implementation <strong>of</strong> <strong>the</strong> project in <strong>the</strong> period <strong>of</strong> December 2000 – March 2003 has been very
important for <strong>the</strong> knowledge enhancement in PM <strong>of</strong> MCSERM team. These elements which help our
group to enhance <strong>the</strong>ir tacit knowledge in PM were as follows:
The SWOT analysis <strong>of</strong> <strong>the</strong> external environment in <strong>the</strong> initiation phase, in order to make <strong>the</strong>
necessary adjustments depending on <strong>the</strong> evolution <strong>of</strong> <strong>the</strong> position <strong>of</strong> stakeholders in <strong>the</strong> period
between defining and gaining <strong>the</strong> project and its actual execution;
The evaluation <strong>of</strong> risks associated with <strong>the</strong> project and adapting project management during <strong>the</strong>
lifecycle, respecting <strong>the</strong> programme objectives, initial budget and execution period;
The flexible managerial approach, with <strong>the</strong> redefinition <strong>of</strong> management procedures in case <strong>of</strong> <strong>the</strong>
changes to <strong>the</strong> external environment in order to minimise risk, but also to obtain <strong>the</strong> desired
results on short and medium term.
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Gabriela Atanasiu and Florin Leon
Because <strong>of</strong> <strong>the</strong> changes in <strong>the</strong> leadership <strong>of</strong> higher education within <strong>the</strong> Ministry <strong>of</strong> Education, project
MATO/RM/9/1 concentrated its implementation efforts on aspects <strong>of</strong> quality culture in higher
education, going from a top-down to a bottom-up strategy. This process benefited from an
accumulation <strong>of</strong> intellectual capital in <strong>the</strong> field <strong>of</strong> quality management in higher education, as a result
<strong>of</strong> <strong>the</strong> actions between 1998-2000 <strong>of</strong> a group <strong>of</strong> experts within <strong>the</strong> General Directorate for Higher
Education in <strong>the</strong> Ministry <strong>of</strong> Education and Research. A succinct description <strong>of</strong> <strong>the</strong> mission <strong>of</strong> this
group, <strong>the</strong> vision and innovative results is described in Brătianu’s work (2002).
With <strong>the</strong> help <strong>of</strong> <strong>the</strong> SWOT analysis for risk minimization, <strong>the</strong> focus <strong>of</strong> <strong>the</strong> project moved from ministry
level to pilot universities, achieved from <strong>the</strong> first time in university management in Romania, as an
actual exercise <strong>of</strong> evaluating <strong>the</strong> study programmes.
The experience accumulated by including experts <strong>of</strong> Romanian origin, actually pr<strong>of</strong>essors in
renowned universities in Europe represented a unique experience for <strong>the</strong> pilot programmes in <strong>the</strong>
considered universities, and a reference moment for <strong>the</strong> development <strong>of</strong> quality culture in Romanian
higher education institutions. As a knowledge transfer, but also experience transfer project, its effects
lasted after final project closure, by continuing its ideas in <strong>the</strong> Calistro project and <strong>the</strong> publication <strong>of</strong> a
valuable document regarding quality in higher education (Popescu & Brătianu, 2004).
5.2 EUA quality culture project
The EUA Quality Culture Project, funded by <strong>the</strong> Socrates Programme, was conceived to enable
participating institutions to discuss how to introduce and embed a quality culture in <strong>the</strong>ir institutions
and develop action plans in specific <strong>the</strong>matic areas (EUA, 2005). In EUA’s first action plan, internal
quality culture was viewed as <strong>the</strong> essential precondition to ensure public accountability and
streng<strong>the</strong>n institutional autonomy. The project showed <strong>the</strong> commitment <strong>of</strong> participating institutions to
develop a more systematic internal quality culture, to identify and compare good practices and to
implement appropriate action plans.
The EUA QC Project divided participant institutions into networks, and each network was responsible
for debating a certain aspect <strong>of</strong> institutional quality culture. Each network held three meetings,
resulting in six final network reports. The first meeting provided an opportunity for understanding each
partner’s institutional and national setting. The second meeting discussed <strong>the</strong> results <strong>of</strong> <strong>the</strong>
institutional analysis and <strong>the</strong>ir implications while <strong>the</strong> third examined <strong>the</strong> institutional action plans.
Thus, <strong>the</strong> meetings were based on three sets <strong>of</strong> documentation (institutional reports, institutional
analyses and action plans), which were <strong>the</strong> result <strong>of</strong> broad internal consultations within each partner
institution to ensure <strong>the</strong>ir validity and to embed <strong>the</strong> project results. The network reports indicate that
institutions gained valuable returns on efforts invested.
It became clear that best practices in internal quality are difficult to present as universal recipes
because each institution must decide for itself what <strong>the</strong>y are, based on a SWOT analysis for instance.
Therefore, it may be worth making a distinction between principles and <strong>the</strong>ir application in actual
practices – with <strong>the</strong> details <strong>of</strong> such practices presented by each institution. Key “good principles” have
to do with <strong>the</strong> overarching framework <strong>of</strong> an internal quality culture. Namely, each university must
organise its internal review to fit its own objectives and be coherent with its own academic and
organisational values. At <strong>the</strong> same time, each institution must balance <strong>the</strong>se against <strong>the</strong> need for
external accountability as defined in its national context while keeping in mind <strong>European</strong> and
international standards. In this context, “good principles” were found to include <strong>the</strong> following (EUA,
2005):
Building a university community and <strong>the</strong> staff’s identification with <strong>the</strong> institution;
Developing <strong>the</strong> participation <strong>of</strong> students in <strong>the</strong> university community;
Embedding a quality culture through internal communication, discussions and devolved
responsibility while understanding <strong>the</strong> resistance to change and developing strategies to
overcome it;
Agreeing upon an overarching framework for quality review processes and standards;
Defining key institutional data – historical, comparative, national and international – and
systematically collecting and analysing <strong>the</strong>m;
Involving <strong>the</strong> appropriate external and internal stakeholders;
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Gabriela Atanasiu and Florin Leon
Stressing <strong>the</strong> self-evaluation stage as a collective exercise for <strong>the</strong> unit under review to ensure <strong>the</strong>
implementation <strong>of</strong> <strong>the</strong> appropriate change (this includes academic and administrative staff and
students);
Ensuring a follow-up <strong>of</strong> <strong>the</strong> internal reviews, e.g. implementation <strong>of</strong> <strong>the</strong> appropriate
recommendations and feedback loops into strategic management.
The impact <strong>of</strong> this project on <strong>the</strong> team <strong>of</strong> <strong>the</strong> Multidisciplinary Centre <strong>of</strong> Structural Engineering & Risk
Management (MCSERM, 2010) was two-fold. On <strong>the</strong> one hand, it allowed <strong>the</strong> enhancing <strong>of</strong>
knowledge by learning several aspects <strong>of</strong> project management from o<strong>the</strong>r partners in <strong>the</strong> <strong>European</strong>
Union. On <strong>the</strong> o<strong>the</strong>r hand, it allowed <strong>the</strong> individual growing <strong>of</strong> intellectual capital and at <strong>the</strong> same time
<strong>the</strong> increase in <strong>the</strong> level <strong>of</strong> intellectual capital <strong>of</strong> <strong>the</strong> Centre team.
6. Managing <strong>European</strong> projects in <strong>the</strong> post-accession phase
The lessons learned from <strong>the</strong> <strong>European</strong> projects in Romania’s pre-accession phase proved to be
valuable assets for <strong>the</strong> management <strong>of</strong> projects in <strong>the</strong> post-accession phase. The individual
accumulation <strong>of</strong> knowledge, but also <strong>the</strong> team cohesion and intellectual capital, as <strong>the</strong> sum <strong>of</strong>
individual knowledge, increased <strong>the</strong> potential <strong>of</strong> successful managing <strong>of</strong> international projects. The
experience earned in managing projects since <strong>the</strong> pre-accession phased has proved very valuable in
winning <strong>the</strong> participation in projects within <strong>the</strong> FP7 programme.
6.1 EFAST project
The first <strong>European</strong> project currently in execution is EFAST (Design Study <strong>of</strong> a <strong>European</strong> Facility for
Advanced Seismic Testing), a <strong>European</strong> collaborative project that deals with <strong>the</strong> study <strong>of</strong> all aspects
regarding <strong>the</strong> design <strong>of</strong> a major testing facility in Europe that would complement and collaborate with
<strong>the</strong> existing ones. Earthquake risk is a major civil protection issue which is related to mitigation
measures for protecting citizens, infrastructures, property and <strong>the</strong> human cultural heritage. Seismic
testing plays a key role for <strong>the</strong> better understanding <strong>of</strong> physical phenomena, <strong>the</strong> validation and
improvement <strong>of</strong> analysis and design methods and for <strong>the</strong> qualification <strong>of</strong> sensitive equipment.
Therefore, <strong>the</strong> availability <strong>of</strong> high level experimental facilities is essential to meet <strong>the</strong> objectives <strong>of</strong>
earthquake mitigation (EFAST, 2010).
6.2 SERIES project
The second <strong>European</strong> project recently gained is SERIES (Seismic Engineering Research
Infrastructure for <strong>European</strong> Synergies). It aims at addressing <strong>the</strong> current situation that <strong>European</strong>
seismic engineering research suffers from extreme fragmentation <strong>of</strong> research infrastructures (RI)
between countries and limited access to <strong>the</strong>m by <strong>the</strong> S/T community <strong>of</strong> earthquake engineering,
especially that <strong>of</strong> Europe’s most seismic regions. Therefore, <strong>the</strong> project is a consortium <strong>of</strong> <strong>the</strong> 23 key
actors in Europe’s seismic engineering research, including 3 industrial beneficiaries. The scope
covers all aspects <strong>of</strong> seismic engineering testing, from eight reaction wall pseudodynamic (PsD)
facilities and ten shake table labs, to EU’s unique tester <strong>of</strong> bearings or isolators, its two major
centrifuges and an instrumented site for wave propagation studies. Transnational access is <strong>of</strong>fered to
a portfolio <strong>of</strong> world class RIs: EU’s largest PsD facility, four diverse shake tables and <strong>the</strong> two
centrifuges. Networking sets up a public distributed database <strong>of</strong> past, present and future test results,
installs distributed testing capabilities at all PsD labs, fostering development <strong>of</strong> up-and-coming ones at
Europe’s most seismic regions, drafts and applies protocols for qualification <strong>of</strong> RIs and engages <strong>the</strong>
entire <strong>European</strong> community <strong>of</strong> earthquake engineering via <strong>the</strong> best possible instances: <strong>the</strong> <strong>European</strong>
Association <strong>of</strong> Earthquake Engineering, EU’s seismic code makers and <strong>the</strong>ir national groups, <strong>the</strong>
<strong>European</strong> construction industry, as well as all relevant S/T associations or networks. Joint research
engages all labs, exploring and prototyping novel actuators (combination <strong>of</strong> electro-dynamic and
hydraulic ones) for better control <strong>of</strong> fast tests or special applications, new sensing and instrumentation
systems, data assimilation in equipment-specimen models for better test control and optimisation <strong>of</strong>
testing campaigns, as well as experimental studies <strong>of</strong> soil-structure interaction at all types <strong>of</strong> testing
facilities (SERIES, 2010).
Recently in <strong>the</strong> spring <strong>of</strong> 2010, within <strong>the</strong> internal evaluation <strong>of</strong> <strong>the</strong> research centres <strong>of</strong> <strong>the</strong> Technical
University <strong>of</strong> Iaşi, TUIASI, several success factors were revealed for our centre, <strong>the</strong> Multidisciplinary
Centre <strong>of</strong> Structural Engineering & Risk Management, in terms <strong>of</strong> growing <strong>the</strong> number <strong>of</strong> ISI-indexed
scientific papers to 25 in 2010, <strong>the</strong> successful entering in <strong>the</strong> FP7 programme <strong>of</strong> <strong>the</strong> <strong>European</strong>
Commission by gaining <strong>the</strong> two FP7 projects, and also o<strong>the</strong>r two on <strong>the</strong> national level, a successful
59

Gabriela Atanasiu and Florin Leon
admittance <strong>of</strong> one Master student to a prestigious university in <strong>the</strong> Ne<strong>the</strong>rlands and <strong>the</strong> successful
registration <strong>of</strong> two PhD students in <strong>the</strong> Eurodoc programme at national level supported by <strong>European</strong>
Structural fond. More details on <strong>the</strong> intellectual capital growth at organisational and individual level
can be found at MCSERM’s web address (MCSERM, 2010).
7. Conclusions
Romania’s participation in <strong>the</strong> global competition has led to an increase interest for project
management, approached from a pr<strong>of</strong>essional perspective, in terms <strong>of</strong> informational awareness for
<strong>the</strong> future project applicants and beneficiaries, and for <strong>the</strong> effective participation to project
management as co-initiators. At <strong>the</strong> same time, some universities as well as NGOs have developed
an increasing number <strong>of</strong> Master studies <strong>of</strong> life-long education in <strong>the</strong> fields <strong>of</strong> project management.
The knowledge transfer projects especially <strong>of</strong>fer resources that can lead in an efficient way to a
fundamental change in <strong>the</strong> culture <strong>of</strong> <strong>the</strong> organizational environment in which <strong>the</strong>y are implemented.
Key benefits for our research team were:
A unique experience on short, medium, and long term by forming a new generation <strong>of</strong> young
researchers, capable to manage <strong>European</strong>-level projects;
The development <strong>of</strong> individual and team level <strong>of</strong> intellectual capital;
A recognition <strong>of</strong> our capacity <strong>of</strong> gaining and managing <strong>European</strong> projects;
A more attractive research centre for young researchers;
Possible extra-financing in <strong>the</strong> future at national level through co-financing <strong>of</strong> <strong>the</strong> programmes <strong>of</strong>
<strong>the</strong> Romanian National Authority for Scientific Research.
References
Andersen, E. S. and Vaagaasar, A. L. (2009). “Project Management Improvement Efforts - Creating Project
Management Value By Uniqueness or Mainstream Thinking?”, Project Management Journal, vol. 40, no. 1,
pp. 19-27, Project Management Institute, Wiley InterScience.
Atanasiu, G. M. (2001). “International management and quality assurance in higher education”, QMedia, vol. 3,
no. 1-2, pp. 102-105.
Atanasiu, G. M. (2006). “Knowledge Transfer through <strong>European</strong> Project Management”, Management &
Marketing, no. 2/2006, Bucharest.
Atanasiu, G. M., Brătianu, C. (2005). “Learning by doing and know-how transfer in <strong>the</strong> MATRA project”, in:
Yannis, Ph. Rusu, C., (eds.), Management <strong>of</strong> technological change, vol. 2, pp.149-153, Technical University
Crete, Greece.
Badger, W., Wiezel, A., Bopp, P. H. and Dunn Stretch (2010). “Leadership Transition and Growth”, International
Journal <strong>of</strong> Construction Education and Research, vol. 6, pp. 46-69.
Blackler, F. (1995). “Knowledge, knowledge work and organisations: An overview and interpretation”,
Organization Studies, vol. 16, pp. 1021-1046.
Brătianu, C. (2002). “The Paradigms <strong>of</strong> University Management”, Ed. Economică, Bucharest.
Brătianu, C. and Atanasiu, G. M. (2000). “Managing institutional change in <strong>the</strong> Romanian universities”, in: Rusu,
C., Gafiţeanu, M. (eds.), Procedures for quality assurance in Romanian higher education, vol. 2, pp. 153-
157, Ed. Economică, Bucharest.
Castells, M. (1996). “The rise <strong>of</strong> <strong>the</strong> network society”, Blackwell, Oxford, UK.
Davies, A., and Brady, T. (2000). “Organisational capabilities and learning in complex product systems: Towards
repeatable solutions”, Research Policy, vol. 29, pp. 931-953.
Doolen, T.L., Hacker, M.E. and Van Aken, E.M.(2003). “Impact <strong>of</strong> organizational context on work team
effectiveness: A study <strong>of</strong> production team”, IEEE Transactions on Engineering Management, vol. 50, pp.
285-296.
Dvir, D., Sadeh, A., and Malch-Pines, A. (2006). “Projects and project managers: The relationship between
project managers’ personality, project types, and project success”, Project Management Journal, vol. 37,
no. 5, pp. 36-48.
EFAST (2010). “Design Study <strong>of</strong> a <strong>European</strong> Facility for Advanced Seismic Testing”, [online]
http://efast.eknowrisk.eu.
Engelkamp, P. (2003). “The impact <strong>of</strong> a Dutch-Romanian technical assistance project within <strong>the</strong> framework <strong>of</strong>
Romania’s endeavour to join <strong>the</strong> <strong>European</strong> Union”, International Journal <strong>of</strong> <strong>the</strong> Black Sea Universities
Network, vol. May, pp. 111- 117.
EUA, <strong>European</strong> University Association (2005). “Developing an internal Quality Culture in <strong>European</strong> Universities”,
EUA Publications.
Gray, C. F. and Larson, E.W. (2003). “Project management. The managerial process”, McGraw Hill Higher
Education, New York.
H<strong>of</strong>stede, G. (1997). “Cultures and organizations: S<strong>of</strong>tware <strong>of</strong> <strong>the</strong> mind”, McGraw-Hill, New York.
60

Gabriela Atanasiu and Florin Leon
H<strong>of</strong>stede, G. (1999). “The universal and <strong>the</strong> specific in 21st-century global management”, Organizational
Dynamics, vol. 28, no. 1, pp. 34-44.
Lam, A. (2000). “Tacit knowledge, organizational learning and societal institutions: An integrated framework”,
Organization Studies, vol. 21, pp. 487-513.
MCSERM (2010). “Multidisciplinary Centre <strong>of</strong> Structural Engineering & Risk Management”, [online]
http://mcserm.tuiasi.ro/en/index.htm.
Mullaly, M. (2006). “Longitudinal analysis <strong>of</strong> project management maturity”, Project Management Journal, vol. 36,
no. 3, pp. 62-73.
Nahm, A.Y., Vonderembse, M.A. and Koufteros, X.A. (2004). “The impact <strong>of</strong> organizational culture on time-based
manufacturing and performance”, Decision Sciences, vol. 35, pp. 579-607.
Popescu, S., Brătianu, C., eds. (2004). “The Guide <strong>of</strong> Quality in Higher Education”, University <strong>of</strong> Bucharest
Publishing House.
SERIES (2010). “Seismic Engineering Research Infrastructure for <strong>European</strong> Synergies”, [online]
http://www.series.upatras.gr/overview.
Shore, B. (2008). “Systematic Biases and Culture in Project Failures”, Project Management Journal, vol. 39, no.
4, pp. 5-16, Project Management Institute, Wiley InterScience.
Shore, B. and Cross, B.(2005). “Exploring <strong>the</strong> role <strong>of</strong> national culture in <strong>the</strong> management <strong>of</strong> large-scale
international science projects”, International Journal <strong>of</strong> Project Management, vol. 23, pp. 55-64.
Tsoukas, H. (1996). “The firm as a distributed knowledge system: A constructionist approach”, Strategic
Management Journal, vol. 17 (Winter Special Issue), pp. 11-25.
Turner, J. and Müller, R. (2006). “Choosing appropriate project managers: Matching <strong>the</strong>ir leadership style to <strong>the</strong>
type <strong>of</strong> project”, Project Management Institute, Newtown Square, PA.
Wang, X., and Liu, L. (2007). “Cultural barriers to <strong>the</strong> use <strong>of</strong> Western project management in Chinese
enterprises: Some empirical evidence from Yunnan Province”, Project Management Journal, vol. 38, no. 3,
pp. 61-73.
Yazici, H. J. (2009). “The Role <strong>of</strong> Project Management Maturity and Organizational Culture in Perceived
Performance”, Project Management Journal, vol. 40, no. 3, pp. 14-33.
61

Developing and Implementing Strategies to Enhance
Intellectual Capital in <strong>the</strong> Online Learning Environment
Bob Barrett
American Public University, Charles Town, USA
docjob00@msn.com
Abstract: The online learning environment has become a highly competitive industry in which many stakeholders
have become more interested and involved in its overall operation. One particular area that most stakeholders
will agree upon is <strong>the</strong> value <strong>of</strong> human capital in this industry. Stewart (1997) classified Intellectual Capital into
three key areas: human capital, structural capital, and customer capital. This paper will focus on <strong>the</strong> human
capital element in <strong>the</strong> online learning environment. Human capital is explained as “<strong>the</strong> capabilities <strong>of</strong> <strong>the</strong>
company’s employees necessary to provide solutions to customers, to innovate and to renew. As a result <strong>of</strong>
changing technology and economic times, many organizations are realizing <strong>the</strong> need to update, innovate, and
rejuvenate. InCaS (2010) noted that “As a result <strong>of</strong> constant changes caused by globalisation, emerging
technologies and shorter product life-cycles, knowledge and innovation have already become <strong>the</strong> main
competitive advantages <strong>of</strong> many companies. Especially <strong>European</strong> small and medium-sized enterprises (SME)
are highly dependent on <strong>the</strong> ability to identify changes in <strong>the</strong>ir global economic environment quickly and respond
to <strong>the</strong>se changes with suitable solutions.” (p. 4) Just liked <strong>the</strong>ir <strong>European</strong> counterparts, American enterprises and
organizations are scanning <strong>the</strong>ir environments and focusing on responding to potential changes in order to
capture and maintain <strong>the</strong>ir market share and prepare for <strong>the</strong> future. In additional in individual capabilities, human
capital includes <strong>the</strong> dynamics <strong>of</strong> an intelligent (learning) organization in a changing competitive environment, its
creativity, and innovativeness” (Stewart, 1997, p. 13). Thus, <strong>the</strong>re has been an increase in <strong>the</strong> focus as to how
online learning providers are investing more money and time in preparing <strong>the</strong>ir online instructional staff.
Sokolowska (2006) commented that “if we look at learning organizations we can see two types <strong>of</strong> trends. She
stated that “such organizations are understood in dynamic organizational categories that are oriented at <strong>the</strong>ir
development, searches for new chances on <strong>the</strong> market and continually increases <strong>the</strong>ir effectiveness, efficiency
and flexibility. The second group <strong>of</strong> learning organizations consists <strong>of</strong> such entities that choose growth through
development <strong>of</strong> <strong>the</strong>ir employees.” (p. 158) This paper examines <strong>the</strong> online learning environment, requirements for
<strong>the</strong> online instructional staff, and strategies to help better prepare and develop <strong>the</strong>ir intellectual capital in this
particular learning environment. Fur<strong>the</strong>r, this paper will examine how <strong>the</strong>se strategies are reinforced by <strong>the</strong>
commitment <strong>of</strong> <strong>the</strong> educational institution in terms <strong>of</strong> preparing <strong>the</strong>ir online instructors, as well as mentoring <strong>the</strong>m
along <strong>the</strong> way.
Keywords: online learning, human capital, intellectual capital, teacher training, eLearning
1. Organizational and environmental changes and intellectual capital
With <strong>the</strong> many technological changes occurring both in education, work, and homes, many changes
have been observed, measured, analyzed, and discussed in terms <strong>of</strong> intellectual capital. As a result <strong>of</strong>
changing technology and economic times, many organizations are realizing <strong>the</strong> need to update,
innovate, and rejuvenate. InCaS (2010) noted that “As a result <strong>of</strong> constant changes caused by
globalisation, emerging technologies and shorter product life-cycles, knowledge and innovation have
already become <strong>the</strong> main competitive advantages <strong>of</strong> many companies. Especially <strong>European</strong> small
and medium-sized enterprises (SME) are highly dependent on <strong>the</strong> ability to identify changes in <strong>the</strong>ir
global economic environment quickly and respond to <strong>the</strong>se changes with suitable solutions.” (p. 4)
Just liked <strong>the</strong>ir <strong>European</strong> counterparts, American enterprises and organizations are scanning <strong>the</strong>ir
environments and focusing on responding to potential changes in order to capture and maintain <strong>the</strong>ir
market share and prepare for <strong>the</strong> future. Thus, <strong>the</strong> key question is whe<strong>the</strong>r we are better <strong>of</strong>f today
than before in terms <strong>of</strong> developing our intellectual capital? Has <strong>the</strong> onset <strong>of</strong> technological
advancements really helped or hindered our learning and knowledge building process? Fur<strong>the</strong>r, have
we, as a nation, taken advantage <strong>of</strong> such development to <strong>the</strong> betterment <strong>of</strong> our own lives, as well as
o<strong>the</strong>rs in our society? This paper will address various strategies used in <strong>the</strong> online learning
environment to develop and enhance <strong>the</strong> online learning environment in terms <strong>of</strong> learning experience
for learners, instructional staff, and support staff. Each <strong>of</strong> <strong>the</strong>se individuals help to comprise <strong>the</strong>
intellectual capital <strong>of</strong> <strong>the</strong> learning environment, as well as contribute to <strong>the</strong> ongoing existence and
preparation for future growth in this particular industry.
The online learning environment has become a highly competitive industry in which many
stakeholders have become more interested and involved in its overall operation. One particular area
that most stakeholders will agree upon is <strong>the</strong> value <strong>of</strong> human capital in this industry. Stewart (1997)
classified Intellectual Capital into three key areas: human capital, structural capital, and customer
62

Bob Barrett
capital. This paper will focus on <strong>the</strong> human capital element in <strong>the</strong> online learning environment. Human
capital is explained as “<strong>the</strong> capabilities <strong>of</strong> <strong>the</strong> company’s employees necessary to provide solutions to
customers, to innovate and to renew. In additional in individual capabilities, human capital includes
<strong>the</strong> dynamics <strong>of</strong> an intelligent (learning) organization in a changing competitive environment, its
creativity, and innovativeness” (Steward, 1997, p. 13). Thus, <strong>the</strong>re has been an increase in <strong>the</strong> focus
as to how online learning providers are investing more money and time in preparing <strong>the</strong>ir online
instructional staff.
One way that online learning providers help to develop human capital is by <strong>of</strong>fering quality online
training for new and current instructors. Barbara Smith (2000), chief learning <strong>of</strong>ficer for Burson-
Marsteller stated that “If we don’t have <strong>the</strong> best people creating <strong>the</strong> best product, we can’t compete.
What I’m after is creating <strong>the</strong> best people in <strong>the</strong> industry. ELearning is an option that provides us with
real competitive edge – it helps us maximize our intellectual capital” (para. 2). Thus, <strong>the</strong>re is a growing
need for more investment and strategic development in <strong>the</strong> area <strong>of</strong> online learning training to help
enhance <strong>the</strong> skills <strong>of</strong> online instructors.
This paper will provide an overview <strong>of</strong> how several online universities invest in <strong>the</strong>ir online
instructional training, as well as creating ongoing educational opportunities, in order to develop one
segment <strong>of</strong> <strong>the</strong>ir intellectual capital – <strong>the</strong>ir instructors. While online instructors have been empowered
with various technological tools, as well as given <strong>the</strong> task <strong>of</strong> facilitating learning, <strong>the</strong>y also serve as
<strong>the</strong> frontline for customer service questions and guidance. Thus, many online schools have realized
<strong>the</strong> need to develop and implement better strategies for <strong>the</strong>ir online intellectual capital, and some
have spent extra time focused on <strong>the</strong> frontline provides to <strong>the</strong>ir instructors. In <strong>the</strong> next section, <strong>the</strong>re
will be a brief overview <strong>of</strong> what is happening with online learning in <strong>the</strong> United States.
1.1 Current growth in <strong>the</strong> online learning environment
According to Sokolowska (2006), “ if we look at learning organizations we can see two types <strong>of</strong> trends
. . . such organizations are understood in dynamic organizational categories that are oriented at <strong>the</strong>ir
development, searches for new chances on <strong>the</strong> market and continually increases <strong>the</strong>ir effectiveness,
efficiency and flexibility. The second group <strong>of</strong> learning organizations consists <strong>of</strong> such entities that
choose growth through development <strong>of</strong> <strong>the</strong>ir employees.” (p. 158) Along with looked at <strong>the</strong>se learning
organizations, we need to also focus on <strong>the</strong> need to develop core competencies, as well as being
innovative. InCaS (2010) stated that “Market-oriented innovation, transparent structures as well as a
strategic development <strong>of</strong> core competencies are <strong>the</strong>refore essential preconditions for sustainable
growth and future competitiveness. Intellectual Capital (IC) forms <strong>the</strong> basis for high quality products
and services as well as for organizational innovations. So far, conventional management instruments
and balance sheets do not cover <strong>the</strong> systematic management <strong>of</strong> IC.” (p. 4) In this context, we can
examine how online learning is growing and changing, as well as <strong>the</strong> need to examine more closely
why innovation will be a major factor in <strong>the</strong> growth <strong>of</strong> this industry and its intellectual capital. Finally,
Sokolowska (2006) commented that if we look at learning organizations we can see two types <strong>of</strong>
trends. She stated that “such organizations are understood in dynamic organizational categories that
are oriented at <strong>the</strong>ir development, searches for new chances on <strong>the</strong> market and continually increases
<strong>the</strong>ir effectiveness, efficiency and flexibility. The second group <strong>of</strong> learning organizations consists <strong>of</strong>
such entities that choose growth through development <strong>of</strong> <strong>the</strong>ir employees.” (p. 158)
Greer (2010) noted that “Online college education is expanding—rapidly. More than 4.6 million
college students were taking at least one online course at <strong>the</strong> start <strong>of</strong> <strong>the</strong> 2008-2009 school year.
That's more than 1 in 4 college students, and it's a 17 percent increase from 2007.” (para. 1) In 2006,
38 states in <strong>the</strong> United States have established state-led online learning programs, policies regulating
online learning, or both. Also, 25 states have state-led online learning programs, and 18 states are
home to a total <strong>of</strong> 147 virtual charter schools serving over 65,000 students (http://www.nacol.org). In
2001, 56% <strong>of</strong> traditional learning institutions <strong>of</strong>fered distance learning programs. An additional 12% <strong>of</strong>
schools stated <strong>the</strong>y planned on adding distance learning programs to <strong>the</strong>ir curriculum within <strong>the</strong> next
three years (National Center for Education Statistics, 2003). Thus, more secondary- and postsecondary
level teachers will need to seek additional education in order to obtain and master quality
online teaching skills and strategies. As a result, more universities are <strong>of</strong>fering online education
courses and teacher training in order to help recruit and hire more online instructors. Thus, <strong>the</strong>re is a
growing need to increase <strong>the</strong> number <strong>of</strong> online instructors to teach at educational institutions. In <strong>the</strong>
next section <strong>of</strong> this paper, <strong>the</strong> focus will be at examining how technology has been growing and how it
has affected instructors and <strong>the</strong>ir need to update <strong>the</strong>ir skills.
63

2. Technology, faculty, and staff
Bob Barrett
On <strong>the</strong> o<strong>the</strong>r hand, some instructors have not embraced online learning, and perhaps it may be due to
<strong>the</strong>ir lack <strong>of</strong> technology or understanding <strong>of</strong> online education. CDW Government, LLC prepared <strong>the</strong>
21 st Century Campus Report which showed how college faculty have been lagging far behind IT staff
in <strong>the</strong>ir rating <strong>of</strong> online technology. According to <strong>the</strong> report, surveyed 1,000 students, faculty
members, and IT pr<strong>of</strong>essionals, <strong>the</strong>y found <strong>the</strong> following.
68 percent <strong>of</strong> IT staff view virtual learning as an important element in higher education, while only
35 percent <strong>of</strong> <strong>the</strong> faculty feel <strong>the</strong> same.
72 percent <strong>of</strong> IT pros say online collaboration s<strong>of</strong>tware is essential; 31 percent <strong>of</strong> faculty agreed.
61 percent <strong>of</strong> <strong>the</strong> schools surveyed <strong>of</strong>fered online virtual learning.
Students list lack <strong>of</strong> pr<strong>of</strong>essor technology knowledge as <strong>the</strong>ir number one concern (named by 24
percent). Faculty and IT staff list this as <strong>the</strong>ir number two concern, behind budget cuts.
Students increasingly value and expect 21st Century technology in higher education, with 93
percent <strong>of</strong> high-schoolers saying technology is important in <strong>the</strong>ir college choice (63 percent <strong>of</strong>
current college students agreed). (Geteducated.com, 2010, para. 3-7)
As more technology has become available in many parts <strong>of</strong> <strong>the</strong> globe, a new type <strong>of</strong> student
population has emerged. The traditional student image <strong>of</strong> higher learning has been somewhat limited
in many countries, but given <strong>the</strong> impact <strong>of</strong> <strong>the</strong> Internet, this traditional “student body” has changed to
online communities. In <strong>the</strong> field <strong>of</strong> business and management, educators have recognized <strong>the</strong>
demographical changes <strong>of</strong> <strong>the</strong> student population. In a virtual environment, <strong>the</strong> student is not <strong>the</strong>
same traditional student seen in classrooms in previous years, but ra<strong>the</strong>r one that reflects a vast array
<strong>of</strong> cultural differences and needs that require educators to help build “new learning paths” towards <strong>the</strong>
creation <strong>of</strong> virtual learning communities.
The number <strong>of</strong> students taking at least one online course continues to expand at a rate far in excess
<strong>of</strong> <strong>the</strong> growth <strong>of</strong> overall higher education enrollments. The most recent estimate, for fall 2007, places
this number at 3.94 million online students, an increase <strong>of</strong> 12.9 percent over fall 2006. The number <strong>of</strong>
online students has more than doubled in <strong>the</strong> five years since <strong>the</strong> first Sloan survey on online
learning. The growth from 1.6 million students taking at least one online course in fall 2002 to <strong>the</strong> 3.94
million for fall 2007 represents a compound annual growth rate <strong>of</strong> 19.7 percent. The overall higher
education student body has grown at an annual rate <strong>of</strong> around 1.6 percent during this same period
(from 16.6 million in Fall 2002 to 18.0 million for Fall 2007 - Projections <strong>of</strong> Education Statistics to
2017, National Center for Education Statistics). As <strong>the</strong> following table illustrates, over one-fifth <strong>of</strong> all
higher education students are now taking at least one online course.
Who are <strong>the</strong>se 3.9 million students? The overwhelmingly majority (over 80 percent) are studying at
<strong>the</strong> undergraduate level with only 14 percent taking graduate level courses and <strong>the</strong> remainder in
some o<strong>the</strong>r for-credit course. Using survey results and figures from <strong>the</strong> most recent federal data
(Digest <strong>of</strong> Education Statistics: 2007, National Center for Education Statistics) to compare enrollment
patterns shows only slight variations in <strong>the</strong> proportions <strong>of</strong> students by education type. The proportion
<strong>of</strong> undergraduates in online education (83.9 percent) is slightly below that <strong>of</strong> <strong>the</strong> total population <strong>of</strong>
higher education students (85.6 percent). (Allen & Seaman, 2008)
While technology has provided a powerful infrastructure, <strong>the</strong> emerging technologies have allowed
educational institutions, educators, and students to provide education on a much higher playing field –
in a virtual learning environment. Consequently, <strong>the</strong> business world has also worked with technology
in this venture to help assist educational institutions in becoming more modern and adaptive for
change. As a result, <strong>the</strong>se changes only signify to <strong>the</strong> educational and learning communities that
technology recognizes a need for change – but do we, as educators, recognize <strong>the</strong> need for change
completely? Finally, many educational institutions, as well as <strong>the</strong> business world, are focusing on <strong>the</strong>
learning process and its impact on <strong>the</strong>ir organizational structure and employees.
As more people consider online learning to be a new academic endeavor, one must also consider <strong>the</strong>
next step for college graduates – <strong>the</strong> world <strong>of</strong> work. In this regard, <strong>the</strong> corporate environment may
differ from <strong>the</strong> academic setting; however, <strong>the</strong> need to learn and grow is equally important in <strong>the</strong> world
<strong>of</strong> business and academia. While online learning has been focused more on <strong>the</strong> academic setting,
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many companies are learning that online learning has many benefits in <strong>the</strong> corporate/business
environments. Thus, many companies and organizations are focusing on <strong>the</strong> “learning” element <strong>of</strong>
<strong>the</strong>ir employees’ daily work lives, as well as helping to build <strong>the</strong>ir knowledge management with a
concentration on helping <strong>the</strong> organization learn from previous and current experiences. Thompson
(1995) stated that “organizational learning involves <strong>the</strong> acquisition <strong>of</strong> new information and <strong>the</strong> ability to
analyze that information creatively, learn from it, and apply that learning in useful ways.” (p. 95). As
organizations realize that <strong>the</strong>re is a need to “capture” and “utilize” this type <strong>of</strong> learning, <strong>the</strong>y also
realize <strong>the</strong> need for <strong>the</strong> organization, as a whole, to concentrate on building up this learning element
to include everyone in <strong>the</strong>ir respective organization, as well as setting up informal and formal learning
center or circles. While organizations and communities view <strong>the</strong> impact <strong>of</strong> online learning in <strong>the</strong> U.S.,
we also have to look at how type <strong>of</strong> learning is impacting <strong>the</strong> world and our global capital.
3. Virtual learning and its global impact
In <strong>the</strong> business world, when “a brand expands it reach around <strong>the</strong> globe, it achieves favored
perceptions that are greater than <strong>the</strong> sum <strong>of</strong> its national parts” (Holt, Quelch, and Taylor, 2004, p.
191). This branding, known as global branding, relies on <strong>the</strong> input <strong>of</strong> <strong>the</strong> various stakeholders and
how <strong>the</strong>ir cultural differences can enhance <strong>the</strong> quality and acceptance <strong>of</strong> such a brand. In <strong>the</strong> field <strong>of</strong>
education, one needs to understand how <strong>the</strong>se new virtual learning communities have created a new
type <strong>of</strong> global branding <strong>of</strong> education in terms <strong>of</strong> linking various stakeholders throughout <strong>the</strong> world into
a stronger and more diversified learning environment. Contextually, one can see a new, global
branding <strong>of</strong> course management systems, which affects and supplements <strong>the</strong> needs <strong>of</strong> growing,
virtual learning communities. Thus, this leads us to <strong>the</strong> next part <strong>of</strong> this paper’s focus, <strong>the</strong> <strong>European</strong>
and American approaches towards Intellectual Capital.
4. Intellectual capital – <strong>European</strong> and U.S. approaches
According to Answers.com, “Intellectual capital collectively refers to all resources that determine <strong>the</strong>
value and <strong>the</strong> competitiveness <strong>of</strong> an enterprise. As such, it includes as subsets <strong>the</strong> attributes that
concur to building all financial statements as well as <strong>the</strong> balance sheet.” (para. 1) While intellectual
capital can be examined and discussed in terms <strong>of</strong> employees, organizational capabilities or
customers, <strong>the</strong> main focus <strong>of</strong> this paper will focus on <strong>the</strong> area <strong>of</strong> human capital. Stewart (1997)
classified Intellectual Capital into three identified areas in <strong>the</strong> following:
Human Capital: The capabilities <strong>of</strong> <strong>the</strong> company’s employees necessary to
provide solutions to customers, to innovate and to renew. In addition to individual
capabilities, human capital includes <strong>the</strong> dynamics <strong>of</strong> an intelligent (learning)
organization in a changing competitive environment, its creativity, and
innovativeness.
Structural Capital: The infrastructure <strong>of</strong> human capital, including <strong>the</strong>
organizational capabilities to meet market requirements. Infrastructure includes
<strong>the</strong> quality and reach <strong>of</strong> information technology systems, company images,
databases, organizational concept and documentation.
Customer Capital: The relationships with people with whom a company does
business. Although this usually means clients and customers, it can also mean
suppliers. It has also been referred to as relationship capital. (cited in
http://www.cpavision.org/vision/wpaper05b.cfm)
In order to manage Human Capital, management needs to measure various factors to determine
whe<strong>the</strong>r employees are benefitting <strong>the</strong> organization and to what degree. How can <strong>the</strong>y be measure?
Here are some items that management can evaluate in this area.
Training programs
Credentials
Experience
Competence
Recruitment
Mentoring
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Learning programs
Individual potential
Bob Barrett
Personality (cited in http://www.cpavision.org/vision/wpaper05b.cfm)
While many companies may promote <strong>the</strong> importance <strong>of</strong> training and education, many entities are
rethinking and re-evaluating <strong>the</strong> use <strong>of</strong> <strong>the</strong>ir funds to help support <strong>the</strong>ir employees
Consequently, <strong>European</strong> companies have taken a more concentrated effort towards examining <strong>the</strong>ir
Intellectual Capital in terms <strong>of</strong> a series <strong>of</strong> questions, which constitutes what is called <strong>the</strong> Intellectual
Capital Summary (ICS). According to InCaS (2010), “An Intellectual Capital Statement (hereafter
referred to as ICS) is a strategic management instrument for assessing and developing <strong>the</strong> Intellectual
Capital (IC) <strong>of</strong> an organisation. It shows how Intellectual Capital is linked to corporate goals, business
processes and <strong>the</strong> business success <strong>of</strong> an organization using indicators to measure <strong>the</strong>se elements”
(p. 7). Which leads us to <strong>the</strong> next step – how do we create an Intellectual Capital Statement for a
company – especially for an online learning institution? InCaS (2010) <strong>of</strong>fers <strong>the</strong> following guidance:
Helps you determine strengths and weaknesses <strong>of</strong> strategic IC factors (diagnosis)
Prioritises improvement opportunities with <strong>the</strong> highest impact (decision support)
Supports <strong>the</strong> implementation <strong>of</strong> actions for organizational development (optimisation and
innovation)
Enhances transparency and <strong>the</strong> involvement <strong>of</strong> employees (internal communication)
Diminishes strategic risks and controls <strong>the</strong> success <strong>of</strong> actions (monitoring)
Facilitates <strong>the</strong> communication <strong>of</strong> corporate value towards stakeholders (reporting) (p. 8).
If we look at <strong>the</strong> above questions, this will help us to understand why constant review and update <strong>of</strong>
employees’ skills and abilities are important not only to <strong>the</strong> organization and its future, but also to <strong>the</strong>
employee. The following section will examine <strong>the</strong> characteristics <strong>of</strong> an online instructor, as well as
examine <strong>the</strong> technological and skills requirements needed by instructors.
5. Online instructor characteristics and skills sets
Many candidates have a variety <strong>of</strong> reasons for applying or online teaching jobs. For some individuals,
online teaching is a wave <strong>of</strong> <strong>the</strong> future, and yet for o<strong>the</strong>rs, it may be a more convenient option for a
teaching career. Here are some characteristics <strong>of</strong> online instructors.
Many online teaching positions are being filled by part-time instructors.
Many colleges and universities have found that this helps to reduce some administration <strong>of</strong>
benefits and pay – so part-time faculty have been a “quick fix” for <strong>the</strong>ir current need.
Part-time adjuncts are used more than full-time faculty.
They usually work a full-time job, along with teaching part-time for one or more online programs.
There has been an increase <strong>of</strong> instructors teaching online that have online degrees <strong>the</strong>mselves.
Overall, many universities and colleges with online course <strong>of</strong>ferings are filling <strong>the</strong>ir online teaching
positions with adjuncts in order to meet <strong>the</strong> growing demand for online courses. Ra<strong>the</strong>r than recruiting
full-time, permanent instructors, <strong>the</strong>se educational institutions are seeking a contingent workforce to
fill <strong>the</strong> immediate needs.
While many people may not enjoy driving to a physical classroom or lecturing for periods <strong>of</strong> 2-3 hours
straight, some see <strong>the</strong> opportunity to teach in <strong>the</strong>ir own home or <strong>of</strong>fice on an arranged scheduled.
However, before one can consider such an opportunity, <strong>the</strong>re needs to be an assessment <strong>of</strong> one’s
skills sets in order to determine if a candidate possesses <strong>the</strong> necessary skills to become an online
instructor. Some <strong>of</strong> <strong>the</strong>se skills range from technological, educational, teaching and/or relevant work
experience. Listed below are some questions to quickly overview some <strong>of</strong> <strong>the</strong> skills necessary in each
<strong>of</strong> <strong>the</strong>se areas.
Technological Skills
Is <strong>the</strong> candidate computer literate?
Can <strong>the</strong> candidate use email, word processing, and spreadsheet s<strong>of</strong>tware?
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Educational Skills
Does <strong>the</strong> instructor have a master’s degree with at least 18 graduate credits in <strong>the</strong> given subject
area?
Teaching Skills
Has <strong>the</strong> candidate taught before (private or public sectors)?
Work Experience
Does <strong>the</strong> candidate have work/industry experience?
As discussed in previous sections, in order to sustain growth and future competitiveness many
organizations need to strive for high quality products and services. In terms <strong>of</strong> online learning,
educational institutions need to <strong>of</strong>fer high-quality teacher training order to ensure that <strong>the</strong>y are hiring,
training, and retaining <strong>the</strong> best instructional staff. As a result, it is this emphasis on <strong>the</strong> development
<strong>of</strong> <strong>the</strong> human capital side <strong>of</strong> <strong>the</strong>ir intellectual capital that will be noticed by <strong>the</strong>ir students, accrediting
bodies, and community in general.
As a result <strong>of</strong> <strong>the</strong> various teaching learning environment, most educational institutions have realized
<strong>the</strong> need to invest more time and money in instructor training to help enhance and develop <strong>the</strong>ir
intellectual capital. Thus, this training approach may vary in terms <strong>of</strong> duration <strong>of</strong> <strong>the</strong> training, as well
as <strong>the</strong> topics covered. In <strong>the</strong> following section, <strong>the</strong> author has examined how one educational
institution, <strong>of</strong>fering both face-to-face and online courses, approaches <strong>the</strong>ir training program for current
and potential instructors.
6. Training program and strategies for online instructor
The following section outlines a typical training program for online instructors.
Module 1 – Teaching and Learning
In this module, students learn about <strong>the</strong> various communications tools used in <strong>the</strong> online learning
environment. Potential instructors examine and discuss how adults learn. Also, <strong>the</strong>y explore how
teach and learning are connected.
Module 2 – Teaching Strategies
During this module, students learn <strong>the</strong> important <strong>of</strong> time management and how to effectively plan <strong>the</strong>ir
teaching schedules. A key focus is on team facilitation and conflict management strategies. While we
hope that all learning experiences are positive, instructors need to know how to handle conflicts that
may occur.
Module 3 – Helping Students to Think Critically
In this module, students will look at Bloom’s Taxonomy and how it is used in course design and
curricula. There is a key discussion on <strong>the</strong> connections between teaching and learning <strong>the</strong>ories.
Finally, potential instructions will discuss how critical thinking is used in <strong>the</strong> classroom.
Module 4 – Providing Feedback
During this module, students will look at sample student work and critique it with <strong>the</strong> use <strong>of</strong> a standard
rubric. They will focus on various criteria, as well as applying comments on APA style and format.
Module 5 – Ethical Issues
Why is confidentiality important in <strong>the</strong> learning environment? Students will look at <strong>the</strong> problems
associated with plagiarism and learn how to use a plagiarism database. Finally, <strong>the</strong> class will explore
critical issues <strong>of</strong> disability, harassment, and <strong>the</strong> Family Educational Rights and Privacy Act (FERPA).
Module 6 – University Teaching – Policies and Procedures
During this final module, students will learn more about <strong>the</strong>ir role and function as a facilitator in online
learning. A key discussion will be held on <strong>the</strong> university’s mission and how it reflects <strong>the</strong> university’s
culture. Finally, <strong>the</strong> instructor will lead a discussion on how to follow correct procedures when certain
policy issues arise.
Upon completion <strong>of</strong> <strong>the</strong>se modules, <strong>the</strong> course facilitator prepares an evaluation form for each
enrolled student. Should <strong>the</strong> facilitator determine that a candidate would benefit from additional
mentorship or coaching, he or she will indicate this on <strong>the</strong> evaluation form, as well as discussing <strong>the</strong>se
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facts with <strong>the</strong> program manager? As a form <strong>of</strong> reinforcement and development <strong>of</strong> <strong>the</strong> instructional
staff, some educational institutions uses coaches to help mentor <strong>the</strong>ir intellectual capital. Mentors may
be assigned for <strong>the</strong> first 1 or 2 courses that a new online instructor is assigned to (a good measure,
which is ano<strong>the</strong>r Industry Standard). In any event, seasoned instructors are recruited to fill <strong>the</strong>se
positions, in order to help work with various new instructors to help guide <strong>the</strong>m during <strong>the</strong> early part <strong>of</strong>
<strong>the</strong>ir online teaching careers.
7. Conclusion
As many companies may promote <strong>the</strong> importance <strong>of</strong> training and education, many entities are
rethinking and re-evaluating <strong>the</strong> use <strong>of</strong> <strong>the</strong>ir funds to help support <strong>the</strong>ir employees. Educational
institutions, like o<strong>the</strong>r businesses and organizations, are taking note <strong>of</strong> <strong>the</strong>ir various resources that
determine <strong>the</strong> value and competitiveness <strong>of</strong> <strong>the</strong>ir industry. While <strong>the</strong>y examine what works and does
not function, <strong>the</strong>y are starting to look more at <strong>the</strong>ir assessment instruments to determine if <strong>the</strong>re is
something else <strong>the</strong>y should be examining from within <strong>the</strong>ir educational facilities. However, it is equally
important to also understand what is required <strong>of</strong> an online instructor, as well as <strong>the</strong> skills requirements
for <strong>the</strong>se individuals in order to see what <strong>the</strong>y need and what can be <strong>of</strong>fered to develop <strong>the</strong>ir skills.
Finally, InCaS (2010) suggested <strong>the</strong> following questions to help capture <strong>the</strong> value creating model for
companies.
What product or service does <strong>the</strong> business <strong>of</strong>fer?
How can customers benefit from this product or service?
Which market segments / groups <strong>of</strong> customers are targeted?
To whom will <strong>the</strong> proposition be appealing?
From whom will resources be received?
How are <strong>the</strong> products or services created?
How are <strong>the</strong>y going to be delivered to <strong>the</strong> customers?
How will <strong>the</strong> customer pay for <strong>the</strong> product or service?
What is <strong>the</strong> price/margin for <strong>the</strong> product or service <strong>of</strong>fered to <strong>the</strong> customer? (p. 19)
As more and more educational institutions <strong>of</strong>fer additional programs in <strong>the</strong> online learning
environment, <strong>the</strong>y will need to consider all aspects <strong>of</strong> <strong>the</strong>ir Intellectual Capital, especially <strong>the</strong> human
capital element. Thus, <strong>the</strong>ir investment and valuing <strong>of</strong> <strong>the</strong>ir instructional staff will help <strong>the</strong>m to
compete and sustain <strong>the</strong>ir stance in <strong>the</strong> marketplace – as well as learn from o<strong>the</strong>rs in how to create
and implement better strategies in <strong>the</strong>se areas.
References
Allen, I.E., & Seaman, J. (2008). Staying <strong>the</strong> course: Online education in <strong>the</strong> United States, 2008. The Sloan
Consortium. Retrieved July 2, 2009, from http:www.sloanconsortium.org/publications/survey/pdf/staying_<strong>the</strong>_course.pdf.
AAHE. (2003). Towards a taxonomy <strong>of</strong> electronic portfolios.
http://webcenter1.aahe.org/electronicportfolios/taxonomy.html#taxonomy
Answers.com . Intellectual Capital. http://www.answers.com/topic/intellectual-capital#External_links. Retrieved
Nov. 5, 2009.
Barrett, H. C. (2001). Expert showcase: Dr. Helen Barrett on electronic portfolio development. Retrieved October
10, 2003, from http://ali.apple.com/ali_sites/ali/exhibits/1000156/
Barrett. H. (2005). Researching electronic portfolios: Learning, engagement, collaboration, through technology. In
L. Pelliccione and L. Dixon (2008). ePortfolios: Beyond assessment to empowerment in <strong>the</strong> learning
landscape. Ascilite Melbourne 2008 proceedings. Retrieved 2/1/10.Brinker, B. Intellectual Capital:
Tomorrow’s Asset and Today’s Challenge. http://www.cpavision.org/vision/wpaper05b.cfm. Retrieved
November 5, 2009. As cited in T.A. Stewart, (1997). Intellectual Capital. New York: Doubleday Currency.
pp. 62-63.
Costantino, P., De Lorenzo, M., & Kobrinski, E. (2006). Developed a pr<strong>of</strong>essional teaching portfolio. USA:
Pearson.
Chronicle <strong>of</strong> Higher Education (October 31, 2010). Online learning: By <strong>the</strong> numbers. Retrieved Oct. 31, 2010.
http://chronicle.com/article/OnlineLearning-Enrollment/125202/.
<strong>European</strong> ICS Guideline (n.d.). http://www.in<strong>the</strong>kzone.com/pdfs/Intellectual_Capital_Statement.pdf. Retrieved
Dec. 15, 2010.
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Bob Barrett
Geteducated.com (July 27, 2010). Virtual online learning rated key by college IT staff, not faculty. Retrieved Nov.
1, 2010. http://www.geteducated.com/online-education-facts-and-statistics/latest-onlineLearning-news-andresearch/367-virtual-onlineLearning-rated-key-by-college-it-staff-not-faculty.
Goldsby, Fazal (2001). In John DiMarco (2006). Web Portfolio Design and Applications. Idea Group Inc. pp. 607-
608. (retrieved 6/1/2008)
Greenberg (2004). In John DiMarco (2006). Web Portfolio Design and Applications. Idea Group Inc. pp. 607-608.
(retrieved 6/1/2008)
Greer, J. (2010). Study: Online education continues its meteoric growth. U.S. News. Retrieved Oct. 15, 2010.
http://www.usnews.com/articles/education/online-education/2010/01/26/study-online-education-continuesits-meteoric-growth.html.
Holt, D. B., Quelch, J. A., & Taylor, E. L. (2004). Managing <strong>the</strong> global brand: A typology <strong>of</strong> consumer perceptions.
The global market: Developing a strategy to managing across borders. San Francisco: Jossey-Bass.
LDP e-Portfolio Report http://bearlink.berkeley.edu/ePortfolio/page5.html (retrieved 6/1/2008).
Merryfield, M. (2003). Like a veil: Cross-cultural experiential learning online. Contemporary Issues in Technology
and Teacher Education, 3(2), 146-171.
Pelliccione, L. & Dixon, L. (2008). ePortfolios: Beyond assessment to empowerment in <strong>the</strong> learning landscape.
Ascilite Melbourne 2008 proceedings. Retrieved 2/1/10.
Ravet, S. & Layte, M. (2004). E-portfolio: Revolutionizing eLearning. In T. Acosta and Y. Liu (2006). Chapter II
ePortfolios: Beyond Assessment. Idea Group
Robinson, A., & Udall, M. (2004). A framework for formative assessment: Initiating quality learning conversations.
Learning and Teaching in High Education, 1, 112-115.
Shavelson, R.J., Klein, S., and Benjamin, R. (Oct. 16, 2009). Inside Higher Ed. The limitations <strong>of</strong> portfolios.
http://www.insidehighered.com/layout/set/print/views/2009/10/16/shavelson. Retrieved 12/15/2009.
Sobolewska, O. (2006). ELearning w szkoleniu kadr – raport z badań. Zarządzanie zasobami ludzkimi, 3-4 (48-
49) 100-108.
Thompson, J.W. (1995). The renaissance <strong>of</strong> learning in business. In S. Chawla and J. Renesch (1995). Learning
organizations: Developing cultures for tomorrow’s workplace. Portland, Oregon: Productivity Press.
Tosh, D. (2004). E-portfolios and Weblogs: One vision for e-portfolio development. In T. Acosta and Y. Liu
(2006). Chapter II ePortfolios: Beyond Assessment. Idea Group
U.S. Department <strong>of</strong> Education (2008). ELearning: Putting a world-class education at <strong>the</strong> fingertips <strong>of</strong> all children.
Retrieved on March 16, 2008 from
http://www.ed.gov//about/<strong>of</strong>fices/list/os/technology/reports/eLearning.html
69

Intellectual Capital Dynamics within <strong>the</strong> Learning
Organization
Ruxandra Bejinaru 1 and Stefan Iordache 2
1 Steven <strong>the</strong> Great University <strong>of</strong> Suceava, Romania
2 Academy <strong>of</strong> Economic Studies, Bucharest, Romania
ruxandrabejinaru@yahoo.com
stefan.iordache1@gmail.com
Abstract: Throughout this paperwork we present <strong>the</strong> research we undertook with respect to <strong>the</strong> dynamics <strong>of</strong>
intellectual capital within <strong>the</strong> learning organization. Lately, <strong>the</strong> valuation <strong>of</strong> intellectual capital has become an
industry <strong>of</strong> itself and companies struggle to continuously multiply and refresh resources. Nowadays, building a
real-time learning organization represents <strong>the</strong> mission <strong>of</strong> many entrepreneurs. Thus <strong>the</strong> paper objectives are to
determine <strong>the</strong> specific implications and variations <strong>of</strong> <strong>the</strong> intellectual capital as an important component to be
managed and to be shaped within <strong>the</strong> learning organization. The learning organization and <strong>the</strong> intellectual capital
are both largely debated concepts and <strong>the</strong> universal evolution provides more and more issues to discuss due to
<strong>the</strong>ir dynamic nature. Considering that in order for <strong>the</strong> learning organization to properly work it’s required a
dynamic mechanism, we have analyzed <strong>the</strong> intellectual capital circuit within this type <strong>of</strong> organization. In our view,
intellectual capital represents knowledge with various shapes, ei<strong>the</strong>r tangible or intangible, which may be
exploited to produce financial or o<strong>the</strong>r benefits for <strong>the</strong> organization. The intellectual capital is a dynamic
component that may continuously be modelled with respect to its quantity, quality, value, usefulness or intensity
<strong>of</strong> use and this is exactly what <strong>the</strong> statute <strong>of</strong> <strong>the</strong> learning organization implies: a continuous adaptation,
continuous learning, continuous exploitation <strong>of</strong> resources and opportunities. The structure <strong>of</strong> <strong>the</strong> paper will firstly
present <strong>the</strong> dynamic approach <strong>of</strong> <strong>the</strong> authors upon <strong>the</strong> intellectual capital and <strong>the</strong> learning organization,
emphasizing <strong>the</strong> key connections between <strong>the</strong>m. Fur<strong>the</strong>r, within ano<strong>the</strong>r section <strong>of</strong> <strong>the</strong> work we shall describe <strong>the</strong>
dynamic processes within <strong>the</strong> learning organization for <strong>the</strong> individuals’ level as well as for <strong>the</strong> organizational level.
Throughout <strong>the</strong> next part we design a novel perspective <strong>of</strong> <strong>the</strong> intellectual capital dynamics including its specific
processes within <strong>the</strong> learning organization. The concluding remarks attempt to convince <strong>the</strong> audience about <strong>the</strong>
righteousness <strong>of</strong> <strong>the</strong> approach, to prove <strong>the</strong> two concepts interconnectivity and to award each one’s merits
regarding evolution.
Keywords: intellectual capital, <strong>the</strong> learning organization, knowledge dynamics, knowledge management
1. Concepts introduction
Organizations are founded upon <strong>the</strong> humans’ knowledge. Only knowledge and knowledge-based
organizations can dominate <strong>the</strong> markets (Drucker, 1995). It has long been recognized that 'economic
prosperity rests upon knowledge and its useful application' (Teece 1981). Starting from <strong>the</strong> hypo<strong>the</strong>sis
that <strong>the</strong> engine <strong>of</strong> an organization’s management works on knowledge, <strong>the</strong>n each process <strong>of</strong> decision,
planning or implementation <strong>of</strong> a strategy within <strong>the</strong> organization rely on a continuous circuit <strong>of</strong>
ga<strong>the</strong>ring, analyzing and using data and on <strong>the</strong> knowledge dynamics. Thus, we may suspect that <strong>the</strong>
continuous learning process, <strong>the</strong> continuous supply and administration <strong>of</strong> knowledge should innovate
and improve people and <strong>the</strong> organization. Knowledge dynamics could help organizations to increase
<strong>the</strong>ir capacity <strong>of</strong> facing <strong>the</strong> continuous challenges <strong>of</strong> change. Within this paper we shall discuss about
how knowledge dynamics helps and develops <strong>the</strong> organization’s intellectual capital. Our paper is
based on <strong>the</strong> conceptualization <strong>of</strong> intellectual capital being based upon knowledge dynamics and its
representation within <strong>the</strong> learning organization.
Intellectual capital has been considered by many, defined by some, understood by a select few, and
formally valued by practically no one (Stewart, 1997; Sveiby, 1997). Therein lays one <strong>of</strong> <strong>the</strong> greatest
challenges facing business leaders and academic researchers today and tomorrow. As difficult as
may be to quantify <strong>the</strong> input <strong>of</strong> intellectual capital or <strong>the</strong> processing <strong>of</strong> knowledge, we will continuously
try to do so until we shall have <strong>the</strong> right equation that generates <strong>the</strong> impressive output. The
intellectual capital dynamics represents a defining feature <strong>of</strong> <strong>the</strong> learning organization as <strong>the</strong> first is an
important and complex resource to be managed within <strong>the</strong> latter one’s framework. Each component <strong>of</strong>
<strong>the</strong> intellectual capital will integrate and contribute in various ways.
The learning organization strongly relates its existence to intellectual capital and to all its forms. In this
context <strong>the</strong> learning organization is <strong>the</strong> perspective <strong>of</strong> a system that explores, shapes, develops and
uses <strong>the</strong> employees capabilities, capacities and skills in order to gain competitive advantage and
benefits. Among <strong>the</strong>se, human capital is a fundamental component due to its endless generation <strong>of</strong>
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innovation as well as its impressive adaptation to <strong>the</strong> organization’s needs. Human capital may be
rebuild on a greater speed <strong>the</strong>n structural and customer capital which need more time to reach a
convenient estate. However, in order for <strong>the</strong> human capital to instantaneously bounce from one stage
to ano<strong>the</strong>r, pushing forward its evolution <strong>the</strong>re has to be an appointed knowledge dynamics.
2. Introducing knowledge dynamics and connections to intellectual capital
When stressing <strong>the</strong> significance <strong>of</strong> <strong>the</strong> phrase “real time learning organization” we are talking about
<strong>the</strong> capability <strong>of</strong> organizations to act in real time, as meaning at <strong>the</strong> right moment, at <strong>the</strong> right spot and
in <strong>the</strong> right way. For organizations, to act in real time means to be at least as dynamic as <strong>the</strong>
environment, in order to capture <strong>the</strong> market need and to supply it accordingly. The learning
organization’s dynamics relates both to its structure and components. Within <strong>the</strong> learning organization
knowledge has various statutes: resource, tool, competitive advantage and output. Distinguishing
<strong>the</strong>se shall lead to pages <strong>of</strong> examples that remain unique and shall capture only an infinitely small
part <strong>of</strong> <strong>the</strong> whole. Understanding knowledge dynamics requires non-linear thinking. We mustn’t break
phenomena into events, not even processes into stages or activities into actions, <strong>the</strong>refore, don’t
break <strong>the</strong> whole into pieces. This judgement attains to Senge who explained what a mistake this is
and that this way a problem should seem easier to solve (Senge, 1990). It is not entirely our fault,
argues <strong>the</strong> author, as we were taught to do so, but this early education is definitely making it harder
for us to focus differently. Non-linear thinking means to view <strong>the</strong> whole system at once, to understand
<strong>the</strong> way it works and to capture its dynamics, because only this way we shall visualize <strong>the</strong> real world.
(Bratianu, 2009) The same happens with knowledge; it is all around and if we look at <strong>the</strong> pieces we
shall see data or information; if we look towards a certain point we shall see only that and miss <strong>the</strong>
rest; like a detective solving a big case it’s up to us to pick data, to link information and to built
valuable knowledge.
When related to intellectual capital, knowledge has to distinguish through its value for <strong>the</strong>
organization. Knowledge actively generates value, only throughout its use. The greater <strong>the</strong> knowledge
dynamics is <strong>the</strong> greater impact <strong>of</strong> intellectual capital value. Knowledge creates value by incorporating
it into <strong>the</strong> company’s products. Knowledge dynamics significantly influences <strong>the</strong> company’s capacity
<strong>of</strong> producing and delivering valuable economic products to clients. Incorporating knowledge into <strong>the</strong>
learning organization it will lead to valuable outputs which not only that enclose knowledge but also
were <strong>the</strong> result <strong>of</strong> well processed knowledge.
Research undertaken in domains like knowledge management, intellectual capital and learning
organization obviously emphasize <strong>the</strong> actual estate <strong>of</strong> disciplines in <strong>the</strong> context <strong>of</strong> organizational
change. Each <strong>of</strong> <strong>the</strong>se disciplines represents <strong>the</strong> need to shape <strong>the</strong> employee’s knowledge as a must
for <strong>the</strong> survival in <strong>the</strong> present business environment. Out <strong>of</strong> <strong>the</strong> whole picture, <strong>the</strong> researcher will
construct <strong>the</strong> cause-effect relationship between <strong>the</strong> learning organization and its knowledge
dynamics.
Although knowledge has been studied since Plato and Aristotle, <strong>the</strong> use <strong>of</strong> knowledge management
within corporations gained visibility for <strong>the</strong> first time when Michael Polanyi began his research in 1958.
O’Dell and Grayson (1998) state that “Polanyi’s work served as base for <strong>the</strong> well known <strong>the</strong>ories <strong>of</strong>
knowledge management and several volumes on organizational learning, belonging to Japanese
author - Ikujiro Nonaka”. Polanyi introduced knowledge, in 1958, as something that may have an
intrinsic value and put forward two types <strong>of</strong> knowledge –tacit and explicit. Nonaka (1991) has
confirmed again <strong>the</strong> concepts <strong>of</strong> Polanyi regarding <strong>the</strong> knowledge levels and introduced what we call
nowadays “<strong>the</strong> knowledge creating company”. Nonaka claimed that organizations were not
machinery, but living organisms. This pr<strong>of</strong>ound analogy has created a logical bound between
knowledge and organizations and initiated a change <strong>of</strong> paradigm towards attributing attention to
workers’ group thoughts within <strong>the</strong> organization as being knowledge generative.
Before Nonaka’s research in 1991, occidentals viewed organizations as “a machine that processed
information”. According to this point <strong>of</strong> view, <strong>the</strong> single useful knowledge were <strong>of</strong>ficial data, codified
procedures, universal principles. Since ever, and still nowadays <strong>the</strong> Japanese perspective regarding
knowledge dynamics is distinct from <strong>the</strong> one <strong>of</strong> occidentals. Wheatley (2001) explains that <strong>the</strong>
Occident is fur<strong>the</strong>r preoccupied about explicit knowledge while <strong>the</strong>ir Japanese colleagues discover
<strong>the</strong> most <strong>of</strong> results within <strong>the</strong> tacit dimension <strong>of</strong> knowledge. Part <strong>of</strong> this approach for <strong>the</strong> value <strong>of</strong>
organizational knowledge started while <strong>the</strong> information age. The appearance <strong>of</strong> information
consolidated systems- world wide web, networks, eMail, instant messaging and exchange <strong>of</strong>
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information lead to <strong>the</strong> vision that management <strong>of</strong> knowledge might be <strong>the</strong> fundamental issue
supporting an organization’s activity. And this doesn’t mean that information is knowledge. Deming
(1994) accurately argued that “in o<strong>the</strong>r words, regardless <strong>of</strong> how complete and fast it is, it doesn’t
represent knowledge. Only when information achieves to be understood and assimilated, <strong>the</strong>n it
transforms into knowledge”.
Explicit knowledge was defined by Anne Brooking (1991), a specialist in <strong>the</strong> leadership domain, as
“<strong>the</strong> knowledge that a person can provide to ano<strong>the</strong>r person in order to be verified. This could mean
that <strong>the</strong>y can be explained through speaking, but is generally preferred to be codified, in writing.” In
business administration, many have seen <strong>the</strong> knowledge management as resuming to <strong>the</strong> explicit
knowledge. This point <strong>of</strong> view is limited and we try to expand it by bringing into discussion <strong>the</strong>
knowledge dynamics.
Tacit knowledge implies <strong>the</strong> human understanding and individual knowledge. Tacit knowledge hides
within persons and is mainly acquired experientially. Huang, Lee and Wang (2001) state: “<strong>the</strong> use <strong>of</strong>
such experiences allows society to transform <strong>the</strong>se into structured knowledge more throughout
analysis and feedback”. Tacit knowledge is <strong>of</strong>ten very personal and difficult to catch, but <strong>the</strong>y may
have a greater value potential. There doesn’t seem to be a secure way to efficiently undertake <strong>the</strong>
transfer <strong>of</strong> tacit knowledge. But it is important to create an environment that supports knowledge
dynamics. The more opportunities, instruments and contexts we create for knowledge sharing, <strong>the</strong>
more possible is to succeed in transferring <strong>the</strong> tacit knowledge. Within <strong>the</strong> learning organization, tacit
knowledge exists inside <strong>the</strong> individuals and inside <strong>the</strong> group. There is no way to <strong>the</strong>oretically
differentiate <strong>the</strong>m, but <strong>the</strong> difference is seen through effects, through practice.
3. Channelling <strong>the</strong> intellectual capital
Intellectual capital comprises both human capital and structural capital for <strong>the</strong> purpose <strong>of</strong> using <strong>the</strong>ir
synergy in order to increase <strong>the</strong> organization’s growth. The company’s value depends and also
comprises <strong>the</strong> entire value <strong>of</strong> workers, toge<strong>the</strong>r with <strong>the</strong> company structure. Actually “<strong>the</strong> intellectual
capital develops <strong>the</strong> company values and optimizes <strong>the</strong> company business operations” -Davenport
(1996). Intellectual capital implies human resources, information technology, business strategy and
employees participation in order to rapidly transfer <strong>the</strong> imperative experiences across <strong>the</strong> company.
For individuals to share knowledge within <strong>the</strong> company, <strong>the</strong> management has to facilitate <strong>the</strong>
dynamics <strong>of</strong> knowledge among employees, enabling <strong>the</strong>m to become knowledge workers. The
company has to put at disposal <strong>of</strong> members <strong>the</strong> available information, to provide communication and
to train everyone to use <strong>the</strong> information and technology <strong>the</strong> company possesses. (Hunter, 2002)
Discussing <strong>the</strong> intellectual capital dynamics means to have an integrative view <strong>of</strong> <strong>the</strong> following
aspects. Competences include knowledge and practical abilities on which <strong>the</strong>y base. The attitude
refers to <strong>the</strong> employee volition <strong>of</strong> using his/her knowledge and abilities to serve <strong>the</strong> organization’s
interest and he/she may be influenced by motivation and behaviour. Intelligence refers to <strong>the</strong>
employee’s capacity to use knowledge and abilities in various contexts and in order to increase
knowledge and competences throughout learning. Relating capacity represents <strong>the</strong> individual ability to
establish relations with o<strong>the</strong>rs -clients, suppliers, business partners and o<strong>the</strong>r stakeholders. The
innovation and development rate comprises <strong>the</strong> intangible aspects that may improve <strong>the</strong> intellectual
capital, all <strong>the</strong> ‘elements’ that were built or conceived and that will have an impact upon <strong>the</strong> future
value <strong>of</strong> <strong>the</strong> organization’s intellectual capital, but that didn’t proved <strong>the</strong>ir impact yet.
Koeing, U. and Memhill, A. (2004) observed that, communication should be maximised within <strong>the</strong>
organization. The most important factor in order to have a successful organization is to install within
<strong>the</strong> organization an excellent communication system with <strong>the</strong> purpose to deliver its members <strong>the</strong>
necessary information that <strong>the</strong>y might use to accomplish <strong>the</strong> production requirements. Kaplan and
Norton (1996) had a different view and mentioned that individual non-performance and lack <strong>of</strong> ideas
can’t be always guilt <strong>of</strong> <strong>the</strong> organization’s members. The organization’s structure may influence <strong>the</strong>
unsatisfactory behaviour <strong>of</strong> employees and <strong>the</strong> low results.
Building <strong>the</strong> intellectual capital best shape is <strong>the</strong> learning organization’s business while <strong>of</strong>fering <strong>the</strong>
best <strong>of</strong> knowledge is <strong>the</strong> employees business. And we agree to this because <strong>the</strong>re are fundamental
differences between <strong>the</strong> organizational and individual knowledge. The nature <strong>of</strong> <strong>the</strong> organization is to
manage valuable knowledge only for itself and <strong>the</strong> individuals inside. The individuals’ nature is to
adapt <strong>the</strong>ir work –<strong>of</strong> creating knowledge –to <strong>the</strong> organization’s requirements and also resources.
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Figure 1: Influence <strong>of</strong> knowledge dynamics to <strong>the</strong> creation and development <strong>of</strong> intellectual capital
within a learning organization
The intellectual capital existing inside <strong>the</strong> organization generates that organization’s values,
knowledge and intelligences. The output <strong>of</strong> values, <strong>of</strong> knowledge and intelligences depends greatly on
<strong>the</strong> input. The organization’s intellectual capital is built with <strong>the</strong> aid <strong>of</strong> human elements and structural
elements. Within our figure you can observe twice <strong>the</strong> term “intelligence” as it once relates to <strong>the</strong>
individual and <strong>the</strong>n to <strong>the</strong> group/company. The bottom line <strong>of</strong> this figure is that <strong>the</strong> circuit has <strong>the</strong>
logics and obviously shows <strong>the</strong> dynamics <strong>of</strong> intellectual capital within <strong>the</strong> organization. The
represented process is continuous and each time its “loop” is different as all components are dynamic
and change <strong>the</strong>ir proportions. The dynamics <strong>of</strong> human elements is irreversible and unstoppable as
individuals learn ei<strong>the</strong>r through training (if provided) or through practicing and experiencing; <strong>the</strong>
dynamics <strong>of</strong> <strong>the</strong> structural elements is <strong>the</strong> consequence <strong>of</strong> humans’ entrepreneurship. The nature <strong>of</strong>
humans is to change everything around in order to suit <strong>the</strong>ir interests and this is why humans learned
in time to get things moving.
4. Intellectual capital within <strong>the</strong> learning organization
Rastogi (2002) views differently <strong>the</strong> links between <strong>the</strong> human capital and <strong>the</strong> structural capital. He
thinks that intellectual’s capital productivity depends on <strong>the</strong> strength and vitality <strong>of</strong> all its components,
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as well as on <strong>the</strong> links between <strong>the</strong>m. From our perspective, we would state that intellectual capital is
a strong integrator within <strong>the</strong> learning organization. The organization’s intellectual capital supports its
employees’ orientation to simultaneously collaborate and engage to sustain <strong>the</strong> achievement <strong>of</strong>
objectives in business. The force comes out <strong>of</strong> a trust relationship based on ethics and reciprocity <strong>of</strong>
help among members, as well as on a strong team felling fed within <strong>the</strong> organization. These are <strong>the</strong>
company’s fundaments, values and vision, on <strong>the</strong> primary level or shared vision and team learning on
a fur<strong>the</strong>r level.
The matter is <strong>of</strong> choosing <strong>the</strong> right perspective: ei<strong>the</strong>r regarding intellectual capital as a stock or as a
flow. It is not an easy task to perceive <strong>the</strong> dynamics <strong>of</strong> reality it is something that needs a lot <strong>of</strong>
learning, practice and a special kit. Our research led us to <strong>the</strong> answer that a mature learning
organization represents that kit. The full kit, to which intellectual capital relates, contains – <strong>the</strong>
personal mastery, <strong>the</strong> mental models, <strong>the</strong> shared vision, <strong>the</strong> team learning and <strong>the</strong> system’s thinking.
Intellectual capital needs <strong>the</strong> discipline <strong>of</strong> personal mastery because you can’t make use <strong>of</strong> something
if you don’t concentrate on comprehending its’ dimension, on controlling its’ spreading resonance and
finally on fur<strong>the</strong>r modelling its’ trajectory. Personal mastery means to know what you have done and
to push fur<strong>the</strong>r your work in order to accomplish what you have been able to, but “have never arrived
to” (Senge, 1990).
Fur<strong>the</strong>r speaking, having <strong>the</strong> mental models is nei<strong>the</strong>r so difficult nor enough but working through
<strong>the</strong>m is a start. This is how <strong>the</strong> organization’s intellectual capital will be always under <strong>the</strong> influence <strong>of</strong>
<strong>the</strong> mental models, or name it ‘action’. The shared vision within a learning organization is <strong>the</strong> affair
that keeps everyone and everything toge<strong>the</strong>r. To reality, <strong>the</strong> shared vision is not an idea as it is to us,
but an impressive force. We believe that intellectual capital will generate <strong>the</strong> competitive advantage
through its power as a function <strong>of</strong> factors like how it is perceived and what it is used for. A shared
vision keeps <strong>the</strong> team toge<strong>the</strong>r and <strong>of</strong>fers commitment to <strong>the</strong> same cause and this represents ano<strong>the</strong>r
strong integrator within <strong>the</strong> learning organization. (Bratianu, 2008) The phrase -team learning- seems
much easier to approach but <strong>the</strong> significance <strong>of</strong> <strong>the</strong> concept does not reduce itself to <strong>the</strong> translation.
Team learning means alignment and not <strong>of</strong> individuals to something but <strong>of</strong> <strong>the</strong> group to <strong>the</strong> common
something. We approached <strong>the</strong> above concepts under <strong>the</strong> aegis <strong>of</strong> <strong>the</strong> learning organization and
<strong>the</strong>re is one more to discuss. Senge talks about systems thinking as being <strong>the</strong> right option for our
perception. He says that <strong>the</strong> right way to solve a problem is to look at <strong>the</strong> whole <strong>of</strong> it and not at parts
<strong>of</strong> it. Splitting <strong>the</strong> whole into pieces will degenerate truth and results. We realize that systems thinking
is like <strong>the</strong> vital law for <strong>the</strong> learning organization and that it can’t function o<strong>the</strong>rwise.
Social capital affects both human capital and knowledge dynamics, increasing <strong>the</strong> intellectual capital
<strong>of</strong> <strong>the</strong> organization. Intellectual capital according to Stewart (1999) is “<strong>the</strong> sum <strong>of</strong> everything inside <strong>the</strong>
company that confers intellectual and/or material competitive advantage: knowledge, information,
intellectual property, experience that may be used to create wealth.” Intellectual capital regards <strong>the</strong>
permanent supervision and evaluation <strong>of</strong> knowledge within an organization, and it is fundamentally
different from creation and utilization <strong>of</strong> knowledge (that being knowledge management). Knowledge
management works for <strong>the</strong> purpose <strong>of</strong> creating intellectual capital to <strong>the</strong> organization. In o<strong>the</strong>r words,
knowledge management is <strong>the</strong> basic level <strong>of</strong> forming and developing competitive advantage,
consciously and pr<strong>of</strong>essionally. “What a company knows, <strong>the</strong> way that uses what it knows and how
fast something new and important can be obtained are part <strong>of</strong> <strong>the</strong> new perspectives generation
processes, <strong>of</strong> developing and using forecast, <strong>of</strong> engaging to competences and action based
capacities, and <strong>of</strong> learning from feedback. This is <strong>the</strong> intellectual capital.” (Rastogi, 2000) In 1980, a
research regarding <strong>the</strong> performances <strong>of</strong> Japanese companies concluded that <strong>the</strong>re exist major
differences <strong>of</strong> performance that may be attributed to non-material actives. A series <strong>of</strong> articles issued
at <strong>the</strong> end <strong>of</strong> <strong>the</strong> 1980 and in 1990, were explaining <strong>the</strong> use and measurement <strong>of</strong> intellectual capital
as a mean to better evaluate <strong>the</strong> company’s value. Today <strong>the</strong> most significant corporations identify
intellectual capital as a significant part in determining <strong>the</strong> market value.
There is no difficulty <strong>of</strong> understanding <strong>the</strong> essence <strong>of</strong> <strong>the</strong> concept ‘intellectual capital’ but it’s
confusing to correlate its semantic dynamics and variety <strong>of</strong> interpretations in time. It seems that we
have to wait for <strong>the</strong> strongest metaphor <strong>of</strong> intellectual capital to show up and make everyone to
converge. Maybe when we finish <strong>the</strong> debates about <strong>the</strong> content <strong>of</strong> intellectual capital we shall reach to
measure it. The measurement is possible but <strong>the</strong> results are still not reflecting reality, <strong>the</strong>y show
distortions. Confronting <strong>the</strong> human capital on individual level and on organizational level we observe
<strong>the</strong> similarity. Human capital at individual level consists in knowledge, intelligence and values and
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parts <strong>of</strong> <strong>the</strong>se may exist into <strong>the</strong> o<strong>the</strong>r components <strong>of</strong> <strong>the</strong> organizational intellectual capital. The errors
may come up when measuring twice <strong>the</strong> same knowledge, or third times <strong>the</strong> intelligence from <strong>the</strong>
human capital, <strong>the</strong> social capital and <strong>the</strong> relational capital. The problem is that <strong>the</strong>se three dimensions
are associated to <strong>the</strong> dynamic nature <strong>of</strong> intellectual capital but <strong>the</strong> basic structure <strong>of</strong> <strong>the</strong> organizational
intellectual capital does not change, which confines understanding and evaluating <strong>the</strong> potential <strong>of</strong>
intellectual capital.
5. The dynamics <strong>of</strong> <strong>the</strong> intellectual capital and <strong>the</strong> influence <strong>of</strong> knowledge
dynamics
Intellectual capital is a key factor to innovation and represents a competitive advantage in nowadays
knowledge based economy. At <strong>the</strong> same time, knowledge dynamics is recognized as a fundamental
activity for catching, increasing and supporting intellectual capital within <strong>the</strong> organizations. This
means that successful administration <strong>of</strong> intellectual capital is tightly bound to knowledge dynamics
processes in <strong>the</strong> organization; in consequence this implies that using knowledge dynamics in practice
ensures <strong>the</strong> extraction and development <strong>of</strong> intellectual capital.
Nonaka (2000) states that, despite <strong>the</strong> widely recognized importance <strong>of</strong> intellectual capital, even if
many times intellectual capital is equalized with knowledge, exists very little applicability <strong>of</strong> <strong>the</strong> way
organizations achieve to create intellectual capital actually by managing knowledge dynamics. In
addition, to Nonaka and Konno (1998) knowledge creation requires a common context <strong>the</strong>y call “ba”
(signifying “space”). Ba represents a shared context that may exist in various forms: as physical,
virtual, or mental space and explains why knowledge, as opposite to information, can’t be separated
from context – this being incorporated in <strong>the</strong> ba. In order to provide <strong>the</strong> appropriate ba, <strong>the</strong>re are
some requirements <strong>the</strong> learning organization has to check on. Firstly, <strong>the</strong> learning organization is <strong>the</strong>
one that best grants <strong>the</strong> benefits <strong>of</strong> knowledge sharing. Secondly, <strong>the</strong>re are more processes <strong>of</strong>
knowledge conversion and each <strong>of</strong> <strong>the</strong>se processes occurs within a different context, or ba. In a third
place, individuals must be included and guided towards <strong>the</strong> appropriate context which finally will lead
to knowledge creation. It is easy to observe that, within different departments, knowledge dynamics
varies both in processes dimension and prevalence regarding certain types <strong>of</strong> knowledge conversion.
Practice observations show that one <strong>of</strong> <strong>the</strong> problems organizations’ confront with when <strong>the</strong>y project
and analyze knowledge dynamics are inside any organization and that knowledge is used in different
ways depending on <strong>the</strong> department. For example, inside an organization is probable that within <strong>the</strong>
departments responsible with production and delivery <strong>of</strong> goods prevails explicit knowledge being
enclosed into processes and procedures. On o<strong>the</strong>r behalf, inside <strong>the</strong> same organization, <strong>the</strong> research
department is probable to abound <strong>of</strong> tacit knowledge. On individual level, intellectual capital
represents at least <strong>the</strong> basic issue when a person wants to develop continuously his/her knowledge
and increase his/her productivity, through applying each available organizational methodology.
The existence <strong>of</strong> knowledge dynamics serves as an organization competence that helps creating <strong>the</strong>
intellectual capital at <strong>the</strong> necessary level that might heighten <strong>the</strong> organization’s performance. The link
between intellectual capital and knowledge dynamics at individual level may be reduced to a person’s
motivation to increase his/her participation in such a way to contribute at building an organization
oriented towards learning. On <strong>the</strong> organizational level we picture <strong>the</strong> dynamic processes on <strong>the</strong>
vertical axis contributing to transform individuals’ assets into organizational, and on <strong>the</strong> horizontal axis
<strong>the</strong>y reflect <strong>the</strong> progressive knowledge transformation into action. (Bratianu, 2008)
6. Conclusions
We hope that we have convinced you about <strong>the</strong> righteousness <strong>of</strong> <strong>the</strong> approach as we have been
proving <strong>the</strong> two concepts interconnectivity and granted each one’s merits regarding evolution. In our
opinion <strong>the</strong> learning organization concentrates on employees and this will undisputedly lead to
increase skills and capacities, to improve methods and tools <strong>of</strong> work and to discover new channels
and paths <strong>of</strong> correlating things. Our conviction is that all <strong>the</strong>se may be achieved within <strong>the</strong> learning
organization throughout <strong>the</strong> managing <strong>of</strong> knowledge dynamics, and <strong>of</strong> course that intellectual capital
can’t be removed from <strong>the</strong> equation.
In order to form a working mechanism <strong>of</strong> knowledge dynamics and intellectual capital we have to
comprehend <strong>the</strong>ir specific “personalities” and preview <strong>the</strong>ir processing toge<strong>the</strong>r. O<strong>the</strong>rwise, such
segregation limits <strong>the</strong> understanding <strong>of</strong> knowledge as a valuable resource for a company’s growth
and development. Learning invariably needs to be treated as an endogenous factor in <strong>the</strong> formation <strong>of</strong>
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a company’s absorptive capacity, which, in turn, leads to <strong>the</strong> assimilation <strong>of</strong> new knowledge with prior
knowledge. (Liyanage, 2002)
An organization oriented towards learning is an organization able to create, attract, interpret and
enhance knowledge dynamics by purposefully changing <strong>the</strong> behavior and structure in order to
discover o<strong>the</strong>r new perspectives <strong>of</strong> development. We regard learning as endogenous to knowledge
processes and argue that it forms an integral part <strong>of</strong> knowledge development, knowledge absorption,
and interchanges. In <strong>the</strong> formation <strong>of</strong> knowledge and intellectual capital, learning plays a critical role,
especially in filling out <strong>the</strong> knowledge gaps <strong>of</strong> individuals, teams, and systems. (Liyanage, 2002) The
conceptual connections between all <strong>the</strong>se concepts are plenty and logical and if you don’t miss out
<strong>the</strong> fact that <strong>the</strong>y are fruits <strong>of</strong> re-thinking reality you’ll find this as <strong>the</strong> most solid argument to believe
<strong>the</strong>y work.
We conclude that <strong>the</strong> intellectual capital is a dynamic component that may continuously be modelled
with respect to its quantity, quality, value, usefulness or intensity <strong>of</strong> use and this is exactly what an
au<strong>the</strong>ntic learning organization implies: endless dynamics.
References
Augier, M. & Morten, T. (1999) Networks, cognition and management <strong>of</strong> tacit knowledge, Journal <strong>of</strong> Knowledge
Management, 3. (pp. 252-261).
Auer, Thomas (2004) Benchmarking Intellectual Capital. Wissen Management Magazine.
Augier, M. & Morten, T. (1999) Networks, cognition and management <strong>of</strong> tacit knowledge, Journal <strong>of</strong> Knowledge
Management, 3. (pp. 252-261).
Becker, Garry S. (1993) Human Capital: A Theoretical and Empirical Analysis, with Special Reference to
Education; Third edition. Chicago and London: University <strong>of</strong> Chicago Press
Bratianu, C. (2010) A Critical Analysis <strong>of</strong> Nonaka’s Model <strong>of</strong> Knowledge Dynamics, Electronic Journal <strong>of</strong>
Knowledge Management Volume 8 Issue 2 (pp193-200), online at www.ejkm com
Bratianu, C., Bejinaru, R., Iordache, S. (2010) Knowledge Dynamics in Negotiation, 17 th International Economic
<strong>Conference</strong>, “Lucian Blaga” University <strong>of</strong> Sibiu, Romania, 13-14 May 2010, pg 58, ISBN-978-973-739-987-8
Bratianu, C. (2009) The Frontier <strong>of</strong> Linearity in <strong>the</strong> Intellectual Capital Metaphor Electronic Journal <strong>of</strong> Knowledge
Management Volume 7 Issue 4, (pp415 -424), online at www.ejkm com
Bratianu, C. (2008) A dynamic structure <strong>of</strong> <strong>the</strong> organizational intellectual capital, in: Naaranoja, M. (ed.)
Knowledge management in organizations, pp.233-243, Vaasa: Vaasan Yliopisto.
Bejinaru, R., Iordache, S. (2010) Knowledge Channeling in <strong>the</strong> Learning Organization, 5 th International
<strong>Conference</strong> on Business Excellence, 15-16 October 2010 Brasov, Infomarket Publishing House, Romania,
pg. 59, ISBN 978-973-1747-23-1 vol 1.
Bontis, Nick (1998) Intellectual capital: an exploratory study that develops measures and models, Management
Decision 36/2, 63–76, MCB University Press, ISSN 0025-1747
Brooking, A., (1991) Corporate memory: strategies for knowledge management. New York: International
Thomson Business Press.
Brooking, A., (1997) Intellectual capital: core asset for <strong>the</strong> third millennium enterprise. New York: International
Thomson Business Press.
Davenport, T H., (1996) Knowledge management and <strong>the</strong> broader firm: strategy, advantage, and performance.
(Eds.), Knowledge management handbook (p. 2-3). New York: CRC Press.
Deming, W. E. (1994) The New Economics, 2d edition. Cambridge, MA: MIT Press.
Deming, W. E. (2000) The new economics for industry, government, education (2nd ed.). Cambridge, MA: MIT
Press.
Drucker, Peter F. (1995) Managing in a Time <strong>of</strong> Great Change, New York: Truman Talley Books/Dutton
Edvinssion, L. (1997) Developing intellectual capital at Skandia, Long Range Panning
Huang, K, T, Lee, Y. W., & Wang, R. Y. (2001) Quality information and knowledge. Upper Saddle River, NJ:
Prentice Hall PTR.
Hunter, Lauret (2002) Intellectual Capital Accumulation and Apprpriation. Working Paper. Melbourne, Australia
Kaplan, R. S. and D. P. Norton (1996) The Balanced Scorecard: Translating Strategy into Action Boston: Harvard
Business School Press
Koenig, U. & Membrillo, A. (2004) Impat <strong>of</strong> Individual Knowledge on <strong>the</strong> Increase <strong>of</strong> Sustenable Intellectual
Capital <strong>of</strong> Organization. Working Paper, Manheim Univeristy
K<strong>of</strong>man, F., Senge, P., Kanter, R. M., & Handy, C. (1995) Learning organizations: developing cultures for
tomorrow's workplace. Portland, OR: Productivity Press.
Kogut, B. & Zander, U. (1995) Knowledge <strong>of</strong> <strong>the</strong> firm and <strong>the</strong> evolutionary <strong>the</strong>ory <strong>of</strong> <strong>the</strong> multinational corporation,
Journal <strong>of</strong> International Business Studies, 4: 625-645.
Krogh, G. V., Ichijo, K., & Nonaka, I. (2000) Enabling knowledge creation: how to unlock <strong>the</strong> mystery <strong>of</strong> tacit
knowledge and release <strong>the</strong> power <strong>of</strong> innovation. New York: Oxford University Press.
Krogh, G. & Nonaka, I. (1994) ”A dynamic <strong>the</strong>ory <strong>of</strong> organizational knowledge creation', Organization. Science,
Vol. 5, pp.14œ37
76

Ruxandra Bejinaru and Stefan Iordache
Liyanage, Shantha (2002) Knowledge and Intellectual Capital Management Processes: Grounding Knowledge
and Understanding <strong>the</strong> Organizational Learning, Journal <strong>of</strong> Universal Computer Science, vol. 8, no. 5, 526-
535.
Miller, R., Stewen M. (1996) Measuring What People Know: Human Capital Accounting for <strong>the</strong> Knowledge
Economy, Paris: OECD.
Nonaka, I. and Takeuchi, H. (1995) The Knowledge-creating Company. New York: Oxford University Press.
Nonaka, I. (1991) The knowledge-creating company. Harvard Business Review on Knowledge Management. (pp.
21-45). Boston, MA: Harvard Business School Publishing.
Nonaka, Ikujiro and Noboru Konno (1998) The Concept <strong>of</strong> ‘Ba’: Building a Foundation for Knowledge Creation,
California Management Review, 40(3), 40-55
O'Dell, C., & Grayson, C. J. Jr. (1998) The transfer <strong>of</strong> internal knowledge and best practice: if only we knew what
we know. New York: The Free Press.
Rastogi, P. (2000) Knowledge management and intellectual capital - <strong>the</strong> new virtuous reality <strong>of</strong> competitiveness.
Human Systems Management 19, (pp. 39-49).
Senge, P. (1990) The fifth discipline: <strong>the</strong> art & practice <strong>of</strong> <strong>the</strong> learning organization. New York: Doubleday Press.
Senge, P., Kleiner, A., Roberts, C., Ross, R., Roth, G., & Smith, B. (1999) The dance <strong>of</strong> change: <strong>the</strong> challenges
to sustaining momentum in learning organizations. New York: Doubleday/Currency
Simon A.R. (1993) A complete guidein knowledge, Cambridge, MA: MIT Press., 1-55860-245-3
Stewart, T. A. (1999) Intellectual capital: <strong>the</strong> new wealth <strong>of</strong> organizations. New York: Currency Doubleday.
Sullivan, P. H. (2000) Value-driven intellectual capital: how to covert intangible corporate assets into market
value. New York: John Wiley & Sons, Inc.
Stewart, T.A. (1997) Intellectual Capital: The New Wealth <strong>of</strong> Organizations, Doubleday/Currency, New York, NY
Sveiby, K.E. (1997) The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets,
Berrett-Koehler, New York, NY.
Teece, D.J. (2000) Managing Intellectual Capital, Oxford: Oxford University Press.
Takeuchi, H. (2001) Towards a universal management concept <strong>of</strong> knowledge, in Nonaka, I., Teece, DJ (Eds),
Managing Industrial Knowledge – Creation, Transfer and Utilization, Sage, London
Varela, F. J., Thompson, E., & Rosch, E. (1991) The embodied mind. Cambridge, MA: MIT Press.
Venzin, Markus, Georg von Krogh, and Johan Roos (1998) Future Research into Knowledge Management,
Knowing in Firms: Understanding, Managing and Measuring Knowledge, Sage Publications.
Wheatley, M. (2001) The real work <strong>of</strong> knowledge management. Human Resources Information Management
Journal. (pp. 30-37).
77

Education and Training Practice Strategies in Small and
Medium Sized Enterprises
Andrea Bencsik, Vendel Lőre and Andrea Sólyom
Széchenyi István University, Győr, Hungary
bencsik.andrea@yahoo.com
lore@sze.hu
solyoma@sze.hu
Abstract: The role <strong>of</strong> knowledge is a determinative factor in <strong>the</strong> life <strong>of</strong> economy and society. To determine
knowledge is not an easy task yet <strong>the</strong> real task is to determine <strong>the</strong> right knowledge. From this view knowledge is
a sum <strong>of</strong> experience, ideas and cognitions which can help companies to remain in markets and to realize a
maximum pr<strong>of</strong>it. At <strong>the</strong> same time changes <strong>of</strong> circumstances project in advance that contents and demands <strong>of</strong>
<strong>the</strong> right knowledge are changing. In <strong>the</strong> past more than 10 years studying, education and human resource (HR)
development have become determinative factors in <strong>the</strong> area <strong>of</strong> HR management. It means much more than
earlier from <strong>the</strong> view <strong>of</strong> companies. It has become a strategic question and simultaneously it is a dominant source
<strong>of</strong> competitiveness. Why do we have to manage knowledge? We have to manage knowledge because
intellectual capital is in <strong>the</strong> foreground <strong>of</strong> organizational statements. However, it is clear that knowledge can be
difficult to account for however, its importance is indisputable. The more companies can keep and exploit <strong>the</strong>ir
employees’ knowledge, <strong>the</strong> more <strong>the</strong>y will be able to attain business success. Their knowledge can be found in
many divisions (departments, workshops, industrial units, etc), it is dissipated and cannot be reached by every
employee. Therefore companies have to discover <strong>the</strong>ir knowledge again and again, <strong>the</strong>y have to find solutions
which have already been born in ano<strong>the</strong>r unit. In this paper we will analyse a special segment on <strong>the</strong> basis <strong>of</strong> an
empirical survey. We investigated <strong>the</strong> behaviour and strategies <strong>of</strong> small and medium sized enterprises (SMEs) in
<strong>the</strong> area <strong>of</strong> knowledge-handling. This survey was realized by questionnaires and wide range statistical methods
were used during processing. As a result we will show how <strong>the</strong>se companies are prepared to operate in a
knowledge-based economy and in which areas <strong>the</strong>y have prominent deficiencies.
Keywords: education, knowledge, knowledge management, strategy, SME, training
1. Knowledge as a strategic factor
In <strong>the</strong> past more than 10 years studying, education and human resource (HR) development have
become determinative factors in <strong>the</strong> area <strong>of</strong> HR management. It means much more than earlier from
<strong>the</strong> view <strong>of</strong> companies. It has become a strategic question and simultaneously it is a dominant source
<strong>of</strong> competitiveness.
We have talked about knowledge a lot, but we have not defined it. This task is not too simple because
knowledge is an inconceivable and complex notion so we can only circumscribe it. To this we can use
a definition <strong>of</strong> Davenport – Prusak, (2001) that is a practical viewing: Knowledge is a heterogeneous
and continuously changing mix from limited experiences, values and joined information. It is expertise
that can give a frame to judgement and attainment <strong>of</strong> new information and experiences and it
originates and useful in <strong>the</strong> knowledge possessing people’s mind. Companies take care <strong>of</strong> this
knowledge not only in documents and stock-lists, but <strong>the</strong>y store it up in <strong>the</strong>ir proceedings, practical
activities and standards as a part <strong>of</strong> organizational routine. (Davenport and Prusak, 2001)
Knowledge has value <strong>the</strong>refore we can catch it as an element <strong>of</strong> property. Knowledge is capable <strong>of</strong>
value creation, so we can catch it as an element <strong>of</strong> capital. Intellectual capital is an amount <strong>of</strong> special
knowledge that can give competitive advantages and it is in possession <strong>of</strong> companies.
But what gives studying a strategic role? It is a very simple context. Most knowledge – especially not
formalized (tacit) knowledge – can be acquired and accumulated over a long time inside an
organization. This type <strong>of</strong> knowledge can be copied and adapted with more difficulties than any o<strong>the</strong>r
types <strong>of</strong> sources (Davenport and Prusak, 2001; Sveiby, 2001; Prahalad and Hamel 1990). On <strong>the</strong>
basis <strong>of</strong> <strong>the</strong> above mentioned features, knowledge becomes a source <strong>of</strong> a competitive advantage in
<strong>the</strong> long run from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> strategy. With <strong>the</strong> accumulation <strong>of</strong> this input, companies can
build a well-protected competitive factor for a long time as competitors can copy knowledge but only
with difficulty and, fur<strong>the</strong>rmore, it can take a long time.
This way <strong>of</strong> thinking is available not only at an organizational level, but also at a macroeconomic level.
The difference can be made in two directions. One <strong>of</strong> <strong>the</strong>m is <strong>the</strong> conventional relative product cost
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Andrea Bencsik et al.
strategy which aims to reduce <strong>the</strong> costs <strong>of</strong> products and services (Csath, 2008). The second is aimed
at by <strong>the</strong> <strong>European</strong> Union (EU) which is an economic growth strategy on <strong>the</strong> basis <strong>of</strong> knowledge.
This strategy says that added knowledge-value is also a resource which can be maintained for a long
time. International researchers agree that knowledge, innovation and creativity are needed for
sustainable development. However, <strong>the</strong> economy can become too vulnerable by <strong>the</strong> cost reduction
strategy.
1.1 Research purposes
We have continued this research from <strong>the</strong> view <strong>of</strong> practice, but we cannot work without <strong>the</strong>oretical
basis. Economic operators have to find answers to <strong>the</strong> provocations <strong>of</strong> <strong>the</strong> environment – it is similar
to that <strong>of</strong> nature where we have to adapt very fast to survive and development. Changes <strong>of</strong>
environment launch a process <strong>of</strong> adaptation at companies that proceed in a competitive surrounding.
There are operators who can get advantages in this process and <strong>the</strong> o<strong>the</strong>rs run into a
disadvantageous situation. The solutions that are advantageous can spread and <strong>the</strong> o<strong>the</strong>rs can fall
into <strong>the</strong> background.
On <strong>the</strong> basis <strong>of</strong> <strong>the</strong>se analogies we can catch <strong>the</strong> changes <strong>of</strong> knowledge-based economy. (Farkas,
2003)
This new economy is only a challenge for companies <strong>the</strong>y need to fit to survival.
This is a threat on <strong>the</strong> one hand, because who cannot adapt to this demand well enough, <strong>the</strong>y can fall
into <strong>the</strong> background. But on <strong>the</strong> o<strong>the</strong>r hand every change is a possibility for companies to get a
competitive advantage.
These changes can be possibilities, if <strong>the</strong> needed resources – knowledge - are at <strong>the</strong> companies on a
suitable level. O<strong>the</strong>rwise we have to handle changes as a threat.
In this new knowledge-based economy <strong>the</strong> economic operators can have chance to adaptation or
increase <strong>the</strong>ir competitiveness that can accumulate suitable resources - knowledge - in a proactive
way.
The function <strong>of</strong> small and medium-sized enterprises depends on <strong>the</strong>ir capabilities to catch knowledge,
how <strong>the</strong>y use it during <strong>the</strong>ir value creation, because <strong>the</strong> added knowledge-value becomes more and
more significant in <strong>the</strong> economic processes. (Mészáros - Bálint, 2003)
We asked <strong>the</strong> question: do Hungarian SMEs possess any knowledge-based strategies and if so <strong>the</strong>n
what kind <strong>of</strong> HR policy supports <strong>the</strong>se features? To answer this question a special segment <strong>of</strong> <strong>the</strong>
Hungarian economy was investigated that <strong>of</strong> SMEs. This area is not popular among Hungarian
researchers but it is known from international literature that <strong>the</strong>se enterprises play a main role in
knowledge-based sectors (Sveiby 2001). According to <strong>the</strong> above mentioned questions in this paper
we will show <strong>the</strong> results <strong>of</strong> our survey which was conducted by questionnaires in 2009 and in <strong>the</strong>
focus <strong>of</strong> this survey education and training supported by HR management and leadership was
highlighted. This survey is one in a row <strong>of</strong> earlier surveys, but it differs as in this case s<strong>of</strong>t factors
(which are difficult to measure) are in <strong>the</strong> focus, such as quality <strong>of</strong> leadership or personal features
expected from employees.
The survey focused on <strong>the</strong> following areas:
Knowledge transfer, knowledge creation and organizational culture which supports studying and
leadership. These were investigated by a group <strong>of</strong> variables with 22 items which are dominant in
organizations.
We measured different types <strong>of</strong> studying in organizations which are typical at <strong>the</strong> investigated
companies.
We investigated which competencies and personal features are important in <strong>the</strong> process <strong>of</strong>
employee selection.
We analysed in which area <strong>the</strong>re are <strong>the</strong> biggest problems in connection with HR.
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Andrea Bencsik et al.
We wanted to know if enterprises have a connection with higher education and if so what types <strong>of</strong>
connections exist. If not, we wanted to know what kind <strong>of</strong> obstructive factors can be found.
2. Strategic background
It was mentioned earlier that at <strong>the</strong> level <strong>of</strong> national economy <strong>the</strong>re are two basic strategies. But how
do <strong>the</strong>se two strategies appear in companies?
To answer this question <strong>the</strong> well-known Porter’s strategies model can be used. In this model <strong>the</strong>re are
three different strategies:
Cost leadership: a company <strong>of</strong>fers a widespread palette <strong>of</strong> products with which it can reach a big
lot size. It can generate <strong>the</strong> decline <strong>of</strong> specific costs.
Differentiation strategy: on <strong>the</strong> basis <strong>of</strong> some features <strong>of</strong> products or services (which are very
different from competitors’ products or services) companies can realize competitive advantages.
Focus or strategic scope: companies can make a conquest <strong>of</strong> one or some segments. In
consequence <strong>of</strong> this focus companies can use <strong>the</strong>ir competitive advantages.
In <strong>the</strong>se strategies <strong>the</strong> above mentioned two strategic directions can be found. In <strong>the</strong> case <strong>of</strong>
companies cost leadership, this is <strong>the</strong> same as <strong>the</strong> relative product cost strategy at <strong>the</strong> level <strong>of</strong>
national economy. Differentiation strategy and focus or strategic scope <strong>of</strong>ten goes hand in hand with
knowledge-based strategies. In this case <strong>the</strong> source <strong>of</strong> competitive advantages can be knowledge
capital and, toge<strong>the</strong>r with it, <strong>the</strong> role <strong>of</strong> education and training.
2.1 Types <strong>of</strong> studying in <strong>the</strong> SMEs sector
Education and training – as a function <strong>of</strong> HR management – have a key role in <strong>the</strong> realization <strong>of</strong>
knowledge-based strategies. Education and training appear in companies as a necessity although
<strong>the</strong>y can be realized sometimes only in an implicit form.
During <strong>the</strong> process <strong>of</strong> modelling three classic types <strong>of</strong> knowledge capital were used:
Customer capital is <strong>the</strong> sum <strong>of</strong> outside organizational relationships, connections with customers
and distributors in <strong>the</strong> market and connections with investors and competitors. Altoge<strong>the</strong>r it also
contains formal and informal business connections.
Structural capital contains such elements <strong>of</strong> knowledge which are not in close connection with
employees, but are in connection with a company. Its most important element is organizational
culture and <strong>the</strong> o<strong>the</strong>rs are <strong>the</strong> management’s experience, internal processes, routines and
systems.
Intellectual capital is <strong>the</strong> third group <strong>of</strong> human capital. It contains explicit knowledge, experience,
competencies, expertise, etc.
These three types <strong>of</strong> capital join each o<strong>the</strong>r hierarchically and form a value chain.
As a result <strong>of</strong> our earlier research a <strong>the</strong>oretical model has been formed. This model aims to show
which factors are significant during SMEs training processes. Two different training types are typical.
One <strong>of</strong> <strong>the</strong>m is information and knowledge acquired from <strong>the</strong> external environment. Its typical form is
to keep connections with higher education, pr<strong>of</strong>essional organizations, chambers, etc. The o<strong>the</strong>r is
very different and uses <strong>the</strong> internal sources <strong>of</strong> companies, both individual and team learning. This
builds on knowledge transfer, knowledge sharing and knowledge multiplication. The well-known
methods are teamwork, a mentor system, spontaneous collaboration, pr<strong>of</strong>essional teams, etc. This
system <strong>of</strong> connections is shown in Figure 1.
2.2 Hypo<strong>the</strong>ses
H1: According to <strong>the</strong> conventional view, education and training practices <strong>of</strong> SMEs lag behind bigger
companies. This means external knowledge acquisition causes competitive disadvantages.
H2: Organizational cultures and leadership which build on internal conditions and support informal
knowledge are influenced by <strong>the</strong> measure <strong>of</strong> companies. The smaller measure improves <strong>the</strong>
conditions <strong>of</strong> informal learning.
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Figure 1: Significant factors during SMEs training processes
H3: There are typical strategies <strong>of</strong> knowledge development. Some organizations prefer formal
learning, o<strong>the</strong>rs prefer informal learning.
H4: Organizations in knowledge-intensive industries have different HR demands from companies that
are not research-based
3. Research methodology and characteristics <strong>of</strong> sample
This survey was realized by questionnaires. A simple structure was used in <strong>the</strong> questions. In case <strong>of</strong>
subjective elements a Likert-scale was used with five grades due to perspicacity. Wide range
statistical methods were used during processing. First we used simple statistics by Micros<strong>of</strong>t Excel,
after that <strong>the</strong> SPSS 15.0 programme was accommodated with multiplication analyses.
A random sample was taken from all over <strong>the</strong> country. More than 400 questionnaires were collected,
but 365 were left in <strong>the</strong> database after data cleaning.
The sample can be characterized by three features:
Size <strong>of</strong> enterprise;
Questioned people’s status; and
Areas <strong>of</strong> business.
3.1 Size <strong>of</strong> enterprises
More than 50% <strong>of</strong> <strong>the</strong> sample were micro-enterprises, approximately 30% were small enterprises and
4.5% <strong>of</strong> big companies were left in <strong>the</strong> sample in order to compare <strong>the</strong>ir results.
3.2 Areas <strong>of</strong> business
Table 1: Division <strong>of</strong> samples
Division <strong>of</strong> industry in <strong>the</strong> sample Rate %
Agriculture and fishing 5
Building industry 14.8
Processing industry 13.1
Trade 23.7
Catering 8
Delivery and storage 4.5
Financial and economic 8.9
Education 2.1
Medical services 1.2
Repair work and o<strong>the</strong>r services 18.7
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In this sample enterprises were in a well-diversified structure. Commercial businesses were at <strong>the</strong>
highest rate <strong>the</strong>n repair work and o<strong>the</strong>r services follow. This rate is a typical feature <strong>of</strong> Hungary.
3.3 Questioned people’s status
On <strong>the</strong> basis <strong>of</strong> <strong>the</strong> above mentioned third feature, questioned people were classified in <strong>the</strong> following
categories:
Leaders in a high position and owners (55.3%);
Functional leaders (26.6%);
Leaders in a lower position (18.1%).
4. Results
4.1 SME training from a conventional view
Hypo<strong>the</strong>sis 1.
To confirm <strong>the</strong> first hypo<strong>the</strong>sis <strong>the</strong> uses <strong>of</strong> training from external sources <strong>of</strong> SMEs were investigated.
Connections with higher education and o<strong>the</strong>r conventional training and development elements <strong>of</strong> HR
were focused on: participation in organized training or participation in pr<strong>of</strong>essional programmes.
(Tables 2 and 3).
Table 2: Cooperation with higher education
There is no
connection and
SMEs do not want
to have one.
(%)
There is no
connection but
SMEs want to
have a
connection.
(%)
There are
connections but
SMEs do not
operate well
(%)
There are
connections and
SMEs want to
develop <strong>the</strong>m
(%)
Employees’ pr<strong>of</strong>essional
education in higher
education 56.3 22.8 4.2 16.7
Participation in writing a
<strong>the</strong>sis 57.1 15.2 8.3 19.4
Cooperation in research
with higher education 72.9 16.2 3.2 7.7
Answers in research panels
Experts’ participation in
higher education as a
74.5 16.2 2.9 6.4
lecturer
Informal connections with
65.8 16.2 4.6 13.4
pr<strong>of</strong>essors
Participation in programmes
61.7 12.9 4.5 20.9
<strong>of</strong> higher education 64.9 15.8 2.8 16.5
Participation in job fairs 72 16.7 4.9 6.4
Table 3: Conventional forms <strong>of</strong> education, training and study in SME
Absolutely not
typical (%)
Not typical
(%)
Meanly
typical (%)
Typical
(%)
Absolutely
typical (%)
Enterprises support studying
financially 11.9 31.6 25.8 23.8 6.9
There is organized education
Leaders’ behaviour supports
14.6 35.5 20.8 22.5 6.5
studying
Participating in pr<strong>of</strong>essional
7.3 24.3 33.8 26.8 7.8
programmes 6.7 13.7 31.6 32.1 15.9
Relationships with chambers 14.6 23.3 26.7 23.6 11.8
Tables 2 and 3 confirm hypo<strong>the</strong>sis 1. Those answers which are particularly remarkable concern <strong>the</strong>
connection with higher education. Independent from <strong>the</strong> type <strong>of</strong> answers “<strong>the</strong>re is no connection and
<strong>the</strong>y do not want to have one” had a high percentage.
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This result shows that SMEs operate in a very closed system <strong>of</strong>ten without enough information and
knowledge. Our experience is that this attitude originates from distrust which was a problem during
<strong>the</strong> completion <strong>of</strong> <strong>the</strong> questionnaires. In <strong>the</strong> cases <strong>of</strong> <strong>the</strong>se enterprises, external learning is a category
<strong>of</strong> exception ra<strong>the</strong>r than an accepted standard solution. These statements are confirmed by <strong>the</strong>
following facts that enterprises do not keep connections with higher education but <strong>the</strong>y are no
obstructions at all. In our opinion it means that <strong>the</strong>se enterprises are very distrustful and <strong>the</strong>y do not
feel this area is important.
4.2 Informal learning
Hypo<strong>the</strong>sis 2.
It is well-known that a lot <strong>of</strong> features <strong>of</strong> organizational culture, HR and leadership support informal
knowledge transfer and knowledge creation.
An open atmosphere, a non-hierarchical relationship between leaders and employees, accepted
learning and a motivational atmosphere have to be emphasized from organizational characteristics.
Higher independence <strong>of</strong> employees, support <strong>of</strong> initiations which come from <strong>the</strong> bottom, flexible jobs,
support <strong>of</strong> collaboration are important in leaders’ features.
These facts were operationalized by 22 variates. In our analysis <strong>the</strong> sample was divided into two
different groups: enterprises with fewer than 20 employees and enterprises with more than 20
employees. In our experience this size <strong>of</strong> company is an important element from <strong>the</strong> view <strong>of</strong> a
knowledge management system.
A t- test was used with an independent sample. Significant facts are:
There are close connections among employees;
They is frequent conflict in <strong>the</strong> organization;
The organizational structure is hierarchical;
Activities are not flexible;
Higher leaders support employees’ initiations;
There are frequent initiations from <strong>the</strong> bottom to <strong>the</strong> top;
Organizations operate on <strong>the</strong> basis <strong>of</strong> trust;
An open atmosphere is characteristic.
From <strong>the</strong>se significant facts it can be clearly seen that <strong>the</strong> size <strong>of</strong> organization is dominant. In smaller
organizations mutual trust, an open atmosphere and fewer conflicts are dominant. These features are
very useful when sharing and creating knowledge. Organizational structures <strong>of</strong> <strong>the</strong>se smaller
companies support our establishment. In <strong>the</strong>se organizations hierarchical relationships and strict
control are at a lower level. These conditions are favourable for informal knowledge sharing. In <strong>the</strong>se
smaller companies initiations <strong>of</strong>ten come from <strong>the</strong> bottom and <strong>the</strong>se initiations are supported by <strong>the</strong>
CEO as well.
From this analysis it can be seen that smaller organizations <strong>of</strong>fer very good conditions for a
knowledge management system thanks to a s<strong>of</strong>t organizational culture and principles <strong>of</strong> leadership. It
is not an accident that knowledge-based organizations are over-represented among SMEs because in
<strong>the</strong>ir cases conditions <strong>of</strong> knowledge transfer and knowledge creation are optimal.
4.3 Learning strategies <strong>of</strong> SMEs
Hypo<strong>the</strong>sis 3.
To investigate <strong>the</strong> third hypo<strong>the</strong>sis cluster analysis was used. Ten variables were called in which
contained external and internal elements <strong>of</strong> knowledge. These variables and <strong>the</strong> results <strong>of</strong> this
investigation can be seen in <strong>the</strong> following table.
As a result <strong>of</strong> cluster analysis we have a stable structure which describes four different strategies.
83

Table 4: Types <strong>of</strong> learning in organizations
Andrea Bencsik et al.
Types <strong>of</strong> learning Cluster centres
1 2 3 4
Enterprises support studying financially 0.43 -0.42 0.97 -0.72
There are organized educations 0.47 -0.53 1.03 -0.65
Leaders’ behaviour supports studying 0.20 -0.13 0.93 -0.73
Independent collaboration among employees -0.31 0.60 0.77 -0.79
Teamwork -0.25 0.52 0.74 -0.85
Mentor system -0.07 0.01 0.77 -0.45
Participating in pr<strong>of</strong>essional programmes 0.33 -0.29 1.05 -0.78
Relationships with chambers 0.46 -0.37 0.95 -0.71
Knowledge sharing -0.28 0.47 0.65 -0.66
Theoretical methods in teams -0.15 0.36 0.87 -0.83
Rate (%) 28.53 27.38 17.29 26.8
The results shows 28.5% <strong>of</strong> cases belong to a strategy which is based on conventional elements <strong>of</strong>
learning. In this strategy internal knowledge creation is featured at a lower level, but external learning
is featured (see values <strong>of</strong> cluster centres). The second group can be featured by opposite values. In
this case conditions <strong>of</strong> knowledge sharing and knowledge creation are given based on internal
sources. In <strong>the</strong> lowest rate (17.3%) <strong>the</strong>re are companies in which both strategies are featured (cluster
3). In <strong>the</strong> fourth group 26.8% <strong>of</strong> those companies do not feature in any <strong>of</strong> <strong>the</strong> strategies.
This cluster analysis verified our hypo<strong>the</strong>sis. Companies have typical strategies such as
conventional HR development and educational strategy or knowledge-based strategy. We have also
found companies where both strategies are employed or companies where none <strong>of</strong> <strong>the</strong> strategies are
employed at all.
4.4 HR requirements
Hypo<strong>the</strong>sis 4.
During <strong>the</strong> investigation we looked for personality features in connection with young people with a
degree. A list and scores <strong>of</strong> <strong>the</strong>ir importance can be seen in Figure 2.
Language knowledge
Certificated capabilities
Computer science
Pr<strong>of</strong>essional relationship
Loyalty
Ability for teamwork
Creativity
Adaptability
Motivation
Flexibility
Pr<strong>of</strong>essional experience
Loadability
Independence
Pr<strong>of</strong>essional knowledge
Ability to problem solve
Reliability
Requirements from Young People with a Higher Degree
3 3,5 4 4,5
scores
Figure 2: Requirements from young people with a higher degree
84
5

Andrea Bencsik et al.
Reliability is <strong>the</strong> first on this list, followed by problem solving and pr<strong>of</strong>essional knowledge. It is
surprising that informatics and language knowledge are in <strong>the</strong> background but this can be explained
by <strong>the</strong> aims and behaviour <strong>of</strong> SMEs. They work in local markets but do not produce exports. This can
explain why language knowledge is in <strong>the</strong> last position. Infrastructural causes can explain why
computer science remains in <strong>the</strong> background (remember <strong>the</strong>re are more than 50% <strong>of</strong> microenterprises
in <strong>the</strong> sample.)
According to hypo<strong>the</strong>sis 4 <strong>the</strong> role <strong>of</strong> enterprise size was investigated from <strong>the</strong> view <strong>of</strong> <strong>the</strong>ir
requirements towards young people with a higher degree. But <strong>the</strong>re were no significant differences in
any facts at all. Due to this result hypo<strong>the</strong>sis 4 was rejected.
5. Conclusion
In this research SMEs were investigated from <strong>the</strong> view <strong>of</strong> a knowledge-based economy. The question
was how <strong>the</strong>y can face future challenges. We know that knowledge and study are very important for
companies, <strong>the</strong>ir role have become more and more determined. In spite <strong>of</strong> <strong>the</strong>se facts <strong>the</strong>y cannot
keep abreast <strong>of</strong> financial things because <strong>the</strong> purpose <strong>of</strong> <strong>the</strong> companies is to reach <strong>the</strong> highest pr<strong>of</strong>it.
Information has become very valuable, but flow channels stay in <strong>the</strong> background, because people
distrust each o<strong>the</strong>r very much.
Forms <strong>of</strong> education and training were investigated. Education and teaching in a conventional meaning
are in <strong>the</strong> background in <strong>the</strong> case <strong>of</strong> <strong>the</strong>se SMEs which means that <strong>the</strong> only opportunity to acquire
knowledge is externally. Small and medium-sized enterprises do not feel <strong>the</strong> importance <strong>of</strong> study and
knowledge, <strong>the</strong> necessity to built organizational culture and atmosphere to operate <strong>the</strong>se systems.
According to <strong>the</strong> interpretation <strong>of</strong> knowledge in a wider frame – which means <strong>the</strong> view <strong>of</strong> knowledge
management – SMEs are in a good position because <strong>the</strong>ir size allows <strong>the</strong>m to form interpersonal
connections and to use democratic leadership. They are favourable to knowledge sharing and
knowledge creation which is a new paradigm <strong>of</strong> our modern economic life.
It was established that learning has four strategies in <strong>the</strong> case <strong>of</strong> SMEs.
There are organizations which cannot be featured by any strategy at all. There are organizations
which have conventional and knowledge-based strategies, too. We could find organizations which
have only conventional or only knowledge-based strategies.
This survey had a deeper insight into <strong>the</strong> investigation <strong>of</strong> how <strong>the</strong> size <strong>of</strong> companies influences
demands from HR. In this case <strong>the</strong>re were no significant differences among <strong>the</strong> facts.
Ultimately it can be established that SMEs have deficiencies from <strong>the</strong> view <strong>of</strong> conventional education
and teaching but <strong>the</strong>y have competitive advantages in <strong>the</strong> area <strong>of</strong> informal knowledge transfer,
knowledge sharing and knowledge creation.
They know that <strong>the</strong>y have to change <strong>the</strong>ir behaviour and thinking, <strong>the</strong>y know that demand is
increasing continuously, but <strong>the</strong>y are not on <strong>the</strong> suitable level that <strong>the</strong>y can compete with bigger or
multinational companies. We should not be surprised because <strong>the</strong> small and medium-sized
enterprises do not get any support – from <strong>the</strong> government - that would be needed. Nowadays <strong>the</strong>re is
only one source - <strong>the</strong> EU support - in Hungary. According to <strong>the</strong> share <strong>of</strong> funds <strong>of</strong> National
Development Plan-2, <strong>the</strong> multinational companies working in Hungary can get more than <strong>the</strong> half <strong>of</strong>
<strong>the</strong> useable amount. So we can have concerns about <strong>the</strong> future <strong>of</strong> small and medium-sized
enterprises and we cannot be surprised if <strong>the</strong>y become distrustful and unstable.
In this situation we can ask.
What can we do at <strong>the</strong> universities so that we can prepare students - who will work at <strong>the</strong>se small and
medium-sized companies – that <strong>the</strong>se enterprises can become really serious pillars <strong>of</strong> Hungarian
economy and <strong>the</strong>se companies should mean for us possibilities <strong>of</strong> development in future.
This research was very interesting and useful for us, for companies and for economic experts, too and
we would like to continue our analysis to bring deeper relations into light.
85

References
Andrea Bencsik et al.
Antal-Mokos Z., Balaton, K., Drótos, Gy. and Tari, E. (2000). Stratégia és szervezet. Budapest: KJK-KERSZÖV
Jogi és Üzleti Kiadó.
Bakacsi, Gy., Bokor, A., Császár, Cs., Gelei, A., Kováts K. and Takács, S. (2004). Stratégiai emberi erőforrás
menedzsment. Budapest: KJK- KERSZÖV Jogi és Üzleti Kiadó Kft.
Bencsik, A (2009). A tudásmenedzsment emberi oldala. Miskolc: Z-Press Kiadó.
Csath, M. (2008). Globalizációs végjáték. Budapest: Kairosz Kiadó.
Davenport, T. and Prusak, L. (2001). Tudásmenedzsment. Budapest: Kossuth Kiadó.
Dinya, L. (2005). Szervezetek sikere és válsága. Budapest: Akadémia Kiadó.
Farkas, F. (2003). The Role <strong>of</strong> Leadership in Knowledge Management and Knowledge Transfer In: Knowledge
Transfer Small and Mediumsized Enterprises and Regional Development in Hungary Szeged
Kocsis, É. and Szabó, K. (2000). A posztmodern vállalat. Budapest: Oktatási Minisztérium.
Mészáros, T., Bálint, A. (2003). The Vision <strong>of</strong> Hungarian Small and MediumSized Enterprises In: Lengyel I.
(2003) Knowledge Transfer Small and Medium Sized Enterprises Development in Hungary JATEPress
Szeged
Nonaka, I., Toyama, R. and Byosiere, P. (2001). A <strong>the</strong>ory <strong>of</strong> organizational knowledge creation: Understanding
<strong>the</strong> dynamic process <strong>of</strong> creating knowledge In: Handbook <strong>of</strong> organizational learning & knowledge. New
York: Oxford University Press. pp. 491- 517.
Prahalad, C. K. and Hamel, G. (1990). The core competence <strong>of</strong> <strong>the</strong> corporation. Harvard Business Review, No.
3. pp. 79-91.
Reinhardt, R., Bornemann, M., Pawlowsky, P. and Schneide, U. (2001). Intellectual capital and knowledge
management: Perspectives on measuring knowledge In: Handbook <strong>of</strong> organizational learning & knowledge.
New York: Oxford University Press. pp. 794-820.
Sajtos, L. and Mitev, A. (2007). SPSS kutatási és adatelemzési kézikönyv. Budapest: Alinea. Salamonné H. A.
(2000). Jövőkép és stratégiaalkotás. Budapest: Kossuth Kiadó.
Sveiby, K. E. (2001). Szervezetek új gazdagsága: a menedzselt tudás. Budapest: KJK- KERSZÖV Jogi és Üzleti
Kiadó Kft.
86

Relation Between Organizational Learning and
Organizational Commitment: Case Study <strong>of</strong> a Private Bank
in North Cyprus
Ayşen Berberoğlu and Emine Ünar
Cyprus International University, Cyprus
aysen_umut@hotmail.com
Abstract: The aim <strong>of</strong> this paper is to assess <strong>the</strong> level <strong>of</strong> perceived organizational learning (being a learning
organization) and organizational commitment and to state whe<strong>the</strong>r <strong>the</strong>re is a statistically meaningful relationship
between <strong>the</strong>se two concepts within <strong>the</strong> case. The research questions for this case study are as follows: Q1: What
is <strong>the</strong> level <strong>of</strong> perceived organizational learning and organizational commitment? Q2: Is <strong>the</strong>re a relationship
between organizational learning and organizational commitment? The population <strong>of</strong> this empirical study was
expected to be around 140 respondents who are workers <strong>of</strong> a medium-size private bank which is trying to be a
learning organization in practice and questionnaire method was used to carry out <strong>the</strong> research. However 140
questionnaires were distributed, only 80 <strong>of</strong> <strong>the</strong>m had returned. The questionnaire was a composition <strong>of</strong>
“Dimensions <strong>of</strong> Learning Organization Questionnaire, (DLOQ)” which is developed by Watkins and Marsick
(1993) and “Organizational Commitment Questionnaire (OCQ)” developed by Meyer, Allen and Smith (1993).
Also includes questions regarding demographic information <strong>of</strong> respondents. The result <strong>of</strong> <strong>the</strong> study showed that
organizational commitment level in <strong>the</strong> organization is moderate and <strong>the</strong> employees can not be precisely grouped
according to <strong>the</strong> types <strong>of</strong> organizational commitment. The findings about organizational learning showed that
employees perceive <strong>the</strong>ir organization as a learning organization. Finally, <strong>the</strong> correlation analysis showed that
<strong>the</strong>re is a positive relationship between organizational commitment and organizational learning in this case.
Keywords: organizational learning, learning organizations, organizational commitment, affective commitment,
continuance commitment, normative commitment
1. Introduction
Knowledge management is an important and <strong>of</strong>ten discussed concept. In this manner, organizational
learning or learning organizations reserve a considerable place in <strong>the</strong> literature. Although <strong>the</strong>re is a
border between individual learning and organizational learning, organizational learning is clearly
mediated by <strong>the</strong> learning <strong>of</strong> individual organizational members (Popper and Lipchitz
2003).Continuously, <strong>the</strong> outcome <strong>of</strong> organizational learning is generally discussed as being positive
(Mullins 2005).
Organizational commitment, which is ano<strong>the</strong>r important concept in <strong>the</strong> field <strong>of</strong> organizational behavior,
is defined in terms <strong>of</strong> <strong>the</strong> strength <strong>of</strong> an individual’s identification with and involvement in a particular
organization. According to Allen and Meyer (1990), <strong>the</strong> three components <strong>of</strong> organizational
commitment are <strong>the</strong> “Affective” (AC), “Continuance” (CC) and “Normative” (NC) commitment where
employees with strong affective commitment remain because <strong>the</strong>y “want to”, those with strong
continuance commitment because <strong>the</strong>y “need to” and those with strong normative commitment
because <strong>the</strong>y feel <strong>the</strong>y “ought to” do so. Society tends to benefit from employees' organizational
commitment in terms <strong>of</strong> lower rates <strong>of</strong> job movement and, perhaps, higher national work productivity
and/or quality (Quirin, Donnelly and O’Bryan, 2001).
The purpose <strong>of</strong> this research is to study <strong>the</strong> level <strong>of</strong> perceived organizational learning and
organizational commitment within a private bank and to find out whe<strong>the</strong>r <strong>the</strong>re is a relationship
between <strong>the</strong>se two important concepts.
2. Literature review
2.1 Organizational learning
In today’s world <strong>of</strong> rapid change both individuals and organizations should be capable <strong>of</strong> learning in
order to adapt to <strong>the</strong>ir environment. Learning means change, but change <strong>of</strong> a relatively permanent
kind (Mullins 2005). According to Senge (1990), learning organizations are easy to implement
because, deep down, we are all learners. Change, learning, and adaptation have all been used to
refer to <strong>the</strong> process by which organizations adjust to <strong>the</strong>ir environment (Fiol and Lyles 1985).
Learning that relates to firms encompasses both processes and outcomes and can be described as
<strong>the</strong> way firms build, supplement and organize knowledge and routines around <strong>the</strong>ir activities
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Ayşen Berberoğlu and Emine Ünar
(Dodgson 1993). Psychological and organizational factors conspire to make organizations and <strong>the</strong>ir
members resist change and miss opportunities to create preferred futures (Edmondson and Moingeon
1998). The factors influencing <strong>the</strong> learning process according to Mullins (2005) are shown in Figure 1
below:
External Factors
Relationships
Rewards and Punishments
Environment
The internal and external factors are
constantly affecting each o<strong>the</strong>r
Internal Processes
Perception
Memory
Motivation
Attitudes
Ability Level
Emotions
Personality
Figure 1: Factors influencing <strong>the</strong> larning process (source: Mullins 2005)
In <strong>the</strong> literature <strong>the</strong>re are three important types <strong>of</strong> learning:
1-Single-Loop
2- Double-Loop
3- Triple-Loop
According to Lassey (1998), single loop learning is where <strong>the</strong> collective learning causes changes in
<strong>the</strong> rules that govern action for organization; whereas double loop learning is <strong>the</strong> stage where
collective learning causes changes to <strong>the</strong> insights which determine <strong>the</strong> rules. In triple loop learning,
which was developed by Swieringa and Wierdsma (1992) expanded as a fur<strong>the</strong>r level <strong>of</strong> learning after
single and double loop, collective learning causes changes in <strong>the</strong> principles upon which <strong>the</strong>
organization was founded. According to Argyris (1999), it is possible to divide <strong>the</strong> literature into two
main categories: <strong>the</strong> practice oriented and prescriptive literature <strong>of</strong> “<strong>the</strong> learning organization”
promulgated mainly by consultants and practitioners and predominantly skeptical scholarly literature
<strong>of</strong> “organizational learning” produced by academics.
Organizational Learning can be described as <strong>the</strong> ways firms build, supplement and organize
knowledge and routines around <strong>the</strong>ir activities and within <strong>the</strong>ir cultures, and adapt and develop
organizational efficiency by improving <strong>the</strong> use <strong>of</strong> broad skills <strong>of</strong> <strong>the</strong>ir workforces (Dodgson 1993).
Organizational Learning introduces a perspective that learning is not only <strong>the</strong> capability <strong>of</strong> individuals;
learning can also happen on a group level, starting from individual level to organization level (Amiri et
al 2010).
March (1991), in <strong>the</strong>ir studies regarding organizational learning, stated that <strong>the</strong> problem <strong>of</strong> balancing
exploration and exploitation is very important. Exploration included things captured by terms such as
search, variation, risk taking, experimentation, play, flexibility, discovery, innovation whereas
exploitation included such things as refinement, choice, production, efficiency, selection,
implementation, execution. According to March (1991), adaptive systems that engage in exploration
to <strong>the</strong> exclusion <strong>of</strong> exploitation are likely to find that <strong>the</strong>y suffer <strong>the</strong> costs <strong>of</strong> experimentation without
gaining many <strong>of</strong> its benefits whereas systems that engage in exploitation to <strong>the</strong> exclusion <strong>of</strong>
exploration are likely to find <strong>the</strong>mselves trapped in suboptimal stable equilibria. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong>
concept <strong>of</strong> learning organizations also became an important concept in management literature.
According to Greenberg (2005), Learning Organizations are ones that are successful at acquiring,
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Ayşen Berberoğlu and Emine Ünar
cultivating and applying knowledge that can be used to help it adapt to change. Regarding this,
Managers should establish a commitment to change, adopt an informal organizational culture and
develop an open organizational culture. According to Senge (1990), disciplines <strong>of</strong> learning
organizations can be grouped as five “competent technologies”. Senge lists <strong>the</strong>m as 1.Systems
thinking, 2.Personal Mastery, 3. Mental Model, 4. Building shared vision and 5. Team learning. Senge
advocated that <strong>the</strong>se disciplines should develop toge<strong>the</strong>r and systems thinking should be <strong>the</strong> fifth
discipline.
2.2 Organizational commitment
Organizational commitment is defined in terms <strong>of</strong> <strong>the</strong> strength <strong>of</strong> an individual’s identification with and
involvement in a particular organization and attitudinal commitment can generally be characterized by
at least three factors: (1) a strong belief in and acceptance <strong>of</strong> <strong>the</strong> organization’s goals and values; (2)
a willingness to exert considerable effort on behalf <strong>of</strong> <strong>the</strong> organization; and (3) a definite desire to
maintain organizational membership (Porter, Steers and Boulian, 1974:606). Although organizational
commitment has several conceptualizations in <strong>the</strong> literature, <strong>the</strong> popular concept were made by Allen
& Meyer as <strong>the</strong> three components <strong>of</strong> organizational commitment which are <strong>the</strong> “Affective” (AC),
“Continuance” (CC) and “Normative” (NC) commitment. Employees with strong affective commitment
remain because <strong>the</strong>y “want to”, those with strong continuance commitment because <strong>the</strong>y “need to”
and those with strong normative commitment because <strong>the</strong>y feel <strong>the</strong>y “ought to” do so (Allen and
Meyer 1990). These are <strong>the</strong> components <strong>of</strong> organizational commitment ra<strong>the</strong>r than types because an
employee’s relationship with an organization might reflect varying degrees <strong>of</strong> all three like an
employee might feel both a strong attachment to an organization and a sense <strong>of</strong> obligation to remain
(Meyer and Allen 1997).
The three dimensional concept <strong>of</strong> organizational commitment determined by Allen & Meyer, refers to
<strong>the</strong> affective commitment, continuance commitment and normative commitment. Affective,
continuance and normative commitment are best viewed as distinguishable components, ra<strong>the</strong>r than
types, <strong>of</strong> attitudinal commitment; that is employees can experience each <strong>of</strong> <strong>the</strong>se psychological states
to varying degrees (Allen and Meyer 1990).
Affective commitment stands for <strong>the</strong> emotional commitment <strong>of</strong> <strong>the</strong> individuals and how <strong>the</strong>y cling to
<strong>the</strong> organizational objects and <strong>the</strong>y become one with <strong>the</strong>m. It reflects <strong>the</strong> employee’s emotional
commitment to <strong>the</strong> organization and how <strong>the</strong>y integrate with it (İnce and Gül, 2005). The
representative feelings <strong>of</strong> an employee bearing affective commitment were presented as; “I would be
very happy to spend <strong>the</strong> rest <strong>of</strong> my career with this organization”, “I feel a strong sense <strong>of</strong> belonging
to my organization” and “This organization has a great deal <strong>of</strong> personal meaning for me” (Francesco
and Gold 2005).
Continuance commitment refers to <strong>the</strong> strength <strong>of</strong> a person’s desire to remain working for an
organization due to his or her belief that it may be costly to leave, because <strong>the</strong> longer people remain
in <strong>the</strong>ir organizations, <strong>the</strong> more <strong>the</strong>y stand to lose what <strong>the</strong>y have invested in <strong>the</strong> organization over
<strong>the</strong> years; for example retirement plans or <strong>the</strong> close friendships (Greenberg 2005).Continuance
commitment was expected to develop in response to conditions (e.g., side bets*) that increase <strong>the</strong>
cost <strong>of</strong> leaving, whereas affective commitment was expected to be particularly sensitive to work
experiences (e.g., job scope; organizational support) (Powell and Meyer 2004).
Normative commitment refers to <strong>the</strong> employees’ feelings <strong>of</strong> obligation to stay with <strong>the</strong> organization
because <strong>of</strong> pressures from o<strong>the</strong>rs and people who have high degrees <strong>of</strong> normative commitment are
greatly concerned about what o<strong>the</strong>r would think <strong>of</strong> <strong>the</strong>m for leaving (Greenberg, 2005). Employees
with normative commitment stay with <strong>the</strong> organization because <strong>the</strong>y feel <strong>the</strong>y should and <strong>the</strong>y have
feelings <strong>of</strong> “I would feel guilty to leave my organization”, “Even if it to my advantage I do not feel it
would be right to leave my organization right now” and “I would not leave my organization right now
because I have a sense <strong>of</strong> obligation to <strong>the</strong> people in it” (Francesco and Gold 2005).
3. Methodology, analysis and findings
3.1 Methodology <strong>of</strong> research
To achieve <strong>the</strong> aim <strong>of</strong> <strong>the</strong> study, survey method was used and <strong>the</strong> collected data was analyzed by
using Statistical Package for Social Sciences (SPSS) version 16.0. In total, 140 questionnaires were
89

Ayşen Berberoğlu and Emine Ünar
distributed and 83 had returned. The answers were analyzed using Descriptives and Correlation Test
to measure <strong>the</strong> level <strong>of</strong> perceived organizational learning and also organizational commitment and
<strong>the</strong>n to find out whe<strong>the</strong>r <strong>the</strong>re is a relationship between <strong>the</strong>se two concepts. A positive methodological
approach was adopted in interpreting <strong>the</strong> findings.
3.2 Population <strong>of</strong> research
The sample <strong>of</strong> <strong>the</strong> research was taken from <strong>the</strong> population <strong>of</strong> a private bank in North Cyprus. The
bank has currently 140 people employed. For <strong>the</strong> research, 140 questionnaires were distributed and
83 <strong>of</strong> <strong>the</strong>m had returned.
3.3 Instrumentation <strong>of</strong> research
The questionnaire was a composition <strong>of</strong> “Dimensions <strong>of</strong> Learning Organization Questionnaire,
(DLOQ)” which is developed by Watkins and Marsick (1993), a condensed version including 21
questions, and “Organizational Commitment Questionnaire (OCQ)” developed by Meyer, Allen and
Smith (1993). The questionnaire was made up <strong>of</strong> three parts. In <strong>the</strong> first part, <strong>the</strong> demographic
information <strong>of</strong> <strong>the</strong> respondents were asked, like gender, educational background and working time.
The second part <strong>of</strong> <strong>the</strong> questionnaire consisted <strong>of</strong> <strong>the</strong> questions for measuring perceived
organizational learning, separated on basis <strong>of</strong> individual learning, team or group learning and
organizational learning. The last part <strong>of</strong> <strong>the</strong> questionnaire included <strong>the</strong> questions regarding <strong>the</strong> level <strong>of</strong>
organizational commitment and <strong>the</strong>y are grouped as affective, continuance and normative
respectively. A three level scale was used to measure <strong>the</strong> answers; 1-Agree, 2-Undecided and 3-
Disagree. The questionnaire was translated into Turkish to get <strong>the</strong> best answers from respondents.
3.4 Demographic information
The questionnaire <strong>of</strong> <strong>the</strong> research was made up <strong>of</strong> three parts. First part is <strong>the</strong> questions regarding
demographic information <strong>of</strong> <strong>the</strong> employees, second part was <strong>the</strong> questions assessing <strong>the</strong> perceived
organizational learning and third part was <strong>the</strong> questions regarding organizational commitment. The
first part <strong>of</strong> <strong>the</strong> questionnaire is analyzed below in <strong>the</strong> frequency tables. As can be seen in Table 1,
57.8% <strong>of</strong> <strong>the</strong> respondents were female and <strong>the</strong> remaining 42.2% were male workers.
Table 1: Frequencies <strong>of</strong> gender
Valid
Frequency Percent Valid Percent Cumulative Percent
Female 48 57,8 57,8 57,8
Male 35 42,2 42,2 100,0
Total 83 100,0 100,0
According to Table 2, Frequencies <strong>of</strong> Educational Level, half <strong>of</strong> <strong>the</strong> respondents were high school
graduates (53.0%) and among <strong>the</strong> remaining majority were university graduates with a Bachelor
Degree (28.9%).
Table 2: Frequencies <strong>of</strong> educational level
Valid
Frequency Percent Valid Percent Cumulative Percent
Masters Degree 5 6,0 6,0 6,0
Bachelor Degree 24 28,9 28,9 34,9
High School 44 53,0 53,0 88,0
O<strong>the</strong>r 10 12,0 12,0 100,0
Total 83 100,0 100,0
Lastly, Table 3 shows <strong>the</strong> status and work time <strong>of</strong> <strong>the</strong> respondents. The majority <strong>of</strong> <strong>the</strong> respondents
were clerks who are working in this bank for between 2-10 years. Also among <strong>the</strong> respondents 8 <strong>of</strong>
<strong>the</strong>m were assistant supervisors working between 10-19 years and 8 <strong>of</strong> <strong>the</strong>m were supervisors with
<strong>the</strong> same working time.
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Ayşen Berberoğlu and Emine Ünar
Table 3: Cross tabs for status and work time <strong>of</strong> respondents
Work Time
Manager Supervisor
Status
Assistant
Supervisor Clerk O<strong>the</strong>r
Less than 2 years 1 0 1 7 1 10
Between 2-10 years 1 2 7 28 8 46
Between 10-19 Years 2 9 8 3 1 23
More than 20 years 1 3 0 0 0 4
Total 5 14 16 38 10 83
3.5 Analysis and findings <strong>of</strong> research questions
The first research question <strong>of</strong> <strong>the</strong> study was regarding <strong>the</strong> level <strong>of</strong> perceived organizational learning
and organizational commitment.
Firstly <strong>the</strong> level <strong>of</strong> Affective, Continuance and Normative Commitment was measured individually.
According to <strong>the</strong> descriptive statistics in Table 4, <strong>the</strong> employees <strong>of</strong> this organization have a tendency
toward being undecided. So it will not be feasible to group <strong>the</strong> employees according to <strong>the</strong>ir
commitments.
Table 4: Descriptive statistics for affective, continuance and normative commitment
N Minimum Maximum Mean Std. Deviation
Aff. Com. 76 1,00 2,33 1,7456 ,32600
Con. Com. 73 1,00 3,00 1,8721 ,43525
Nor. Com. 76 1,00 2,67 1,7456 ,38727
Valid N (listwise) 68
Continously, <strong>the</strong> overall level organizational commitment is shown in <strong>the</strong> Table 5 below.
Table 5: Descriptive statistics for organizatinal commitment
N Minimum Maximum Mean Std. Deviation
OC 68 1,06 2,44 1,8039 ,27326
Valid N (listwise) 68
Table 5 also shows that <strong>the</strong> employees have stated that <strong>the</strong>y are undecided, so in general
organizational commitment level is moderate in this case.
Secondly, <strong>the</strong> level <strong>of</strong> organizational learning based on individual, team and organizational learning
was analyzed separately.
In Table 6, it can be seen that <strong>the</strong> mean <strong>of</strong> each learning variable is below <strong>the</strong> average and resulting
from this, <strong>the</strong> level <strong>of</strong> being a learning organization is relatively tend to be high according to <strong>the</strong>
answers <strong>of</strong> respondents.
Table 6: Descriptive statistics
N Minimum Maximum Mean Std. Deviation
Ind. Learn 78 1,00 3,00 1,6923 ,50757
Team Learn 80 1,00 3,00 1,7125 ,55814
Org. Learn 76 1,00 3,00 1,6974 ,50270
Valid N (listwise) 74
Also Table 7 shows that employees perceive <strong>the</strong>ir organization as a learning organization.
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Table 7: Descriptive statistics
Ayşen Berberoğlu and Emine Ünar
N Minimum Maximum Mean Std. Deviation
OL 74 1,00 2,83 1,6914 ,44909
Valid N (listwise) 74
The second research question for <strong>the</strong> study was whe<strong>the</strong>r <strong>the</strong>re is a relationship between
organizational learning and organizational commitment. Correlation analysis was used to determine
this relationship.
According to Table 8, <strong>the</strong>re is a positive relationship between <strong>the</strong>se two concepts regarding <strong>the</strong> case
(Pearson correlation: 0.277). Also this relationship is found to be statistically significant (sig: 0.026 <
0.05). S
Table 8: Correlation organizational learning and organizational commitment
OL
OC
OL OC
Pearson Correlation 1 ,277 *
Sig. (2-tailed) ,026
N 74 64
Pearson Correlation ,277 * 1
Sig. (2-tailed) ,026
N 64 68
*. Correlation is significant at <strong>the</strong> 0.05 level (2-tailed).
4. Conclusions
The study has tried to provide empirical findings about <strong>the</strong> current situation <strong>of</strong> <strong>the</strong> private bank
regarding perceived organizational learning and organizational commitment. The findings <strong>of</strong> <strong>the</strong>
research pointed out that <strong>the</strong> employees <strong>of</strong> this private bank have <strong>the</strong> organizational commitment on a
moderate level and it is not feasible to group <strong>the</strong>m according to a type organizational commitment. As
can be seen in Table 4, <strong>the</strong> workers in this bank have 1,74 and 1,87 mean points on a three-item
scale which can be interpreted as “undecided”. An interesting point is that none <strong>of</strong> <strong>the</strong> participants
have selected point 3 “Disagree” for questions <strong>of</strong> affective and normative commitment which shows
us participants are closer to being affectively or normatively committed in this situation. Overall
descriptive statistics for Organizational Commitment in Table 5, contains 1,8 mean points which can
be interpreted as <strong>the</strong> level <strong>of</strong> commitment is moderate. Continuously, in Table 6, descriptive statistics
showed that each <strong>of</strong> <strong>the</strong> three concepts <strong>of</strong> organizational learning have a mean score below average
so can be considered as “undecided”. Fur<strong>the</strong>rmore, <strong>the</strong> perceived level <strong>of</strong> organizational learning, in
o<strong>the</strong>r words perceived level <strong>of</strong> being a learning organization, is again below <strong>the</strong> average. Finally, <strong>the</strong>
correlation analysis was applied and results stated that <strong>the</strong>re is a positive relationship between
organizational learning and organizational commitment, however without a cause-result relationship in
current situation.
5. Suggestions
Today’s organizations are living in a rapidly changing environment. To cope with change,
organizations should have more and more knowledge, thus <strong>the</strong>y need to learn continuously. To learn
continuously, organizations should ensure an effective learning environment and culture that facilitate
<strong>the</strong>ir members learning opportunities. Suggestion for <strong>the</strong> banks may be evaluating <strong>the</strong>ir human
resources in terms <strong>of</strong> <strong>the</strong>ir availability for building a learning environment. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong>y
should evaluate <strong>the</strong>ir actual cultures, working environments. To fully understand work-related
attitudes, we must focus on people’s attitudes towards work, commitments to <strong>the</strong>ir organizations
(Greenberg 2005). Previous literature showed that, organizational commitment has an important
impact on employee turnover, work performance, work attendance and stress. The suggestion that
can be made to develop organizational commitment within <strong>the</strong> banks can be to practice human
resource management activities which exert influence on employees’ organizational commitment and
lead <strong>the</strong>m to stay with <strong>the</strong> organization for a longer period <strong>of</strong> time, regarding <strong>the</strong> positive relation
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Ayşen Berberoğlu and Emine Ünar
between commitment and work time. Also, have <strong>the</strong>ir employees emotionally committed to <strong>the</strong>ir
organizations by using positive encouragements.
References
Allen N. J. and Meyer J. P. (1990) “The Measurement and Antecedents <strong>of</strong> Affective, Normative and Continuance
Commitment to <strong>the</strong> Organization” Journal <strong>of</strong> Occupational and Organizational Psychology Vol:63, pp1-18.
Amiri A. N., Jandghi G., Alvani S. M., Hosnavi R. and Ramezan M. (2010) “Increasing <strong>the</strong> Intellectual Capital in
Organization: Examining <strong>the</strong> Role <strong>of</strong> Organizational Learning” <strong>European</strong> Journal <strong>of</strong> Social Sciences, Vol. 14
No.1, pp98-108
Argyris C. (1999) “On Organizational Learning” Wiley-Blackwell, Oxford
Dodgson M. (1993) “Organizational Learning: A Review <strong>of</strong> Some Literature”, Organization Studies, Vol: 14 No: 3,
pp 375-394.
Edmondson A. and Moingeon B. (1998) “From Organizational Learning to Learning Organization” Management
Learning, Vol. 29 No.1, pp. 5-20
Fiol C. M. And Lyles M. A. (1985) “Organizational Learning”, The Academy <strong>of</strong> Management Review, Vol. 10, No.
4. pp. 803-813.
Francesco A. M. and Gold B. A. (2005) “International Organizational Behaviour 2n Ed.” Pearson Prentice Hall
Greenberg J. (2005) “Managing Behavior in Organizations” Pearson Education, New Jersey
İnce M. and Gül H. (2005) “Yönetimde Yeni Bir Paradigma: Örgütsel Bağlılık” Çizgi Kitabevi Yayınları
Lassey P. (1998) “Developing a Learning Organization” Kogan Page Publishers, London
March J. G. (1991) “Exploration and Exploitation in Organizational Learning” Organization Science, Vol.2 No.1
pp.71-87
Meyer John P. And Allen Natalie J. (1997) “Commitment in <strong>the</strong> Workplace: Theory, Research and Application”
Sage Publications
Meyer J. P. and Allen N. J. And Smith C.A. (1993) “Commitment to Occupations: Extension and Test <strong>of</strong> A Three
Component Conceptualization” Journal <strong>of</strong> Applied Psychology, Vol: 78, pp 538-551.
Mullins, L. J. (2005) “Management and Organizational Behavior”, 7 th ed., Pearson Education, Essex.
Popper M. and Lipshitz R. (2003) “Organizational Learning: Mechanisms, Culture, and Feasibility”, Essential
Readings in Management Learning, Sage Publications, London, pp 37-52.
Powell D. M. And Meyer J. P. (2004)“Side-Bet Theory and <strong>the</strong> Three Component Model <strong>of</strong> Organizatiional
Commitment” Journal <strong>of</strong> Vocational Behaviour Vol:65, pp:157-177
Porter L.W., Steers R. M. And Boulian P.V. (1974) “Organizational Commitment, Job Satisfaction and Turnover
Among Psychiatric Technicians” Journal <strong>of</strong> Applied Psychology Vol: 59, pp603-609
Quirin J. J. Donnelly D. P. And O'Bryan D. (2001) “Antecedents <strong>of</strong> Organizational Commitment: The Role <strong>of</strong>
Perception <strong>of</strong> Equity” Advances in Accounting Behavioural Research, Vol:4, pp261-280.
Senge, P. (1990) “The Fifth Discipline. The art and practice <strong>of</strong> <strong>the</strong> learning organization”, London: Random
House.
Swieringa J. and Wierdsma A. F. M. (1992) “Becoming a LEARNİNG Organization: Beyond <strong>the</strong> Learning Curve”
Addison-Wesley, Reading
Watkins, K. E., & Marsick, V. J. (1999). “Dimensions <strong>of</strong> <strong>the</strong> Learning Organization Questionnaire” [Online],
http://www.partnersforlearning.com/questions2.asp
93

Knowledge Dynamics Modeling Using Analytic Hierarchy
Process (AHP)
Constantin Bratianu, Adriana Agapie, and Ivona Orzea
Academy <strong>of</strong> Economic Studies, Bucharest, Romania
cbratianu@yahoo.com
adriana.agapie@clicknet.ro
ivona.orzea@gmail.com
Abstract: The purpose <strong>of</strong> this paper is to present a new perspective in modeling knowledge dynamics <strong>of</strong> <strong>the</strong>
human capital by using <strong>the</strong> Analytic Hierarchy Process (AHP). The <strong>the</strong>oretical approach is based on <strong>the</strong> dynamic
equilibrium equation <strong>of</strong> <strong>the</strong> level <strong>of</strong> organizational knowledge, and on <strong>the</strong> AHP ma<strong>the</strong>matical model developed by
Saaty. The dynamic equilibrium equation is derived for a time interval ∆T, and contains <strong>the</strong> following terms: <strong>the</strong>
level <strong>of</strong> total organizational knowledge variation ∆K in <strong>the</strong> time interval ∆T, <strong>the</strong> knowledge creation variation ∆Cr
in <strong>the</strong> time interval ∆T, <strong>the</strong> knowledge acquisition ∆A variation in <strong>the</strong> time interval ∆T, and <strong>the</strong> knowledge loss
variation ∆L in <strong>the</strong> time interval ∆T. Since each <strong>of</strong> <strong>the</strong>se terms has a different relative importance in <strong>the</strong>
organizational knowledge balance, it is necessary to find a way <strong>of</strong> evaluating <strong>the</strong>ir weighting factors. For this
purpose we use <strong>the</strong> AHP ma<strong>the</strong>matical model since it allows us a structuring <strong>of</strong> knowledge dynamics on <strong>the</strong> main
components <strong>of</strong> <strong>the</strong> equilibrium equation. For <strong>the</strong> present research we considered a structure composed <strong>of</strong> three
levels: (1) <strong>the</strong> goal level – increasing <strong>the</strong> level <strong>of</strong> organizational knowledge; (2) <strong>the</strong> criteria or strategies level –
<strong>the</strong> strategy for increasing knowledge creation (C1), <strong>the</strong> strategy for increasing acquisition <strong>of</strong> new knowledge
(C2), and <strong>the</strong> strategy for reducing knowledge loss (C3); (3) <strong>the</strong> activities level – hiring new valuable human
resources (A1), developing training programs (A2), creating a performing motivation <strong>of</strong> employees (A3), and
purchasing books, journals, s<strong>of</strong>tware programs, and o<strong>the</strong>r information materials (A4). This structured model <strong>of</strong>
AHP has been applied as an empirical research within a large company. We sent questionnaire to a number <strong>of</strong>
500 employees, and received valid answers from 173 respondents. The method is based on paired comparisons
<strong>of</strong> strategies with respect to <strong>the</strong> goal <strong>of</strong> increasing <strong>the</strong> level organizational knowledge, and <strong>the</strong>n on paired
comparisons <strong>of</strong> activities with respect to each strategy we defined. These paired comparisons yield matrices that
lead to systems <strong>of</strong> linear equations. Actually we get an eigenvalue problem whose solution is <strong>the</strong> vector <strong>of</strong>
priorities for strategies, and <strong>the</strong>n for activities with respect to each strategy. Values <strong>of</strong> <strong>the</strong> vector <strong>of</strong> priorities for
strategies are <strong>the</strong> weighting factors for <strong>the</strong> equilibrium equation components. The new model we propose proved
valuable in understanding much better <strong>the</strong> knowledge dynamics, as <strong>the</strong> main component <strong>of</strong> <strong>the</strong> intellectual capital
<strong>of</strong> a company.
Keywords: analytic hierarchy process, knowledge acquisition, knowledge creation, knowledge dynamics,
knowledge loss
1. Introduction
Knowledge dynamics is a very complex and multidimensional process. It can be defined and studied
at <strong>the</strong> individual, group, or organizational level. Knowledge dynamics refers to <strong>the</strong> time rate <strong>of</strong> change
<strong>of</strong> knowledge fields (Bratianu & Andriessen, 2008), under <strong>the</strong> action <strong>of</strong> organizational integrators
(Bratianu, 2008). The main processes which can be integrated into <strong>the</strong> complex process <strong>of</strong> knowledge
dynamics are <strong>the</strong> following: knowledge creation, knowledge acquisition, knowledge loss, knowledge
sharing, knowledge storage and retrieval, knowledge diffusion, conversion from one form <strong>of</strong>
knowledge into ano<strong>the</strong>r form <strong>of</strong> knowledge, and organizational learning (Geisler & Wickramasinghe,
2009; Hawryszkiewycz, 2010; Lak<strong>of</strong>f & Johnson, 1999; Nonaka & Takeuchi, 1995; Nonaka, Toyama
& Hirata, 2008; Ortenblad, 2001; Pinker, 2007; Szulansky, 1996). Due to complexity <strong>of</strong> integrating
toge<strong>the</strong>r all <strong>of</strong> <strong>the</strong>se processes, many researchers developed models for individual processes, like
knowledge creation, knowledge sharing and so on. One <strong>of</strong> <strong>the</strong> first comprehensive knowledge
dynamics models able to deal with several processes is that created by Nonaka and his co-workers
(Nonaka, 1994; Nonaka & Takeuchi, 1995; Nonaka, 1998; Nonaka, Konno & Toyama, 1998; Nonaka,
Toyama & Byosiere, 2001). This model has been developed progressively and it is one <strong>of</strong> <strong>the</strong> most
cited model in <strong>the</strong> literature.
The purpose <strong>of</strong> this paper is to present a new perspective in modeling knowledge dynamics <strong>of</strong> <strong>the</strong>
human capital by using <strong>the</strong> Analytic Hierarchy Process (AHP). The research approach is both
<strong>the</strong>oretical and empirical. The <strong>the</strong>oretical approach is based on <strong>the</strong> dynamic equilibrium equation <strong>of</strong>
<strong>the</strong> level <strong>of</strong> organizational knowledge, and on <strong>the</strong> AHP ma<strong>the</strong>matical model developed by Saaty
(1994, 2009).
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2. Knowledge dynamics models
Constantin Bratianu et al.
We shall describe firstly <strong>the</strong> most known knowledge dynamics model elaborated by Nonaka and his
co-workers. The model covers two individual processes <strong>of</strong> knowledge conversion, and two
organizational processes <strong>of</strong> knowledge sharing. It is structured on three layers: knowledge assets, <strong>the</strong>
Ba platform, and <strong>the</strong> SECI conversion structure. These three layers interact one to each o<strong>the</strong>r
generating <strong>the</strong> knowledge spiral. The knowledge assets layer generates <strong>the</strong> inputs for <strong>the</strong> o<strong>the</strong>r layers
and receives <strong>the</strong>ir outputs. It is <strong>the</strong> controlling process layer. The Ba platform is <strong>the</strong> dynamic context
<strong>of</strong> knowledge creation. The SECI (Socialization-Externalization-Combination-Internalization) layer
constitutes <strong>the</strong> engine <strong>of</strong> knowledge creation in <strong>the</strong> virtual space determined by <strong>the</strong> epistemological
and ontological dimensions. The whole model is based on <strong>the</strong> two knowledge forms: tacit knowledge
and explicit knowledge. Socialization is <strong>the</strong> process <strong>of</strong> transferring tacit knowledge through social
interaction. Tacit knowledge sharing meets several individual and organizational barriers, among
<strong>the</strong>m stickiness being <strong>the</strong> most important (Szulansky, 1996; Szulansky & Jensen, 2004).
Externalization is <strong>the</strong> process <strong>of</strong> conversion tacit knowledge into explicit knowledge. It is an individual
process. The effectiveness <strong>of</strong> this process depends on <strong>the</strong> intelligent use <strong>of</strong> metaphors, analogies and
cognitive models (Andriessen, 2006, 2008; Lak<strong>of</strong>f & Johson, 1999; Pinker, 2007). Combination is <strong>the</strong>
process <strong>of</strong> transfering explicit knowledge through social interaction. Internalization is <strong>the</strong> process <strong>of</strong>
structuring <strong>the</strong> explicit knowledge as tacit knowledge. It is an individual process, reciprocating in a
way <strong>the</strong> process <strong>of</strong> externalization. Internalization is very close to learning-by-doing. The foundation <strong>of</strong>
<strong>the</strong> SECI model for knowledge conversion is Ba, a Japanese concept that can be translated
approximately by “place”. Nonaka et all. (2001, p.499) define Ba “as a context in which knowledge is
shared, created, and utilized, in recognition <strong>of</strong> <strong>the</strong> fact that knowledge needs a context in order to
exists”. Knowledge held by a person can be shared, re-created, and enriched only when that person
is active in Ba. We may say briefly that Ba is a dynamic context <strong>of</strong> interactions between individuals, or
between an individual and his environment. The Nonaka’s model <strong>of</strong> knowledge dynamics is an
important contribution to <strong>the</strong> field <strong>of</strong> organizational knowledge dynamics. However, <strong>the</strong>re are some
inherent limitations we have to be aware <strong>of</strong> when using this model in practice (Bratianu, 2010;
Gourlay, 2006; Nissen, 2006).
Nissen (2006) developed <strong>the</strong> knowledge flows model for <strong>the</strong> organizational knowledge dynamics.
Nissen expended practically <strong>the</strong> Nonaka’s model into a three dimensional framework, and including
time as an independent fourth dimension. He introduces two new concepts: life cycle and flow time.
Both <strong>of</strong> <strong>the</strong>m helps Nissen to explore <strong>the</strong> variation <strong>of</strong> knowledge in time. The extended model
proposed by Nissen brings in new dimensions and extended possibilities <strong>of</strong> analyzing knowledge
dynamics. Ano<strong>the</strong>r extension <strong>of</strong> <strong>the</strong> Nonaka’s model has been performed by a group <strong>of</strong> researchers
formed <strong>of</strong>: Gregorio Martin de Castro, Pedro Lopez Saez, Jose Emilio Navas Lopez and Raquel
Galindo Dorado (2007). They considered knowledge dynamics in both epistemological and
ontological dimensions, at four distinct levels: individual, group, organizational and interorganizational.
The name <strong>of</strong> <strong>the</strong> model is EO-SECI, and it comes from: E - epistemological dimension, O –
ontological dimension, S – socialization, E – externalization, C – combination, I – internalization. The
main characteristics <strong>of</strong> this extended model are <strong>the</strong> following: (a) keeping <strong>the</strong> four processes from
Nonaka’s model; (b) knowledge develops along <strong>the</strong> ontological dimension from one phase to ano<strong>the</strong>r,
without intermediate transformation; (c) considering two simultaneous adjacent streams <strong>of</strong> knowledge
with respect to <strong>the</strong> main upward stream, reflecting <strong>the</strong> feedforward and feedback <strong>of</strong> <strong>the</strong> whole
process. These two adjacent streams lead to a self-reinforcing loop, which represents a better
description than <strong>the</strong> knowledge spiral from Nonaka’s model.
3. The new knowledge dynamics model based on <strong>the</strong> AHP philosophy
In any organization <strong>the</strong> level <strong>of</strong> total knowledge is changing in time as a result <strong>of</strong> <strong>the</strong> following factors:
(a) knowledge creation inside <strong>the</strong> organization; (b) knowledge acquisition from <strong>the</strong> external
environment; (c) knowledge loss. Knowledge creation has been research both at <strong>the</strong> individual and
organizational levels, most <strong>of</strong> its characteristics being incorporated into <strong>the</strong> models presented above
(Bratianu & Orzea, 2010). Knowledge acquisition has been less explored, although it is an important
way <strong>of</strong> increasing <strong>the</strong> organizational knowledge level. Basically, an organization may buy books,
journals, databases, s<strong>of</strong>tware programs, expertise, patents and many knowledge embedded products.
Knowledge loss is a relatively new issue in knowledge management research. According to DeLong
(2004, p.4), “Leaders will have to address <strong>the</strong> challenges <strong>of</strong> knowledge retention if <strong>the</strong>y hope to avoid
<strong>the</strong> unacceptable costs <strong>of</strong> lost knowledge”. Thus, knowledge retention and knowledge loss reduction
must enter <strong>the</strong> balance <strong>of</strong> organizational knowledge. Knowledge creation and knowledge acquisition
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Constantin Bratianu et al.
will have a positive contribution to <strong>the</strong> level <strong>of</strong> total organizational knowledge, and knowledge loss will
have a negative contribution since it represents a vector crossing <strong>the</strong> organization interface toward
<strong>the</strong> external business environment. The dynamic equilibrium equation for <strong>the</strong> level <strong>of</strong> <strong>the</strong> total
organizational knowledge, developed for a time interval ∆T, is given by:
∆K = Fc(∆Cr) + Fa(∆A) – Fl(∆L) (1)
where: ∆K is <strong>the</strong> knowledge variation in organization during ∆T time; ∆Cr – knowledge creation
variation during ∆T time; ∆A – knowledge acquisition variation during ∆T time; ∆L – knowledge loss
variation during ∆T time; Fc, Fa, Fl – weighting factors for each component <strong>of</strong> equation (1).
The dynamic equilibrium equation for a generic component <strong>of</strong> equation (1), called strategy or criterion
is given by:
∆C = W1(∆A1) + W2(∆A2) + W3(∆A3) + W4(∆A4) (2)
where: ∆C is <strong>the</strong> generic component (i.e. knowledge creation, knowledge acquisition, and knowledge
loss) variation in <strong>the</strong> time interval ∆T; ∆Ai – <strong>the</strong> activity (i) variation in <strong>the</strong> time interval ∆T; Wi – <strong>the</strong>
weighting factor for activity (i).
Thus, <strong>the</strong> level <strong>of</strong> knowledge in organization depends <strong>of</strong> how much new knowledge is creating during
a given time period, how much knowledge is obtained from <strong>the</strong> external environment through different
methods in <strong>the</strong> same time period, and on <strong>the</strong> knowledge loss toward <strong>the</strong> external environment
through people leaving <strong>the</strong> company. People may leave <strong>the</strong> company due to <strong>the</strong>ir retirement age, in
searching for better pr<strong>of</strong>essional and payment opportunities, or being fired. Knowledge sharing is not
contained in equation (1) because it does not contribute to <strong>the</strong> variation <strong>of</strong> maximum level <strong>of</strong>
knowledge in organization. Knowledge sharing is a process by which <strong>the</strong> organizational knowledge
field is homogenized. Thus, knowledge sharing contributes to <strong>the</strong> increase in <strong>the</strong> average level <strong>of</strong>
organizational knowledge through its dissemination, but not to <strong>the</strong> level <strong>of</strong> total quantity <strong>of</strong> knowledge.
The second part <strong>of</strong> <strong>the</strong> ma<strong>the</strong>matical model is based on <strong>the</strong> Saaty’s AHP. The structure we consider
for this research is composed <strong>of</strong> three levels, as shown in fig.1.
Knowledge
creation (C1)
New employees
(A1)
Training
programs (A2)
Increasing
organizational
knowledge
Knowledge
acquisition (C2)
Efficient
motivation (A3)
Figure 1: The knowledge dynamics structure according to AHP method
4. Research methodology
4.1 The AHP philosophy
Knowledge loss
(C3)
Buying
knowledge bases
The philosophy <strong>of</strong> analytic hierarchy processes (AHP) as a tool in decision making resides in
analyzing several alternatives from different points <strong>of</strong> view-referred as criteria. Thus, a hierarchy is
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Constantin Bratianu et al.
built where at <strong>the</strong> top is <strong>the</strong> problem to be taken into consideration, next layer consists in <strong>the</strong> criteria
or strategies to be considered and <strong>the</strong> last layer resides in <strong>the</strong> several alternatives as activities or
actions under discussion. Based on comparative judgments, a positive matrix <strong>of</strong> choices is derived for
<strong>the</strong>se criteria. The ranking importance <strong>of</strong> <strong>the</strong>se criteria is achieved afterwards as a vector <strong>of</strong> priorities,
based on <strong>the</strong> <strong>the</strong>ory <strong>of</strong> eigenvectors.The same procedure is applied for <strong>the</strong> alternatives considered
with respect to every criterion. In <strong>the</strong> syn<strong>the</strong>sis mode, weights beard by <strong>the</strong> criteria are applied to <strong>the</strong>
considered alternatives and lastly, <strong>the</strong> corresponding totals for each alternative are calculated.
The attempt to measure <strong>the</strong> increase in <strong>the</strong> level <strong>of</strong> organizational knowledge within a large company
has as central focus <strong>the</strong> evaluation <strong>of</strong> <strong>the</strong> employee’s perceptions toward four activities: hiring new
valuable human resources (A1), developing training programs (A2), creating a performing motivation
for <strong>the</strong> employees (A3) and purchasing books, journals, s<strong>of</strong>tware programs and o<strong>the</strong>r informative
materials (A4).This evaluation is organized through <strong>the</strong> consideration <strong>of</strong> three criteria, each <strong>of</strong> <strong>the</strong>se
having a certain influence on <strong>the</strong> previously mentioned four activities. Specifically, <strong>the</strong> three criteria
considered are <strong>the</strong> strategy for increasing knowledge creation (C1), <strong>the</strong> strategy <strong>of</strong> increasing
acquisitions <strong>of</strong> new knowledge (C2) and <strong>the</strong> strategy for reducing knowledge loss (C3.) Thus, a tree
level hierarchy is going to be considered as <strong>the</strong> framework in which <strong>the</strong> employee’s perceptions with
respect to <strong>the</strong> goal <strong>of</strong> measuring <strong>the</strong> level <strong>of</strong> organizational knowledge will be numerically quantified.
4.2 The survey
In <strong>the</strong> following it will be presented <strong>the</strong> general form <strong>of</strong> <strong>the</strong> survey considered and one example <strong>of</strong>
answer will be indicated in square brackets. Also, it will be showed how <strong>the</strong> answers were processed.
In <strong>the</strong> first page were asked general information about <strong>the</strong> position <strong>of</strong> <strong>the</strong> respondent in <strong>the</strong>
considered company. The survey’s second page was devoted to <strong>the</strong> determination <strong>of</strong> <strong>the</strong> priority
vectors <strong>of</strong> <strong>the</strong> three chosen criteria in <strong>the</strong> knowledge variation in organization (<strong>the</strong> strategy for
increasing knowledge creation (C1), <strong>the</strong> strategy <strong>of</strong> increasing acquisitions <strong>of</strong> new knowledge (C2) and
<strong>the</strong> strategy for reducing knowledge loss (C3.)). The goal in this research is to increase <strong>the</strong> level <strong>of</strong>
organizational knowledge. The scale considered for this research is from 1 (equally important) to 9
(extremely important). Questions are formulated in comparative terms, as shown below:
1.a) Given <strong>the</strong> goal, what do you think is more important : <strong>the</strong> strategy for increasing knowledge
creation (C1) or <strong>the</strong> strategy <strong>of</strong> increasing acquisitions <strong>of</strong> new knowledge (C2). [C1]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [6]
2.a) Given <strong>the</strong> goal, what do you think is more important : <strong>the</strong> strategy for increasing knowledge
creation (C1) or <strong>the</strong> strategy for reducing knowledge loss (C3.). [C3]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [4]
3.a) Given <strong>the</strong> goal, what do you think is more important: <strong>the</strong> strategy <strong>of</strong> increasing acquisitions <strong>of</strong>
new knowledge (C2) or <strong>the</strong> strategy for reducing knowledge loss (C3.). [C3]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [6]
The survey’s third page was devoted to <strong>the</strong> determination <strong>of</strong> <strong>the</strong> priority vectors <strong>of</strong> <strong>the</strong> alternatives
(hiring new valuable human resources (A1), developing training programs (A2), creating a performing
motivation for <strong>the</strong> employees (A3) and purchasing books, journals, s<strong>of</strong>tware programs and o<strong>the</strong>r
informative materials (A4).) taking into consideration <strong>the</strong> criterions in <strong>the</strong> above level <strong>of</strong> hierarchy. For
<strong>the</strong> first criterion or strategy for increasing knowledge creation (C1), questions were formulated as
follows:
4. a) Given <strong>the</strong> criterion (C1), what do you think is more important: hiring new valuable human
resources (A1) or developing training programs (A2)? [A2]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [8]
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Constantin Bratianu et al.
5. a) Given <strong>the</strong> criterion (C1), what do you think is more important: hiring new valuable human
resources (A1) or creating a performing motivation for <strong>the</strong> employees (A3)? [A3]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [8]
6. a) Given <strong>the</strong> criterion (C1), what do you think is more important: hiring new valuable human
resources (A1) or purchasing books, journals, s<strong>of</strong>tware programs and o<strong>the</strong>r informative materials (A4)
? [A4]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [5]
7. a) Given <strong>the</strong> criterion (C1), what do you think is more important: developing training programs (A2)
or creating a performing motivation for <strong>the</strong> employees (A3) ? [A3]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [7]
8. a) Given <strong>the</strong> criterion (C1), what do you think is more important: developing training programs (A2)
or purchasing books, journals, s<strong>of</strong>tware programs and o<strong>the</strong>r informative materials (A4)? [A2]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one. [5]
9. a) Given <strong>the</strong> criterion (C1), what do you think is more important: developing creating a performing
motivation for <strong>the</strong> employees (A3) or purchasing books, journals, s<strong>of</strong>tware programs and o<strong>the</strong>r
informative materials (A4)? [A3]
b) Please indicate, on a scale from 1 to 9 to what extent you consider your previous choice is more
important than <strong>the</strong> o<strong>the</strong>r one.[8]
Similar questions as those from 4 to 9 are establishing comparisons among alternatives A1 to A4 with
respect to <strong>the</strong> next two criteria, C2 and C3 , so that a total <strong>of</strong> 21 questions are used as a base for
establishing decision matrices associated with one respondent .
4.3 The pairwise comparison matrix for one individual’s answers, vector <strong>of</strong> priorities
and <strong>the</strong> interpretation <strong>of</strong> <strong>the</strong> results obtained in <strong>the</strong> classical framework <strong>of</strong> <strong>the</strong>
AHP
Paired comparison judgments in <strong>the</strong> AHP are applied to pairs <strong>of</strong> homogeneous elements and
summarized in a matrix <strong>of</strong> judgments. Scoring is applied to rank <strong>the</strong> three alternatives in terms <strong>of</strong> each
<strong>of</strong> <strong>the</strong> three criteria considered (Agapie, 2010; Bratianu et all., 2010). Based on this survey, four
matrices <strong>of</strong> judgments are built, for every respondent. First matrix, denoted with C, C=(cij)i,j=1,2,3
,corresponds to <strong>the</strong> comparisons among <strong>the</strong> three criteria(C1, C2 and C3) and it is a positive,
reciprocal one (cij>0, cij=1/cji ,i,j=1,2,3 and i≠j) with ones on <strong>the</strong> main diagonal (cii=1, i=1,2,3). If
criterion C1 is considered to be 6 times more important than criterion C2 <strong>the</strong>n we write C1 > 6 C2 and
we assign c12=5. Thus, <strong>the</strong> matrix <strong>of</strong> judgments-C- is determined assuming values equal to one on <strong>the</strong>
main diagonal and also reversibility <strong>of</strong> <strong>the</strong> preferences-so that if C1 is preferred to C2 at a
corresponding absolute value <strong>of</strong> 6, <strong>the</strong> C2 criterion will be preferred to C1 at an absolute value <strong>of</strong> 1/6,
which is 0.166 (c21=0.166). The next three matrices are corresponding to <strong>the</strong> choices done among <strong>the</strong>
alternatives A1, A2, A3 ,A4 from three points <strong>of</strong> view: <strong>the</strong> strategy for increasing knowledge creation
(C1), <strong>the</strong> strategy <strong>of</strong> increasing acquisitions <strong>of</strong> new knowledge (C2) and <strong>the</strong> strategy for reducing
knowledge loss (C3.).These matrices are denoted C1 A1,A2,A3,A4 and respectively C2 A1,A2,A3,A4 , C3 A1,A2,A3,A4
For all this four matrices, <strong>the</strong> corresponding vector <strong>of</strong> priorities is calculated in an eigenvalue
formulation. The solution is obtained by raising <strong>the</strong> matrix to a sufficiently large power, <strong>the</strong>n summing
over <strong>the</strong> rows and normalizing to obtain <strong>the</strong> priority vector. The process is stopped when <strong>the</strong>
difference between components <strong>of</strong> <strong>the</strong> priority vector obtained at <strong>the</strong> k-th power and at <strong>the</strong> (k+1)
power is less than some predetermined small value. The vector <strong>of</strong> priorities is <strong>the</strong> derived scale
associated with <strong>the</strong> matrix <strong>of</strong> comparisons (Saaty,1994; Saaty, 2009; Saaty & Louis, 2001). After
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Constantin Bratianu et al.
setting priorities for <strong>the</strong> criteria, pair wise comparisons are also made ratings <strong>the</strong>mselves to set
priorities for <strong>the</strong>m under each criterion and dividing each <strong>of</strong> <strong>the</strong>ir priorities by <strong>the</strong> largest rated intensity
to get <strong>the</strong> ideal intensity. Finally, alternatives are scored by checking <strong>of</strong>f <strong>the</strong>ir respective ratings under
each criterion and summing <strong>the</strong>se ratings for all criteria. For <strong>the</strong> example considered in <strong>the</strong> section
above, <strong>the</strong> first two pairwise comparison matrices are given in Tables 1 and 2.
Table 1: The pairwise comparison matrix C
Absolute judgments amongst criteria C1 C2 C3
C1 1 6 0.25
C2 0.166 1 0.166
C3 4 6 1
A1,A2,A3,A4
Table 2: The pairwise comparison matrix C1
Absolute judgments amongst alternatives A1, A2, A3 ,A4 with respect to
Criterion 1
A1 A2 A3 A4
A1 1 0.125 0.125 0.2
A2 8 1 0.142 5
A3 8 7 1 8
A4 5 0.2 0.125 1
The correspondent vector <strong>of</strong> priorities for <strong>the</strong> C matrix calculated as briefly presented above is given
by any column in <strong>the</strong> above normalized matrix, as presented in Table 3.
Table 3: Vector <strong>of</strong> priorities for <strong>the</strong> pairwise comparison matrix C
Vector <strong>of</strong> priorities for <strong>the</strong> pairwise comparison matrix C
C1
C2
C3
0.20736
0.09572
0.69691
The interpretation is that, in <strong>the</strong> view <strong>of</strong> <strong>the</strong> particular person who answered <strong>the</strong> survey, <strong>the</strong> prevalent
criterion determining <strong>the</strong> increase in <strong>the</strong> level <strong>of</strong> organizational knowledge is <strong>the</strong> strategy for reducing
knowledge loss, corresponding to C3, since it has <strong>the</strong> highest value: 0.69691. Second in this line <strong>of</strong>
reasoning is <strong>the</strong> strategy for increasing knowledge creation , corresponding to C2 with a value in <strong>the</strong>
associated vector <strong>of</strong> priorities <strong>of</strong> 0.20736 and <strong>the</strong> least important criterion would be to <strong>the</strong> strategy <strong>of</strong>
increasing acquisitions <strong>of</strong> new knowledge , corresponding to C2, with a value <strong>of</strong> 0.095727 in <strong>the</strong>
priority vector. Similarly were determined <strong>the</strong> priority vectors corresponding to <strong>the</strong> pair wise matrices
<strong>of</strong> judgments <strong>of</strong> <strong>the</strong> four alternatives with respect <strong>of</strong> <strong>the</strong> three criteria.In Table 4 is given <strong>the</strong>
corresponding vectors <strong>of</strong> priorities to matrices C1 A1,A2,A3,A4 .
Table 4: Corresponding vector <strong>of</strong> priorities to matrices C1 A1,A2,A3,A4 , C2 A1,A2,A3,A4 , C3 A1,A2,A3,A4
Vector <strong>of</strong> priorities corresponding
to matrix C1 A1,A2,A3,A4 1
Vector <strong>of</strong> priorities corresponding
to matrix C2 A1,A2,A3,A4 1
Vector <strong>of</strong> priorities corresponding
to matrix C3 A1,A2,A3,A4 1
A1 0.07536 0.67814 0.03784
A2 0.12651 0.15191 0.35230
A3
A4
0.70623 0.09432 0.10885
0.09188 0.07561 0.50099
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Constantin Bratianu et al.
5. Data processing: aggregation in <strong>the</strong> syn<strong>the</strong>sis mode following <strong>the</strong>
traditional methodology in AHP <strong>the</strong>ory
The survey was electronically delivered to 500 employees from a large company and <strong>the</strong> rate <strong>of</strong>
response was 37.5%. Out <strong>of</strong> <strong>the</strong> received answers, 173 were valid answers. The priority vector <strong>of</strong> <strong>the</strong>
criteria considered to influence <strong>the</strong> increase in <strong>the</strong> level <strong>of</strong> organizational knowledge was calculated
as an average on <strong>the</strong> individual vectors <strong>of</strong> priority, using <strong>the</strong> Gauss 9.0 program. Individual’s vector <strong>of</strong>
priorities for <strong>the</strong> pairwise comparison matrix (as presented in table 5) were averaged over all <strong>the</strong>
respondents and yielded <strong>the</strong> values in <strong>the</strong> first row <strong>of</strong> <strong>the</strong> Table 7 (0.46958, 0.27069, 0.25972). These
can be interpreted as follows: given <strong>the</strong> goal <strong>of</strong> increasing <strong>the</strong> level <strong>of</strong> organizational knowledge,
employees’s perceptions regarding <strong>the</strong> three strategies C1, C2 C3 rank <strong>the</strong> <strong>the</strong> strategy for increasing
knowledge creation (C1), as being <strong>the</strong> most important, with a weight <strong>of</strong> 0.46958, <strong>the</strong> strategy <strong>of</strong>
increasing acquisitions <strong>of</strong> new knowledge (C2) on <strong>the</strong> second place, with a weight <strong>of</strong> 0.27069 and <strong>the</strong>
strategy for reducing knowledge loss (C3.) as being sensibly less important than <strong>the</strong> previous one,
with a weight <strong>of</strong> 0.25972.The weight <strong>of</strong> <strong>the</strong> Alternative 1 (hiring new valuable human resources) from
<strong>the</strong> point <strong>of</strong> view <strong>of</strong> <strong>the</strong> strategy for increasing knowledge creation (C1), is calculated again as <strong>the</strong>
average over <strong>the</strong> individual values (as shown in Table 6, first column ) and <strong>the</strong> corresponding
priorities vectors are also presented in Table 5.
Table 5: Syn<strong>the</strong>sis in <strong>the</strong> distributive mode
Distributive Mode C1 C2 C3
A1
A2
A3
A4
0.46958 0.27069 0.25972
0.22479 0.28449 0.16035
0.29176 0.23199 0.33765
0.38039 0.30160 0.26511
0.10305 0.18191 0.23687
In order to establish <strong>the</strong> composite or global priorities <strong>of</strong> <strong>the</strong> alternatives considered we lay out in a
matrix <strong>the</strong> local priorities <strong>of</strong> <strong>the</strong> alternatives with respect to each criterion and multiply each column <strong>of</strong>
vectors by <strong>the</strong> priority <strong>of</strong> <strong>the</strong> corresponding criterion and add across each row, which results in <strong>the</strong>
composite or global priority vector <strong>of</strong> <strong>the</strong> alternatives. Corresponding results are presented in Table 6.
Table 6: Syn<strong>the</strong>sis
Distributive Mode
A1
A2
A3
A4
0.22421
0.28750
0.32912
0.15915
As a straight conclusion, from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> assessing <strong>the</strong> importance <strong>of</strong> <strong>the</strong> four alternatives
(hiring new valuable human resources (A1), developing training programs (A2), creating a performing
motivation for <strong>the</strong> employees (A3) and purchasing books, journals, s<strong>of</strong>tware programs and o<strong>the</strong>r
informative materials (A4) <strong>the</strong> respondents’ perception rank A1 to A4 to be sensibly equall, with A3
being <strong>the</strong> most important, followed by A2 and A1. The last one in this list <strong>of</strong> importance is A4, with a
weight <strong>of</strong> 0.15915.
6. Discussion and conclusions
The purpose <strong>of</strong> this paper is to present a new model for organizational knowledge dynamics by using
<strong>the</strong> philosophy and ma<strong>the</strong>matical processing <strong>of</strong> AHP. The proposed model is based on <strong>the</strong> equilibrium
equation for <strong>the</strong> level <strong>of</strong> total organizational knowledge, and contains <strong>the</strong> following contributions: (a)
knowledge creation; (b) knowledge acquisition, and (c) knowledge loss. In order to obtain <strong>the</strong> relative
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Constantin Bratianu et al.
importance <strong>of</strong> <strong>the</strong>se contributions (Fcr, Fa, and Fl) we used <strong>the</strong> AHP model. According to this model
we considered as that <strong>the</strong> level <strong>of</strong> total organizational knowledge depends on three strategies or
criteria whict represents <strong>the</strong> above equation contributions: (C1) increasing knowledge creation; (C2)
increasing knowledge acquisition, and (C3) decreasing knowledge loss. The next level <strong>of</strong> structuring
contains activities thought to implement <strong>the</strong>se strategies: (A1) hiring valuable human resources; (A2)
organizing training programs; (A3) developing an efficient motivation, and (A4) buying books, journals,
databases, and s<strong>of</strong>tware programs. Using AHP ma<strong>the</strong>matical processing we can obtain out <strong>of</strong> <strong>the</strong>se
structured scheme <strong>the</strong> vector <strong>of</strong> priorities for <strong>the</strong> defined criteria, and <strong>the</strong> vectors <strong>of</strong> priorities for
activities for each individual criterion, and <strong>the</strong>n on <strong>the</strong> whole organization. The values <strong>of</strong> <strong>the</strong>se
priorities constitute <strong>the</strong> weighting factors for equations (1) and (2) defining <strong>the</strong> dynamics <strong>of</strong>
organizational knowledge. The empirical research has been done in a large company, by distributing
questionnaires to a number <strong>of</strong> 500 employees. We received 173 valid answers, and processed <strong>the</strong>m
using <strong>the</strong> program Gauss 9.0. results demonstrate <strong>the</strong> usefulness <strong>of</strong> this new model for knowledge
dynamics.
The conceptual model is generic and it can be applied to any organization. If necessary, it can be
enlarged in order to contain more components and to reflect in a better way <strong>the</strong> variation <strong>of</strong> <strong>the</strong>
organizational knowledge dynamics. The practical importance <strong>of</strong> this model consists in determining
<strong>the</strong> vector <strong>of</strong> priorities for a defined structure <strong>of</strong> knowledge strategies. Knowing <strong>the</strong>se priorities, <strong>the</strong>
top management is able to emphasize and to invest in <strong>the</strong> strategy with <strong>the</strong> highest priority. Also, it is
useful to learn and understand <strong>the</strong> relative importance <strong>of</strong> each strategy, and each activity within a
given strategy, in order to make adequate managerial decisions. This new model is an useful
qualitative and quantitative tool for managerial decisions making. The qualitative dimension comes
from <strong>the</strong> structuring <strong>the</strong> main organizational strategies and activities, and <strong>the</strong> quantitative dimension
comes from <strong>the</strong> computing vectors <strong>of</strong> priorities for <strong>the</strong>se strategies and activities.
Acknowledgements
We would like to acknowledge <strong>the</strong> support received from UEFISCSU Romania through PNII research
project ID_1812/2008.
References
Agapie, A. (2010) Numerical scales for decision makers preference judgements in <strong>the</strong> analytic hierarchy process,
in: Bratianu, C., Lixandroiu, D., Pop, N. (eds.) Business excellence, Vol.1, pp.1-5. Brasov: Infomarket.
Andriessen, D. (2006) On <strong>the</strong> metaphorical nature <strong>of</strong> intellectual capital: a textual analysis, Journal <strong>of</strong> Intellectual
Capital, Vol.7, no.1, pp.93-110.
Andriessen, D. (2008) Knowledge as love. How metaphors direct our efforts to manage knowledge organizations,
Knowledge Management Research & Practice, Vol.6, pp.5-12.
Bratianu, C. (2008) A dynamic structure <strong>of</strong> <strong>the</strong> organizational intellectual capital, in: Naaranoja, M. (ed.)
Knowledge management in organizations, pp.233-243. Vaasa: Vaasan Yliopisto.
Bratianu, C. (2010) A critical analysis <strong>of</strong> Nonaka’s model <strong>of</strong> knowledge dynamics, in: <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 2 nd
<strong>European</strong> <strong>Conference</strong> on Intellectual Capital, ISCTE Lisbon University Institute, Lisbon, Portugal, 29-30
March 2010, pp.115-120, Academic Publishing, Reading.
Bratianu, C., Andriessen, D. (2008) Knowledge as energy: a metaphorical analysis, in: <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 9 th
<strong>European</strong> <strong>Conference</strong> on Knowledge Management, Southampton Solent University, 4-5 September 2008,
pp.75-82, Academic Publishing, Reading.
Bratianu, C., Agapie, A., Orzea, I., Agoston, S. (2010) Inter-generational learning dynamics in universities, in:
<strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 11 th <strong>European</strong> <strong>Conference</strong> on Knowledge Management, pp.146-155, Universidade
Lusiada de Villa Nova de Famalicao, Portugal, 2-3 september, 2010.
Bratianu, C., Orzea, I. (2010) Organizational knowledge creation, Management & Marketing, Vol.5, no.3, pp.41-
62.
Castro, G.M., Saez, P.L., Lopez, J.E.N., Dorado, R.G. (2007) Knowledge creation process, <strong>the</strong>ory and empirical
evidence from knowledge-intensive firms. London: Palgrave Macmillan.
DeLong, D.W. (2004) Lost knowledge. Confronting <strong>the</strong> threat <strong>of</strong> an aging workforce. Oxford: Oxford University
Press.
Geisler, E., Wickramasinghe, N. (2009) Principles <strong>of</strong> knowledge management. Theory, practice, and cases. New
York: M.E.Sharpe.
Gourlay, S. (2006) Conceptualizing knowledge creation: a critique <strong>of</strong> Nonaka’s <strong>the</strong>ory, Journal <strong>of</strong> Management
Studies, Vol.43, No.7, pp.1415-1436.
Hawryszkiewicz, I. (2010) Knowledge management. Organizing knowledge based enterprises. New York:
Palgrave Macmillan.
Lak<strong>of</strong>f, G., Johnson, M. (1999) Philosophy in <strong>the</strong> flesh. The embodied mind and its challenge to western thought.
New York: Basic Books.
101

Constantin Bratianu et al.
Nissen, M.E. (2006) Harnessing knowledge dynamics. Principled organizational knowing & learning. London:
IRM Press.
Nonaka, I. (1994) A dynamic <strong>the</strong>ory <strong>of</strong> organizational knowledge creation, Organization Science, Vol.5, No.1,
pp.14-37.
Nonaka, I. (1998) The concept <strong>of</strong> ‘Ba’: building foundation for knowledge creation, California Management
Review, Vol.40, No.3, Spring, pp.40-54.
Nonaka, I., Konno, N., Toyama, R. (1998) Leading knowledge creation: a new framework for dynamic knowledge
management. In, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 2 nd Annual Knowledge Management <strong>Conference</strong>, Haas School <strong>of</strong>
Business, University <strong>of</strong> California Berkely, 22-24 September 1998.
Nonaka, I., Takeuchi, H. (1995) The knowledge creating company. How Japanese companies create <strong>the</strong>
dynamics <strong>of</strong> innovation. Oxford: Oxford University Press.
Nonaka, I., Toyama, R., Byosiere, Ph. (2001) A <strong>the</strong>ory <strong>of</strong> organizational knowledge creation: understanding <strong>the</strong>
dynamic process <strong>of</strong> creating knowledge, in: Dierkes, M., Berthoin Antal, A., Child, J., Nonaka, I. (eds.)
Handbook <strong>of</strong> Organizational learning & knowledge, pp.491-517. Oxford: Oxford University Press.
Nonaka, I., Ryoko, T., Hirata, T. (2008) Managing flow. A process <strong>the</strong>ory <strong>of</strong> <strong>the</strong> knowledge-based firm. New York:
Palgrave Macmillan.
Ortenblad, A. (2001) On differences between organizational learning and learning organization, The Learning
Organization, Vol.8, No.3, pp.125-133.
Pinker, S. (2007) The stuff <strong>of</strong> thought. Language as a window into human nature. New York: Penguin Books.
Saaty, T.L. (1994) Highlights and critical points in <strong>the</strong> <strong>the</strong>ory and application <strong>of</strong> <strong>the</strong> Analytical hierarchy Process,
<strong>European</strong> Journal <strong>of</strong> Operational Research, Vol.74, pp.426-447.
Saaty, T.L. (2009) Theory and applications <strong>of</strong> <strong>the</strong> analytic network process. Decision making with benefits,
opportunities, costs and risks. Pittsburgh: RWS Publications
Saaty, T.L., Luis, G.V. (2001) Models, methods, concepts & applications <strong>of</strong> <strong>the</strong> analytic hierarchy process.
Boston: Kluwer Academic Publishers
Szulansky, G. (1996) Exploring internal stickiness: impediments to transfer <strong>of</strong> best practice within <strong>the</strong> firm,
Strategic Management Journal, Vol.17, Winter special issue, pp.27-43.
Szulansky, G., Jensen, R,J. (2004) Overcoming stickiness: an empirical investigation <strong>of</strong> <strong>the</strong> role <strong>of</strong> <strong>the</strong> template
in <strong>the</strong> replication <strong>of</strong> organizational routines, Managerial and Decision Economics, Vol.25, pp.347-363.
102

Knowledge Sharing Through Communities <strong>of</strong> Practice
Sheryl Buckley and Apostolos Giannakopoulos
University <strong>of</strong> Johannesburg, Gauteng, South Africa
sbuckley@uj.ac.za
paulg@uj.ac.za
Abstract: Higher education institutions aim at preparing young adults for <strong>the</strong> world-<strong>of</strong>-work, be it as employees,
managers, self-employed workers or entrepreneurs. At <strong>the</strong> same time <strong>the</strong>y generate new knowledge in <strong>the</strong> form
<strong>of</strong> published papers, ei<strong>the</strong>r research by individuals or in partnership with o<strong>the</strong>r academics. This article aimed to
determine <strong>the</strong> knowledge sharing culture and trust attitudes <strong>of</strong> academics using a portal in a higher education
institution such as a university. It is common knowledge that knowledge sharing, especially implicit knowledge,
forms <strong>the</strong> pivot <strong>of</strong> increasing <strong>the</strong> intellectual capital <strong>of</strong> any organisation. This paper is part <strong>of</strong> a greater study
which aimed at establishing communities <strong>of</strong> practice at an educational institution by first determining existing
practices <strong>of</strong> academics among <strong>the</strong>mselves and <strong>the</strong>n developing <strong>the</strong> means to enhance existing communities <strong>of</strong>
practices and creating new ones. Since <strong>the</strong>re was an existing portal which was used for communication among
academics, it was felt such a tool could be used in a more productive and formal way which was to formalise
communities <strong>of</strong> practice. Communities <strong>of</strong> practice “thrive on passion” and “die” because <strong>of</strong> <strong>the</strong> lack <strong>of</strong> it and
constant communication fuels knowledge sharing. The rationale was that as a portal already exists and is a good
tool for communication, <strong>the</strong>n by collecting data about <strong>the</strong> reasons why academics use <strong>the</strong> portal it will give rise to
a number <strong>of</strong> criteria which can be used to enhance communication and thus knowledge sharing which impacts on
<strong>the</strong> intellectual capital <strong>of</strong> <strong>the</strong> institution. To achieve this aim a questionnaire consisting <strong>of</strong> open- and closed-ended
questions was administered to academics. An empirical survey on communities <strong>of</strong> practice at a University in
South Africa, confirmed previous research findings about what gives rise to communities <strong>of</strong> practice and on <strong>the</strong>
o<strong>the</strong>r hand, through qualitative and quantitative research, established a number <strong>of</strong> criteria which could be used
by any higher education institution ei<strong>the</strong>r to create new communities <strong>of</strong> practice or support existing ones, which
<strong>the</strong>y can ultimately blend to form a society <strong>of</strong> communities <strong>of</strong> practice within <strong>the</strong> university.
Keywords: knowledge sharing, communities <strong>of</strong> practice, higher education, technology, trust
1. Introduction
In <strong>the</strong> pre-industrial age, communities existed to connect people. With <strong>the</strong> advent <strong>of</strong> <strong>the</strong> knowledge
worker, <strong>the</strong> workplace has undergone ano<strong>the</strong>r transformation. Now, jobs that involve <strong>the</strong> most
complex type <strong>of</strong> interactions make up <strong>the</strong> fastest-growing segments in many industries (Sauve, 2007).
The reality is that in many industries (including <strong>the</strong> educational industry) in which situations change
rapidly, formal learning once or twice a year does not provide employees with <strong>the</strong> experience or
knowledge <strong>the</strong>y need to achieve ongoing success on <strong>the</strong> job. This means that organisations and
universities must revise <strong>the</strong>ir budgets and shift <strong>the</strong>ir resources from formal learning settings to
informal situations in which <strong>the</strong> most learning actually takes place.
While <strong>the</strong> changing nature <strong>of</strong> work is key, it is important not to overlook technology trends and how
<strong>the</strong>y influence <strong>the</strong> expectations and requirements <strong>of</strong> workers. The rise <strong>of</strong> social computing based on
highly innovative new Web 2.0 technologies <strong>of</strong>fers a new paradigm for how people approach learning
and knowledge sharing and is beginning to have a powerful impact on corporate learning (Sauve,
2007). Today <strong>the</strong> concept <strong>of</strong> knowledge sharing through new interactive online tools is taking hold in
an increasing number <strong>of</strong> public and private organisations (Monaghan, 2007). As communities <strong>of</strong>
practice (CoPs) around <strong>the</strong> globe use appropriate technology in new ways to serve <strong>the</strong>ir purposes,
<strong>the</strong> technologies becoming available to <strong>the</strong>m are also evolving. Communities experience tensions in
many activities. Firstly, organisations <strong>of</strong>ten fail to recognise that knowledge is created and shared
through social interaction between people (McElroy, 2002:30) and secondly, Muller (2006:384) is <strong>of</strong>
<strong>the</strong> opinion that communities rely on <strong>the</strong> existence <strong>of</strong> trust relationships among members.
This article discusses briefly <strong>the</strong> important key concepts such as technology, knowledge sharing and
trust which are interlinked in a functioning CoP and form <strong>the</strong> <strong>the</strong>oretical framework <strong>of</strong> <strong>the</strong> paper which
leads to <strong>the</strong> research question to be answered. Then <strong>the</strong> research methodology follows whereby
quantitative and qualitative methods are used to establish whe<strong>the</strong>r existing interactions among
academics constitute an informal community , practicing in a certain domain, <strong>the</strong> three necessary
conditions <strong>of</strong> <strong>the</strong> existence <strong>of</strong> a community <strong>of</strong> practice (Wenger, 2004). Conclusions and
recommendations follow and a new framework for establishing communities <strong>of</strong> practice is suggested.
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2. Technology and infrastructure
Sheryl Buckley and Apostolos Giannakopoulos
Improvements in communication and transportation technology over recent centuries have resulted in
shifts in community ties from being primarily people-to-people in geographical places to people-topeople
irrespective <strong>of</strong> local geography (Jones & Grandhi, 2005:216). A group can interact without
everyone ga<strong>the</strong>ring at a particular time. As a result people on very different schedules or in distant
time zones can still exchange messages and sustain discussions (Kollock & Smith, 1999).
The main emphasis <strong>of</strong> technology should be to enable community participants to share experience
(Finerty, 1997). In a university context, computers can help students and academics locate community
resources (people, information, etc.) based on <strong>the</strong>ir need (Hay, 1993). It can be argued that
academics looking for knowledge connect with those who possess it and in this way <strong>the</strong>y are able to
improve <strong>the</strong>ir practice and create a competitive sustainable advantage for <strong>the</strong>mselves and <strong>the</strong>
institution. One way to achieve this is through a CoP.
Online communities have a purpose, are supported by technology, and are guided by norms and
policies (Preece, 2000). Beenen, Ling, Wang, Chang, Resnick and Kraut (2004) argue despite <strong>the</strong>
vibrancy <strong>of</strong> online communities, large numbers <strong>of</strong> <strong>the</strong>m fail. For example, Butler found that 50% <strong>of</strong>
social, hobby, and work mailing lists had no traffic over a 4-month period. Under-contribution is a
problem even in communities that do survive. In a majority <strong>of</strong> active mailing lists, fewer than 50% <strong>of</strong>
subscribers posted even a single message in a 4-month period.
For Tyler, Wilkinson and Huberman (n.d.), email has become <strong>the</strong> predominant means <strong>of</strong>
communication in <strong>the</strong> information society. Email has been established as an indicator <strong>of</strong> collaboration
and knowledge exchange (Wellman, 2002; Whittaker & Sidner, 1996). This volume <strong>of</strong> data enables
<strong>the</strong> discovery <strong>of</strong> shared interests and relationships where none were previously known (Schwartz &
Wood, 1992). Given its ubiquity, it is a promising resource for tapping into <strong>the</strong> dynamics <strong>of</strong> information
within organisations, and for extracting <strong>the</strong> hidden patterns <strong>of</strong> collaboration and leadership that are at
<strong>the</strong> heart <strong>of</strong> CoP. This is one reason e-mail is still a very successful community tool in spite <strong>of</strong> all <strong>the</strong>
recent developments: it integrates community interactions in <strong>the</strong> tool where people spend a large
portion <strong>of</strong> <strong>the</strong>ir working and social lives (Wenger et al., 2005).
Wenger et al. (2005) maintain that great care should be taken in <strong>the</strong> design process <strong>of</strong> technological
tools to facilitate CoPs as <strong>the</strong> technologies need to support <strong>the</strong> intertwined evolution <strong>of</strong> domain,
community and practice without overbuilding and which are <strong>the</strong> salient features (Wenger, 2004) <strong>of</strong> a
CoP.
3. Knowledge sharing
One <strong>of</strong> <strong>the</strong> most important aspects <strong>of</strong> CoPs is that a group <strong>of</strong> people share knowledge, learn toge<strong>the</strong>r
and create common practices. Community members frequently help one ano<strong>the</strong>r solve problems, give
one ano<strong>the</strong>r advice and develop new approaches or tools for <strong>the</strong>ir field. As <strong>the</strong>y share ideas and
experiences, people develop a shared way <strong>of</strong> doing things, a set <strong>of</strong> common practices. Sometimes
<strong>the</strong>y formalise <strong>the</strong>se in guidelines and standards, but <strong>of</strong>ten <strong>the</strong>y simply remain ‘what everybody
knows’ about good practice. Since CoPs focus on topics that people are <strong>of</strong>ten passionately interested
in, <strong>the</strong>y can become important sources <strong>of</strong> individual identity.
The interactions involved, and <strong>the</strong> ability to undertake larger or more complex activities and projects
through cooperation, bind people toge<strong>the</strong>r and help to facilitate relationship and trust. Organisations
<strong>of</strong>ten fail to recognise that knowledge is created and shared through social interaction between
people. These interpersonal relationships form a pattern and are referred to as social innovation
capital or social capital (McElroy, 2002:30). It is in communities that “individuals develop <strong>the</strong> capacity
to create, refine, share and eventually apply knowledge – knowledge that makes an individual a
valuable organisational resource” (Thomas, 2002). Although <strong>the</strong>se communities are mainly selforganisational,
<strong>the</strong>re needs to be a certain measure <strong>of</strong> facilitation, encouragement and management
in <strong>the</strong> manner in which knowledge is created, shared and applied, even if it is only to ensure a
supportive environment.
Hew and Hara (2007:589) add that conversation is also an important conduit for knowledge sharing
among members in CoPs. Batson, Ahmad and Tsang (2002:439), on <strong>the</strong> o<strong>the</strong>r hand, maintain that
individuals are willing to help one ano<strong>the</strong>r and share knowledge because <strong>of</strong> egoism, altruism,
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collectivism and principlism. The ultimate goal in <strong>the</strong> egoism-related motive is to increase one’s own
personal benefit (e.g. pay, prizes and recognition). Altruism is a motive that increases <strong>the</strong> welfare <strong>of</strong>
one or more individuals o<strong>the</strong>r than oneself. Collectivism is a motive that aims to increase <strong>the</strong> welfare
<strong>of</strong> <strong>the</strong> group. The difference between altruism and collectivism can be made clearer by viewing
altruism as serving <strong>the</strong> community to benefit a group as a whole. Principlism is a motive with <strong>the</strong> end
goal <strong>of</strong> upholding some moral principles.
Ano<strong>the</strong>r important aspect for <strong>the</strong> successful functioning <strong>of</strong> a knowledge-sharing CoP is active
participation <strong>of</strong> a substantial part (ideally, all) <strong>of</strong> its members. Dixon (2000:84) argues that <strong>the</strong> CoP
model allows organisations to overcome barriers to sharing information that conventional technologybased
KM systems <strong>of</strong>ten encounter. This sentiment is shared by Hayes and Walsham (2000:61), who
say that for a community to be truly vibrant, <strong>the</strong>re should be active participation <strong>of</strong> members in o<strong>the</strong>r
knowledge-exchange activities; engaging in live chats, Q&A sessions, providing asynchronous
feedback on previous postings etc.
With regard to online sharing <strong>of</strong> knowledge, research shows that <strong>the</strong>re are numerous reasons
individuals could have for sharing <strong>the</strong>ir knowledge with o<strong>the</strong>r members <strong>of</strong> a CoP online. These range
from self-esteem boosting to altruistic and conformist considerations. For a community to be vibrant
<strong>the</strong>re should also be active participation on <strong>the</strong> demand side. The second requirement for a
successful CoP is its members’ willingness to use <strong>the</strong> CoP as a source <strong>of</strong> new knowledge. These two
major requirements (willingness to share knowledge and willingness to use a CoP as a source <strong>of</strong>
knowledge) apply to any CoP, be it face-to-face or virtual.
Fur<strong>the</strong>rmore, because CoPs provide a safe forum where people are comfortable in sharing
challenges and perspectives on a common topic, <strong>the</strong>y serve as breeding grounds for innovation
(Slater & Narver, 2000:1170).
4. Trust
Many authors (Kramer & Tyler, 1996:128; Lave & Wenger, 1991:39; Wenger, 1998) agree that trust is
a pivotal and essential element in long-term social relationships. Individuals will <strong>of</strong>ten refrain from any
interaction with o<strong>the</strong>rs whom <strong>the</strong>y do not trust. Trust is <strong>the</strong> confidence an individual has that ano<strong>the</strong>r
person or persons will behave only as <strong>the</strong>y are expected to and will do so in a socially acceptable and
ethical manner; and this confidence is essential in long-term relationships because <strong>of</strong> <strong>the</strong> lack <strong>of</strong> a
comprehensive set <strong>of</strong> rules to govern such relationships.
Muller (2006:384) is <strong>of</strong> <strong>the</strong> opinion that communities rely on <strong>the</strong> existence <strong>of</strong> trust relationships among
members. This is due to <strong>the</strong> fact that <strong>the</strong> environment <strong>of</strong> communities is commonly evolving. Members
have to adapt <strong>the</strong>ir behaviour to those evolutions and thus trust constitutes an efficient coordinating
device by allowing a certain degree <strong>of</strong> flexibility in behaviour.
Roberts (2000:440) suggests that trust is a necessary precondition for sharing and mutual
understanding. It is also necessary for <strong>the</strong> transfer <strong>of</strong> knowledge. Wathne, Roos and von Krogh
(1996:39) posit that high trust leads to greater openness between CoP members. Integrity-based trust
has an important role to play in motivating knowledge sharing. People are not likely to be motivated to
share <strong>the</strong>ir knowledge with ano<strong>the</strong>r individual or a community if <strong>the</strong>y perceive <strong>the</strong>m to be dishonest or
unreliable. Similarly, when people view a community as upholding trustworthy values, such as mutual
reciprocity, honesty, reliability and commitment, <strong>the</strong>re is likely to be a greater degree <strong>of</strong> motivation to
participate and share <strong>the</strong>ir knowledge (Coopey, 1998:369).
Willingness to share knowledge in a voluntary manner, especially tacit knowledge, based on trust and
using available technology to communicate in an informal community could form <strong>the</strong> platform for <strong>the</strong>
creation <strong>of</strong> CoPs in any organisation, especially in an educational institution such as a University. The
question <strong>the</strong>n arises: Do CoPs exist at a University <strong>of</strong> South Africa? To answer this question it is
necessary to establish whe<strong>the</strong>r <strong>the</strong> three main ingredients <strong>of</strong> a CoP namely, community, domain, and
practice exist.
5. Research methodology
In order to establish <strong>the</strong> existence <strong>of</strong> CoPs at a HE institution in SA, quantitative and qualitative data
was collected from academics (an informal community) who made use <strong>of</strong> a portal (technology) to
communicate. This portal was created by a department with a view to improve communication and
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enhancing <strong>the</strong> sharing <strong>of</strong> views and ideas among <strong>the</strong> academics. Indirectly <strong>the</strong> seeds for <strong>the</strong>
development <strong>of</strong> CoPs were sown. However, this portal did not last very long. By doing a post mortem,
<strong>the</strong> rationale was that if indeed CoPs did exist, why did <strong>the</strong>y not last? It became <strong>the</strong>n necessary to
determine <strong>the</strong> feelings and attitudes <strong>of</strong> academics to <strong>the</strong> portal and why such an innovative idea had
died a relatively sudden death, because <strong>the</strong>oretically it should have improved <strong>the</strong> existing situation at
a HE institution in SA. Fur<strong>the</strong>r, it was assumed that if academics became aware <strong>of</strong> <strong>the</strong> benefits <strong>of</strong> a
CoP, <strong>the</strong>y might resurrect <strong>the</strong> use <strong>of</strong> a portal or any o<strong>the</strong>r means <strong>of</strong> sharing <strong>the</strong>ir knowledge. Since
only one University was used, and only one department this could be an important limitation as <strong>the</strong>
results cannot be generalised. However, <strong>the</strong> results could also be used to create a framework for
establishing CoPs at a University. The sample consisted <strong>of</strong> 26 academics in a department. A
questionnaire consisting <strong>of</strong> nine questions including open- and closed-ended questions was
administered. A weekly email reminder was sent to <strong>the</strong> participants for <strong>the</strong> duration <strong>of</strong> two weeks.
Although only 16 participants completed <strong>the</strong> questionnaire and this could be ano<strong>the</strong>r limitation. The
reason was that <strong>the</strong> department experienced a high turnover <strong>of</strong> academics. The sample may
<strong>the</strong>refore be considered too small to generalise but trends can be noted.
6. Results and discussion
Firstly, data was collected about <strong>the</strong> frequency <strong>of</strong> <strong>the</strong> use <strong>of</strong> <strong>the</strong> portal. Initially <strong>the</strong>re were 26
members who had used <strong>the</strong> portal: 15 respondents were active and 11 respondents were lurkers. The
questionnaire was completed by 69% <strong>of</strong> <strong>the</strong> respondents. During <strong>the</strong> use <strong>of</strong> <strong>the</strong> portal, <strong>the</strong>re were 771
threads and a total <strong>of</strong> 1 026 posts in a five month period (see Figure 1).
Number <strong>of</strong> Posts
800
700
600
500
400
300
200
100
0
Portal posts
1
Members during a five month period
Figure 1: Portal posts
The highest number <strong>of</strong> respondents ever online was five.
Carl
Derek
Glenda
Hans
Helena
Jacqui
Jessel
Johan
Nola
Pr<strong>of</strong> Les
Rita
Rose
RPM
Sheryl
Talania
A description <strong>of</strong> <strong>the</strong> questionnaire follows, where <strong>the</strong> respondents had to explain or give reasons for
<strong>the</strong>ir answers so that insight into <strong>the</strong>ir views could be gained. Subsequently, an analysis <strong>of</strong> <strong>the</strong>ir
responses gave rise to a number <strong>of</strong> <strong>the</strong>mes and categories (see Tables 3 and 4).
Question 1: Have you used <strong>the</strong> portal?
The portal was used by 82% <strong>of</strong> <strong>the</strong> respondents and 18% stated that <strong>the</strong>y did not actively use <strong>the</strong>
portal except for lurking and o<strong>the</strong>r reasons. Reasons for not actively using it were lack <strong>of</strong> time and
some indicated that <strong>the</strong>y did not know that <strong>the</strong> portal existed. The lurkers are to be expected, for
different reasons. Although this type <strong>of</strong> behaviour occurs naturally in human beings, communities
frequently have a core group <strong>of</strong> high contributors and a large group <strong>of</strong> lurkers who ask or contribute
little.
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Question 2: The portal is currently not being used. Would you be interested in such a portal in
<strong>the</strong> future?
Fifty five percent <strong>of</strong> <strong>the</strong> respondents stated that <strong>the</strong>y would be interested in a portal in <strong>the</strong> future and
45% were not interested. The reasons given for <strong>the</strong> positive response were that virtual communities
encourage participants to make use <strong>of</strong> electronic documents and record keeping, something that <strong>the</strong>
typical knowledge worker should do, but sadly, rarely does.
Checking every day in case <strong>the</strong>y were missing something on <strong>the</strong> portal was considered a waste <strong>of</strong>
time by six respondents.
The portal was created and made available to all those who wanted to add value in <strong>the</strong> department. It
was a convenient ga<strong>the</strong>ring place, whe<strong>the</strong>r formal or informal, which allowed for a more voluntary
exchange <strong>of</strong> ideas. The respondents felt that <strong>the</strong>re was a need for o<strong>the</strong>r academics to participate for
<strong>the</strong> portal to be successful. However, such participation would have to be voluntary. Some
respondents felt it was “a waste <strong>of</strong> time reading everyone’s junk and too time-consuming” and this
could contribute to 18% not actively participating (see question 1).
Ano<strong>the</strong>r respondent felt that <strong>the</strong> portal “was a platform that enables us to speak freely” and that it
should have a strong “academic focus”. Some respondents indicated that <strong>the</strong>y preferred face-to-face
communication. This statement reinforces <strong>the</strong> idea that human beings thrive on real-life, real-time
communication so <strong>the</strong>y can see body language and similar means <strong>of</strong> communication.
On <strong>the</strong> negative side, some respondents felt that <strong>the</strong> portal did not work because <strong>of</strong> academics not
participating, so <strong>the</strong>y did not see it working in <strong>the</strong> future as “it was not used correctly”. Some
respondents felt a lot <strong>of</strong> <strong>the</strong> information on <strong>the</strong> portal could have been accessed via e-mail.
Question 3: How <strong>of</strong>ten did you use <strong>the</strong> portal?
Twenty six percent <strong>of</strong> <strong>the</strong> respondents used <strong>the</strong> portal twice a day and ano<strong>the</strong>r 26% more than twice
a week (see Table 1). The low percentages could be attributed to <strong>the</strong> workloads <strong>of</strong> <strong>the</strong> academics.
Table 1: How <strong>of</strong>ten did you use <strong>the</strong> portal?
Usage Percentage
Once a day 12%
Twice a day 26%
Less than twice a week 12%
Twice a week 12%
More than twice a week 26%
Once a month 12%
Question 4: From where did you access <strong>the</strong> portal?
The majority, 87%, <strong>of</strong> <strong>the</strong> respondents indicated that <strong>the</strong>y accessed <strong>the</strong> portal from work, 6% from
home and <strong>the</strong> rest did not answer <strong>the</strong> question.
Question 5: Was <strong>the</strong> portal easy to access?
Seventy two percent <strong>of</strong> <strong>the</strong> respondents indicated that <strong>the</strong> portal was easy to access. This high
number is surprising because in question 2 some respondents stated that “it was a pain to get into”
and <strong>the</strong> rest said it was difficult to access. Those that found <strong>the</strong> portal easy to access said it was
“easy to navigate, very simple layout”, “it was just a matter <strong>of</strong> pointing my browser to <strong>the</strong> web” and “it
was installed on my favourites, making it easy to access <strong>the</strong> logon page provided”. Some used <strong>the</strong>ir
personal Internet account from home, as <strong>the</strong>y found that <strong>the</strong> portal used very little bandwidth, which
made it affordable compared to <strong>the</strong> university web-based e-mail service. Its easy accessibility made
its use more attractive. This eliminates <strong>the</strong> possibility <strong>of</strong> some academics not using <strong>the</strong> portal owing to
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inaccessibility. On <strong>the</strong> negative side, some said that <strong>the</strong> portal was slow and that it should be userfriendly.
Question 6: Did you find <strong>the</strong> portal easy to navigate?
All except two respondents, who did not answer <strong>the</strong> question, found <strong>the</strong> portal easy to navigate.
Reasons given were that “things were categorised” and “laid out according to standard forum/content
management systems with menus and sub-menus”. This also reinforces <strong>the</strong> validity <strong>of</strong> responses to
question 5 where <strong>the</strong> portal was found to be “easy to navigate, very simple layout”.
Question 7: What did you use <strong>the</strong> portal for?
One <strong>of</strong> <strong>the</strong> respondents stated that <strong>the</strong> portal should be used in a constructive way and that it “must
be used to improve information sharing”. The fact that a high percentage (63%) <strong>of</strong> <strong>the</strong> respondents
used <strong>the</strong> portal to share information is very encouraging, since this forms one <strong>of</strong> <strong>the</strong> most important
pillars <strong>of</strong> a CoP. Sharing <strong>of</strong> knowledge in a voluntary manner leads to a win-win situation.
Only 45% <strong>of</strong> respondents used <strong>the</strong> portal to communicate with o<strong>the</strong>r academics members (see Table
2).
Table 2: What did you use <strong>the</strong> portal for?
Purpose Percentage
To find information 54%
To keep abreast <strong>of</strong> new developments 36%
To communicate 45%
To share information 63%
The fact that <strong>the</strong> portal was used to keep abreast <strong>of</strong> new developments, if only by 36% <strong>of</strong> <strong>the</strong>
respondents, is a very important finding because it means that academics saw <strong>the</strong> benefits <strong>of</strong> using
<strong>the</strong> portal (see Table 2). As one <strong>of</strong> <strong>the</strong> respondents put it: “it helped me … access new knowledge”,
while ano<strong>the</strong>r said: “it helped me know more about my colleagues, access new knowledge and also
share my thoughts with colleagues”. And this is where <strong>the</strong> value <strong>of</strong> creating a platform for academics
to interact is confirmed. This forms one <strong>of</strong> <strong>the</strong> main functions <strong>of</strong> an academic institution.
Question 8: Did you find <strong>the</strong> portal a helpful tool?
Thirty six percent <strong>of</strong> <strong>the</strong> respondents found <strong>the</strong> portal a helpful tool, 45% did not, and two did not
answer <strong>the</strong> question. The reasons were: “it can become very cumbersome in <strong>the</strong> department to
access documents or to gain hold <strong>of</strong> someone and <strong>the</strong> portal made this possible which I considered
invaluable at least until everyone stopped using it as people usually sent e-mails about important
events, minutes <strong>of</strong> meetings and <strong>the</strong>se were also placed on <strong>the</strong> portal”. However, “it was a pain
checking both”. O<strong>the</strong>r reasons were that respondents felt “it was superfluous as a lot <strong>of</strong> <strong>the</strong>
information is distributed by o<strong>the</strong>r means”, “too time-consuming” and “too much information on it and
not all was useful”. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> portal was found to be “easy to contact academics and
place common documents in <strong>the</strong> repository”. Ano<strong>the</strong>r respondent said that one “could never find any
relevant information, <strong>the</strong> portal was used for personal gains/grievances”. For ano<strong>the</strong>r, “it helped me to
know more about my colleagues, access new knowledge and also share my thoughts with
colleagues. Not being at <strong>the</strong> <strong>of</strong>fice, you managed to get a feeling <strong>of</strong> <strong>the</strong> current happenings in <strong>the</strong>
department. There was no need for floods <strong>of</strong> e-mail if information is available”.
Finally, convenience was ano<strong>the</strong>r reason identified for using <strong>the</strong> portal as <strong>the</strong> platform for sharing
ideas and information. It has to be built on its own, frequently requiring intensive and laborious
interaction among members <strong>of</strong> <strong>the</strong> organisation and as a result a shared understanding or meaning
about <strong>the</strong> knowledge that is created has to be developed. As stated by <strong>the</strong> respondent quoted earlier,
“not being in <strong>the</strong> <strong>of</strong>fice, you managed to get a feeling <strong>of</strong> <strong>the</strong> current happenings in <strong>the</strong> department”.
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Question 9: In your opinion, what could have been done to make <strong>the</strong> portal a more effective
tool in <strong>the</strong> department?
A number <strong>of</strong> reasons were given in answer to this question. One respondent felt that <strong>the</strong>re was “not
enough emphasis on <strong>the</strong> functionality <strong>of</strong> <strong>the</strong> portal especially to those people who were less inclined
to use it. Had more academics participated in using <strong>the</strong> portal and more emphasis been put on
functionality, I believe <strong>the</strong> portal could have nullified <strong>the</strong> university intranet/web presence in <strong>the</strong>
department. The point <strong>of</strong> a virtual community is that like a fax machine or a telephone, without o<strong>the</strong>r
people to use it with, it is ra<strong>the</strong>r useless”. There was a need to “market it to people so that academics
will be aware”. For ano<strong>the</strong>r respondent, <strong>the</strong> “portal will only be useful when people are not co-located.
It provided little value communicating online with someone in an <strong>of</strong>fice nearby”. Some respondents
felt <strong>the</strong>re was a “need for clear guidelines for use”. “Changing academics attitudes towards
information sharing and participation would be helpful” as “<strong>the</strong> portal wasn’t <strong>the</strong> problem it was <strong>the</strong>
people using it that didn’t participate which <strong>the</strong>n renders it ineffective”. O<strong>the</strong>r comments received from
respondents were that <strong>the</strong> portal needed to be structured properly and that relevant content needed to
be added to <strong>the</strong> portal, it should be created “for a specific purpose”, and that “if it was hosted under
<strong>the</strong> university URL or linked to <strong>the</strong> intranet or having o<strong>the</strong>r colleagues from o<strong>the</strong>r departments as
members would be advantageous”. Finally, respondents were <strong>of</strong> <strong>the</strong> opinion that academics buy-in
was necessary, and that “all relevant policies, templates and procedures” should be placed on <strong>the</strong>
portal and good communication topics activated.
This questionnaire revealed that <strong>the</strong>re was clearly a need to advertise <strong>the</strong> portal so that most users
could have access to it. This is evident from remarks such as, “‘having o<strong>the</strong>r colleagues from o<strong>the</strong>r
departments as members would be advantageous”, “market it to people so that academics will be
aware” and “get academics buy-in”. This is ano<strong>the</strong>r important finding because it can be used in <strong>the</strong>
future building <strong>of</strong> a CoP.
Ano<strong>the</strong>r aspect that was revealed is that attitudes play an important role in <strong>the</strong> functioning <strong>of</strong> a CoP.
That was indicated by respondents who said: “changing academics attitudes towards information
sharing and participation would be helpful” as “<strong>the</strong> portal wasn’t <strong>the</strong> problem it was <strong>the</strong> people using it
that didn’t participate which <strong>the</strong>n renders it ineffective”. When <strong>the</strong> responses were analysed, <strong>the</strong>
following 20 <strong>the</strong>mes (see Table 3 and Table 4) were categorised using content analysis and open
coding.
Table 3: Initial categories identified in <strong>the</strong> questionnaire
1. time 8. locality 15. communication (online and
face-to-face)
2. advertise (awareness and
marketing)
9. domain 16. innovation
3. lurking 10. pr<strong>of</strong>essional identity 17. personal development
4. build relationships 11. practice 18. convenience
5. infrastructure 12. attitudes 19. keeping abreast <strong>of</strong> new
developments
6. knowledge sharing 13. meaningful work 20. voluntary participation
7. frequency 14. encouragement
These <strong>the</strong>mes in Table 3 were fur<strong>the</strong>r grouped into <strong>the</strong> following three categories (Table 4):
Table 4: Final categories <strong>of</strong> <strong>the</strong>mes in <strong>the</strong> questionnaire
Domain 6, 9, 16
Practice 1, 2, 3, 5, 7, 8, 10, 11, 13, 14, 17, 18, 19, 20
Community 4, 12, 15
Evident criteria for a CoP emerged from <strong>the</strong> questionnaire. Without <strong>the</strong> members realising it, <strong>the</strong>y had
voluntarily formed a CoP through <strong>the</strong> use <strong>of</strong> <strong>the</strong> portal. Though management had initiated <strong>the</strong> portal
109

Sheryl Buckley and Apostolos Giannakopoulos
for <strong>the</strong> department, its aim was merely to improve communication among academics members. But
<strong>the</strong> academics went a step fur<strong>the</strong>r and used <strong>the</strong> portal for many o<strong>the</strong>r purposes, which are in line with
an active CoP. Some <strong>of</strong> <strong>the</strong> respondents grabbed <strong>the</strong> opportunity to use <strong>the</strong> portal in a formal as well
as informal way for exchanging ideas. As ano<strong>the</strong>r respondent indicated, “<strong>the</strong> portal was a convenient
ga<strong>the</strong>ring place, whe<strong>the</strong>r formal or informal, which allows for a more voluntary exchange <strong>of</strong> ideas”.
The social aspect is highlighted here. Ano<strong>the</strong>r indicated that <strong>the</strong> portal “allows for a more voluntary
exchange <strong>of</strong> ideas”. This view is in line with that <strong>of</strong> Wenger (2004).
What also emerged from <strong>the</strong> use <strong>of</strong> <strong>the</strong> portal was that although <strong>the</strong>re were some inhibitors (such as
available time), those who made extensive use <strong>of</strong> <strong>the</strong> portal reaped <strong>the</strong> benefits, since <strong>the</strong>y had
something in common (domain) to discuss in group form (community) and practised (practice) <strong>the</strong>ir
ideas. Domains, community and practice are <strong>the</strong> main ingredients <strong>of</strong> a functioning CoP (Wenger,
2004). Domain: There was a common goal (a common focus according to Wenger [2004]) which was
served by <strong>the</strong> portal, established by <strong>the</strong> department in order to improve knowledge-sharing practices.
Sixty three percent <strong>of</strong> <strong>the</strong> respondents used <strong>the</strong> portal to communicate with o<strong>the</strong>r academic members
in a formal as well as informal (socialising) way. This is in line with <strong>the</strong> findings <strong>of</strong> Batson, Ahmad and
Tsang (2002:439) who support <strong>the</strong> same view and who maintain that individuals are willing to help
one ano<strong>the</strong>r and share knowledge because <strong>of</strong> egoism, altruism, collectivism and principlism.
Community: The community consisted <strong>of</strong> <strong>the</strong> members <strong>of</strong> <strong>the</strong> department, <strong>the</strong> relationships <strong>the</strong>y had
formed among <strong>the</strong>mselves and a sense <strong>of</strong> belonging <strong>the</strong>y felt towards <strong>the</strong> community. The members
feel <strong>the</strong>y belong to <strong>the</strong> community. Wenger (2004), too, sees a CoP as involving people who interact
and who develop relationships that enable <strong>the</strong>m to address problems and share knowledge. The
community builds relationships that enable collective learning.
Practice: Practice was evident among <strong>the</strong> users <strong>of</strong> <strong>the</strong> portal in terms <strong>of</strong> <strong>the</strong> body <strong>of</strong> knowledge, how
<strong>the</strong>y operated and used <strong>the</strong> documents <strong>the</strong>y shared with one ano<strong>the</strong>r. Wenger (2004) emphasises
that <strong>the</strong> practice in a CoP anchors <strong>the</strong> learning in what people do. The practice is <strong>the</strong> body <strong>of</strong>
knowledge, methods, tools, stories, cases and documents which members share and develop
toge<strong>the</strong>r.
Figure 2 presents a framework based on <strong>the</strong> <strong>the</strong>mes specified in Table 4. These <strong>the</strong>mes were
grouped into <strong>the</strong> three key elements <strong>of</strong> a CoP: domain, community and practice. This framework could
be used to assist in <strong>the</strong> creation <strong>of</strong> new CoPs and to improve existing CoPs where a society <strong>of</strong> CoPs
can ultimately develop. The findings positively suggest that a CoP might increase knowledge sharing
in a university. Domain has been linked to management, as management is perceived to have <strong>the</strong>
resources to create awareness among <strong>the</strong> academic community, to educate, encourage use, provide
support (financial and technical) and reward sharing. Without <strong>the</strong> support and approval <strong>of</strong>
management, no CoP can be created. Community and practice have been linked to academics.
Academics could develop, use, support, mentor and evaluate CoPs. Finally, CoPs are integrated to
form global societies <strong>of</strong> CoPs in which academics participate.
7. Conclusion
From <strong>the</strong> results, <strong>the</strong> question as to whe<strong>the</strong>r CoPs existed was affirmative since <strong>the</strong> main elements <strong>of</strong>
a CoP ei<strong>the</strong>r featured, or were accepted by most <strong>of</strong> <strong>the</strong> respondents. One factor that appears to
inhibit ei<strong>the</strong>r <strong>the</strong> flourishing <strong>of</strong> an existing CoP or <strong>the</strong> formation <strong>of</strong> a new one is too little time. Most <strong>of</strong>
<strong>the</strong> respondents accepted <strong>the</strong> o<strong>the</strong>r elements. This is very encouraging, since if <strong>the</strong> necessary
elements to establish a CoP are available, <strong>the</strong>n half <strong>of</strong> <strong>the</strong> objective has already been achieved. The
two factors that appear from <strong>the</strong> findings to play an important role in <strong>the</strong> effectiveness <strong>of</strong> knowledge
sharing are <strong>the</strong> attitudes <strong>of</strong> <strong>the</strong> academics and advertising <strong>of</strong> <strong>the</strong> CoP by management. Management
has <strong>the</strong> ability to create an atmosphere that can be conducive to <strong>the</strong> sharing and creating <strong>of</strong>
knowledge among academics by focusing on <strong>the</strong> domain, community and practice.
It is <strong>the</strong> combination <strong>of</strong> a domain, community and practice that constitute a community <strong>of</strong> practice.
And it is by developing <strong>the</strong>se three elements in parallel that such a community is cultivated. In a
higher education institution, where knowledge is created, disseminated and transmitted, management
perhaps needs to play an even more active role in developing communities <strong>of</strong> practice if such
communities are to be successful.
110

Themes identified
from <strong>the</strong> portal
If existing
CoP
Domain
Academics
Create
awareness
(advertise
existing and
new CoPs)
UJ
managemen
Innovation
Knowledge sharing
Domain
Use CoP
Build relationships
Communication
Attitudes
Sheryl Buckley and Apostolos Giannakopoulos
Community
Support CoP
Educate &
encourage
(workshops)
Mentor CoP
Practice
Evaluate
CoP
Use CoPs
Academics
develop or
build new
CoPs
Encouragement
Meaningful work
Personal development
Practice
Time
Advertise
Lurking
Infrastructure
Frequency
Locality
Pr<strong>of</strong>essional identity
Convenience
Keeping abreast with
new developments
Voluntary participation
Figure 2: Framework for creation <strong>of</strong> a CoP (adapted from Buckley, 2009:178)
References
Batson, C.D., Ahmad, N. & Tsang, J. (2002). Four motives for community involvement. Journal <strong>of</strong> Social Issues,
58:429-445.
Beenen, G., Ling, K., Wang, X., Chang, K., Resnick, P. & Kraut, R.E. (2004). Using social psychology to motivate
contributions to online communities. [Online]. Available from:
http://www.si.umich.edu/~presnick/papers/cscw04preprint.pdf. (Accessed 8 September 2009).
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Support CoP
Integrate
CoPs
Mentor CoP
Evaluate
CoP
Create
global/societies
<strong>of</strong> CoPs
Integrate
CoPs

Sheryl Buckley and Apostolos Giannakopoulos
Buckley, S.B. (2009. Knowledge sharing through communities <strong>of</strong> practice at institutions <strong>of</strong> higher education.
University <strong>of</strong> Johannesburg.
Coopey, J. (1998). Learning to trust and trusting to learn: a role for radical <strong>the</strong>atre. Management Learning,
29(3):365-82.
Dixon, N. (2000). Common knowledge: How companies thrive by sharing what <strong>the</strong>y know. Boston: Harvard
Business School Press.
Finerty, T. (1997). Integrating learning and knowledge infrastructure. Journal <strong>of</strong> Knowledge Management, 1.2:98-
104.
Hay, K.E. (1993). Legitimate peripheral participation, instructionism, and constructivism: Whose situation is it
anyway? Educational Technology, 33(3):33-38.
Hayes, N. & Walsham, G. (2000). Competing interpretations <strong>of</strong> computer supported co-operative work.
Organization, 7(1):49-67.
Hew, K.F. & Hara, N. (2007). Empirical study <strong>of</strong> motivators and barriers <strong>of</strong> teacher online knowledge sharing.
Educational Technology Research and Development, 55(6):573-595.
Jones, Q. & Grandhi, S.A. (2005). Supporting proximate communities with P3-Systems: Technology for
connecting people-to-people-to-geographical-places. In M. Wilber (Ed.). The interaction society: Practice,
<strong>the</strong>ories and supportive technologies (pp. 215-224). Hershey: Idea Group.
Kollock, P. & Smith, M. (1999). Communities in cyberspace. London: Routledge.
Kramer, R M & Tyler, T R. (1996). Trust in Organisations: Frontiers <strong>of</strong> <strong>the</strong>ory and
Research. Thousand Oaks, CA: Sage Publications.
Lave, J. & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York: Cambridge
University Press.
McElroy, M.W. (2002). Social innovation capital. Journal <strong>of</strong> Intellectual Capital, 3(1):30-39.
Monaghan, J. (2007). Linking school ma<strong>the</strong>matics to out-<strong>of</strong>-school ma<strong>the</strong>matical activities: student interpretation
<strong>of</strong> task, understandings and goals. International Electronic Journal <strong>of</strong> Ma<strong>the</strong>matics Education, 2(2):50-71.
Muller, P. (2006). Reputation, trust and <strong>the</strong> dynamics <strong>of</strong> leadership in communities <strong>of</strong> practice. Journal <strong>of</strong>
Management and Governance, 10(4):381-400.
Preece, J. (2000). Online communities: Designing usability, supporting sociability. New York, NY: John Wiley &
Sons.
Roberts, J. (2000). From know-how to show-how: The role <strong>of</strong> information and communications technology in <strong>the</strong>
transfer <strong>of</strong> knowledge. Technology Analysis and Strategic Management, 12(4):429-43.
Sauve, E. (2007). Informal knowledge transfer. Training and Development, 61(3):22-25.
Slater, S.F. & Narver, J.C. (2000). Market oriented is more than being customer-led. Strategic Management
Journal, 20:1165-1168.
Tyler, J.R., Wilkinson, D.M. & Huberman, B.A. (n.d.). Email as spectroscopy: Automated discovery <strong>of</strong> community
structure within organisations. [Online]. Available from:
http://www.hpl.hp.com/research/idl/papers/email/email.pdf. (Accessed 8 September 2009).
Schwartz, M.F. & Wood, D.C.M. (1992). Discovering shared interests among people using graph analysis <strong>of</strong>
global electronic mail traffic. Communications <strong>of</strong> <strong>the</strong> ACM, 36(8):78-89.
Smith, M.K. (2006). Communities <strong>of</strong> practice. [Online]. Available from:
http://www.infed.org/biblio/communities_<strong>of</strong>_practice.htm. (Accessed 7 December 2009).
Thomas, B.S. (2002). Understanding communities <strong>of</strong> practice. [Online]. Available from:
http://www.totalkm.com/knxchanges/cop.html. (Accessed 10 June 2009).
Wathne K., Roos J. & von Krogh G. (1996). Towards a Theory <strong>of</strong> Knowledge Transfer in a Co-operative Context.
In von Krogh G. and Roos J. (Eds.) Managing Knowledge. Perspectives on Co-operation and Competition,
Sage.
Wellman, B. (2002). Designing <strong>the</strong> Internet for a networked society: Little boxes, globalisation and networked
individualism. Communications <strong>of</strong> <strong>the</strong> ACM, 45(5):91-96.
Wenger, E. (1998). Communities <strong>of</strong> practice. Learning as a social system. [Online]. Available from: http://www.coi-l.com/coil/knowledge-garden/cop/lss.shtml.
(Accessed 7 December 2009).
Wenger, E. (2004). Knowledge management as a doughnut: Shaping your knowledge strategy through
communities <strong>of</strong> practice. Ivey Business Journal, January/February.
Wenger, E., White, N., Smith, J.D. & Rowe, K. (2005). Technology for communities. [Online]. Available from:
http://www.technologyforcommunities.com. (Accessed 7 December 2009).
Whittaker, S. & Sidner, C. (1996). Email overload: Exploring personal information management <strong>of</strong> email. In
<strong>Proceedings</strong> <strong>of</strong> CHI ’96, ACM Press, pp. 276-283.
112

The Mediating Effects <strong>of</strong> Sensemaking and Measurement
on <strong>the</strong> Intellectual Capital and Performance Linkage
Donley Carrington 1 and Mike Tayles 2
1 University <strong>of</strong> <strong>the</strong> West Indies, Barbados
2 Hull University Business School, UK
donley.carrington@cavehill.uwi.edu
m.e.tayles@hull.ac.uk
Abstract: Intellectual capital can be a major factor that can aid Caribbean policy makers as <strong>the</strong> region transitions
from agricultural based to services based economies with tourism being <strong>the</strong> largest contributor to GDP. This
paper adds to <strong>the</strong> extant literature by providing literature on IC within <strong>the</strong> Caribbean and <strong>the</strong> tourism industry.
Additionally, while <strong>the</strong> research has emphasized defining and measuring IC and its components, and <strong>the</strong>ir impact
on firm’s performance <strong>the</strong>oretical questions remain concerning <strong>the</strong> synergistic, dynamic and contextual nature <strong>of</strong>
IC. Therefore this paper adds to <strong>the</strong> literature by using sensemaking to provide <strong>the</strong> foundation for understanding
<strong>the</strong> interaction <strong>of</strong> <strong>the</strong> IC components and firm’s performance. This paper reports on <strong>the</strong> development and testing
<strong>of</strong> a <strong>the</strong>oretical model concerning <strong>the</strong> mediating effects <strong>of</strong> measurement <strong>of</strong> IC and sensemaking on <strong>the</strong>
components <strong>of</strong> IC and performance linkage. SEM was used to test <strong>the</strong> model and structural relationships among
<strong>the</strong> variables. The study shows that HC, RC and SC are related to sensemaking, that measurement <strong>of</strong> IC is
associated with performance, that measurement <strong>of</strong> IC mediates <strong>the</strong> relationships between RC and performance
and SC and performance, and it validates <strong>the</strong> relationship between HC and performance.
Keywords: Caribbean, intellectual capital, sensemaking, SEM, hospitality
1. Introduction
The Caribbean has been transitioning from agricultural based economies to economies based on
services, with tourism being <strong>the</strong> largest contributor to GDP. This “intangible” economy has resulted in
a change from tangible assets being <strong>the</strong> major driver <strong>of</strong> performance to intangibles playing a key role
in that performance. The intangibles, such as employee competencies, technical and administrative
infrastructure and organizational processes will all influence <strong>the</strong> entity’s performance. The Human
Resource, Marketing and Information Systems fraternities have each argued <strong>of</strong> <strong>the</strong> relationship
between <strong>the</strong>ir component and firm’s performance. Given <strong>the</strong>se approaches, it is understandable why
current IC researchers, have ei<strong>the</strong>r examined <strong>the</strong> independent relationships existing between each IC
component and performance, or have proposed that one component is more important than ano<strong>the</strong>r
(Riahi-Belkaoui, 2003; Youndt and Snell 2004). This has compounded <strong>the</strong> problem <strong>of</strong> valuing IC in
organizations. Many corporate leaders are left without an understanding <strong>of</strong> <strong>the</strong> importance <strong>of</strong> IC to
organizational effectiveness, whereas, <strong>the</strong>y understand <strong>the</strong> importance <strong>of</strong> <strong>the</strong> tangible and financial
assets.
Thus, while progress has been made in IC research, few studies have been presented on developing
countries with Malaysia (Tayles et al., 2007) and Sri Lanka (Abeyesekera 2008) being <strong>the</strong> exceptions.
Locating <strong>the</strong> research in <strong>the</strong> Caribbean hospitality industry, this study contributes to <strong>the</strong> extant IC
literature and practice within <strong>the</strong> hospitality industry. To date three studies have been conducted on IC
within <strong>the</strong> hospitality industry Anton et al, (2005), Engstrom et al, (2003) and Erickson and McCall
(2008). Additionally, sensemaking is used to provide <strong>the</strong> foundation for understanding how <strong>the</strong> three
IC components interact. Accordingly this paper, which is part <strong>of</strong> a larger study that investigated <strong>the</strong>
characteristics and significance placed on <strong>the</strong> various components <strong>of</strong> IC and <strong>the</strong> measurement <strong>of</strong> IC
in <strong>the</strong> Caribbean hospitality industry, reports on <strong>the</strong> development and testing <strong>of</strong> a <strong>the</strong>oretical model
concerning <strong>the</strong> mediating effects <strong>of</strong> measurement <strong>of</strong> IC and sensemaking on <strong>the</strong> components <strong>of</strong> IC
and performance linkage.
2. Literature review
Intellectual Capital represents <strong>the</strong> resources <strong>of</strong> an organisation that have been formalized, captured
and leveraged to create assets <strong>of</strong> a higher value (Bontis 1999, Sveiby 1997). The first stage in <strong>the</strong>
development <strong>of</strong> IC literature focused on <strong>the</strong> presentation <strong>of</strong> models and <strong>the</strong> development <strong>of</strong>
frameworks, while <strong>the</strong> second stage focused on <strong>the</strong> impact <strong>of</strong> IC on <strong>the</strong> behaviour <strong>of</strong> markets (Petty
and Guthrie 2000). The debate continues pertaining to defining IC and this lack <strong>of</strong> consensus on an
agreed taxonomy <strong>of</strong> IC has resulted <strong>the</strong> research being mixed or poorly defined. However, in seeking
113

Donley Carrington and Mike Tayles
to develop a definition <strong>of</strong> IC a deconstruction <strong>of</strong> <strong>the</strong> concept has resulted in three components, human
capital, relational capital and structural capital forming <strong>the</strong> conceptual framework.
Human capital is not measured by <strong>the</strong> number <strong>of</strong> employees but it relates to employees’ education,
skills, training, experience, attitudes, genetic inheritance and values (Litschker et al., 2006). Relational
capital refers to ei<strong>the</strong>r relationships existing between employees and external economic actors
(Stewart, 1997), or relationships existing among employees and o<strong>the</strong>r departments within <strong>the</strong>
organisation (Tsai and Ghoshal 1998). Structural capital includes all <strong>the</strong> non-human storehouses <strong>of</strong>
knowledge in organizations and anything whose value to <strong>the</strong> company is higher than its tangible value
(Roos et al. 1997).
The literature has thus emphasized <strong>the</strong> direct link <strong>of</strong> <strong>the</strong>se individual components or <strong>the</strong> composite <strong>of</strong>
IC on a firm’s performance. The human resource management literature asserts that human capital is
one <strong>of</strong> <strong>the</strong> major factors contributing to <strong>the</strong> continued success <strong>of</strong> organizations as demonstrated in
studies by Huselid et al (1997) and Khandekar and Sharma (2005). The marketing fraternity purports
that <strong>the</strong>re is a relationship between relational capital and performance. Narver and Slater (1990)
empirical study has shown <strong>the</strong> RC element <strong>of</strong> market orientation positively affects performance. The
SC developed in organisations through <strong>the</strong>ir information systems and management processes also
leverage an organisation’s performance. Huang and Liu (2005) found that innovation capital has a
non-linear relationship with firm performance. Chen et al. (2005) in <strong>the</strong>ir study found that IC has a
positive impact on market value and financial performance. Wang and Chang (2005) showed that <strong>the</strong>
IC components affected performance directly, with <strong>the</strong> exception <strong>of</strong> human capital which influences
performance indirectly through <strong>the</strong> o<strong>the</strong>r IC components.
A process that illustrates how organisations can routinely integrate <strong>the</strong> three intellectual capital
components is sensemaking. This concept <strong>of</strong> sensemaking is defined by Weick (1995) as a process
<strong>of</strong> making sense and assigning meaning to events in <strong>the</strong> environment, by applying stored knowledge,
experience, values and beliefs to new situations in an effort to understand <strong>the</strong>m. Thomas, Clark and
Gioia (1993, p.240) describe sensemaking as "<strong>the</strong> reciprocal interaction <strong>of</strong> information seeking,
meaning ascription, and action”. Theoretically, <strong>the</strong> more competent an organization’s workforce (HC),
well developed and highly effective its repositories <strong>of</strong> codified knowledge (SC) and opportunities for
engaging in social networks (RC), individuals will be able to more effectively make sense <strong>of</strong> events
within it. Penrose (1959) asserts that a firm be viewed as "a collection <strong>of</strong> individuals who have had
experience in working toge<strong>the</strong>r, for only in this way can 'teamwork' be developed" (1959: 46), which
would suggest a relationship between human capital and sensemaking. Shariq (1998) argues that, in
order to make sense or create understanding, humans bring prior knowledge and context to <strong>the</strong>
information and without <strong>the</strong> human context <strong>the</strong> information by itself will have no meaning. The
structural capital and <strong>the</strong> relational capital in a firm can be enhanced by its relationship with
sensemaking in that <strong>the</strong>re are many aspects to <strong>the</strong> learning embedded in such shared experience.
Therefore it is posited that <strong>the</strong>re is a relationship among <strong>the</strong> components <strong>of</strong> IC and sensemaking.
Additionally, <strong>the</strong> literature demonstrates a relationship between sensemaking and performance.
Thomas, Clark and Gioia (1993) tested <strong>the</strong> relative strength <strong>of</strong> <strong>the</strong> direct and indirect paths between
sensemaking activities <strong>of</strong> scanning, interpretation and action on performance and found that <strong>the</strong>
performance measures were significantly related to <strong>the</strong> sensemaking processes.
Measurement has always been important for organizations to assess <strong>the</strong>ir performance in key areas.
A plethora <strong>of</strong> literature has been published in support <strong>of</strong> methods for measuring and managing IC.
Sveiby (2005) has identified 34 such measurement techniques. However, <strong>the</strong> validity <strong>of</strong> <strong>the</strong>se
measurement systems has been challenged. Pike and Roos (2004) have argued that completeness,
distinctness, independence, agreeability and commensurability should be present in any model
proposing to measure business performance. Their study revealed that a number <strong>of</strong> <strong>the</strong> IC
measurement models did not meet <strong>the</strong> tenets <strong>of</strong> measurement <strong>the</strong>ory identified.
In assessing <strong>the</strong> validity <strong>of</strong> measurement in <strong>the</strong> IC arena, one can examine its ability to affect
behaviour ra<strong>the</strong>r than to represent properties <strong>of</strong> objects in numerical terms. Flamholtz (1980) asserted
that <strong>the</strong> purpose <strong>of</strong> measurement in organisations is to influence people behaviour. He argues that
measurement is intended to perform certain predefined psychological functions through its process
and its output. The output function, which is <strong>the</strong> numbers produced by <strong>the</strong> act <strong>of</strong> measurement, is
used as an input signal to facilitate decisions and actions, <strong>the</strong> process function on <strong>the</strong> o<strong>the</strong>r hand,
serves as a catalyst for systematic planning, establishes an operational criterion, and motivates <strong>the</strong>
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decision-makers. In support <strong>of</strong> Flamholtz’s (1980) notion <strong>of</strong> <strong>the</strong> dual role <strong>of</strong> measurement, <strong>the</strong>
measurement <strong>of</strong> IC can be approached from an internal focus where <strong>the</strong> issues raised about
behavoiural changes due to <strong>the</strong> process <strong>of</strong> measurement will be addressed or from an external focus
which requires that <strong>the</strong> properties outlined in <strong>the</strong> scientific approach to measurement being adhered
to. Research pertaining to <strong>the</strong> scientific approach to measurement <strong>of</strong> IC which is appropriate for those
measures that have an external focus has attracted a fleeting glance in <strong>the</strong> literature, whereas <strong>the</strong>
behavioural implication <strong>of</strong> measurement <strong>of</strong> IC has not received any attention.
3. Methodology
A quantitative approach was used to assess <strong>the</strong> significance placed on IC and <strong>the</strong> impact <strong>of</strong> IC on
performance in <strong>the</strong> hospitality industry in <strong>the</strong> Caribbean. The three independent variables were
human capital, relational capital and structural capital, dependent variable was performance and <strong>the</strong>
mediating variables were sensemaking and measurement <strong>of</strong> IC in <strong>the</strong> model testing <strong>the</strong> hypo<strong>the</strong>sized
relationships as depicted in Figure 1.
Human Capital
Relational Capital
Structural Capital
Sensemaking
Measurement
<strong>of</strong> IC
Perceived
Performance
Figure 1: The hypo<strong>the</strong>sized model
A survey was used as <strong>the</strong> data collection method. Human capital was measured with 16 items,
relational capital 17 items and structural capital 15 items. These items were drawn from items used by
Bontis (1998), Han et al (1998), Youndt and Snell (2004), Reed et al (2006), and Huang, Lu<strong>the</strong>r et al.
(2007). The mediating variable <strong>of</strong> sensemaking was measured with eight items drawn from empirical
studies by Thomas and McDaniel (1990), and Gioia and Thomas (1996). The second mediating
variable Measurement <strong>of</strong> IC contained 13 items drawn from <strong>the</strong> work <strong>of</strong> Brander-Brown and McDowell
(1995), Sveiby (1997) and Stewart (1997). The items used to measure <strong>the</strong>se mediating variables are
described in Appendix 1. The dependent variable performance was assessed by 14 items, guided by
<strong>the</strong> work <strong>of</strong> Brander Brown and McDonnell (1995), Fitzgerald and Moon (1996) and Bontis (1997).
The survey instrument was piloted to a mixture <strong>of</strong> academics and pr<strong>of</strong>essionals within <strong>the</strong> hospitality
industry. The results <strong>of</strong> <strong>the</strong> pilot process were used to revise <strong>the</strong> questionnaire.
The telephone directories <strong>of</strong> <strong>the</strong> various territories within <strong>the</strong> Caribbean were used to provide <strong>the</strong>
sampling frame. This provided a comprehensive list <strong>of</strong> all types <strong>of</strong> accommodations within <strong>the</strong> study
area. The websites <strong>of</strong> <strong>the</strong> Caribbean Tourism Organisation and <strong>the</strong> Caribbean Hotel Association were
used to provide information on <strong>the</strong> number <strong>of</strong> rooms for each property identified in <strong>the</strong> sampling
115

Donley Carrington and Mike Tayles
frame. The result <strong>of</strong> this activity provided a sampling frame <strong>of</strong> 1,291 properties. The list was reduced
to 429 properties by excluding guesthouses and properties with less than 40 rooms.
Given <strong>the</strong> demographics and geography <strong>of</strong> <strong>the</strong> Caribbean, a local resident was used as <strong>the</strong> conduit
for <strong>the</strong> distribution and return <strong>of</strong> <strong>the</strong> questionnaires from <strong>the</strong> 429 properties within <strong>the</strong> fifteen
territories. The initial posting resulted in 46 questionnaires being returned. Follow up processes were
implemented which resulted in a 42 percent return rate. Non response bias was evaluated using
Lambert and Harrington (1990) approach. The t-tests revealed no significant difference among <strong>the</strong>
twenty survey items tested. These results do not rule out non-response bias, but suggest that nonresponse
may not be a problem.
4. Results and discussion
The results <strong>of</strong> <strong>the</strong> CFA in relation to <strong>the</strong> measurement models for <strong>the</strong> constructs <strong>of</strong> human capital,
relational capital, structural capital, sensemaking, measurement <strong>of</strong> IC and performance were
assessed for unidimensionality, convergent validity, average variance extracted and discriminant
validity. The results revealed that <strong>the</strong> unstandardized coefficients exceeded twice <strong>the</strong> respective
standard errors for <strong>the</strong> indicators thus suggesting evidence <strong>of</strong> convergent validity. Table 1 indicates
that <strong>the</strong> factors have construct validity as construct reliabilities exceeded 0.79, variance extracted in
excess <strong>of</strong> 0.4 and factor loadings in excess <strong>of</strong> 0.4. All error variances were positive and all critical
ratios significant as <strong>the</strong>y exceeded 1.96.
Table 1: Selected results from Amos
Indicator Variance extracted Minimum factor Construct Cronbach’s Alpha
loading
reliability
HC 0.4836 0.607 0.808 .888
RC 0.4290 0.657 0.812 .888
SC 0.5587 0.624 0.796 .857
Sensemaking 0.5040 0.527 0.964 .838
Measurement <strong>of</strong> IC 0.4100 0.4916 0.858 .815
Performance 0.6462 0.713 0.966 .944
In relation to <strong>the</strong> IC components <strong>the</strong> chi-square difference test was used to assess discriminant
validity. The results revealed that <strong>the</strong> Χ 2 value received from <strong>the</strong> unconstrained model was lower than
<strong>the</strong> values received in <strong>the</strong> model where <strong>the</strong> trait correlations are constrained to unity. This indicated
that <strong>the</strong> traits were not perfectly correlated and discriminant validity was achieved.
The structural models for <strong>the</strong> IC constructs <strong>of</strong> HC, RC and SC, <strong>the</strong> mediating variables <strong>of</strong>
sensemaking and measurement <strong>of</strong> IC and <strong>the</strong> dependent variable performance were assessed using
selected indices <strong>of</strong> GFI, IFI, CFI, RMSEA and Χ 2 presented in table 2.
Table 2: Selected indices
Indicator Χ 2 df p GFI IFI CFI RMSEA
Human Capital 46.706 27 .014 .942 .972 .971 .063
Relational Capital 18.104 9 .034 .967 .947 .946 .079
Structural Capital 34.127 14 .002 .947 .975 .975 .089
Intellectual Capital 310.884 206 .000 .906 .944 .944 .054
Sensemaking 43.123 9 .000 .925 .924 .926 .147
Measurement <strong>of</strong> IC 6.728 5 .242 .984 .991 .991 .044
Performance 111.0 27 .002 .919 .930 .929 .073
The results indicated a poor fit using <strong>the</strong> chi-square only to test <strong>the</strong> statistical fit <strong>of</strong> <strong>the</strong> intellectual
capital. The subjective indices indicate a reasonably good fit for <strong>the</strong> model (GFI =.906; CFI = .944;
RMSEA = .054). Table 2 indicated that <strong>the</strong> values for <strong>the</strong> GFI, IFI, CFI and RMSEA fall within <strong>the</strong> cut<strong>of</strong>fs
as advocated by Bentler and Bonett (1980) and Bollen (1989). The selected indices for <strong>the</strong>
structural model for sensemaking with <strong>the</strong> exception <strong>of</strong> <strong>the</strong> RMSEA fall within <strong>the</strong> accepted
thresholds. The results for <strong>the</strong> structural models for measurement <strong>of</strong> IC and performance indicated
that <strong>the</strong> model have an acceptable fit as all indices were within <strong>the</strong> acceptable thresholds. These
results in conjunction with correlation analysis (table 3) among <strong>the</strong> variables indicated that a model to
test <strong>the</strong> mediating roles <strong>of</strong> sensemaking and measurement <strong>of</strong> IC on <strong>the</strong> components <strong>of</strong> IC and
perceived performance could be developed.
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Table 3: Pearson’s correlation coefficients (N=182)
Variable HC SC RC SM ICM HPP
Human Capital (HC)
Structural Capital (SC) .528
Relational Capital (RC) .429 .583
Sensemaking (SM) .544 .772 .622
Measurement (ICM) .225 .489 .252 .348
Perceived Performance (HPP) .413 .480 .288 .432 .437
The correlation statistics are all significant at p

Donley Carrington and Mike Tayles
level (∆Χ 2 , 3 d.f. = 5.337) whereas <strong>the</strong> Χ 2 difference test between <strong>the</strong> full mediation and <strong>the</strong> direct
effects models was significant at <strong>the</strong> p < 0.05 level (∆Χ 2 , 1 d.f. = 6.282). The full mediation model was
<strong>the</strong> preferred model and used to test for mediation based on Hair et al (2006) approach.
The results <strong>of</strong> <strong>the</strong> measurement model revealed, <strong>the</strong> standardized regression weights for <strong>the</strong> manifest
variables exceeded 0.5, positive error variances, and 13 <strong>of</strong> <strong>the</strong> 14 critical ratios were significant at <strong>the</strong>
p

Donley Carrington and Mike Tayles
In evaluating measurement <strong>of</strong> IC as a mediating variable table 6 presents <strong>the</strong> standardized path
coefficients for <strong>the</strong> paths between <strong>the</strong> mediator measurement <strong>of</strong> IC and <strong>the</strong> components <strong>of</strong> IC and <strong>the</strong>
dependent variable performance.
Table 6: Standardized path coefficients for measurement <strong>of</strong> IC
Independent
Variable
Step 1
Perceived
performance
Standardized Path coefficients
(given if significant at 0.05 or less)
Step 2
Measurement <strong>of</strong>
IC
Dependent variable
Step 3
Perceived
performance
Interpretation
HC .220 * .092 (ns) .197 * No mediation
RC .250 * -.313 * -.093 (ns) Full mediation
SC .583 * .731 * .229 * Partial mediation
Mediator
Measurement <strong>of</strong> IC .318 * Significance achieved
mediation is possible
* significant at 0.05 or less
Step 1 – Path coefficients between HC, RC and SC and performance
Step 2 – Path coefficients between HC, RC and SC and measurement <strong>of</strong> IC (mediator)
Step 3 – Path coefficients between HC, RC and SC and performance with measurement <strong>of</strong> IC as
mediator
The non-significant path between measurement <strong>of</strong> IC and HC would indicate that <strong>the</strong>re is no
mediatory role <strong>of</strong> measurement <strong>of</strong> IC between HC and performance. The non-significant path
between RC and performance in step 3, while <strong>the</strong> paths between RC and measurement <strong>of</strong> IC in step
2 and between RC and performance in step 1 are significant this would indicate full mediation. In <strong>the</strong>
case <strong>of</strong> SC and measurement <strong>of</strong> IC being a mediator, all three paths are significant at <strong>the</strong> 0.05 or less
level toge<strong>the</strong>r with <strong>the</strong> standardized path coefficient in step 1 being higher than in step 3 this supports
a hypo<strong>the</strong>sis <strong>of</strong> partial mediation.
HC had a direct positive effect on Performance as <strong>the</strong> standardized parameter estimate between <strong>the</strong>
two constructs was 0.197 with a critical ratio <strong>of</strong> 2.124 and a p-value <strong>of</strong> 0.034. This finding
corroborates that <strong>of</strong> Youndt and Snell (2004) who reported in <strong>the</strong>ir study that HC was significantly
related to performance (β= 0.211, p

Donley Carrington and Mike Tayles
indirectly associated with performance through <strong>the</strong> employee and operational measures. The direct
effects model <strong>the</strong> path coefficient between <strong>the</strong> two constructs has a standardized parameter estimate
<strong>of</strong> 0.229 that is positive, with a critical ratio <strong>of</strong> 1.105 and p-value=0.269. This insignificant direct effect
between SC and performance implies that internal organisational systems, repositories <strong>of</strong> knowledge,
routines and procedures, and <strong>the</strong> information systems designed to capture, store and disseminate <strong>the</strong>
organizational explicit knowledge do not appear to impact directly on <strong>the</strong> performance <strong>of</strong> <strong>the</strong> hotels in
<strong>the</strong> Caribbean. This finding which is similar to that <strong>of</strong> Cleary (2009) does not corroborate o<strong>the</strong>r
empirical studies (Do Rosario Cabrita and Landeira Vaz 2006).
The results indicated that <strong>the</strong> path coefficient between measurement <strong>of</strong> IC and performance was
0.229, which was statistically significant (p < .01). This implied a modest but significant relationship
between <strong>the</strong> measurement <strong>of</strong> IC and performance as supported in earlier studies (Van der Stede et
al., 2006 and Hyvonen, 2007). This study supports Widener (2006) who found that firms which
established a performance measurement system that provide top managers with critical information
pertaining to its resources and capability positively affected <strong>the</strong>ir performance.
5. Conclusion
This research sought to examine <strong>the</strong> impact <strong>of</strong> IC on firm performance mediated by measurement <strong>of</strong>
IC and sensemaking in <strong>the</strong> Caribbean. While a rich source <strong>of</strong> <strong>the</strong>oretical and normative research
exists, <strong>the</strong> paucity <strong>of</strong> empirical research on <strong>the</strong> topic in developing countries created <strong>the</strong> catalyst and
provided few leads on how to operationalise <strong>the</strong> constructs <strong>of</strong> <strong>the</strong> components <strong>of</strong> IC in order to study
<strong>the</strong>ir impacts. The results achieved found <strong>the</strong>oretical support, adding a degree <strong>of</strong> validation to <strong>the</strong>
methods adopted. Some unexpected results were also investigated, finding viable explanations in <strong>the</strong>
interaction effects between <strong>the</strong> main variables. The study provided a unique framework, model,
survey instruments and empirical analysis to measure relationships among <strong>the</strong> constructs <strong>of</strong> HC, RC,
SC, measurement <strong>of</strong> IC, sensemaking and performance. Empirical results <strong>of</strong> <strong>the</strong> current study provide
evidence that HC impacted directly on performance; RC and SC impacted indirectly on performance
being mediated by measurement <strong>of</strong> IC; and HC, RC and SC have a positive and significant
relationship with sensemaking.
The empirical findings have provided additional precision to <strong>the</strong> underlying <strong>the</strong>ories. This study
provided an ‘all-in-one’ model and methodology for testing relationships among <strong>the</strong> components <strong>of</strong> IC,
sensemaking, measurement <strong>of</strong> IC and performance. The uniqueness <strong>of</strong> this study rests in <strong>the</strong> fact that
it <strong>of</strong>fers a methodology for examining a new combination <strong>of</strong> constructs arranged in a specific pattern.
These ideas and contributions are special, since a newly developed model was added to <strong>the</strong> IC
literature, in that, this study provided a model indicating how IC can be leveraged to have a significant
impact on performance. These findings show that hotels can build this strategic capability by
management effectively deploying practices which facilitate <strong>the</strong> interaction and interrelationships
among <strong>the</strong> three components <strong>of</strong> IC.
6. Appendix 1
Sense-making scale
SM1 One or two members <strong>of</strong> <strong>the</strong> team dominate <strong>the</strong> decision making #
SM2 In <strong>the</strong> hotel <strong>the</strong>re is free and open exchange <strong>of</strong> idea among members <strong>of</strong> <strong>the</strong> team
SM3 Decision making in this hotel is participative
SM4 Committees, cross functional teams, task groups are regularly formed to deal with strategic
issues.
SM5 All members <strong>of</strong> <strong>the</strong> management team participate in strategic decision making on a regular basis
SM6 Decision making in <strong>the</strong> hotel is interactive
SM7 When faced with a problem/situation I use my previous experience to solve <strong>the</strong> problem #
SM8 Written rules and procedures are followed when addressing issues
# Items removed after CFA due to factor loadings below 0.5
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Measurement <strong>of</strong> IC Scale
Donley Carrington and Mike Tayles
M1 We have greatly reduced <strong>the</strong> time it takes to resolve a customer problem #
M2 Our hotel has a high turnover <strong>of</strong> Tour companies and o<strong>the</strong>r travel affiliates #
M3 The time it takes to go through a process (check-in/out, booking, cleaning, serving) has been
decreasing over <strong>the</strong> years.
#
M4 Our hotel tracks <strong>the</strong> number <strong>of</strong> hours <strong>of</strong> training for each employee #
M5 Customer satisfaction
M6 Employee satisfaction #
M7 Customer complaints
M8 Customer retention
M9 Employee training
M10 Market share
M11 We take action in <strong>the</strong> organisation because we know that we are being evaluated #
M12 The ratio <strong>of</strong> revenue earn per employee in <strong>the</strong> hotel has been increasing over <strong>the</strong> past two
years
#
M13 We quite <strong>of</strong>ten use “mystery guests” to evaluate our customer service #
# Items removed after CFA due to factor loadings below 0.5
Items 5 – 10 were measured using a seven point Likert Scale where respondents were asked “In your
assessment, what is <strong>the</strong> extent to which <strong>the</strong> following are measured in your hotel? Please use <strong>the</strong>
scale [Infrequently = 1, very frequently = 7]”. The o<strong>the</strong>r items were assessed using a seven point
Likert scale using 7 for strongly agreed and 1 strongly disagreed.
References
Abeysekera, I. (2008) Intellectual capital disclosure trends: Singapore and Sri Lanka. Journal <strong>of</strong> Intellectual
Capital, 9, 723.
Anton, J. M., Andrada, L. R. & Alberdi, C. E. (2005) Proposal <strong>of</strong> an Intellectual Capital model for <strong>the</strong> Spanish
hospitality sector. International Journal <strong>of</strong> learning and intellectual capital, 2, 305-320.
Bentler, P. M. & Bonett, D. (1980) Significance tests and goodness <strong>of</strong> fit in <strong>the</strong> analysis <strong>of</strong> covariance structures.
Psychological Bulletin, 88, 588-606.
Bontis, N. (1998) Intellectual Capital: an exploratory study that develops measures and models Management
Decision, 36, 63-76.
Bontis, N., Chua, C. K. & Richardson, S. (2000) Intellectual capital and business performance in Malaysian
industries. Journal <strong>of</strong> Intellectual Capital, 1, 85-100.
Bontis, N., Dragonetti, N., Jacobsen, K. & Roos, G. (1999) The Knowledge Toolbox: A Review <strong>of</strong> <strong>the</strong> tools
available to measure and manage intangible resources. <strong>European</strong> Management Journal, 17, 391-402.
Brander-Brown, J. & Mcdonnell, B. (1995) The balanced score-card: short-term guest or long-term resident?
International Journal <strong>of</strong> Contemporary Hospitality Management,, 7, 7-11.
Chen, M.-C., Cheng, S.-J. & Yuhchang, H. (2005) An empirical investigation <strong>of</strong> <strong>the</strong> relationship between
intellectual capital and firm's market value and financial performance. Journal <strong>of</strong> Intellectual Capital, 6, 159-
177.
Cleary, P. (2009) Exploring <strong>the</strong> relationship between management accounting and structural capital in a
knowledge intensive sector. Journal <strong>of</strong> Intellectual Capital, 10, 37-52.
Do Rosario Cabrita, M. & Bontis, N. (2008) Intellectual capital and business performance in <strong>the</strong> Portuguese
banking industry. International Journal <strong>of</strong> Technology Management, 43, 212-.
Edvinsson, L. & Malone, M. (1997) Intellectual capital: Realizing your company's true value by finding its hidden
brainpower, New York, Harper Collins.
Engstorm, T. E. J., Westnes, P. & Westnes, S. (2003) Evaluating intellectual capital in <strong>the</strong> hotel industry. Journal
<strong>of</strong> Intellectual Capital, 4, 289-303.
Erickson, G. S. & Mccall, M. (2008) Intellectual capital and <strong>the</strong> hospitality industry. Competition Forum, 6.
Fitzgerald, L. & Moon, P. (1996) Performance Measurement in Service Industries: Making it Work London, CIMA.
Flamholtz, E. (1980) The process <strong>of</strong> measurement in managerial accounting: A Psycho-technical systems
perspective. Accounting, Organisations and Society.
121

Donley Carrington and Mike Tayles
Goh, P. C. & Lim, K. P. (2004) Disclosing intellectual capital in company annual reports: Evidence from Malaysia.
Journal <strong>of</strong> Intellectual Capital, 5, 500-511.
Hair, J. F., Black, W. E., Anderson, R. E. & Tatham, R. L. (2006) Multivariate data analysis, Upper Saddle River,
Pearson/Prentice Hall.
Han, J. K., Kim, N. & Srivastiva, R. (1998) Market orientation and organizational performance: is innovation a
missing link? Journal <strong>of</strong> marketing, 62, 30-45.
Huang, C. J. & Liu, C. J. (2005) Exploration for <strong>the</strong> relationship between innovation, IT and performance. Journal
<strong>of</strong> Intellectual Capital, 6, 237 - 252.
Huselid, M., Jackson, S. & Schuler, R. (1997) Technical and strategic human resource management
effectiveness as determinants <strong>of</strong> firm performance. The Academy <strong>of</strong> Management Journal.
Kaplan, R. S. & Norton, D. (1996) Using <strong>the</strong> balance scorecard as a strategic management system. Harvard
Business Review,, 74, 75-86.
Khandekar, A. & Sharma, A. (2005 ) Managing human resource capabilities for sustainable competitive
advantage: An empirical analysis from Indian global organisations Education and Training, 47, 628-639.
Kline, R. B. (1998) Principles and Practice <strong>of</strong> Structural Equation Modeling, New York, The Guildford Press.
Lambert, D. & Harrington, T. (1990) Measuring nonresponse bias in customer service mail surveys. Journal <strong>of</strong>
Business Logistics, 11, 5-25.
Litschker, M., Markom, A. & Schunder, S. (2006) Measuring and analyzing intellectual assets: an integrative
approach. Journal <strong>of</strong> Intellectual Capital, 7, 160-174.
Moon, Y. & Kym, H. G. (2006) A model for <strong>the</strong> value <strong>of</strong> Intellectual Capital. Canadian Journal <strong>of</strong> Administrative
Sciences, 23, 253-269.
Narver, J. C. & Slater, S. F. (1990) The Effect <strong>of</strong> a Market Orientation on Business Pr<strong>of</strong>itability Journal <strong>of</strong>
Marketing, 54, 20-35.
Penrose, E. T. (1959) The Theory <strong>of</strong> Growth <strong>of</strong> <strong>the</strong> Firm London: Oxford University Press.
Petty, R. & Guthrie, J. (2000) Intellectual Capital Literature Review: Measurement, Reporting and Management.
Journal <strong>of</strong> Intellectual Capital, 1, 155-176.
Pike, S. & Roos, G. (2004) Ma<strong>the</strong>matics and modern business management. Journal <strong>of</strong> Intellectual Capital, 5,
243-257.
Reed, K., Lubatkin, M. & Srinivasan, N. (2006) Proposing and Testing an Intellectual Capital-Based View <strong>of</strong> <strong>the</strong>
Firm. Journal <strong>of</strong> Management Studies, 43, 867-893.
Riahi-Belkaoui, A. (2003) Intellectual capital and firm performance <strong>of</strong> US multinational firms. A study <strong>of</strong> <strong>the</strong>
resource based and stakeholders views. Journal <strong>of</strong> Intellectual Capital, 4, 202-214.
Roos, J., Roos, G., Dragonetti, N. & Edvinsson, L. (1997) Intellectual Capital: Navigating <strong>the</strong> new business
landscape, London, Macmillan Press Ltd.
Shariq, S. Z. (1998) Sense making and artifacts: An exploration into <strong>the</strong> role <strong>of</strong> tools in knowledge management.
Journal <strong>of</strong> Knowledge Management., 2.
Stewart, T. (1997) Intellectual capital: The wealth <strong>of</strong> organizations, London, Nicholas Brealey Publishing.
Sveiby, K. (1997) The New Organizaational Wealth: Managing and Measuring Knowledge based assets, San
Francisco, Berrett-Koehler.
Sveiby K (2005) Measuring Models for Intangible Assets and Intellectual Capital
Tayles, M., Pike, R. & S<strong>of</strong>ian, S. (2007) Intellectual capital, management accounting practices and corporate
performance; perceptions <strong>of</strong> managers. Accounting, Auditing & Accountability Journal, 20, 522.
Thomas, J. B., Clark, S. M. & Gioia, D. A. (1993) Strategic Sensemaking and Organisational Performance:
Linkages among Scanning, Interpretation, Action and Outcomes. Academy <strong>of</strong> Management Journal, 36,
239-270.
Tsai, W. & Ghoshal, S. (1998) Social capital and value creation: The role <strong>of</strong> intrafirm networks. Academy <strong>of</strong>
Management Journal, 41, 464-477.
Wang, J. (2008) Investigating market value and intellectual capital for S&P 500. Journal <strong>of</strong> Intellectual Capital, 9,
546.
Wang, W.-Y. & Chang, C. (2005) Intellectual capital and performance in causal models: Evidence from <strong>the</strong>
information technology industry in Taiwan. Journal <strong>of</strong> Intellectual Capital, 6, 222-236.
Weick, K. (1995) Sensemaking in Organisations, London, Sage.
Widener, S. (2006) Associations between strategic resource importance and performance measure use: The
impact on firm performance Management Accounting Research, 17, 433-457.
Youndt, M. A. & Snell, S. A. (2004) Human resource configurations, intellectual capital and organisational
performance. Journal <strong>of</strong> management issues, 16, 337-361.
122

Is “If it Can’t be Measured it Can’t be Managed” Really
True?
John Dumay and Jim Rooney
University <strong>of</strong> Sydney, Australia
john.dumay@sydney.edu.au
jim.rooney@sydney.edu.au
Abstract: Is “If it can’t be measured it can’t be managed” really true? We cast doubt on its truth by critically
studying Intellectual Capital (IC) practice over six years at an internationally recognised public sector IC leader.
During this time <strong>the</strong> ‘Land and Property Authority <strong>of</strong> NSW’ (Lands) implemented IC practices. Initially Lands
struggled to cope with <strong>the</strong> significant challenges associated with retaining <strong>the</strong> knowledge ingrained in an ageing
workforce but as a result succeeded becoming a growing dynamic Government Business Enterprise (GBE) at a
time when most <strong>of</strong> <strong>the</strong> public sector is getting smaller. During <strong>the</strong> IC journey Lands has achieved recognition for
its IC reporting and practices in <strong>the</strong> absence <strong>of</strong> a definitive set <strong>of</strong> IC measures. Lands struggled with an inability
to develop a specific set <strong>of</strong> IC metrics to communicate its success. However, Lands effectively communicates <strong>the</strong>
impact <strong>of</strong> its IC practices through its IC statements based on an ongoing narrative. We conclude from <strong>the</strong>
evidence presented that IC practices are possible without necessarily needing concrete IC measures. The
conclusion highlights <strong>the</strong> struggle many organisations face when developing appropriate IC measures. While
<strong>the</strong>re appears to be a fixation on developing ‘accounting for IC’, we advocate <strong>the</strong> fixation is misplaced and <strong>the</strong> IC
journey is better communicated narrating <strong>the</strong> story <strong>of</strong> how IC was mobilised. Doing so allows for more focus on
IC practices ra<strong>the</strong>r than accounting. This opens <strong>the</strong> debate as to whe<strong>the</strong>r accounting can provide a solution as IC
is more complex than providing an IC balance sheet.
Keywords: intellectual capital, measuring, managing, reporting, IC balance sheet, complexity
1. Introduction
The purpose <strong>of</strong> our paper is to examine whe<strong>the</strong>r or not <strong>the</strong> catchcry “If it can’t be measured it can’t be
managed” is true in <strong>the</strong> context <strong>of</strong> intellectual capital (IC). We are motivated to answer <strong>the</strong> catchcry
because <strong>the</strong> academic literature is preoccupied with continued calls for developing new IC measures
and frameworks. However a critique has emerged <strong>of</strong> developing new ways <strong>of</strong> measuring IC and
developing frameworks due to <strong>the</strong> plethora <strong>of</strong> existing frameworks and possible counterproductive
behavioural impacts. Managing via numbers has been identified as one <strong>of</strong> <strong>the</strong> “deadly sins” <strong>of</strong>
managing.
Our interest in exploring <strong>the</strong> catchcry results from our continued research into managing, measuring
and reporting <strong>of</strong> IC at <strong>the</strong> Land and Property Management Authority <strong>of</strong> NSW (Lands). More
specifically we were intrigued by <strong>the</strong> statement in 2009 Annual Report stating “we are challenged to
find improved metrics which reflect outcomes at an organisational level as well as remaining
meaningful and appropriate to our operational divisions”. Despite Lands having won several
prestigious awards for managing and reporting IC we witnessed continued tension in <strong>the</strong> balance
between measuring IC and managing IC.
In order to examine this tension we structure <strong>the</strong> paper as follows. First we present a brief review <strong>of</strong>
<strong>the</strong> contemporary literature in relation to measuring IC. Next we describe Lands and <strong>the</strong>ir IC
practices. This is followed by an analysis <strong>of</strong> <strong>the</strong> data from our research, which examines <strong>the</strong> tension
between measuring and managing IC. Finally, we summarise our conclusions, identify limitations and
avenues for future research
2. Literature review
Is <strong>the</strong> saying “If it can’t be measured, it can’t be managed” really true? Ever since Peter Drucker
(1954) introduced <strong>the</strong> concept <strong>of</strong> “Management by Objectives” (MBO) managers have been
preoccupied by <strong>the</strong>ir attempts to identify and measure key organisational objectives and measure
progress against <strong>the</strong>m. More specifically, from an IC perspective, frameworks such as <strong>the</strong> Balanced
Scorecard (BSC) are underpinned by <strong>the</strong> same logic. As Kaplan and Norton (1992, 71) attest “What
you measure is what you get”. Recent academic IC articles suggest <strong>the</strong> preoccupation with measuring
IC continues unabated. We examined recently published papers by <strong>the</strong> Journal <strong>of</strong> Intellectual Capital
(2009 and 2010) and found a continued concern for developing new IC measures or calls to develop
new IC frameworks. For example, from <strong>the</strong> new measures perspective, after examining IC in <strong>the</strong>
heath care industry Sillanpää et al. (2010, 119) concluded: “Future research on this topic could focus
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on a more detailed analysis <strong>of</strong> individual IC factors and seek suitable ways to manage and measure
<strong>the</strong>m”. Ano<strong>the</strong>r example is Cleary (2009, p. 37) who argues “… strongly that firms adapt/develop
management accounting systems to furnish <strong>the</strong>mselves with <strong>the</strong> appropriate information required for
<strong>the</strong> management and measurement <strong>of</strong> <strong>the</strong>ir increasingly valuable stock <strong>of</strong> IC”. From <strong>the</strong> frameworks
perspective, Ramírez (2010, p. 261) suggests “fur<strong>the</strong>r [public sector IC] research could attempt to
develop an intellectual capital framework that helps to understand <strong>the</strong> interrelationships between <strong>the</strong>
three IC components”. Secundo et al. (2010) go even fur<strong>the</strong>r and develop <strong>the</strong>ir own dashboard <strong>of</strong>
metrics for higher education and research. However, Dumay (2009a) critiqued <strong>the</strong> need to develop
more IC frameworks, as a plethora <strong>of</strong> IC measurement frameworks already exist (see Sveiby, 2010).
Additionally, Dumay (2009b, 489) “openly questions <strong>the</strong> need to develop fur<strong>the</strong>r IC <strong>the</strong>ory and
advocates a way forward by outlining a critical approach to researching and implementing IC in
practice”.
This critique <strong>of</strong> IC measurement and frameworks has extended beyond <strong>the</strong> annals <strong>of</strong> <strong>the</strong> Journal <strong>of</strong>
Intellectual Capital. In 2009 a special edition <strong>of</strong> Critical Perspectives in Accounting critically examined
measuring IC (see Mouritsen and Roslender, 2009). The papers investigate measuring IC from <strong>the</strong>
perspectives <strong>of</strong> ethics (Mårtensson, 2009; McPhail, 2009), transparency (Gowthorpe, 2009; Nielsen
and Madsen, 2009) and implementing IC measures in practice. Overall <strong>the</strong>re is a concern with
measuring IC and whe<strong>the</strong>r or not it produces <strong>the</strong> desired results (Mouritsen and Roslender, 2009,
802).
Catasús et al. (2007, p. 505) also explored measuring and managing IC and concluded “that <strong>the</strong>
relationship between indicating [measuring] and acting is not significant and that <strong>the</strong> introduction <strong>of</strong>
mobilizing gives a better model fit”. Their argument implies managing effectively requires action
before measuring can have any impact. Thus, measuring is about discerning <strong>the</strong> results <strong>of</strong> one’s
actions ra<strong>the</strong>r than measuring in <strong>the</strong> hope that something positive happens. Unfortunately if this is
done <strong>the</strong> o<strong>the</strong>r way around, by measuring first, significant problems can arise as lamented by Behn
(2003, 599) “…what people measure <strong>of</strong>ten is not precisely what <strong>the</strong>y want done. And people,
responding to <strong>the</strong> explicit or implicit incentives <strong>of</strong> <strong>the</strong> measurement, will do what people are
measuring, not what <strong>the</strong>se people actually want done”. As Kerr (1995) outlines this can be counterproductive
as people tend to be rewarded for achieving <strong>the</strong> numbers ra<strong>the</strong>r than being rewarded for
<strong>the</strong> desired outcomes. Demming (1986, 24) also identified <strong>the</strong> fallacy <strong>of</strong> managing by numbers by
advocating “running a company on visible figures alone” as one <strong>of</strong> <strong>the</strong> seven deadly sins <strong>of</strong> managing.
Additionally, he claims “<strong>the</strong> most important things can’t be measured” as <strong>the</strong>y are ei<strong>the</strong>r not known
until revealed or <strong>the</strong>ir importance is not know beforehand. Thus, <strong>the</strong> unease with numbers as an all
powerful and all knowing phenomenon extends beyond measuring IC.
The concern with measuring IC and its impact is intriguing and prompts <strong>the</strong> question “Does measuring
IC lead to managing IC?” We are motivated to explore this question as a result <strong>of</strong> our research at
Lands. We have been conducting research into IC practices at Lands since 2004 and noted in our
most recent round <strong>of</strong> interviews and analysis <strong>of</strong> IC statements a continued tension between
measuring and managing IC. Lands (2009, 14) states in its latest annual report “As in previous years,
we are challenged to find improved metrics which reflect outcomes at an organisational level as well
as remaining meaningful and appropriate to our operational divisions”. Yet, Lands is considered an
exemplary public sector entity in <strong>the</strong> practice <strong>of</strong> managing its IC, suggesting an ongoing tension in
between measuring and managing IC. Therefore we will explore whe<strong>the</strong>r or not measuring IC is
actually required for managing IC in <strong>the</strong> context <strong>of</strong> Lands.
3. Lands
Lands is an Australian public sector entity employing more than 2000 people. Formerly known as <strong>the</strong>
NSW Department <strong>of</strong> Lands from 2003 to July 2009 it was renamed as a result <strong>of</strong> <strong>the</strong> Government
creating thirteen separate super agency clusters from existing New South Wales (NSW) Departments.
Lands mainly comes under <strong>the</strong> auspice <strong>of</strong> <strong>the</strong> Minister for Planning. Additionally, Lands inherited
several o<strong>the</strong>r bodies dealing with managing and developing land in NSW (NSW Government, 2009).
Over <strong>the</strong> last decade Lands faced public sector reforms resulting in creating Government Business
Enterprise (GBE) structures. These structures focus on delivering pr<strong>of</strong>it to <strong>the</strong> Government ra<strong>the</strong>r than
requiring public funding, being typical <strong>of</strong> recent Australian public sector reforms (English et al., 2005).
By July 2010 Lands had completely converted its operations into GBEs. Thus, Lands relies on an
ability to generate revenue from <strong>the</strong> services provided to its customers to sustain and grow <strong>the</strong>
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organisation. As result, Lands’ managers need to focus on developing revenue streams from <strong>the</strong>ir
services and reporting <strong>the</strong> results to NSW Treasury and <strong>the</strong> wider community. The strategic
cornerstone <strong>of</strong> creating GBE structures was to “seek to identify, value and demonstrate <strong>the</strong>
Knowledge (Intellectual) Capital within <strong>the</strong> Department” (Lands 2004, 4). As a result a commitment
was made by <strong>the</strong> Director General to implement practices aimed at improving <strong>the</strong> IC and knowledge
stocks <strong>of</strong> Lands and to publish an IC statement in <strong>the</strong> 2004/2005 annual report. The statement, first
published in 2005, continues to be published (see Lands 2005a; 2006; 2007; 2008; 2009). Notably,
Lands was <strong>the</strong> first Australian Government entity to publish a specific IC statement and is seen as
leading exemplar <strong>of</strong> <strong>the</strong> practice from both a public sector and Australian perspective. From 2008 to
2010 Lands won <strong>the</strong> “Knowledge Capital Reporting Award” at <strong>the</strong> Australasian Reporting Awards 1 .
Additionally, Lands won <strong>the</strong> 2009 Asian Most Admired Knowledge Enterprise (MAKE) Award for <strong>the</strong>
public sector.
From <strong>the</strong> evidence above, we can conclude Lands is seen externally as successful in adopting IC
management and reporting practices. But <strong>the</strong> impetus <strong>of</strong> our paper is to examine <strong>the</strong> impacts from an
internal perspective, in particular <strong>the</strong> tension between measuring and managing IC we identified
earlier. Our data, based on <strong>the</strong> authors’ Lands research from 2005 to 2010, consists <strong>of</strong> field notes,
interview recordings and transcripts along with analysing documents such as meeting minutes,
business plans and annual reports. In our most recent research, conducted in 2010, we interviewed
senior management, most whom have participated since 2005, and new senior managers working
with <strong>the</strong> newly added bodies. We also continued to analyse annual reports and internal documents.
4. Measuring for managing?
Our motivation is to explore <strong>the</strong> emerging <strong>the</strong>me <strong>of</strong> measurement as a prerequisite for successfully
managing IC. We were motivated by Lands’ (2009, 14) admission that “we are challenged to find
improved metrics which reflect outcomes” so we decided to fur<strong>the</strong>r explore <strong>the</strong> <strong>the</strong>me. Initially Lands
advocated <strong>the</strong> Balanced Scorecard (BSC) as its main means <strong>of</strong> measuring IC (Lands 2004, 6). As a
result, <strong>the</strong> initial business plan for Lands (2005b) documented fifteen non-financial key performance
indicators (KPIs) within <strong>the</strong> BSC framework. For example, one strategic priority was to (Lands 2005b,
9) “Determine customer needs and service gaps by undertaking a market analysis and customer
survey” supported by <strong>the</strong> KPI <strong>of</strong> “% improvement in customer satisfaction”. However, within <strong>the</strong> plan
<strong>the</strong>re were no targets set for any <strong>of</strong> <strong>the</strong> indicators. Not setting targets may seem like not knowing
where one is going but as <strong>the</strong> Director General (DG) outlined in a 2005 interview:
“… <strong>the</strong> best application <strong>of</strong> <strong>the</strong> Balanced Scorecard is not to implement it chapter and
verse, a la Kaplan and Norton, but to take <strong>the</strong> framework and apply it and modify it to
your own organisational needs”.
Consistent with <strong>the</strong> DG’s words, when Lands released its second IC Statement (Lands 2005a, 11-8),
a tailored BSC framework and a modified Danish IC Statement framework were combined (see
Mouritsen et al., 2003) as Figure 1 outlines.
Figure 1: Lands IC statement framework 2006-9
1 See http://dev.arawards.com.au/index.php/eng/Winners/2010-Award-Recipients/Special-Awards
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Taking <strong>the</strong> strategic goal <strong>of</strong> improving customer satisfaction as a primary example, fur<strong>the</strong>r scrutiny <strong>of</strong>
customer satisfaction measures shows it is never explicitly achieved, as <strong>the</strong> original metric, “%
improvement in customer satisfaction”, does not appear in any IC Statement. However, over time, <strong>the</strong>
emerging role <strong>of</strong> measuring customer-oriented IC can be shown in Table 1.
Table 1: Customer based measures in Lands IC statements 2005-9
IC Statement Year 2005 2006 2007 2008 2009
Land title transactions registered x x x x
Plans registered x x x x
Copies <strong>of</strong> land title related documents supplied to customers x x x x
Boundary determinations x x x x
Survey enquiries x x x x
Number <strong>of</strong> formal customer complaints
New Soil Conservation Services clients:
x x x x
■ Consult x x x x
■ Works x x x x
■ Operations x x x x
% <strong>of</strong> all eligible perpetual leases converted to freehold x x x x
No. <strong>of</strong> major regional reserves established x x x x
Total recreational trails and tracks established on Crown land x x x
New land valuations issued to Office <strong>of</strong> State Revenue x
New land valuations issued for rating purposes x
Supplementary valuations issued x
Land valuation objections received x
Land valuation objections processed x
Percentage <strong>of</strong> land valuations changed as a result <strong>of</strong> objection x
Percentage <strong>of</strong> enclosure permits granted x
Number <strong>of</strong> Community Trust Boards x
New State Parks established x
No. <strong>of</strong> internet feedback requests x x
No. <strong>of</strong> hits on website x x
O<strong>the</strong>r customer based measures 2 22 12 12 12
The 2005 IC Statement reports only two measures, expanding to 22 in 2006 and stabilising to 12 in
subsequent years. However, a proxy measure such as “Number <strong>of</strong> formal customer complaints”
exists. But when examining <strong>the</strong> measure as summarised in Table 2, a 200% increase in complaints is
disclosed. A rejoinder to <strong>the</strong> increase in 2008 is disclosed in <strong>the</strong> 2009 IC Statement with a change in
recording <strong>of</strong> <strong>the</strong> measure, now based on <strong>the</strong> ISO9001:2000 quality standard. This implies ei<strong>the</strong>r a
tightening <strong>of</strong> <strong>the</strong> definition, causing an increase in formal complaints, or simply an increase in
complaints. Ei<strong>the</strong>r way, we cannot argue increasing customer satisfaction based on <strong>the</strong> disclosed
measures. More specifically, proxy measures are required, as a Lands wide customer survey was
never undertaken as originally intended.
Table 2: Formal customer complaints 2005-9
2005 2006 2007 2008 2009 %Change
Number <strong>of</strong> formal customer complaints 4 3 3 9 12 200%
Hence, we have a conundrum. How can Lands continue to advocate improvement in customer
satisfaction when <strong>the</strong> metrics <strong>of</strong> <strong>the</strong> IC report do not support <strong>the</strong> rhetoric? To answer, we outline <strong>the</strong>
method Lands employs to communicate developing IC via <strong>the</strong>ir IC Statements. In <strong>the</strong> 2008/9 IC
Statement Lands links <strong>the</strong> strategic priority <strong>of</strong> servicing client needs to service quality by actively
communicating and consulting with customers.
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It is by exploring links through narrative, ra<strong>the</strong>r than discrete measures, that readers <strong>of</strong> IC Statements
can get a sense <strong>of</strong> <strong>the</strong> actions taken by Lands to satisfy customers, outlining its success or failure.
For example, <strong>the</strong> ability to process online requests for Land Title searches within two minutes, with
<strong>the</strong> aim to continue satisfying <strong>the</strong> target, communicates a sense <strong>of</strong> providing a customer satisfying
service, even if it is not explicitly spelt out. Similarly, <strong>the</strong> fact <strong>the</strong>re are 10,000 subscribers to <strong>the</strong>
Crown Lands eNewsletter suggests <strong>the</strong> same outcome.
This is not to diminish <strong>the</strong> importance <strong>of</strong> communicating <strong>the</strong> IC measures as published. Ra<strong>the</strong>r, it
reaffirms Dumay’s (2008, p. 518) original findings when he showed “… how at Lands <strong>the</strong> use <strong>of</strong>
narrative became routinized in <strong>the</strong> activities <strong>of</strong> management. Thus narrative was no longer used to
only provide understanding <strong>of</strong> <strong>the</strong> IC measures and <strong>the</strong> reasoning behind <strong>the</strong> use <strong>of</strong> IC, but to provide
a mechanism that engendered fur<strong>the</strong>r management action and subsequent organisational change”.
The engendering <strong>of</strong> management action, thus mobilizing IC, before <strong>the</strong> need to measure IC is also
supported by Catasús et al. (2007). However, even though Lands considers <strong>the</strong>mselves successful in
managing its IC, Lands is still struggling with <strong>the</strong> desire to measure IC.
The challenge to find appropriate IC measures began early on as identified by <strong>the</strong> DG in a 2005
interview:
“In fact, it’s very easy to write a word essay on Intellectual Capital. It’s much harder to
document it and define it and to quantify it within <strong>the</strong> performance structure <strong>of</strong> an
organisation”.
After five years <strong>the</strong> DG is still searching for IC measures, even though Lands has been successful in
managing IC, as he alludes to in 2010 when reflecting on how to maintain <strong>the</strong> momentum <strong>of</strong> Lands’
success:
“… one <strong>of</strong> <strong>the</strong> real challenges is going to be how to keep a strong arrow point in this
subject matter as opposed to it being diffused. […] I think one <strong>of</strong> <strong>the</strong> things that will help
in that regard is if <strong>the</strong> strong accountancy framework that we all work under, and <strong>the</strong>
reporting frameworks, can more objectively address true points <strong>of</strong> measurement”.
More specifically <strong>the</strong> DG links success to <strong>the</strong> ability to measure IC as outlined below:
“The need for measurement is inextricably linked to a value proposition and, <strong>the</strong>refore,
knowledge management has to have a value proposition. It starts behind <strong>the</strong> eight ball
simply it’s <strong>the</strong> intangible side, and <strong>the</strong>refore, started with a lack <strong>of</strong> measurement. And
this is where, if <strong>the</strong>re’s a disappointment in this space, globally and generally, it’s still in
<strong>the</strong> lack <strong>of</strong> our ability collectively to end up with hard-core metrics. So, I think it’s <strong>the</strong> key
to unlocking this space”.
In contrast, whilst <strong>the</strong> DG was pressuring fur<strong>the</strong>r development <strong>of</strong> IC metrics, a need for both narrative
and numeric reporting was highlighted by <strong>the</strong> reporting manager in 2010:
“I’m not a numbers person, so a narrative is as good to me as a sliding scale or a
financial commitment”.
The same manager also cast doubt on <strong>the</strong> usefulness <strong>of</strong> measuring and whe<strong>the</strong>r or not it resulted in
management action:
“It’s an interesting discussion we have intermittently with <strong>the</strong> Australian Bureau <strong>of</strong>
Statistics. By <strong>the</strong> time you get <strong>the</strong> data and mesh it toge<strong>the</strong>r and present it, taking into
account all <strong>of</strong> <strong>the</strong> assumptions that must be made, well what’s <strong>the</strong> value <strong>of</strong> <strong>the</strong> thing that
you’re reporting and how do you learn anything from it that you can actually adjust?”
Additionally <strong>the</strong> same manager questions whe<strong>the</strong>r or not a ‘standard’ set <strong>of</strong> measures can be found
for Lands because <strong>of</strong> <strong>the</strong> diversity <strong>of</strong> Lands businesses.
“So, it’s important to have a lot <strong>of</strong> different levels and layers <strong>of</strong> input. For us, having an
internal dialogue about what we should be measuring is not that well informed because
we end up with very bespoke business solutions. As to what we should be measuring,
everybody comes back to what <strong>the</strong>y individually want to do”.
The need for a diverse set <strong>of</strong> bespoke measures was confirmed by <strong>the</strong> CIO in 2010. In <strong>the</strong> case <strong>of</strong> <strong>the</strong>
IT department <strong>the</strong> metrics <strong>the</strong>y develop internally are different, and are in addition to <strong>the</strong> metrics
contained in <strong>the</strong> annual report:
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“For example, I prepared and developed an ICT Strategic Plan that runs over five years.
Yes, my achievements are reported in <strong>the</strong> Annual Report. But as part <strong>of</strong> our forward
looking Strategic Plan, which is different form <strong>the</strong> Annual Report, we have our [own]
Intellectual Capital statement. And it contains a lot more metrics that what we do include
in <strong>the</strong> Annual Report. ... <strong>the</strong> Annual Report [IC Statement] is just a summary <strong>of</strong> what we
do”.
Ano<strong>the</strong>r challenge to developing a consistent set <strong>of</strong> measures is <strong>the</strong> impact <strong>of</strong> politics on <strong>the</strong> Lands’s
deliverables and hence what Lands needs to report. This was highlighted by a senior Crown Lands
manager in 2010.
“in <strong>the</strong> past, we’ve developed business plans and strategic plans that have a lot <strong>of</strong> output
counts and it has become quite difficult to maintain it. Because we get a series <strong>of</strong>
interferences politically that actually say, OK, you must do this now. That <strong>the</strong>n impacts
seriously on what we can produce that was in our operational plans. And <strong>the</strong>n to
maintain that, <strong>the</strong>re’s a lot <strong>of</strong> maintenance to change your operational plan to reflect <strong>the</strong>
new political requirement”.
The need to constantly change what is being reported resulted in <strong>the</strong> following observation from <strong>the</strong>
same manager:
“I don’t think we’ve really got on top <strong>of</strong> business reporting in <strong>the</strong> new world <strong>of</strong>
government, trying to get <strong>the</strong> right essence <strong>of</strong> what we report on and what we don’t
report on and [thus] we rely on a database to be able to prepare reports as required”.
This continued tension between <strong>the</strong> need to measure and <strong>the</strong> impact <strong>of</strong> measuring was again
highlighted by <strong>the</strong> reporting manager:
“I have a different view, I don’t think accounting will provide a solution because, it may
provide a solution but it’s going to have to undertake a philosophical move, in that’s it’s
not a matter <strong>of</strong> counting widgets. … you know it’s not a matter <strong>of</strong> so many widgets and so
on. Is one widget better than ano<strong>the</strong>r? Is fifty widgets [better] than no widgets at all or do
you preserve one? Is <strong>the</strong>re a quality issue involved? And <strong>the</strong> complexity <strong>of</strong> <strong>the</strong> situation
is more than a balance sheet”.
The struggle with developing metrics for IC is causing Lands to concentrate more on <strong>the</strong> narrative
than <strong>the</strong> numbers. When we questioned <strong>the</strong> reporting manager about how <strong>the</strong> tension between
measuring IC and narrative would be handled in <strong>the</strong> next Annual Report she commented:
What we’re trying to do now is instead <strong>of</strong>, for want <strong>of</strong> a better word, isolating <strong>the</strong> narrative
into a section, we’re trying to embed it into <strong>the</strong> whole report.
So one <strong>of</strong> <strong>the</strong> items <strong>of</strong> feedback we had is that <strong>the</strong> Intellectual Capital report as we’ve
had it is really quite distinct and central and it does tend to repeat elements that are later
on in <strong>the</strong> annual report. We’re hoping to have each <strong>of</strong> <strong>the</strong> general managers write <strong>the</strong>ir
own narrative. So as [<strong>the</strong> DG] does a narrative at <strong>the</strong> beginning <strong>of</strong> <strong>the</strong> annual report,
each general manager will write a narrative about what <strong>the</strong>ir business has achieved, so
that each one does a summary including <strong>the</strong> finances, a plain English approach too.
Thus, <strong>the</strong> Annual Report (and IC Statement) should reflect more on how Lands mobilised its
resources in achieving its objectives ra<strong>the</strong>r than focusing on developing <strong>the</strong> correct set <strong>of</strong> Lands wide
measures. By allowing individual managers to report on what <strong>the</strong>y have done <strong>the</strong>y should be able to
use measures relevant to <strong>the</strong>ir own agencies instead <strong>of</strong> trying to conform to a predefined set <strong>of</strong>
measures.
So how do <strong>the</strong> above discussions help answer our original question <strong>of</strong> whe<strong>the</strong>r or not measuring IC is
actually required for managing IC? The answer is two fold. First, measures are required, but as part <strong>of</strong>
<strong>the</strong> IC reporting narrative, ra<strong>the</strong>r than as stand alone numbers in a balance sheet <strong>of</strong> intangibles. The
measures are scattered throughout <strong>the</strong> narrative and <strong>the</strong> reader uses <strong>the</strong> measures to help make
sense <strong>of</strong> whe<strong>the</strong>r or not Lands is improving <strong>the</strong>ir IC. But <strong>the</strong>se are not concrete measures and will
probably not be needed in <strong>the</strong> next report. This is not because <strong>the</strong> measures are not useful but
because, as we have seen in <strong>the</strong> quotes above, Lands’s reporting needs evolve based on <strong>the</strong>
bespoke nature <strong>of</strong> its business, political expectations and changing business plans.
The second answer is ‘no’, at least from <strong>the</strong> context <strong>of</strong> a set <strong>of</strong> concrete IC measures relevant to <strong>the</strong>
entire organisation. In this sense <strong>the</strong> balance sheet approach is not required. This is because, as we
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identified earlier, Lands has been successful in adopting IC management and reporting practices.
However, by <strong>the</strong>ir own admission, <strong>the</strong>y have done so while struggling with <strong>the</strong> perceived need for a
set <strong>of</strong> concrete IC measures.
5. Conclusion
We conclude from <strong>the</strong> evidence presented that IC practices are possible without <strong>the</strong> need for concrete
IC measures. Lands has demonstrated its success in managing its IC resources while also showing
dissatisfaction with <strong>the</strong>ir inability to identify a set <strong>of</strong> set <strong>of</strong> concrete IC measures. The conclusion
highlights <strong>the</strong> struggle many organisations face in measuring IC. The fixation with developing
measures and frameworks continues as evidenced by recently published academic papers and in <strong>the</strong>
organisation studied, Lands, where <strong>the</strong>re is a preoccupation with ‘accounting for IC’ in an attempt to
make <strong>the</strong> intangible tangible. It seems academics and practitioners have still not found <strong>the</strong> answer.
We suggest <strong>the</strong> fixation is misplaced and <strong>the</strong> IC journey is better communicated by narrating <strong>the</strong> story
<strong>of</strong> how IC is mobilised. Doing so allows a focus on IC practices ra<strong>the</strong>r than accounting. This opens <strong>the</strong>
debate as to whe<strong>the</strong>r accounting can provide <strong>the</strong> solution. As <strong>the</strong> reporting manager highlighted, “I
don’t think accounting will provide a solution” because “… <strong>the</strong> complexity <strong>of</strong> <strong>the</strong> situation is more than
a balance sheet”. Therefore we recommend following Lands’ example <strong>of</strong> telling <strong>the</strong> story <strong>of</strong> how IC is
mobilised via narratives <strong>of</strong> <strong>the</strong>ir achievements. Doing so conveys <strong>the</strong> message <strong>of</strong> how IC is mobilised
without <strong>the</strong> need for an IC balance sheet.
As always, <strong>the</strong> observations and conclusions we reached here are limited to <strong>the</strong> case <strong>of</strong> Lands and
are based on our objective analysis. Therefore care should be taken in generalising any <strong>of</strong> our
findings. We highlight <strong>the</strong> need to understand <strong>the</strong> IC context before applying our findings.
Our future research will continue to monitor <strong>the</strong> way in which Lands manages, measures and reports
on its IC. This type <strong>of</strong> longitudinal research should continue to provide us with insights in managing,
measuring and reporting IC over time.
6. References
Behn, R. D. (2003) “Why measure performance? Different purposes require different measures”, Public
Administration Review, Vol 63, No 5, pp. 586-606.
Catasús, B., Ersson, S., Gröjer, J.-E. and Wallentin, F. Y. (2007) “What gets measured gets … on indicating,
mobilizing and acting”, Accounting, Auditing & Accountability Journal, Vol 20, No 4, pp. 505-521.
Cleary, P. (2009) “Exploring <strong>the</strong> relationship between management accounting and structural capital in a
knowledge-intensive sector”, Journal <strong>of</strong> Intellectual Capital, Vol 10, No 1, pp. 37-52.
Demming, W. E. (1986) Out <strong>of</strong> <strong>the</strong> Crisis: Quality Productivity and Competitive Position, MIT Press, Cambridge,
MA.
Drucker, P. F. (1954) The Practice <strong>of</strong> Management, Harper-Collins, New York.
Dumay, J. C. (2008) “Narrative disclosure <strong>of</strong> intellectual capital: A structurational analysis”, Management
Research News, Vol 31, No 7, pp. 518-37.
Dumay, J. C. (2009a) “Intellectual capital measurement: A critical approach”, Journal <strong>of</strong> Intellectual Capital, Vol
10, No 2, pp. 190-210.
Dumay, J. C. (2009b) “Reflective discourse about intellectual capital: Research and practice”, Journal <strong>of</strong>
Intellectual Capital, Vol 10, No 4, pp. 489-503.
English, L., Guthrie, J. and Parker, L. (2005) “Debating Public Sector Management and Financial Management
Reforms: An International Study”, Financial Management Change in Australia: Market Experiences,
Information Age Press, USA.
Gowthorpe, C. (2009) “Wider still and wider? A critical discussion <strong>of</strong> intellectual capital recognition, measurement
and control in a boundary <strong>the</strong>oretical context”, Critical Perspectives on Accounting, Vol 20, No 7, pp. 823-
34.
Kaplan, R. S. and Norton, D. P. (1992) “The Balanced Scorecard - Measures that drive performance”, Harvard
Business Review, Vol 70, No 1, pp. 71-9.
Kerr, S. (1995) “On <strong>the</strong> folly <strong>of</strong> rewarding A, while hoping for B”, Academy <strong>of</strong> Management Executive, Vol 9, No 1,
pp. 7-14.
Mårtensson, M. (2009) “Recounting counting and accounting: From political arithmetic to measuring intangibles
and back”, Critical Perspectives on Accounting, Vol 20, No 7, pp. 835-846.
McPhail, K. (2009) “Where is <strong>the</strong> ethical knowledge in <strong>the</strong> knowledge economy?: Power and potential in <strong>the</strong>
emergence <strong>of</strong> ethical knowledge as a component <strong>of</strong> intellectual capital”, Critical Perspectives on
Accounting, Vol 20, No 7, pp. 804-822.
Mouritsen, J., Bukh, P. N., Flagstad, K., Thorbjørnsen, S., Johansen, M. R., Kotnis, S., Larsen, H. T., Nielsen, C.,
Kjærgaard, I., Krag, L., Jeppesen, G., Haisler, J. and Stakemann, B. (2003) Intellectual Capital Statements
– The New Guideline, Danish Ministry <strong>of</strong> Science, Technology and Innovation (DMSTI), Copenhagen.
129

John Dumay and Jim Rooney
Mouritsen, J. and Roslender, R. (2009) “Critical intellectual capital”, Critical Perspectives on Accounting, Vol 20,
No 7, pp. 801-803.
Nielsen, C. and Madsen, M. T. (2009) “Discourses <strong>of</strong> transparency in <strong>the</strong> intellectual capital reporting debate:
Moving from generic reporting models to management defined information”, Critical Perspectives on
Accounting, Vol 20, No 7, pp. 847-854.
NSW Department <strong>of</strong> Lands (Lands) (2004) 2003/2004 Annual Report, New South Wales Government, Sydney.
NSW Department <strong>of</strong> Lands (Lands) (2005a) 2004/2005 Annual Report, New South Wales Government, Sydney.
NSW Department <strong>of</strong> Lands (Lands) (2005b) Corporate Plan 2003-2007, NSW Department <strong>of</strong> Lands, Sydney.
NSW Department <strong>of</strong> Lands (Lands) (2006) 2005/2006 Annual Report, New South Wales Government, Sydney.
NSW Department <strong>of</strong> Lands (Lands) (2007) 2006/2007 Annual Report, New South Wales Government, Sydney.
NSW Department <strong>of</strong> Lands (Lands) (2008) 2007/2008 Annual Report, New South Wales Government, Sydney.
NSW Department <strong>of</strong> Lands (Lands) (2009) 2008/2009 Annual Report, New South Wales Government, Sydney.
NSW Government (2009) "NSW Public Sector: Allocation <strong>of</strong> Departments and o<strong>the</strong>r bodies to clusters."
Retrieved 22/8/2010, Available at; http://www.dpc.nsw.gov.au/publications/news/stories/?a=64058.
Ramírez, Y. (2010) “Intellectual capital models in Spanish public sector”, Journal <strong>of</strong> Intellectual Capital, Vol 11,
No 2, pp. 248-64.
Secundo, G., Margherita, A., Elia, G. and Passiante, G. (2010) “Intangible assets in higher education and
research: mission, performance or both?”, Journal <strong>of</strong> Intellectual Capital, Vol 11, No 2, pp. 140-157.
Sillanpää, V., Lönnqvist, A., Koskela, N., Koivula, U.-M., Koivuaho, M. and Laihonen, H. (2010) “The role <strong>of</strong>
intellectual capital in non-pr<strong>of</strong>it elderly care organizations”, Journal <strong>of</strong> Intellectual Capital, Vol 11, No 2, pp.
107-122.
Sveiby, K. E. (2010, 27/4/2010), “Methods for measuring intangible assets”, Retrieved 22/8/2010,
http://www.sveiby.com/portals/0/articles/IntangibleMethods.htm.
130

Knowledge Utilization <strong>of</strong> Women as Intellectual Capital in
Iranian Research Institutes (a Multiple-Case Study)
Marziye Ehrami 1 , Khodayar Abili 2 , Mohamad Daneshgar 3 and Mehdi Narimani 1
1 International Institute for Energy Studies, Tehran, Iran
2 Tehran University, Tehran, Iran
3 Parsian Bank, Tehran, Iran
Uehrami.marziye@gmail.com
Abstract: An intellectual capital includes knowledge, information, experience and intellectual asset <strong>of</strong> individuals
which can be used for creating opportunities and wealth in organizations. Human capital as a subset <strong>of</strong>
intellectual capital represents individuals' knowledge. Nowadays, women tend to achieve equal opportunities as
men, applying <strong>the</strong>ir knowledge and experiences regardless <strong>of</strong> <strong>the</strong>ir gender. Likewise, women's efforts to
participate in social and political activities have increased rapidly in recent years in Iran. For instance, statistics
show a higher demand to enter universities among women. This study tries to answer <strong>the</strong> following questions: To
what extent and in what aspects has gender composition <strong>of</strong> labor force changed in Iran during <strong>the</strong> last decade?
What opportunities have been provided for women in order to use <strong>the</strong>ir experiences and knowledge? Have
women had <strong>the</strong> same opportunities for promotion as men? In order to conduct <strong>the</strong> study, three Iranian research
institutes have been selected and a researcher-designed questionnaire was used to be completed by both
women and men in those institutes in order to determine gender-related bias. In addition, findings <strong>of</strong> this study
are compared with those <strong>of</strong> o<strong>the</strong>r similar studies for fur<strong>the</strong>r validity and completion <strong>of</strong> data. Based on <strong>the</strong> results
achieved from this study, some recommendations are provided for <strong>the</strong> improvement <strong>of</strong> women as an important
part <strong>of</strong> organization's human capital, too.
Keywords: Intellectual capital, human capital, research institute, multi-case study
1. 0BIntroduction
One <strong>of</strong> <strong>the</strong> most important measures <strong>of</strong> assessing <strong>the</strong> extent to which a country is developed, is <strong>the</strong>
level <strong>of</strong> importance given to women in that country. Scientists consider human as <strong>the</strong> development
factor and believe that <strong>the</strong> level <strong>of</strong> development <strong>of</strong> different societies depends on <strong>the</strong> optimum use <strong>of</strong>
all possible human resources. Considering that women have constructed half <strong>of</strong> <strong>the</strong> society
population, <strong>the</strong>ir presence in <strong>the</strong> society and <strong>the</strong> level <strong>of</strong> <strong>the</strong>ir participation in political, economic,
social and cultural affairs affects <strong>the</strong> extent to which <strong>the</strong> country is developed. Therefore, in almost all
countries using woman's work force is considered as an important element affecting <strong>the</strong> development.
Taking into account <strong>the</strong> scientific and pr<strong>of</strong>essional abilities <strong>of</strong> women, <strong>the</strong>ir presence in different
managerial and decision- making positions is necessary to accomplish development goals and
objectives. However, uninformed and unfair assessment <strong>of</strong> <strong>the</strong> biological differences between men
and women, and generalizing <strong>of</strong> it to different work fields have resulted inevitably in low levels <strong>of</strong>
women’s participation in managerial occupations and areas <strong>of</strong> decision making. In Iran, <strong>the</strong>re is also a
strong need for an effective use <strong>of</strong> abilities <strong>of</strong> all <strong>the</strong> segments <strong>of</strong> <strong>the</strong> society including men and
women. (Zahedi, 2007, PP. 65-66).
Women’s Participation in different managerial positions and decision- making processes becomes
more important when knowing that in this case, demands, talents and creativity <strong>of</strong> about half <strong>the</strong>
population has practically been neglected, while new management <strong>the</strong>ories based on individual
creativity and developing talents <strong>of</strong> all active forces believe that woman is ano<strong>the</strong>r director.
In o<strong>the</strong>r words, actions and reactions <strong>of</strong> a female manager with her colleagues could create an
atmosphere in <strong>the</strong> organizations in which new sources <strong>of</strong> energy are produced; a rich source <strong>of</strong>
emotional understanding <strong>of</strong> staffs that also has cultural advantages and with <strong>the</strong> features like thrift,
responsibility and accountability that leads to organizations efficiency and productivity in those
organizations. In addition, it will provide justice in <strong>the</strong> employment process and increase motivation for
people to participate in <strong>the</strong> process in order to achieve sustainable development.
2. 1BPosition <strong>of</strong> women in Iranian Constitutional Law
Article 21 <strong>of</strong> <strong>the</strong> Iranian constitution refers to women's rights and <strong>the</strong>ir dedication. This article
expressly binds <strong>the</strong> government to support rights <strong>of</strong> women in all respects, in conformity with Islamic
criteria, and contains <strong>the</strong> following sections:
131

Marziye Ehrami et al.
1. Creation <strong>of</strong> a favorable environment for <strong>the</strong> woman's personality to grow and <strong>the</strong> restoration <strong>of</strong>
her rights, both materially and intellectually;
2. Protection <strong>of</strong> mo<strong>the</strong>rs, particularly during pregnancy and child upbringing, and protection <strong>of</strong>
orphans and unguarded children.
3. Establishing competent courts to protect and support <strong>the</strong> family;
4. Support for divorced women and women without a guardian aged and elderly
5. Awarding guardianship <strong>of</strong> children to competent mo<strong>the</strong>rs, in order to protect <strong>the</strong> interests <strong>of</strong>
children, in <strong>the</strong> absence <strong>of</strong> a legal guardian.
In addition to <strong>the</strong> mentioned article which relates directly to <strong>the</strong> women’s rights, section 8 <strong>of</strong> Article 3
<strong>of</strong> <strong>the</strong> Constitution points to public participation in determining political, economic, social and cultural
future without any discrimination between men and women. Besides, according to Article 20, all
citizens <strong>of</strong> <strong>the</strong> country, both men and women, equally enjoy law protection. This article states that all
people have political, economic, social, and cultural rights, in conformity with Islamic criteria.
2.1 Present situation <strong>of</strong> women in <strong>the</strong> field <strong>of</strong> knowledge
It has been about a century since women's formal education started in Iran and almost seventy years
since Iranian women took part in higher education for <strong>the</strong> first time. Statistics show that from among
598,790 admitted students in different academic levels in 2008-2009, 324,173 were women and
274,617 were men. And <strong>of</strong> course <strong>the</strong>re is an increasing trend for <strong>the</strong> number <strong>of</strong> women studying at
Iranian universities in recent years. Meanwhile, <strong>the</strong> deficiency <strong>of</strong> employment rates <strong>of</strong> women
compared with men represents a kind <strong>of</strong> inequality in job distribution and serious obstacles in <strong>the</strong> way
<strong>of</strong> employment <strong>of</strong> women. Considering <strong>the</strong> situation <strong>of</strong> <strong>the</strong> current job market in Iran, Iranian women
are far away from desirable situation. Currently, women's participation rate in jobs is about eleven
percent and <strong>the</strong>ir unemployment rate is about twenty percent. Of <strong>the</strong> country's active population, 85
percent <strong>of</strong> <strong>the</strong> active forces are men and only 15 percent are women. These statistics, however, are
quite different in developed countries. In some countries, about fifty percent <strong>of</strong> <strong>the</strong> works are done by
<strong>the</strong> women and in some developing countries, in <strong>the</strong> agricultural sector, 67 percent <strong>of</strong> <strong>the</strong> workforce is
devoted to women; also 55 percent <strong>of</strong> <strong>the</strong> total world foods are produced by <strong>the</strong> women. In <strong>the</strong> East
Asian countries, which hold an export record in textiles and household appliances, women constitute
74 percent <strong>of</strong> <strong>the</strong> workforce.
Table 1: Statistics on <strong>the</strong> number <strong>of</strong> educated women (www.msrt.ir)
total
525316
73474
598790
Total
man
238200
36417
274617
woman
287116
37057
324173
total
7321
96
7417
Specialized
PhD
man
4520
87
4607
woman
2801
9
2810
total
6062
-
6062
Pr<strong>of</strong>essional
Doctorate
man
2488
-
2488
woman
3574
-
3574
total
40967
1595
42562
132
MA
man
21441
1064
22505
woman
19526
531
20057
total
350449
43841
394290
BA
man
134866
21928
156794
woman
215583
21913
237496
total
120517
27942
148459
Undergraduate man
74885
13338
88223
woman
45632
14604
60236
Kind <strong>of</strong> center
State
Private
Total

Marziye Ehrami et al.
3. Employment status <strong>of</strong> women vs. men in Iran
The improvement in <strong>the</strong> educational level <strong>of</strong> <strong>the</strong> women in <strong>the</strong> society in <strong>the</strong> recent years, has led to
<strong>the</strong> change in <strong>the</strong>ir attitudes and information <strong>of</strong> <strong>the</strong>ir lost opportunities. It, in turn, has logically reduced
fertility rate, controlled population growth rate considerably and also increased tendency <strong>of</strong> women to
participate in <strong>the</strong> job market in <strong>the</strong> hope <strong>of</strong> attaining financial independence.
In <strong>the</strong>se years, despite <strong>the</strong> improvement in <strong>the</strong> educational level <strong>of</strong> women, <strong>the</strong> increase in <strong>the</strong>
marriage average age, <strong>the</strong> increase in <strong>the</strong> number <strong>of</strong> jobs <strong>of</strong>fered to women and also <strong>the</strong> increase in
<strong>the</strong>ir participation rate from 9.1 percent in 1997 to 11.8 percent in 2004, <strong>the</strong>ir job opportunities have
not been improved with <strong>the</strong> same pace, in that unemployment rate <strong>of</strong> urban jobseeker women
doubled within eight years and reached over 24.5 percent.
Table 2 shows unemployment rate <strong>of</strong> men and women during 2001 and 2004 and also its prediction
up to 2009. According to 2006 statistics, unemployment rates <strong>of</strong> men and women were 11 and 17
percent, respectively. Besides, literacy rate, as ano<strong>the</strong>r important indicator, were 90.3 percent and 82
percent <strong>of</strong> <strong>the</strong> men and women in <strong>the</strong> country, respectively in 2006. Among <strong>the</strong> few indicators
presented in table 2 in which Iranian women are in a better position than men, is life expectancy
which was predicted to be 69.07 for men and 71.5 for women in 1388. The most important result <strong>of</strong>
<strong>the</strong> study <strong>of</strong> employment status in recent decades is that <strong>the</strong> tendency to financial independence,
improving <strong>the</strong> level <strong>of</strong> education, empowering girls and women by increasing pr<strong>of</strong>essional skills along
with increasing <strong>the</strong> expertise level lead to increase in <strong>the</strong> presence <strong>of</strong> women in different work fields.
Table 2: Ministry <strong>of</strong> Labor and Social Affairs,2005
man
72.2
72.69
73.16
70.8
71.28
71.5
woman
67.61
68.06
68.5
68.0
68.44
69.07
man
77.89
72.6
75.2
80.0
82.0
86.0
Woman
83.84
84.8
86.3
89.0
90.3
95.0
man
11.69
12.0
10.9
12.9
12.9
16.2
woman
61.82
62.4
62.8
64.5
65.0
69.2
Man
15.78
15.49
14.21
16.4
16.5
18.7
133
woman
84.22
84.51
85.79
83.6
83.5
81.3
Man
18.9
17.5
20.18
17.8
17.0
9.3
Woman
13.93
11.7
10.19
11.30
11.0
8.2
man
31.99
32.22
32.93
33.34
33.66
39.75
woman
32.91
33.31
34.05
34.31
34.80
77.90
population <strong>of</strong>
Country
64.90
65.51
66.99
67.65
68.46
77.90
year
2001
2002
2003
2004
2005
2009

Marziye Ehrami et al.
Note: In 2005 statistics, indexes for unemployment rate, combination <strong>of</strong> active population, rate <strong>of</strong>
economic activity, literacy and life expectancy were all predicted by Iranian Economy Monthly
Magazine, Research Unit. In <strong>the</strong> statistic released in 2009, indexes for literacy rate and life
expectancy were predicted by Iranian Economic Monthly Magazine, Research Unit. Source: Research
Unit <strong>of</strong> IRANIAN Economy Monthly Magazine, from <strong>the</strong> report <strong>of</strong> women Employment <strong>of</strong>fice, Ministry
<strong>of</strong> labor and social Affairs, 2005
3.1 Definition <strong>of</strong> women's empowerment
Conceptually, empowerment does not mean superiority <strong>of</strong> one over ano<strong>the</strong>r (women over men).
Instead, it emphasizes on upgrading self-confidence and self-reliance <strong>of</strong> one. It also means
continuous and active presence <strong>of</strong> women in development programs but not utilizing <strong>the</strong> development
results.
According to <strong>the</strong> United Nation’s Guidelines on Women's Empowerment, women's empowerment
contains <strong>the</strong> following five components:
Sense <strong>of</strong> self-worth
Right <strong>of</strong> ownership and decision-making
Right to have access to opportunities and resources
Right to have control over one's own life, both inside and outside home
Ability to influence <strong>the</strong> direction <strong>of</strong> social change in order to create a fair social and economic
system, nationally and internationally.
According to this definition, women should be seen as active citizens, also called as control
citizenship (<strong>the</strong> highest level and kind <strong>of</strong> participation will be considered) which means decision
making and participation in <strong>the</strong> social affairs and family life. Welfare, access, knowledge, and control
are o<strong>the</strong>r important factors in <strong>the</strong> process <strong>of</strong> empowerment; yet <strong>the</strong> main discussions are on what
factors affect women's empowerment. This study tries to assess <strong>the</strong> rate <strong>of</strong> utilization <strong>of</strong> women’s
capabilities, using individual's empowerment indicators, in selected organizations .The end, a
questionnaire with 32 questions was prepared and distributed among women in <strong>the</strong> selected
organizations after its validity and reliability was verified. In addition, in order to avoid unilateral
judgments, ano<strong>the</strong>r questionnaire, containing 11 questions was developed and distributed among
male employees in which <strong>the</strong>y were asked to tell <strong>the</strong>ir views about women’s empowerment as well as
women’s work. The total sample included 412 women and 210 men and <strong>the</strong> results are illustrated in
figures 1 and 2.
Figure 1: Analysis men's questionnaire
134

Figure 2: Analysis <strong>of</strong> women's questionnaire
4. Conclusions
Marziye Ehrami et al.
In Iran, like many o<strong>the</strong>r countries, women take part in various social and political scenes toge<strong>the</strong>r with
men, although <strong>the</strong>ir participation is limited to low-level jobs. However, <strong>the</strong> tendency to attain
knowledge in <strong>the</strong> fields like IT, business and entrepreneurship has recently been increased among
women.
There is no doubt that more presence <strong>of</strong> women in such areas leads to more improvement and
development in <strong>the</strong> society. In order to promote employment conditions <strong>of</strong> women in science-related
fields, <strong>the</strong> following points are recommended:
1. Identification <strong>of</strong> knowledge oriented jobs and utilization <strong>of</strong> educated women in <strong>the</strong>se jobs
2. Participation <strong>of</strong> women in training courses to improve <strong>the</strong>ir knowledge and experience
3. Emphasis on decent democracy and struggle against sexism
4. Promotion <strong>of</strong> decent women to higher managerial positions
5. Support <strong>of</strong> women's rights protection organizations as well as NGOs formed to solve women's
problems
References
Iranian Constitutional Law
Ministry <strong>of</strong> Labor and Social Affairs,(2005)
Ministry <strong>of</strong> Science Site, www.msrt.ir
Yaghubi, Vali (2009) , see <strong>the</strong> empowerment <strong>of</strong> women and <strong>the</strong>ir role in country's development process,
www.mardomsalari.com , Tehran, Iran .
Zahedi, Shamsosadat (2007), Women and Development , Iranian cultural studies, Tehran ,Iran.
135

Earnings Quality and O<strong>the</strong>r Factors Affecting Intellectual
Capital Performance in Banks: The UAE Case
Magdi El-Bannany
College <strong>of</strong> Business Administration, University <strong>of</strong> Sharjah, UAE
Liverpool Business School, Liverpool JMU, UK
Ain Shams University, Egypt
melbannany@sharjah.ac.ae
m.el-bannany@ljmu.ac.uk
magdi_elbannany@yahoo.co.uk
Abstract: The aim <strong>of</strong> this study is to suggest a framework to explain <strong>the</strong> factors which might have impact on
intellectual capital performance in UAE Banks over <strong>the</strong> period 2006-2009. Multiple regression analysis is used to
test <strong>the</strong> relationship between intellectual capital performance as a dependent variable and certain independent
variables. The results show that earnings quality, bank age, listing age, inflation; bank risk measured by total
reserves as a comprehensive bank risks and bank size variables which have not been considered in previous
studies, have a significant impact on intellectual capital performance. In addition <strong>the</strong> results show that investment
in information technology systems and bank pr<strong>of</strong>itability have significant impact on <strong>the</strong> intellectual capital
performance. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> results show foreign ownership variable, which has not been considered in
previous studies, has no impact on <strong>the</strong> intellectual capital performance. To <strong>the</strong> best <strong>of</strong> my knowledge this is <strong>the</strong>
first paper to provide information about intellectual capital performance in UAE Banks and adds to <strong>the</strong> literature
on <strong>the</strong> determinants <strong>of</strong> <strong>the</strong> level <strong>of</strong> intellectual capital disclosure in banks. In particular, it tests <strong>the</strong> new <strong>the</strong>ories
that earnings quality, bank age, listing age, inflation, foreign ownership, bank risk measured by total reserves as
a comprehensive bank risks indicator; and bank size have impact on <strong>the</strong> intellectual capital performance.
Keywords: intellectual capital performance, earnings quality, bank age, listing age, inflation, bank risk, foreign
ownership, banks, United Arab Emirates
1. Introduction
Intellectual capital performance is playing an important role in <strong>the</strong> value creation for knowledge-based
organizations for reasons such as improving <strong>the</strong> organization’s efficiency and efficacy and hence
leading to gaining a competitive advantage which should lead in turn to maximizing <strong>the</strong> value creation
for <strong>the</strong> organization (see for instance, Nielsen et al., 2006, Goh, 2005 and De Pablos, 2003) and this
makes explaining <strong>the</strong> factors affecting intellectual capital performance a key challenge as argued by
El-Bannany (2008).
Us<strong>of</strong>f et al. (2002, p. 9) stated “knowledge has become <strong>the</strong> key economic resource and <strong>the</strong> dominant
and perhaps even <strong>the</strong> only source <strong>of</strong> competitive advantage”. World Bank (1999, p.20) stated that
“knowledge is our most powerful engine <strong>of</strong> production”. Additionally, Pulic (1998) argued that in a
knowledge based organizations <strong>the</strong> responsible party for <strong>the</strong> achieved good results is definitely <strong>the</strong>
intellectual capital.
So, in knowledge driven organizations such as Banks intellectual capital, play a crucial role in creating
value through improving efficiency and gaining competitive advantage which allow <strong>the</strong>m to compete in
<strong>the</strong> banking market. That is, if <strong>the</strong> intellectual capital performance <strong>of</strong> bank (X) is better than bank (Y)
which is performing <strong>the</strong> same services, this will be reflected in better performance for bank (X)
compared to bank (Y). This is because bank (X) might i.e. adopt certain strategies, e.g. low cost
strategy, which should lead to reduction in <strong>the</strong> production cost <strong>of</strong> <strong>the</strong> services and in turn make this
bank more efficient and hence allow <strong>the</strong> bank from charging lower fees for its services and this should
lead it to gain a competitive advantage in <strong>the</strong> banking market which allows maximizing <strong>the</strong> pr<strong>of</strong>it <strong>of</strong> <strong>the</strong>
bank and hence maximizing <strong>the</strong> value creation.
As argued by El-Bannany (2008), in <strong>the</strong> physical capital based sectors i.e. heavy industries sector
physical ra<strong>the</strong>r than intellectual capital is more important in <strong>the</strong> mechanism <strong>of</strong> value creation. But <strong>the</strong>
intellectual capital based sectors i.e. banking, intellectual ra<strong>the</strong>r than physical capital is more
important in <strong>the</strong> process <strong>of</strong> wealth creation and this give a credit for choosing banking ra<strong>the</strong>r than
o<strong>the</strong>r sectors for <strong>the</strong> empirical part <strong>of</strong> this study. In addition, Kamath and Complex (2007) argued that
banking sector is ideal for intellectual capital research for several reasons i.e. availability <strong>of</strong> reliable
data and <strong>the</strong> nature <strong>of</strong> banking business is intellectually intensive. Moreover, banking staff are
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intellectually more homogeneous than staff in o<strong>the</strong>r sectors as argued by Kubo and Saka (2002).
Hence, <strong>the</strong> UAE Banks as shown in table 1 has been chosen for <strong>the</strong> present study because <strong>of</strong> it
suitability and hoping that <strong>the</strong> result <strong>of</strong> this study will help <strong>the</strong> UAE banking regulators in addressing
<strong>the</strong> factors affecting intellectual capital performance to take actions towards developing <strong>the</strong>ir
performance and in turn maximise <strong>the</strong>ir wealth creation.
The remainder <strong>of</strong> this paper is structured as follows: Second section discusses <strong>the</strong> definition and
measurement <strong>of</strong> intellectual capital performance, third section explain <strong>the</strong> factors affecting intellectual
capital performance, fourth section covers <strong>the</strong> research method used, fifth section presents <strong>the</strong>
empirical results, and sixth section provides <strong>the</strong> conclusions.
Table 1: The sample <strong>of</strong> banks in <strong>the</strong> study
Banks Names and Abbreviations
Abu Dhabi Commercial Bank (ADCB)
Abu Dhabi Islamic Bank (ADIB)
Bank <strong>of</strong> Sharjah (BOS)
Commercial Bank <strong>of</strong> Dubai (CBD)
Commercial Bank International (CBI)
Dubai Bank (DB)
Dubai Islamic Bank (DIB)
Emirates Islamic Bank (EIB)
First Gulf Bank (FGB)
Invest Bank (IB)
Mashreq Bank (MB)
National Bank <strong>of</strong> Abu Dhabi (NBAD)
National Bank <strong>of</strong> Umm Al Qaiwain (NBQ)
National Bank <strong>of</strong> Ras Al-Khaimah (RAKB)
Sharjah Islamic Bank (SIB)
Union National Bank (UNB)
2. Definition and measurement <strong>of</strong> Intellectual capital performance
Several components about intellectual capital have been argued in <strong>the</strong> literature and some <strong>of</strong> <strong>the</strong>se
are:
A hidden assets represented by knowledge <strong>of</strong> employees, customer and supplier
relations, brand loyalty, market position and knowledge (Roos and Roos, 1997).
An intangible asset with <strong>the</strong> ability to add value for <strong>the</strong> company and <strong>the</strong> society
(Mavridis, 2005).
“<strong>the</strong> knowledge, information, intellectual property and experience that can be put to use
to create wealth” (Martinez and Garcia-Meca, 2005, p.305).
“encompasses intangibles such as patents, intellectual property rights, copyrights and
franchises” (Brennan,2001, p.423).
“information, knowledge applied to work to create value” (Edvinsson and Malone, 1997,
p.3).
“broad organisational knowledge unique to a firm, which allows it constantly to adapt to
changing conditions” (Mouritsen, 1998, p.462).
“given to <strong>the</strong> combined intangible assets which enable <strong>the</strong> company to function”
(Brooking, 1996, p.12).
So, intellectual capital is invisible powers which include internal power, external power. The internal
power represented mainly by employees’ knowledge, and external power reflected in characteristics
such as customers relations, brand loyalty and market position and <strong>the</strong>se powers can help <strong>the</strong>
companies to maximize <strong>the</strong>ir wealth.
Roos and Roos (1997, p.415) stated that ‘although <strong>the</strong> stock market is showing us that intellectual
capital is far more important than money and o<strong>the</strong>r traditional assets-a fact that is consistent with <strong>the</strong>
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resource-based perspective-only a few companies are making a serious effort to capture, measure
and better manage it’.
Therefore measuring <strong>the</strong> performance <strong>of</strong> intellectual capital as invisible powers can be seen a difficult
task because <strong>of</strong> <strong>the</strong> absence <strong>of</strong> specific guidelines in that context.
As argued above, intellectual capital consists <strong>of</strong> many important components but as mentioned by
Albert Einstein ‘what is important cannot always be measured’ and because <strong>of</strong> <strong>the</strong> availability <strong>of</strong>
reliable data for human capital component compared to o<strong>the</strong>r components <strong>of</strong> intellectual capital as
argued by El-Bannany (2008); human capital will be used a proxy for intellectual capital performance.
Different features related to human capital have been argued in <strong>the</strong> literature and <strong>the</strong>se are:
“ <strong>the</strong> individual knowledge stock <strong>of</strong> an organisation as represented by its employees”
(Bontis et al., 2000, p. 87).
“human capital generates innovation – whe<strong>the</strong>r <strong>of</strong> new products and services or
improving business processes” (Riahi-Belkaoui, 2003, p.217).
“<strong>the</strong> know-how, information, relationships, and general capabilities that individuals bring
to bear on behalf <strong>of</strong> <strong>the</strong> firm through <strong>the</strong> employment relation” (Galunic and Anderson,
2000, p.3).
“such factors as employees’ knowledge, skill, capability, and attitudes in relation to
fostering performances which customers are willing to pay for and <strong>the</strong> company’s pr<strong>of</strong>it
comes from” (Chen et al., 2004, p.201).
We can conclude that human capital as a major intellectual capital component contains invisible
powers which can lead to improving <strong>the</strong> efficiency <strong>of</strong> <strong>the</strong> companies and hence gaining a competitive
advantage in <strong>the</strong> market which in turn result in higher value for <strong>the</strong> company.
As argued by El-Bannany (2008), human capital can not act without <strong>the</strong> existence <strong>of</strong> physical capital
(<strong>the</strong> initial investment to buy <strong>the</strong> core components <strong>of</strong> <strong>the</strong> business) so this part can not be ignored in
constructing <strong>the</strong> measure <strong>of</strong> intellectual capital performance.
Several measures for intellectual capital performance have been used in <strong>the</strong> literature but <strong>the</strong> Value
Added Intellectual Capital (VAIC) method explained by Pulic (1998) and followed by previous studies
about intellectual capital performance in banks (see for instance, El-Bannany, 2008; Kamath and
Complex 2007; Yalama & Coskun, 2007; Goh, 2005; Mavridis, 2004 & 2005 and Williams, 2001) can
be seen more convenient than o<strong>the</strong>rs for <strong>the</strong> present study because <strong>of</strong> it is simplicity and overcome
<strong>the</strong> problem <strong>of</strong> data availability in some countries which might be needed with more sophisticated
measures:
The steps to calculate <strong>the</strong> Value Added Intellectual Capital (VAIC) as summarized by El-Bannany
(2008) are as follows:
Output = Gross income
Input = Operating expenses (excluding personal costs)
Value added (VA) = output – input
HC = personal cost (considered as investment)
CA = physical capital
Value added <strong>of</strong> human capital (VAHC) = VA/HC
Value added <strong>of</strong> physical capital (VACA) = VA/CA
Value Added Intellectual Capital (VAIC) = VAHC + VACA
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3. Research methodology (factors affecting intellectual capital performance,
hypo<strong>the</strong>sis, sample, research methods)
3.1 Factors affecting intellectual capital performance
In <strong>the</strong> intellectual capital performance in bank literature, many factors have been considered important
in affecting intellectual capital performance <strong>of</strong> <strong>the</strong>se <strong>the</strong> factors <strong>of</strong> investment in information
technology systems, bank pr<strong>of</strong>itability. The present study is investigating for <strong>the</strong> first time <strong>the</strong> affect <strong>of</strong>
<strong>the</strong> factors <strong>of</strong> earnings quality, bank age, listing age, inflation, foreign ownership; bank risk measured
by total reserves as a comprehensive bank risks indicator and bank size on intellectual capital
performance.
3.1.1 Earnings quality
Earnings quality can be linked to verifiability concept ‘which in accounting and earnings context’
means that if we asked two independent certified accountants (A and B) to calculate <strong>the</strong> amount <strong>of</strong>
earnings for a specific company during a certain period <strong>of</strong> time, <strong>the</strong>y should reach <strong>the</strong> same results
proving that <strong>the</strong>y applied <strong>the</strong> same set <strong>of</strong> accounting standards and here <strong>the</strong> human capital level
needed to reach achieve this target should be normal. But as argued by Aljifri (2007) <strong>the</strong> managers <strong>of</strong>
<strong>the</strong> companies might be interested in managing <strong>the</strong> earnings <strong>of</strong> <strong>the</strong>ir companies for reasons such as
earnings smoothing; reduce tax expenses; contractual perspectives; reduce political costs and
management changes and here <strong>the</strong> human capital level needed to reach this target should be up
normal.
No Name (2006, p.294) states that ‘Earnings quality is a multi-dimensional concept; <strong>the</strong>refore, <strong>the</strong>
choice <strong>of</strong> an earnings quality measure will depend on <strong>the</strong> research question posed (which dimension
<strong>of</strong> earnings quality is implied by <strong>the</strong> research question) and <strong>the</strong> availability <strong>of</strong> data and estimation
models (which measures can be estimated)’.
Different measures have been used in <strong>the</strong> literature to measure earnings quality and <strong>of</strong> <strong>the</strong>se accrual
quality can be seen more suitable for <strong>the</strong> present study because <strong>of</strong> its simplicity and help in sorting
out <strong>the</strong> problem <strong>of</strong> data availability associated with <strong>the</strong> more sophisticated measures [see for
instance, Kim and Qi (2010); Teitel and Machuga (2010); Ye, et. al. (2010) and Francis, et al.
(2006)].
Based on <strong>the</strong> above discussion, <strong>the</strong> first hypo<strong>the</strong>sis is;
H1: <strong>the</strong>re is a negative relationship between <strong>the</strong> earnings quality and intellectual capital performance.
3.1.2 Bank age
It has been argued that company age as a proxy for risk has an impact <strong>of</strong> <strong>the</strong> level <strong>of</strong> disclosure. That
is, potential investors will be more cautious in investing in younger ra<strong>the</strong>r than older ones because <strong>of</strong>
relative lack <strong>of</strong> <strong>the</strong> financial history <strong>of</strong> younger companies which in turn might have a negative impact
on predictable earning ability for <strong>the</strong>se companies [see for instance, White, et.al (2007) and Bukh, et.
al (2005)].
Therefore we should expect a negative relationship between <strong>the</strong> company age and its intellectual
disclosure level and as a result <strong>the</strong> need for more human capital ‘intellectual work’ to deal with this
issue will be less important in older compared to younger companies
Therefore, <strong>the</strong> second hypo<strong>the</strong>sis is;
H2: <strong>the</strong>re is a negative relationship between <strong>the</strong> age <strong>of</strong> <strong>the</strong> bank and intellectual capital performance.
3.1.3 Listing age
It has been argued that listing age as a proxy for risk has an impact <strong>of</strong> <strong>the</strong> level <strong>of</strong> disclosure. That is,
newly listed companies are more motivated than eldest listed ones to disclose information in <strong>the</strong>ir
annual reports to reduce <strong>the</strong> risk level and hence attract external fund to it [see for instance, , Barnes
and Walker, 2006; Garcia-Meca, et.al, 2005, Haniffa and Cooke, 2002 and Cook ,1989].
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Based on this argument we can say that <strong>the</strong> need for more intellectual skills to deal with this issue will
be higher for <strong>the</strong> newly listed companies, which are seeking for external funds ra<strong>the</strong>r than eldest listed
ones
Listing status is measured by using a dummy variable equal to 1 if <strong>the</strong> firm is listed in Dubai Financial
Market and 0 if not in each year <strong>of</strong> <strong>the</strong> study period.
Based on <strong>the</strong> above argument, <strong>the</strong> third hypo<strong>the</strong>sis is;
H3: <strong>the</strong>re is a negative relationship between <strong>the</strong> listing age <strong>of</strong> <strong>the</strong> bank and intellectual capital
performance.
3.1.4 Inflation
Inflation can be linked to cash and real income concept ‘which in economics context’ means when
counting for intellectual capital performance <strong>the</strong> results do not reflect <strong>the</strong> real figures because <strong>the</strong>se
are inflated by <strong>the</strong> increases in <strong>the</strong> prices and not in <strong>the</strong> productivity <strong>of</strong> <strong>the</strong> human capital represented
by increasing in <strong>the</strong> level <strong>of</strong> products and services as a result <strong>of</strong> <strong>the</strong> intellectual work.
Based on <strong>the</strong> above argument, <strong>the</strong> fourth hypo<strong>the</strong>sis is;
H4: <strong>the</strong>re is a positive relationship between <strong>the</strong> inflation rate and intellectual capital performance.
3.1.5 Foreign ownership
As a business culture factor, <strong>the</strong> existence <strong>of</strong> foreign ownership might represent a pressure on <strong>the</strong>
management <strong>of</strong> <strong>the</strong> company and lead to recruiting highly intellectual staff which in turn should result
in better human capital performance in <strong>the</strong> process <strong>of</strong> creating wealth and hence attract more foreign
investors to invest in <strong>the</strong>se companies.
Therefore, <strong>the</strong> fifth hypo<strong>the</strong>sis is;
H5: <strong>the</strong>re is a positive relationship between foreign ownership and intellectual capital performance.
3.1.6 Bank risk
Patton and Zelenka (1997, p.611) stated that “<strong>the</strong> percentage <strong>of</strong> intangible assets is a proxy for <strong>the</strong>
extent to which a firm’s future performance depends on risky assets”.
El-Bannany (2008, p.493) argued that increasing <strong>the</strong> percentage <strong>of</strong> intangible assets might give <strong>the</strong>
impression to <strong>the</strong> human capital (as intangible assets) that <strong>the</strong>y are important in contributing to <strong>the</strong>
success <strong>of</strong> <strong>the</strong> company and motivate <strong>the</strong>m to continue in innovating e.g. new products or services or
improving business processes to achieve more benefit to <strong>the</strong> company.
Because banking industry is facing different type <strong>of</strong> risks such as credit, liquidity and interest rate
risks, using total reserves as a comprehensive bank risks variable can be seen better than o<strong>the</strong>rs in
representing <strong>the</strong> level <strong>of</strong> bank i in year t.
Based on <strong>the</strong> above argument, <strong>the</strong> sixth hypo<strong>the</strong>sis is;
H6: <strong>the</strong>re is a positive relationship between bank risk and intellectual capital
performance.
3.1.7 Bank size
Bank size can be linked to investment portfolio <strong>the</strong>ory and considered as a proxy for bank risk which
means that bigger sizes banks are more diversify than smaller ones and hence smaller banks are
riskier than bigger ones and in turn <strong>the</strong> level <strong>of</strong> intellectual work need to face <strong>the</strong> risky situation should
be higher for smaller banks in comparison to bigger ones.
Several measures have been used in <strong>the</strong> banking literature to represent company size such as total
assets, annual sales, market capitalisation, and number <strong>of</strong> employees. As argued by El-Bannany
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(2007, p.124) in <strong>the</strong> absence <strong>of</strong> a scientific <strong>the</strong>oretical basis to measure <strong>the</strong> size <strong>of</strong> <strong>the</strong> bank, total
assets can be seen as a fair basis to measure <strong>the</strong> size <strong>of</strong> <strong>the</strong> bank because it is a comprehensive
indicator compared to o<strong>the</strong>r measures such as deposits which only reflect to what extent <strong>the</strong> bank is
successful in attracting more depositors and hence become big.
Based on <strong>the</strong> above argument, <strong>the</strong> seventh hypo<strong>the</strong>sis is;
H7: <strong>the</strong>re is a negative relationship between bank size and intellectual capital performance.
3.1.8 Control variables
Previous studies about <strong>the</strong> determinants <strong>of</strong> intellectual capital performance revealed that <strong>the</strong> factors
<strong>of</strong> investment in information technology systems; bank pr<strong>of</strong>itability and bank size are important in
explaining intellectual capital performance
El-Bannany (2008, p.491) argued that <strong>the</strong>re is a negative impact <strong>of</strong> investment in IT systems on <strong>the</strong>
employees because it reflects <strong>the</strong> intention <strong>of</strong> <strong>the</strong> management to fire a number <strong>of</strong> staff.
The results <strong>of</strong> <strong>the</strong> study <strong>of</strong> Holden and El-Bannany (2004) revealed that investing in ATMs by <strong>the</strong> UK
banks led to reduction in <strong>the</strong> number <strong>of</strong> staff <strong>of</strong> <strong>the</strong> bank.
Because <strong>of</strong> data availability problem, <strong>the</strong> published data on IT cost for bank i in year t will be used as
a measure <strong>of</strong> investment in information technology systems.
Therefore, <strong>the</strong> eighth a hypo<strong>the</strong>sis is;
H8a: <strong>the</strong>re is a negative relationship between <strong>the</strong> levels <strong>of</strong> investment in information
technology and intellectual capital performance.
El-Bannany (2008) argued that making pr<strong>of</strong>its can be considered as <strong>the</strong> usual financial results and
leave <strong>the</strong> directors to undertake o<strong>the</strong>r useful activities for <strong>the</strong> company such as encouraging staff to
innovate which might increase pr<strong>of</strong>its.
Different measures have been used in banking literature but <strong>the</strong> individual bank i annual net pr<strong>of</strong>it
before taxation divided by shareholders equity in year t will be used to represent <strong>the</strong> bank pr<strong>of</strong>itability
can be seen as suitable for <strong>the</strong> present study.
Based on <strong>the</strong> above argument, <strong>the</strong> eighth b hypo<strong>the</strong>sis is;
H8b: <strong>the</strong>re is a positive relationship between bank pr<strong>of</strong>itability and intellectual
capital performance.
3.2 Research methods
The regression model used in this study is shown as follows:
VAICit = 0 + 1 TNAit + 2 LGAGEit + 3 LISTAGit + 4 INFt + 5 FORit +
6 LGRESVit + 7 LGASSit + 8 LGITit + 9 ROEit +uit
Where:
VAICit = <strong>the</strong> dependent variable – Value Added Intellectual Coefficient for
bank i in year t; measured as explained in section (B) above.
0 = constant;
1, 2,3……
= coefficients <strong>of</strong> <strong>the</strong> independent variables;
Details <strong>of</strong> <strong>the</strong> definitions <strong>of</strong> <strong>the</strong> independent variables are given in table 2.
uit = disturbance term – that is <strong>the</strong> usual error term.
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Table 2: Description <strong>of</strong> independent variables and expected signs
Source <strong>of</strong> data: Annual reports
Variable and abbreviation Measurement Expected Actual
sign sign
Earnings Quality (TNAit) Total net accrual for bank i in year t. - -
Bank Age (LGAGEit) The logarithm <strong>of</strong> <strong>the</strong> age <strong>of</strong> bank i in year t,
measured by <strong>the</strong> number <strong>of</strong> years for <strong>the</strong> bank since
started in business until each year <strong>of</strong> <strong>the</strong> study
period.
- -
Listing Age (LISTAGEit) A dummy variable equal to 1 if <strong>the</strong> bank is listed in
Dubai Financial Market and 0 if not in each year <strong>of</strong>
<strong>the</strong> study period.
- -
Inflation (INFit) Retail Price Index in year t + -
Foreign Ownership (FORit) A dummy variable equal to 1 if <strong>the</strong> bank is allowing
foreign ownership and 0 if not in each year <strong>of</strong> <strong>the</strong>
study period.
+ NS*
Bank risk (LGRESVit) The logarithm <strong>of</strong> total reserves for bank I in year t + +
Bank Size (LGASSit) The logarithm <strong>of</strong> total assets for bank i in year t - -
Investment in information Natural logarithm <strong>of</strong> total cost <strong>of</strong> hardware and - -
technology systems
(LGITit)
s<strong>of</strong>tware <strong>of</strong> computing systems for bank i in year t
Bank pr<strong>of</strong>itability (ROEit) individual bank i annual net pr<strong>of</strong>it before taxation
divided by shareholders equity in year t
+ +
*NS not significant
4. Results and discussion
4.1 Descriptive statistics
Table 3 reports <strong>the</strong> descriptive statistics for <strong>the</strong> intellectual capital performance level and explanatory
factors used in this study. The intellectual capital performance for <strong>the</strong> sample banks throughout <strong>the</strong>
study period varies from 1.81 to 15.23 <strong>of</strong> <strong>the</strong> value <strong>of</strong> <strong>the</strong> calculated intellectual capital performance
and <strong>the</strong> mean for <strong>the</strong> intellectual capital performance is 7.27. The explanatory factors represented by
earnings quality; bank age; listing age; inflation; foreign ownership; bank risk; bank size; investment in
information technology systems and bank pr<strong>of</strong>itability are vary as well and “this gives more credibility
to <strong>the</strong> results <strong>of</strong> <strong>the</strong> study” as argued by Naser and Al-Khatib, (2000).
Table 3: Descriptive statistics for <strong>the</strong> dependent and independent variables
N= 64 observations
Variable Mean SD Min Max
Intellectual Capital Performance (ICPit) 7.27 3.35 1.81 15.23
Earnings Quality (TNAit) 212.86 5908.11 -26428 20107
Bank Age (LGAGEit) 1.42 0.23 0.60 1.62
Listing Age (LISTAGEit) 4.34 2.29 0.00 9.00
Inflation (INFit) 153.25 14.50 133.00 171.50
Foreign Ownership (FORit) 0.70 0.46 0.00 1.00
Bank risk (LGRESVit) 3.05 0.57 1.56 4.04
Bank Size (LGASSit) 4.46 0.45 3.71 5.29
Investment in information technology systems
(LGITit)
1.52 0.40 0.70 2.33
Bank pr<strong>of</strong>itability (ROEit) 0.14 0.08 -0.17 0.31
4.2 Test for multicollinearity
Multicollinearity is a statistical problem which exists if <strong>the</strong>re is a high correlation among one or more <strong>of</strong>
<strong>the</strong> explanatory factors used to explain <strong>the</strong> changes in <strong>the</strong> dependent variable when applying <strong>the</strong>
regression technique and might lead to spoil <strong>the</strong> results. This problem can be detected using <strong>the</strong>
correlation matrix as a diagnostic test. El-Bannany (2002) argues that if <strong>the</strong> simple negative or
positive correlation coefficient between any two variables is say 0.99 or more, <strong>the</strong>n we should suspect
<strong>the</strong> occurrence <strong>of</strong> <strong>the</strong> multicollinearity problem and one way <strong>of</strong> solving this problem is to drop one <strong>of</strong>
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<strong>the</strong> two highly correlated explanatory factors. The multicollinearity test results <strong>of</strong> <strong>the</strong> regression model
explanatory factors (see table 4) show that <strong>the</strong> coefficients among all factors are less than 0.99. The
highest correlation coefficient value is between LGITit and LGASSit and is less than 0.99 (it is 0.80),
which means <strong>the</strong> multicollinearity problem is not existed.
Table 4: The correlation coefficient matrix for <strong>the</strong> independent variables
Independent
Variables
TNAit LGAGEit LISTAGEit INFit FORit LGRESVit LGASSit LGITit ROEit
TNAit - -0.044 0.072 0.106 0.071 0.050 0.044 0.001 -0.087
(0.732) (0.570) (0.406) (0.576) (0.694) (0.728) (0.997) (0.494)
LGAGEit - 0.271* 0.098 0.164 0.422** 0.153 0.195 0.263*
(0.030) (0.439) (0.194) (0.001) (0.228) (0.122) (0.036)
LISTAGEit - 0.460** 0.460** 0.729** 0.761** 0.678** 0.035
(0.000) (0.000) (0.000) (0.000) (0.000) (0.784)
INFit - 0.043 0.162 0.254* 0.298* -0.327**
(0.734) (0.200) (0.043) (0.017) (0.008)
FORit - 0.399** 0.162 0.045 0.092
(0.001) (0.202) (0.723) (0.469)
LGRESVit - 0.786** 0.624** 0.262*
(0.000) (0.000) (0.037)
LGASSit - 0.805** 0.182
(0.000) (0.150)
LGITit - 0.244
(0.052)
ROEit -
The 2-tailed significance level is shown in brackets.
Correlation is significant at <strong>the</strong> 0.05 level (2-tailed).
** Correlation is significant at <strong>the</strong> 0.01 level (2-tailed)
4.3 The problem <strong>of</strong> cross-sectional correlation
The small number <strong>of</strong> banks represented in <strong>the</strong> study sample and <strong>the</strong> repeated use <strong>of</strong> each bank over
time, might lead to <strong>the</strong> existence <strong>of</strong> cross-sectional correlation statistical problem which means that
<strong>the</strong> residuals could be correlated across banks and <strong>the</strong> estimated standard error <strong>of</strong> coefficients might
be biased. As a solution to this potential statistical problem, Petersen (2009) suggested <strong>the</strong> inclusion
<strong>of</strong> dummy variables to represents <strong>the</strong> firms in <strong>the</strong> regression analysis and hence this approach will be
applied in this study.
4.4 Regression results and discussion
The regression analysis has been done using <strong>the</strong> best fitting data approach followed by El-Bannany
(2008, 2002) which can be summarised as adding and dropping some <strong>of</strong> <strong>the</strong> explanatory factors until
reaching to <strong>the</strong> suitable combination <strong>of</strong> factors which robust <strong>the</strong> regression model in terms <strong>of</strong> its
results.
The results (see table 5) show that <strong>the</strong> regression model is significant and explains 83% <strong>of</strong> <strong>the</strong>
relationship between <strong>the</strong> intellectual capital performance and <strong>the</strong> explanatory factors and this indicate
that <strong>the</strong> model is reasonably well specified.
The coefficients for earnings quality, bank age, listing age, inflation, bank risk, bank size, investment
in information technology systems, bank pr<strong>of</strong>itability and some banks dummies are highly significant
(p 0.05) and <strong>the</strong> signs on <strong>the</strong> coefficients <strong>of</strong> <strong>the</strong>se factors are in line with <strong>the</strong> hypo<strong>the</strong>sized direction.
In contrast, <strong>the</strong> coefficient representing foreign ownership is not significant.
The empirical results revealed that: Earnings quality measured by total net accruals <strong>of</strong> bank i in year t
is negatively related to intellectual capital performance (ICPit) and this in line with <strong>the</strong> expectation <strong>of</strong>
hypo<strong>the</strong>sis 1. Bank age measured by <strong>the</strong> logarithm <strong>of</strong> <strong>the</strong> age <strong>of</strong> bank i in year t, measured by <strong>the</strong>
number <strong>of</strong> years for <strong>the</strong> bank since started in business until each year <strong>of</strong> <strong>the</strong> study period is negatively
related to ICPit and this in line with <strong>the</strong> expectation <strong>of</strong> hypo<strong>the</strong>sis 2. Listing age measured by a dummy
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Magdi El-Bannany
variable equal to 1 if <strong>the</strong> bank is listed in Dubai Financial Market and 0 if not in each year <strong>of</strong> <strong>the</strong> study
period is negatively related to ICPit and this in line with <strong>the</strong> expectation <strong>of</strong> hypo<strong>the</strong>sis 3. Inflation
measured by <strong>the</strong> retail price index in year t is positively related to ICPit and this in line with <strong>the</strong>
expectation <strong>of</strong> hypo<strong>the</strong>sis 4. The coefficient <strong>of</strong> foreign ownership measured by a dummy variable
equal to 1 if <strong>the</strong> bank is allowing foreign ownership and 0 if not in each year <strong>of</strong> <strong>the</strong> study period is not
significant which mean that <strong>the</strong>re is no relationship between foreign ownership and ICPit and this
contradicts <strong>the</strong> expectation <strong>of</strong> hypo<strong>the</strong>sis 5 but <strong>the</strong> reason might be known if we classified <strong>the</strong> origin
and <strong>the</strong> ratio <strong>of</strong> <strong>the</strong> foreign ownership component from developing and developed countries. If <strong>the</strong>
majority is from developing countries so results can be accepted because it will a reflect <strong>of</strong> <strong>the</strong>ir
culture and vice versa.
Bank risk measured by <strong>the</strong> logarithm <strong>of</strong> total reserves for bank i in year t is positively related to ICPit
and this in line with <strong>the</strong> expectation <strong>of</strong> hypo<strong>the</strong>sis 6. Bank size measured by <strong>the</strong> logarithm <strong>of</strong> total
assets for bank i in year t is negatively related to ICPit and this in line with <strong>the</strong> expectation <strong>of</strong>
hypo<strong>the</strong>sis 7. Investment in information technology systems measured by Natural logarithm <strong>of</strong> total
cost <strong>of</strong> hardware and s<strong>of</strong>tware <strong>of</strong> computing systems for bank i in year t is negatively related to ICPit
and this in line with <strong>the</strong> expectation <strong>of</strong> hypo<strong>the</strong>sis 8a and <strong>the</strong> results <strong>of</strong> El-Bannany, 2008.
Bank pr<strong>of</strong>itability measured by individual bank i annual net pr<strong>of</strong>it before taxation divided by
shareholders equity in year t is positively related to ICPit and this in line with <strong>the</strong> expectation <strong>of</strong>
hypo<strong>the</strong>sis 8b and <strong>the</strong> results <strong>of</strong> El-Bannany, 2008.
Table 5: The regression results: dependent variable ICPit; Number <strong>of</strong> observations 64
Regressor
Coefficient
t-ratio
Probability
Intercept 70.847 4.811 0.000
TNAit -8.240E-5 -2.709 0.010
LGAGEit -33.381 -5.810 0.000
LISTAGEit -4.209 -7.094 0.000
INFit 0.420 6.579 0.000
FORit 0.870 0.600 0.552
LGRESVit 2.762 2.226 0.031
LGASSit -11.702 -3.780 0.000
LGITit -3.409 -2.668 0.011
ROEit 10.542 3.344 0.002
ADIBit -14.605 -5.286 0.000
BOSit -18.292 -5.287 0.000
CBDit -10.467 -5.548 0.000
CBIit -18.116 -5.069 0.000
DBit -61.259 -7.233 0.000
EIBit -24.179 -7.331 0.000
IBit -24.508 -5.525 0.000
NBADit 13.165 6.617 0.000
NBQit -26.211 -5.926 0.000
RAKBit -28.119 -7.055 0.000
SIBit -20.305 -6.417 0.000
UNBit -10.991 -6.443 0.000
R-SQUARED = 0.89 R-BAR-SQUARED = 0.83
F (21,42) = 15.837 Sig. F. = 0.000
N = 64
5. Conclusions
This study investigates <strong>the</strong> relationship between intellectual capital performance (ICP) and nine
explanatory factors (seven <strong>of</strong> <strong>the</strong>m, namely earnings quality; bank age; listing age; inflation; foreign
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Magdi El-Bannany
ownership; bank risk measured by bank risk measured by total reserves as a comprehensive bank
risks indicator; bank size have not been considered in previous studies) over <strong>the</strong> period 2006-2009
using data for <strong>the</strong> UAE banks.
The main explanatory factors, which have been considered in previous
studies, are investment in information technology (IT) systems and bank pr<strong>of</strong>itability. investment in IT
systems hypo<strong>the</strong>sis presupposes that increasing <strong>of</strong> investing in IT could reflect a bad sign and
threaten <strong>the</strong> job security for some employees and might lead in turn to reduction in <strong>the</strong> production and
innovation level <strong>of</strong> <strong>the</strong>se employees and hence ICP.
Bank pr<strong>of</strong>itability hypo<strong>the</strong>sis reassumes that <strong>the</strong> success might lead to ano<strong>the</strong>r success. That is
achieving <strong>of</strong> pr<strong>of</strong>its means that <strong>the</strong> bank has got fund which can a part <strong>of</strong> it used to reward <strong>the</strong> best
intellectually performance employees and in turn enhancing <strong>the</strong> ICP.
However, none <strong>of</strong> <strong>the</strong> previous studies <strong>of</strong> factors affecting ICP have considered earnings quality; bank
age; listing age; inflation; foreign ownership; bank risk and bank size as paths <strong>of</strong> explaining ICP.
Earnings quality hypo<strong>the</strong>sis states that <strong>the</strong> high <strong>the</strong> quality <strong>of</strong> earnings, <strong>the</strong> less he need for
intellectual work to manage <strong>the</strong>se earnings. The age <strong>of</strong> <strong>the</strong> firm hypo<strong>the</strong>sis states that ICP for older
banks will be less than younger banks because it’s less risky. The listing age hypo<strong>the</strong>sis presuppose
that ICP for earliest ra<strong>the</strong>r than eldest listing banks will better to gain more creditability in <strong>the</strong> market
and hence be able to obtain external funds. Inflation hypo<strong>the</strong>sis presuppose that increasing in retail
index price will lead to inflated in <strong>the</strong> amount <strong>of</strong> calculated ICP. Foreign Ownership hypo<strong>the</strong>sis
assumes that allowing <strong>of</strong> foreign ownership might lead to enhancing <strong>of</strong> ICP for <strong>the</strong> sake <strong>of</strong> attracting
more foreign investment. Bank risk hypo<strong>the</strong>sis <strong>the</strong> ICP for <strong>the</strong> high risky ra<strong>the</strong>r than less risky banks
should be better to overcome this issue. The size hypo<strong>the</strong>sis states that ICP for larger ra<strong>the</strong>r than
smaller banks will be less because it’s less risky.
The results show that earnings quality, bank age, listing age, inflation; bank risk measured by total
reserves as a comprehensive bank risks and bank size variables which have not been considered in
previous studies, have a significant impact on ICP. In addition <strong>the</strong> results show that investment in
information technology systems and bank pr<strong>of</strong>itability have significant impact on <strong>the</strong> ICP. On <strong>the</strong> o<strong>the</strong>r
hand, <strong>the</strong> results show foreign ownership variable, which has not been considered in previous
studies, has no impact on <strong>the</strong> ICP.
There are some limitations to this study. First, more evidence is needed on <strong>the</strong> factors explaining ICP
l before any generalisation <strong>of</strong> <strong>the</strong> results can be made. Second, <strong>the</strong> empirical tests were conducted
only on <strong>the</strong> UAE bank over <strong>the</strong> period 2006-2009 and hence <strong>the</strong> results <strong>of</strong> <strong>the</strong> study cannot be
assumed to extend beyond this group <strong>of</strong> banks or to different study periods. Finally, <strong>the</strong>ories such as
financial crisis, market structure and role duality might be considered for fur<strong>the</strong>r research as a
possible explanation for ICP.
References
Aljifri, K. (2007). Measurement and Motivations <strong>of</strong> Earnings Management:
A Critical Perspective. Journal <strong>of</strong> Accounting – Business & Management 14:75-95.
Barnes, E. and Walker, M. (2006). The Seasoned-Equity Issues <strong>of</strong> UK Firms: Market Reaction and Issuance
Method Choice. Journal <strong>of</strong> Business Finance and Accounting, 33(1/2): 45-78.
Bontis, N., Keow, W., Richardson , S. 2000, ‘Intellectual Capital and Business Performance in Malaysian
Industries’, Journal <strong>of</strong> Intellectual Capital, 1/1: 85-100.
Brennan, N. (2001). ‘Reporting Intellectual Capital in Annual Reports: Evidence from Ireland’, Accounting,
Auditing & Accountability Journal, 14/4: 423-436.
Brooking, A. 1996, Intellectual Capital: Core Assets for <strong>the</strong> Third Millennium Enterprise, Thomson Business
Press, London.
Bukh, P.; Nielsen, C.; Gormsen, P. and Mouritsen, J. (2005). Accounting, Auditing & Accountability Journal, 18/6:
713-732.
Chen, J., Zhu, Z., Xie , H. (2004). ‘Measuring Intellectual Capital: A New Model and Empirical Study’, Journal <strong>of</strong>
Intellectual Capital, 5/1: 195-212.
Cooke, T. (1989). Disclosure in <strong>the</strong> Corporate Annual Reports <strong>of</strong> Swedish Companies. Journal <strong>of</strong> Accounting and
Business Research, 19: 113–24
De Pablos, P. (2003). ‘Intellectual Capital Reporting in Spain: A Comparative View’, Journal <strong>of</strong> Intellectual
Capital, 4/1:61-81.
145

Magdi El-Bannany
Edvinsson, L. & Malone, M. (1997). Intellectual Capital: Realizing Your Company’s True Value by Finding its
Hidden Brain Power, Harper Collins Publisher Inc., New York.
El-Bannany, M. (2008). A Study <strong>of</strong> Determinants <strong>of</strong> Intellectual Capital Performance in Banks: <strong>the</strong> UK Case.
Journal <strong>of</strong> Intellectual capital, 9/3:487-498.
El-Bannany, M. (2007). A Study <strong>of</strong> <strong>the</strong> Determinants <strong>of</strong> Social Disclosure Level in UK Banks. Corporate
Ownership & Control, 5/1:120-130.
El-Bannany, M. (2002), Investment in Information Technology Systems and O<strong>the</strong>r Determinants <strong>of</strong> Bank
Performance in <strong>the</strong> UK and Egypt, Unpublished Ph.D. <strong>the</strong>sis, Liverpool John Moores University, <strong>the</strong> UK.
Francis, J., Olsson, P. and Schipper, K. (2006). Earnings Quality. Foundations and Trends in Accounting, 1/4:
259–340.
Galunic, C. & Anderson, E. (2000). ‘From Security to Mobility: Generalized Investments in Human Capital and
Agent Commitment’, Organization Science, 11: 1-20.
Garcia-Meca, E., Parra, I., Larran, M. and Martinez, I. (2005). The ExplanatoryFactors <strong>of</strong> Intellectual Capital
Disclosure to Financial Analysts. <strong>European</strong> Accounting Review, 14/1: 63-94.
Goh, P. (2005). ‘Intellectual Capital Performance <strong>of</strong> Commercial Banks in Malaysia’, Journal <strong>of</strong> Intellectual
Capital, 6/3: 385-396.
Haniffa, M. and Cooke, T. (2002). Culture, Corporate Governance and Disclosure in Malaysian Corporations.
Abacus, 38/3: 317-349.
Holden, K. & El-Bannany, M. 2004, ‘Investment in Information Technology Systems and O<strong>the</strong>r Determinants <strong>of</strong>
Bank Pr<strong>of</strong>itability in <strong>the</strong> UK’, Applied Financial Economics, 14: 361-65.
Kamath, B. and Complex, N. (2007). The intellectual capital performance <strong>of</strong> <strong>the</strong> Indian banking sector. Journal <strong>of</strong>
Intellectual Capital, 8/1: 96-123.
Kim, D. and Qi, Y. (2010). Accruals Quality, Stock Returns, and Macroeconomic Conditions. The Accounting
Review, 85/3: 937–978.
Kubo, I., Saka, A. (2002), "An inquiry into <strong>the</strong> motivations <strong>of</strong> knowledge workers in <strong>the</strong> Japanese financial
industry", Journal <strong>of</strong> Knowledge Management, 6/3: 262-71.
Martinez, I. & Garcia-Meca, E. (2005). ‘Assessing <strong>the</strong> Quality <strong>of</strong> Disclosure on Intangibles in <strong>the</strong> Spanish Capital
Market’, <strong>European</strong> Business Review, 17/4:305-313.
Mavridis, D. (2005). ‘Intellectual Capital Performance Drivers in <strong>the</strong> Greek Banking Sector’, Management
Research News, 28/5: 43-62.
Mavridis, D. (2004). ‘Intellectual Capital Performance <strong>of</strong> <strong>the</strong> Japanese Banking Sector’, Journal <strong>of</strong> Intellectual
Capital, 5/1: 92-115.
Mouritsen, J. (1998). ‘Driving Growth: Economic Value Added versus Intellectual Capital’, Management
Accounting Research, 9: 461-82.
Naser, K. & Al-Khatib, K. 2000, ‘The Extent <strong>of</strong> Voluntary Disclosure in <strong>the</strong> Board <strong>of</strong> Directors’ Statement: The
Case <strong>of</strong> Jordan’, Advances in International Accounting, vol.13, pp. 99-118.
Nielsen, C., Bukh, P., Mouritsen, J., Johansen, M., Gormsen, P. (2006). ‘Intellectual Capital Statements on <strong>the</strong>ir
way to <strong>the</strong> Stock Exchange’, Journal <strong>of</strong> Intellectual Capital, 7/2: 221-240.
No Name (2006). Measures <strong>of</strong> Earnings Quality. Foundations & Trends in Accounting, 2006, Vol. 1 Issue 4,
pp.294-309.
Patton, J. & Zelenka, I. 1997, ‘An Empirical Analysis <strong>of</strong> <strong>the</strong> Determinants <strong>of</strong> <strong>the</strong>
Extent <strong>of</strong> Disclosure in Annual Reports <strong>of</strong> Joint Stock Companies in <strong>the</strong> Czech Republic’, The <strong>European</strong>
Accounting Review, 6/4: 605-626.
Petersen, M. (2009). "Estimating standard errors in finance panel data sets: Comparing approaches". Review <strong>of</strong>
Financial Studies, 22: 435–480.
Pulic, A. (1998). ‘Measuring <strong>the</strong> Performance <strong>of</strong> Intellectual Capital in Knowledge Economy’, available at
http://www.vaic-on.net/start.htm
Riahi-Belkaoui, A. (2003). ‘Intellectual Capital and Firm Performance <strong>of</strong> US Multinational Firms’, Journal <strong>of</strong>
Intellectual Capital, 4/2: 215-226.
Roos, G. and Ross, J. (1997). Measuring your Company’s Intellectual Performance. Long Range Planning,
30/3:413-426.
Teitel, K. and Machuga, S. (2010). The Interaction <strong>of</strong> Audit Firm Quality and <strong>the</strong> Mexican Code <strong>of</strong> Best Corporate
Practices on Earnings Quality. Review <strong>of</strong> Business Research, 10/1: 32-40.
Us<strong>of</strong>f, C., Thibodeau, J., Burnaby , P. (2002). ‘The Importance <strong>of</strong> Intellectual Capital and its effect on
Performance Measurement Systems’, Managerial Auditing Journal, 17(1/2): 9-15.
White, G.; Lee, A. and Tower, G. (2007). Drivers <strong>of</strong> Voluntary Intellectual Capital Disclosure in Listed
Biotechnology Companies. Journal <strong>of</strong> Intellectual capital, 8/3: 517-537.
Williams, S. (2001). Is Intellectual Capital Performance and Disclosure Practices related? Journal <strong>of</strong> Intellectual
Capital, 2/3: 192-203.
World Bank (1999). Knowledge for Development, Oxford University Press, New York.
Yalama, A., Coskun, M. (2007), Intellectual capital performance <strong>of</strong> quoted banks on <strong>the</strong> Istanbul stock exchange
market, Journal <strong>of</strong> Intellectual Capital, 8/2: 256-271.
Ye, K., et. al. (2010). Does top executive gender diversity affect earnings quality? A large sample analysis <strong>of</strong>
Chinese listed firms. Advances in Accounting, incorporating Advances in International Accounting 26: 47–
54.
146

The Relationship Between Intellectual Capital and Process
and Product Innovation in Banks: An Exploratory Study
Ahmed Elsetouhi and Ibrahim Elbeltagi
Plymouth University, School <strong>of</strong> Management, UK
ahmed.elsetouhi@plymouth.ac.uk
i.elbeltagi@plymouth.ac.uk
Abstract: Innovation becomes an important tool to deal with financial disasters and uncertainty environments.
Therefore, Banks look for <strong>the</strong> most important resources to support process and product Innovation. In <strong>the</strong> new
knowledge based economy, intellectual capital(IC) represents an essential resource and it is essential source <strong>of</strong>
wealth and development. Hence, this study aims to build a conceptual framework for <strong>the</strong> relationship between IC
namely, human capital (HC), structural capital (SC), customer capital (CC) and, product and process innovation.
This research depends on actor network <strong>the</strong>ory (ANT) to explain <strong>the</strong>se relationships. Based on a review <strong>of</strong> literature,
conceptual framework focuses on a series <strong>of</strong> stages which start with determining human actors like HC and
CC, and non-human actors i.e. SC and finish by encouraging o<strong>the</strong>r actors like social capital to join to this network.
Finally, it is <strong>the</strong>oretically expected that relationships between IC and, process and product innovation are
mutual significant positive.
Keywords: Intellectual capital, product innovation, process innovation, actor network <strong>the</strong>ory
1. Introduction
Banks face financial disasters which cause bankruptcy in many banks. They must be able to adapt
and evolve if <strong>the</strong>y wish to survive. Innovation is <strong>the</strong> key stipulation for survival. If banks ignore innovation,
<strong>the</strong>y will pass away (e.g. Johnson 1999; Trott 2005). Resources (ei<strong>the</strong>r tangible or intangible)
considered as inputs to significantly support innovation in banks (Yang et al. 2009). In <strong>the</strong> era <strong>of</strong> <strong>the</strong>
knowledge economy, intellectual capital (IC) becomes important determinants <strong>of</strong> competitive advantages
and has capabilities to face uncertainty environment even though physical assets were key resources
in <strong>the</strong> past. With incessant investments in intangible assets, <strong>the</strong> traditional accounting system
can no longer accurately evaluate <strong>the</strong> real value <strong>of</strong> organization. The market value <strong>of</strong> a firm is equal to
its financial capital plus its intangible assets (Johnson 1999). However, in <strong>the</strong> new economy era, a
firm’s intellectual capital is always greater than its financial capital. The IC <strong>of</strong> an organization is "equal
three to four times over its book value" (Edvinsson and Malone 1997). In addition, in knowledge- intensive
industries, like banks, added value grows mainly from intangible assets and <strong>the</strong> difference
between market value and book value has been increasing continuously. This is due to <strong>the</strong> essential
role <strong>of</strong> IC as a key resource in supporting <strong>the</strong> added value (Stewart 1997).
Previous studies which examined <strong>the</strong> relationship between IC and innovation had characteristically
focused on two major streams. The first group focuses on <strong>the</strong> relationship between IC (i.e. human
capital, structural capital and relational capital) and innovation, specifically, incremental and radical
innovation in manufacturing sector (e.g. Subramaniam and Youndt 2005; Marqués et al. 2006).The
second group focuses on <strong>the</strong> effect <strong>of</strong> IC on innovation but <strong>the</strong>y ignored which kind <strong>of</strong> innovation is
affected by IC (Wu et al. 2008).
By analysing <strong>the</strong> literature review, this study found that many researchers individually examined <strong>the</strong>
relationship between <strong>the</strong> components <strong>of</strong> IC- without a holistic <strong>of</strong> <strong>the</strong> mutual effect <strong>of</strong> <strong>the</strong>se components
- and <strong>the</strong> types <strong>of</strong> innovation, namely, product and process innovation in manufacturing sector
(e.g. Pizarro et al. 2009; Carmona-Lavado et al. 2010; Lau et al. 2010; Rohrbeck et al. 2010). In <strong>the</strong>
same time, most researchers agreed that <strong>the</strong> intellectual capital consist <strong>of</strong>, at least, three components
(i.e. human capital, structural capital and relational capital) (e.g. Bontis 1998; Bollen et al. 2005; Torres
2006; Cohen and Kaimenakis 2007; Chen et al. 2009; Hsu and Fang 2009; Shih et al. 2010).
Hence, this research considers that <strong>the</strong>se studies did not examine <strong>the</strong> relationship between IC and
product innovation and process innovation in both manufacturing and service sector.
There a scarce <strong>of</strong> <strong>the</strong> studies that explored <strong>the</strong> mutual relationships between IC and product innovation
and process innovation. Therefore, <strong>the</strong> present study addresses this gap in <strong>the</strong> literature. So this
study aims to build a conceptual framework depending on actor network <strong>the</strong>ory to explain <strong>the</strong>se relationships
Moreover, Although most <strong>of</strong> previous studies using actor network <strong>the</strong>ory to explain <strong>the</strong>ir
variables have focused on translation stage as central point in this <strong>the</strong>ory, <strong>the</strong>y have ignored how can
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Ahmed Elsetouhi and Ibrahim Elbeltagi
support translation process stage. Therefore this paper focuses support point which examines <strong>the</strong>
strength <strong>of</strong> links among <strong>the</strong> actors that help <strong>the</strong> network to homogeneously work as well as applying
translation stage. It selects banks as a unit analysis for two reasons. First banks are currently volatile
after <strong>the</strong> financial crises that have had negative effects on banks. Researchers expect that innovation
has an essential role to survive and adapts with uncertainty environment. Second, banks represent
one <strong>of</strong> <strong>the</strong> industries that characterize knowledge-intensive industries so intellectual capital becomes
a key resource to sustain innovation.
The reminder <strong>of</strong> <strong>the</strong> paper is organized as follows. The next section reviews <strong>the</strong> literature on IC, innovation
and actor network <strong>the</strong>ory. The third section outlines <strong>the</strong> conceptual framework. The final section
focuses on conclusions and future research.
2. Literature review
2.1 Intellectual capital (IC)
There are various definitions <strong>of</strong> IC in <strong>the</strong> literature. This paper divides <strong>the</strong>se definitions into two
groups. First, many scholars (e.g. Edvinsson 1996; Bontis 1998; Harrison and Sullivan 2000; Cohen
and kaimenakis 2007) consider IC as an especial resource or asset used to achieve a particular goal.
Second, in this group, IC is total intangible assets (e.g. Brooking 1996; Stewart 1997; Roos and Roos
1997; Hsu and Frang 2009).
This study adopts <strong>the</strong> first group definitions for this reason. IC is considered a subset <strong>of</strong> <strong>the</strong> overall
intangible asset base <strong>of</strong> an organization. This implies that <strong>the</strong>re are items <strong>of</strong> an intangible nature that
do not logically form part <strong>of</strong> an organization's intellectual capital (Petty and Guthrie 2000). Those authors
use <strong>the</strong> example <strong>of</strong> a firm's reputation as one such item. "Reputation may be a result <strong>of</strong> <strong>the</strong> wise
use <strong>of</strong> a firm's intellectual capital, but it is not part <strong>of</strong> intellectual capital for itself”. Ano<strong>the</strong>r example,
intellectual property, i.e. patents, trademarks, registered designs, and copyrights, is defined as a part
<strong>of</strong> intangible asset not a component <strong>of</strong> IC and it differs from IC for two reasons as follows:
Intellectual property is more tangible element <strong>of</strong> intangible assets than IC (Bollen et al. 2005).
IC is <strong>the</strong> main input to support intellectual property (Ibid).
Based on <strong>the</strong> above, this study defines intellectual capital as “An integral part <strong>of</strong> intangible assets that
is captured and utilized effectively to create values or competitive advantages and help companies to
achieve its goals”.
Many scholars agreed that IC consists <strong>of</strong> at least three components namely, human capital, structural
capital and relational capital (e.g. Edvinsson 1997; Edvinsson and Malone 1997; Bontis 1998; Mati
2001; Subramanian and Yound 2005; Marques et al. 2006; Montequin et al. 2006; Wu et al. 2008).
First, human capital (HC) refers to <strong>the</strong> summation <strong>of</strong> employees' tacit knowledge, skills, capabilities,
experience, attitude, and commitment, motivation , leadership, and employees’ job satisfaction (e.g.
Brooking 1996; Edvinsson and Malone 1997; Roos and Roos 1997;Bontis 1998; Bollen et al. 2005;
Chiucchi 2008; Chen et al. 2009; Yang and Lin 2009; Shih et al. 2010). It existed in employees’
minds, not in organization (Chen et al. 2009). HC is <strong>the</strong> greatest resource to sustain competitive advantage.
A company can increase its innovations through its human capital. Therefore, leveraging HC
is no longer an issue <strong>of</strong> choice but it is a matter <strong>of</strong> continued existence (Yang and Lin 2009). It has a
little value if it is used separately. As a result, HC requires an encouraging infrastructure to fulfil <strong>the</strong>
organizational goals (Bontis 1998).
Second, structural capital (SC) is <strong>the</strong> non-human stock <strong>of</strong> knowledge like organizational capabilities,
knowledge management systems, reward systems, information technology systems, databases,
managerial institution, organizational structure and organizational culture (e.g. Brooking 1996; Edvinsson
and Malone 1997; Bontis 1998; Chang et al. 2006; Chen et al. 2009; Shih et al. 2010). It is
embedded in organizations, so it cannot be taken away by employees. This means that SC encompasses
any organizational element that facilitates <strong>the</strong> employees’ ability to create wealth for <strong>the</strong> firm
and its stakeholders. If employees have a high level <strong>of</strong> intellect, but <strong>the</strong> organization has poor systems,
<strong>the</strong> overall IC will not reach its fullest potential (Bontis 1998).
Finally, to achieve <strong>the</strong> organizational goals, companies need to <strong>the</strong> final component namely, relational
capital. It refers to <strong>the</strong> connection between companies and outside environment like customer, suppliers,
shareholders, competitors and o<strong>the</strong>r stakeholders. The relationships which are instituted between
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Ahmed Elsetouhi and Ibrahim Elbeltagi
a firm and its customers represent <strong>the</strong> most important part <strong>of</strong> relational capital (Mayo 2001). As well
as, Customer especially represents cornerstone for banking activities because banks face severe
competitive stress not only among each o<strong>the</strong>r but also with non-banks (e.g. Kaynak and Kucukemiroglu
1992; Hull 2002). Therefore, customer maintenance supports banks to adopt banking competitive
environment. Hence, this study focuses on customer capital (CC) including “customer contracts, loyalty,
and satisfaction "(Mayo 2001).
2.2 Innovation
There is a diverse range <strong>of</strong> definitions <strong>of</strong> innovation in <strong>the</strong> literature. The researchers have carried out
an extensive review <strong>of</strong> <strong>the</strong> various definitions used within innovation literature. This study divided
those into three groups, first, many researchers considered that innovation is creative (e.g. Tushman
and Anderson 1986; Hurley and Hult 1998). Second, according to this group, innovation is adoption or
implementation <strong>of</strong> new idea (e.g. Rogers 1983; Damanpour and Evan 1984; Poole and Van de Ven
2004). Third, this group ga<strong>the</strong>red <strong>the</strong> previous two opinions in one definition where innovation included
creating and adoption new idea (e.g. West and Farr 1990; Egbu 2004; Tidd et al. 2004; Oddane
2008).
Depending on <strong>the</strong> above analysis , this study introduce <strong>the</strong> following definition: "Innovation is an intentional
integrated activity to create and adopt new product and process for <strong>the</strong> relevant business unit <strong>of</strong>
adoption to significantly benefit individual, group, organization or society". This definition reveals that:
first, Innovation is limited to planned activity to achieve desirable goals from change. This means that
it should not depend on chance change (West and Farr 1990). Second, Innovation is an integrated
action including both <strong>the</strong> creation and adoption <strong>of</strong> novelty. Creativity is a source <strong>of</strong> <strong>the</strong> new idea for
innovation. This idea becomes benefit if it is marketable (Ibid). Definitions emphasizing ei<strong>the</strong>r creation
or adoption reflect an unproductively narrow understanding <strong>of</strong> innovation. So this study stresses that
innovation includes creation and adoption <strong>of</strong> novelty.
Third, it is important to clarify <strong>the</strong> use <strong>of</strong> <strong>the</strong> term 'new' in <strong>the</strong> context <strong>of</strong> innovation. Innovation researchers
disagree on <strong>the</strong> requirement <strong>of</strong> novelty. Some stress absolute novelty that an innovation
should be objectively new (e.g. a patent). This means that innovation occurs only when something is
entirely new or it has never been done before (Levitt 1962). On <strong>the</strong> o<strong>the</strong>r hand, o<strong>the</strong>rs emphasize
relative novelty that an innovation is newness with respect to various frames <strong>of</strong> references.
Along with <strong>the</strong> last line, this research views that relative novelty is a more useful novelty requirement
than absolute newness. The requirements <strong>of</strong> absolute novelty would have meant great difficulties in
finding relevant cases in Banking sector because this industry depends on manufacturing sector to
get many innovations like ATM (e.g. Leifer et al. 2000; Gaynor 2002, )( as cited in Oddane 2008) .
Many scholars agree with this line like Rogers (1985) referred to "It matters little whe<strong>the</strong>r <strong>the</strong> idea is
'objectively' new as measured by <strong>the</strong> lapse <strong>of</strong> time since its first use or discovery… If <strong>the</strong> idea seems
new and different to <strong>the</strong> individual, it is an innovation but with various types <strong>of</strong> innovation". Therefore,
if an employee carries new idea to an organization from his or her previous job, this idea and its application
would be considered as an innovation. Fourth, <strong>the</strong> precondition to be an acceptable innovation
is useful and achieves significant benefits for all partners (West and Farr 1990).
Innovation is separated into product and process innovation. Product innovation related to <strong>the</strong> final
product which is sold. It focuses on new benefits, ei<strong>the</strong>r improving a current product or developing a
new product, that are introduced to customers (Cheng et al. 2010). Banks have many product innovations
such as ATMs, debit cards, credit cards, personal bank and mortgage equity account (Damanpour
and Gopalakrishnan 2001).while process innovation is new ways introduced to an organization's
production or service operations (input materials, task specifications, work and information flow
mechanisms, and equipment) to produce goods or services (e.g. Damanpour and Gopalakrishnan
2001; Egbu 2004). It focuses on primarily efficiency driven to improve <strong>the</strong> process <strong>of</strong> product development
and commercialization. Banks have many processes innovation for instance, truncation <strong>of</strong> <strong>the</strong>
check handling process, automated voice response systems, customer information file and risk management
systems (Gopalakrishnan et al. 1999) .Process innovation consists <strong>of</strong> technological innovation
and administrative innovation as follows (Edquist et al. 2001).
Technological innovations refer to technological means that significantly create and improve production
methods, including methods <strong>of</strong> product delivery (Srivastava 2007). They are related to basic work
activities and can relate ei<strong>the</strong>r to product or process (e.g. Damanpour and Evan 1984; Ibrahim et al.
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Ahmed Elsetouhi and Ibrahim Elbeltagi
2008).while administrative innovations occur in <strong>the</strong> administrative components <strong>of</strong> <strong>the</strong> organization.
These innovations can directly influence <strong>the</strong> introduction <strong>of</strong> new products or services or <strong>the</strong> process <strong>of</strong>
producing <strong>the</strong>m. They are only indirectly related to <strong>the</strong> basic work activity <strong>of</strong> <strong>the</strong> organization like new
organizational concepts such as teamwork, job enrichment and enlargement, decentralization <strong>of</strong>
planning, quality circles, and just in time delivery. As well as <strong>the</strong>y are more immediately related to its
management like business reengineering (Hammer and Champy 1993).
Drawing on <strong>the</strong> above discussion, novelty <strong>of</strong> banking innovations has many dimensions like (1) a service
is new to banks customers, (2)banks allow to <strong>the</strong>ir customers to share <strong>the</strong>m in service design,
production, and consumption, (3) changing <strong>the</strong> ways which are employed to service delivery
(4)technology is a main element in process innovation ( Den Hertog 2000). Finally, most previous intellectual
capital literatures addressing innovation have focused on <strong>the</strong> relationship between intellectual
capital and radical and incremental innovation. There is no study examining <strong>the</strong> mutual relationship
between IC and product and process innovation, this study try to address <strong>the</strong>se kinds <strong>of</strong> innovation
to fill <strong>the</strong> gap in <strong>the</strong> literatures.
2.3 Actor network <strong>the</strong>ory (ANT)
2.3.1 Background
Although ANT originated in science studies, it is a distinctive approach to social <strong>the</strong>ory. It is developed
by callon (1986), Law (1986) and Latour (1986). This paper analyzes many facts relating to ANT.
First, ANT maps out <strong>the</strong> mutual relationships between humans and non-humans called actors that
create a network described as black box which needs to interpret <strong>the</strong>se interrelationships. Unlike social
networks <strong>the</strong>ory represented networks <strong>of</strong> people. Actors choose each o<strong>the</strong>r in order to achieve
both individual and collective goals (House 2001). As well as, actor network is heterogeneous resources.
Successful organizations employ heterogeneous variables as possible to work in harmony
(Rafea 1999).
Second, ANT focuses on <strong>the</strong> alignment <strong>of</strong> interests. It emphasizes on collective action <strong>of</strong> an organization
to achieve its goals. In o<strong>the</strong>r words, it is a heterogeneous network <strong>of</strong> aligned interests (Latour
2005).Any network may be broken into actors if <strong>the</strong>re is no common goal for ga<strong>the</strong>ring <strong>the</strong>se diverse
actors toge<strong>the</strong>r to perform as one or one actor <strong>of</strong> an actor-network may be moved to ano<strong>the</strong>r actor
network for <strong>the</strong> previous same reason (Monterio 2000). A successful network consists <strong>of</strong> different actors
aligning <strong>the</strong>ir interests. Actors align by having <strong>the</strong>ir interests translated into <strong>the</strong> common interest
<strong>of</strong> <strong>the</strong> network, and by having <strong>the</strong> actors participate in certain ways <strong>of</strong> thinking and acting that maintain
<strong>the</strong> network (Latour 2005). Third, ANT assert that <strong>the</strong> process <strong>of</strong> translation <strong>of</strong> <strong>the</strong>se interests into
stable networks is achieved through a series <strong>of</strong> four "moments <strong>of</strong> translation" namely, problematization,
interssement, enrollment and mobilization (e.g. Rhodes 2009; Young et al. 2010).
2.3.2 Central concepts
The current part describes and reviews <strong>the</strong> concepts related to (ANT) that are showed in Table 1.
Table 1: Conceptions related to ANT
Concept Description
Actor “Actor is a semiotic term, and as such, an actor is not an entity to which human intentional
behaviour can be attributed, but a more abstract term which can refer to ei<strong>the</strong>r human or
non-human entities"(Fountain 1999) .
Network Network is a group <strong>of</strong> knots representing actors and links which mean set <strong>of</strong> relationships
between actors (Young et al. 2010).
Actor network "Actor network is a description <strong>of</strong> <strong>the</strong> way things are, it consists <strong>of</strong> a series <strong>of</strong> heterogeneous
animate and inanimate elements that have been linked to each o<strong>the</strong>r over time" (Callon
1986).
Translation Translation is central point to create a coherent actor network that achieves definitive goal
.It consists <strong>of</strong> problematization, interssement, enrollment and mobilization stage (Rhodes
2009).
Focal actor Focal actor is an actor who convinces o<strong>the</strong>r actors to accept and to fulfill a network's goal
(Potts 2009).
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Ahmed Elsetouhi and Ibrahim Elbeltagi
Concept Description
Problematization Problematization means that focal actor defines <strong>the</strong> nature <strong>of</strong> problem and suggests <strong>the</strong>
objectives that solve it. Therefore, focal actor negotiates with o<strong>the</strong>r actors to adopt <strong>the</strong>se
objectives which become an obligatory passage point (OPP) Callon (1986).
OPP OPP relates to agreed objectives among actors. Network does not allow any actor to enter
into it except <strong>the</strong> actor that adopts network's interests (Ibid).
Interessement Interessement relates to primarily convince all actors to follow <strong>the</strong> way suggested from
focal actor to solve <strong>the</strong> problem (Ibid).
Enrollment Enrollment means that actors accepted to adopt network's goals (Duim and Marwijk 2006).
Mobilization It refers that network's actors try to attract o<strong>the</strong>r actors to share <strong>the</strong>m in sustaining <strong>the</strong>ir
network. This means that actors have loyalty toward <strong>the</strong>ir network's goals. (Rhodes 2009).
3. Conceptual framework
The current study depends on <strong>the</strong> ANT to build a conceptual framework presented in (Figure 1) for
<strong>the</strong> relationship between IC and process and product innovation as follows:
3.1 Define <strong>the</strong> actors and <strong>the</strong> network (support point stage)
Network has Material actor like SC and non-material actors named HC and CC. According to <strong>the</strong> previous
definitions, network consists <strong>of</strong> knots and links. This means that <strong>the</strong>re are interrelationships
among actors which consider as support point to translation stage First, <strong>the</strong> relationship between human
and structural capital was mutual significant positive correlation. This means that organizations
should focus not only on hiring <strong>the</strong> brightest employees but also on supporting and nurturing <strong>the</strong>ir
skills to be able to develop structural capital. Second, human capital has significantly affected on relational
(customer) capital. This refers to <strong>the</strong> qualified employees will have <strong>the</strong> ability to understand customers'
needs for maximizing <strong>the</strong>ir loyalty. Third, structural capital significantly relates to customer
capital. The organizations which adopt customer orientation build efficient organizational routines and
process that service <strong>the</strong>ir clients well. The organizations depending on knowledge from <strong>the</strong>ir own clients
become leader not a follower in its market (e.g. Bontis, 1998; Cohen and Kaimenakis, 2007; Hsu
and Fang, 2009; Chen et al., 2009). Finally, <strong>the</strong> previous results refer that <strong>the</strong>se actors work toge<strong>the</strong>r
in harmony. This paper expects that this stage called support point will sustain next stage..
3.2 Translation
Before explaining <strong>the</strong> four moments <strong>of</strong> translation, focal actor should be defined. As mentioned
above, Leadership represents a component <strong>of</strong> HC. This study focuses on leadership in top management
and separates it from HC to be become focal actor for two reasons: (1) top management is <strong>the</strong>
group <strong>of</strong> decision makers generally charged with organizational strategy and it has authority to deploy
all resources in bank. Therefore, top management has special abilities to convince o<strong>the</strong>r actors to
adopt its aim (2) top management plays an essential role in fostering innovation (e.g. West and Farr
1990; Carmen et al. 2006).
3.2.1 Problematization
In recent years, although banks have applied great innovations, many banks declared bankruptcy.
This put a lot <strong>of</strong> pressure on top management (focal actor) to identify <strong>the</strong> relevant actors or resources
which support process and product innovation. This means that focal actor has not allowed to any
actor to be a part <strong>of</strong> its network but only <strong>the</strong> actor which accept to sustain product and process innovation
.This aim is called (OPP).Many previous studies emphasize that IC (HC, SC and CC) has a
significant effect on innovation as follows:
HC and innovation
Many studies examined <strong>the</strong> effect <strong>of</strong> HC on innovation without focusing on product and process innovation.
HC has a positive influence on innovation. It plays a mediating role to support <strong>the</strong> effect <strong>of</strong> social
capital and entrepreneurial orientation on innovation (Wu et al. 2008). Human capital interacted
with social capital to positively influence radical innovation (Subramaniam and Youndt 2005). On <strong>the</strong>
o<strong>the</strong>r hand, <strong>the</strong> relationship between human capital and product innovation was empirically examined.
The results revealed that human capital has a positive influence on product innovation in manufacturing
sector (Pizarro et al. 2009).
151

Ahmed Elsetouhi and Ibrahim Elbeltagi
(1)
Resources:
(2)
(3)
1- Tangible
assets
2- Intangible
assets
(8)
Encouraging o<strong>the</strong>r
actors network
like social capital
to participate in
this actor.
Intellectual HC
capital:
1- HC
2- SC
3- CC
SC
Figure 1: Conceptual framework
SC and innovation
Previous researchers argued that structural capital has a positive effect on innovation and performance
<strong>of</strong> its new product development (Menona et al. 2002). Wu et al. (2008) indicated that <strong>the</strong> relationship
between SC and innovation is positive and SC supports social capital and entrepreneurial
orientation to positive effect on innovation. SC has a positive effect on incremental innovation
(Subramaniam and Youndt 2005). In additional to, Carmona-Lavado et al. (2010) analyze <strong>the</strong> influ-
(6)
Innovation HC
Innovation SC
Innovation CC
Product
Inn.
Product
Inn.
+
Process
Inn.
+
CC
+
SC
+
+
HC
(7)
+
+
+
(4)
Focal actor (Leadership
for top Management)
OPP (product and process
innovation )
CC
(5)
HC Innovation
SC Innovation
CC Innovation
Product
Inn.
+
+
+
Product
Inn.
Process
Inn.
Key: 2= human and non-human actors, 3= network (Support point), 4+5= problematization,
6=Interessement,
7= enrollment, 8= mobilization
152

Ahmed Elsetouhi and Ibrahim Elbeltagi
ence <strong>of</strong> organizational capital and social capital, on product innovation in Spanish industrial companies.
Their findings showed that structural capital has an indirect effect on product innovation through
positive influence on social capital.
CC and innovation
The integration between customer and innovation process is a powerful mean to reduce failure rates
and to increase <strong>the</strong> revenue from new products (Rohrbeck et al., 2010). CC has a positive effect on
incremental and radical innovation (Subramaniam and Youndt, 2005). Kammerer (2009) show that
customer has a significant effect on product innovation.
Based on previous results, IC (I.e. HC, SC and CC) has an essential role to support innovation so this
study expects that <strong>the</strong>se components will improve both product and process innovation. Consequently,
HC, SC and CC become as candidates to share in <strong>the</strong> focal actor's network.
3.2.2 Interssement
With <strong>the</strong> end <strong>of</strong> <strong>the</strong> previous stage, focal actor has conviction that <strong>the</strong>se actors (HC, SC, CC) have a
key role to sustain product and process innovation. Therefore, focal actor should do great efforts to
convince actors to support its aim. As soon as actors adopt innovation, <strong>the</strong>y will gain a lot <strong>of</strong> interests
from innovation as follows:
HC's interests from innovation
Innovations create <strong>the</strong> desire to make a good prestige, pr<strong>of</strong>essional position, support personal ambition,
growth and increase job satisfaction. They improve <strong>the</strong> stock <strong>of</strong> knowledge (West and Farr,
1990). West (1989) reported that innovation makes changes in job areas "(1) changed work objectives
or introduced new work objectives, (2) changed work techniques (3) Changed whom you deal
with or how you deal with people (4) learned new skills". In addition to, Marqués et al., (2006) mentioned
that incremental and radical innovations have a positive effect on human capital.
SC's interests from innovation
It is also important to highlight <strong>the</strong> effect <strong>of</strong> Incremental and radical innovations on structural capital.
The results assert that both dimensions <strong>of</strong> innovation have a key role to support structural capital
such as, developing rules, databases, knowledge management and it generates innovation culture
inside organization.
CC's interests from innovation
A fur<strong>the</strong>r important result is that Incremental and radical innovations have a greater impact on CC
than <strong>the</strong> o<strong>the</strong>r elements <strong>of</strong> IC (Ibid). This means that, organization has a clear understanding <strong>of</strong> user
wants and needs. Innovation have many advantages for customer for instance, (1) developing customers'
life (2) enabling customers to find new ways to service <strong>the</strong>ir personal needs (3) representing a
mean to enable customers to productively pursue <strong>the</strong>ir individualized satisfaction (4) helping to find
new ways <strong>of</strong> co-solving customer problems (Michel et al. 2008).
3.2.3 Enrollment
The third moment <strong>of</strong> translation is enrollment, when actors are “willing to anchor <strong>the</strong>mselves to <strong>the</strong>
collectors” (Callon 1986). In this stage, actors accept definition <strong>of</strong> focal actor. This acceptance gives
more strength to <strong>the</strong> obligatory passage point than it in previous two moments. These actors consider
that this network is indispensable to achieve all interests. Enrollment is made visible through actors
create and interchange a new ideas with o<strong>the</strong>r actors and adoption product and process innovation
(e.g. Potts 2009; Rhodes 2009). Focal actor should improve an appropriate working environment to
enable <strong>the</strong>se actors to support product and process innovation.
3.2.4 Mobilization
Current actors are encouraging o<strong>the</strong>rs to participate in <strong>the</strong>ir actor-network. Mobilization supports <strong>the</strong>
emergence <strong>of</strong> spokespersons that convince o<strong>the</strong>r actors not linked before to enter to <strong>the</strong>ir actornetwork
(Potts 2009). Therefore, this activity significantly streng<strong>the</strong>ned <strong>the</strong> IC actor-network. For example,
social capital is possible to add this element to IC actor-network that Zheng et al. (2010) mentioned
that social capital has significant positive effect on innovation and it supports human capital to
be more effective in innovation.
153

Ahmed Elsetouhi and Ibrahim Elbeltagi
Finally, <strong>the</strong> stability <strong>of</strong> <strong>the</strong> actor- network depends on <strong>the</strong> strength <strong>of</strong> relationships between actors and
focal actor as well as <strong>the</strong> ability <strong>of</strong> spokespersons to attract o<strong>the</strong>r actors (Rhodes 2009). As a result <strong>of</strong>
<strong>the</strong>se examinations, it is expected that <strong>the</strong> relationships between IC and process and product innovation
are mutually positive in banks.
4. Conclusions and future research
Past studies examined <strong>the</strong> effect <strong>of</strong> IC (HC, SC and CC) on radical and incremental innovation. There
are scarce in prior studies that investigate <strong>the</strong> mutual relationship between IC and product and process
innovation. Therefore, this study analyzes <strong>the</strong>se relationships through building a conceptual
framework depending on (ANT) to explain <strong>the</strong>se relationships. ANT focuses on two stages as follows:
First, support point stage concerns to examine <strong>the</strong> interrelationships among actors. Previous studies
proved that <strong>the</strong>re are positive interactions between HC, SC and CC. This emphasizes that <strong>the</strong>se actors
work toge<strong>the</strong>r in harmony. Therefore, this stage will support <strong>the</strong> next stage. Second, Interssement
indicate that focal actor should do great efforts to convince <strong>the</strong>se actors to support its aim. Many researchers
showed that innovation has many interests to HC, SC and CC. For example, innovation
helps customer to find new ways to solve his problems and provides new skills to employees (e.g.
West 1989; Marqués et al. 2006). Third, enrollment means that actors accept <strong>the</strong> focal actor's aim.
Fourth, mobilization reveals that current actors are looking for o<strong>the</strong>rs actors to participate in <strong>the</strong>ir actor-network
like social capital.
Finally, this study presented a conceptual framework depending on ANT to explain <strong>the</strong>se relationships.
It is expected that relationships between IC and process and product innovation are mutually
positive. Future research should empirically examine this conceptual framework and it should insert
and test social capital as a new actor to <strong>the</strong> current network.
References
Bollen, L., Vergauwen, P. and Schnieders, S. (2005)" Linking Intellectual Capital and Intellectual Property to
Company Performance", Management Decision, Vol 43, No. 9, pp 1161-1185.
Bontis, N. (1998)"Intellectual Capital: An Exploratory Study that Develops Measures and Models, Management
Decision, Vol 36, No.2 ,pp63–76.
Brooking, A (1996) Intellectual Capital – Core Asset for <strong>the</strong> Third Millennium Enterprise, International Thomson
Business Press, London.
Callon, M. (1986) "Some Elements <strong>of</strong> Sociology <strong>of</strong> Translation—Domestication <strong>of</strong> <strong>the</strong> Scallops and <strong>the</strong> Fishermen
<strong>of</strong> St-Brieuc Bay", in J. Law (ed.) Power, Action and Belief: A New Sociology <strong>of</strong> Knowledge? , pp196–
223, London: Routledge.
Carmen, C., la Luz, F. and Salustiano, M. (2006)"Influence <strong>of</strong> Top Management Team Vision and Work Team
Characteristics on Innovation: The Spanish case", <strong>European</strong> Journal <strong>of</strong> Innovation Management, Vol 9, No.
2, pp 179 – 201.
Carmona-Lavado, A., Cuevas-Rodríguez, G. and Cabello-Medina, C. (2010) “Social and Organizational Capital:
Building <strong>the</strong> Context for Innovation”, Industrial Marketing Management, Vol 39, pp 681–690.
Chen, M., Cheng, S. and Hwang, Y. (2005)"An Empirical Investigation <strong>of</strong> <strong>the</strong> Relationship between Intellectual
Capital and Firms' Market Value and Financial Performance", Journal <strong>of</strong> Intellectual Capital, Vol 6, No.2, pp
159-176.
Chiucchi, M. (2008) “Exploring <strong>the</strong> Benefits <strong>of</strong> Measuring Intellectual Capital. The Aimag Case Study”, Human
Systems Management, Vol 27, No. 3, pp 217-230.
Cohen, S. and Kaimenakis, N. (2007), "Intellectual Capital and Corporate Performance in Knowledge-Intensive
SMEs", The Learning Organization, Vol 14, No. 3, pp 241-262.
Damanpour, F. and Gopalakrishnan, S. (2001) “The Dynamics <strong>of</strong> <strong>the</strong> Adoption <strong>of</strong> Product and Process Innovations
in Organization”, Journal <strong>of</strong> Management Studies, Vol 38, No.1, pp 45-66.
Damanpour, F. and Evan, W. (1984) “Organizational Innovation and Performance: The Problem <strong>of</strong> Organizational
Lag”, Administrative Science Quarterly, Vol 29, pp 392-402.
Den Hertog, P. (2000) “Knowledge Intensive Business Services as Co-producers <strong>of</strong> Innovation”, 6 Countries Programme
<strong>Conference</strong> on Services in Innovation, Utrecht 11-12 May.
Duim, R. and Marwijk, R. (2006) " The Implementation <strong>of</strong> an Environmental Management System for Dutch Tour
Operators: An Actor-network Perspective", Journal <strong>of</strong> Sustainable Tourism, Vol 14, No. 5, pp 449- 472.
Edvinsson, L. (1997)" Developing Intellectual Capital at Skandia", Long Range Planning, Vol 30, No.3, pp 366-
373.
Edvinsson, L. and Malone, M. (1997)" Intellectual Capital: <strong>the</strong> Proven Way to Establish Your Company's Real
Value by Measuring Its Hidden Values", Judy Piatkus, London.
Edquist, C., Hommen, L. and Mckelvey, M. (2001) Innovation and Employment: Process versus Product Innovation,
Edward Elgar Publishing Limited, UK.
154

Ahmed Elsetouhi and Ibrahim Elbeltagi
Egbu, C. (2004) “Managing Knowledge and Intellectual Capital for Improved Organizational Innovations in The
Constructions Industry: An Examination <strong>of</strong> Critical Success Factors”, Engineering, Construction and Architectural
Management, Vol 11, No.5, pp301-315.
Fountain, R. (1999) “Knowledge: Theory <strong>of</strong> Science”. Journal <strong>of</strong> Curriculum Studies, Vol 31, No.3, pp 339- 359.
Gopalakrishnan, S., Bierly, P. and Kessler, E. (1999) “A Reexamination <strong>of</strong> Product and Process Innovations Using
A Knowledge –Based View”, The Journal <strong>of</strong> High Technology Management Research, Vol 10, No.1, pp
147-166.
Hammer, M. and Champy, J. (1993) Reengineering <strong>the</strong> Corporation, Harper Business, New York.
Harrison, S. and Sullivan P. (2000) " Pr<strong>of</strong>iting from Intellectual Capital: Learning from Leading Companies", Journal
<strong>of</strong> Intellectual Capital, Vol 1, No.1, pp 33-46.
Hsu, Y. and Fang, W. (2009)" Intellectual Capital and New Product Development Performance: The Mediating
Role <strong>of</strong> Organizational Learning Capability", Technological Forecasting & Social Change, Vol 76, No. 5, pp
664–677.
Hull, B., (2002) “A structure for Supply-Chain Information Flows and its Application to <strong>the</strong> Alaskan Crude Oil Supply
Chain”, Logistics Information Management, Vol 15, No.1, pp 8- 23. Hurley, R. and Hult, T. (1998) “Innovation,
Market Orientation, and Organizational Learning: An Integration and Empirical Examination”, Journal
<strong>of</strong> Marketing, Vol 62, No. 3, pp 42-54.
Ibrahim, A., Mohamed, E., Saad, A. and Ramayah, T. (2008) “Determining Technological Innovation and Competitiveness:
A Cross Organizational Analysis <strong>of</strong> <strong>the</strong> Malaysian Manufacturing Industry”,
www.sbm.itb.ac.id/wp-content/uploads/2010/01/Vol-1-No-2-December-
Johnson, W. (1999) “An Integrative Taxonomy <strong>of</strong> Intellectual Capital: Measuring <strong>the</strong> Stock and Flow <strong>of</strong> Intellectual
Capital Components in <strong>the</strong> Firm “, International Journal <strong>of</strong> Technology Management, Vol 18, No. 5-8, pp
562 – 575.
Kammerer, D. (2009)"The Effects <strong>of</strong> Customer Benefit and Regulation on Environmental Product Innovation:
Empirical Evidence from Appliance Manufacturers in Germany", Ecological Economics, Vol. 68, No. 8-9, pp
2285-2295.
Kaynak, E. and Kucukemiroglu, O. (1992) “Sourcing <strong>of</strong> Industrial Products: Regiocentric Orientation <strong>of</strong> Chinese
Organizational Buyers”. <strong>European</strong> Journal <strong>of</strong> Marketing, Vol 26, No.5, pp 23-55.
Latour, B. (1986) "The Powers <strong>of</strong> Association", in J. Law (ed.) Power, Action and Belief: A New Sociology <strong>of</strong>
Knowledge?, pp 234–263, London: Routledge.
Latour, B. (2005) Reassembling <strong>the</strong> Social: An Introduction to Actor Network Theory, Oxford University Press,
Oxford.
Lau, A., Tang, E. and Yam, R. (2010) “Effects <strong>of</strong> Supplier and Customer Integration on Product Innovation and
Performance: Empirical Evidence in Hong Kong Manufacturers”, Journal <strong>of</strong> Product Innovation, Vol 27, No.
5, pp 761-777.
Law, J. (1986) "On <strong>the</strong> Methods <strong>of</strong> Long-Distance Control—Vessels, Navigation and <strong>the</strong> Portuguese Route to
India", in J. Law (ed.) Power, Action and Belief: A New Sociology <strong>of</strong> Knowledge? pp 234–263, London:
Routledge.
Levitt, T. (1962) Innovation Marketing, Pan Books, London.
Marqués, D., Simón, F. and Carańa, C. (2006) “The effect <strong>of</strong> Innovation on Intellectual Capital: An Empirical
Evaluation in <strong>the</strong> Biotechnology and Telecommunications Industries”, International Journal <strong>of</strong> Innovation
Management, Vol 10, No. 1, pp 89-112.
Mayo, A. (2001) “The Role <strong>of</strong> Employee Development in <strong>the</strong> Growth <strong>of</strong> Intellectual Capital”, Personnel Review,
Vol 29 No. 4, pp 521-533.
Menona, A., Chowdhury, J. and Lukas, B. (2002)"Antecedents and Outcomes <strong>of</strong> New Product Development
Speed An Interdisciplinary Conceptual Framework" Industrial Marketing Management, Vol 31, No. 4, pp
317-328.
Monterio, E. (2000) “Actor-Network Theory and Information Infrastructure”, in From Control to Drift, C. U. Ciborra
(ed.), pp 71-86, Oxford University Press, Oxford.
Michel, S., Brown, S. and Gallan, A. (2008) " Service-Logic Innovations: How to Innovation Customers, Not
Product", California Management Review, Vol 50, No. 3, pp 49-65.
Oddane, T. (2008) “Organizational Conditions for Innovation: A Multi-perspective Approach to Innovation in a
Large Industrial Company”, Norwegian University <strong>of</strong> Science and Technology.
Pizarro, I., Real, J. and Rosa, D. (2009) “The Role <strong>of</strong> Entrepreneurial Culture and Human Capital in Innovation”,
Working Paper Series, Department <strong>of</strong> Business Administration, Universidad Pablo de Olavide.
Poole, M. and Van de Ven, A. (2004) Handbook <strong>of</strong> Organizational Change and Innovation, Oxford University
Press, New York.
Potts, L. (2009)" Using Actor Network Theory to Trace and Improve Multimodal Communication Design", Technical
Communication Quarterly, Vol 18, No.3, pp 281–301.
Rafea, A. (1999) "Power, Curriculum Making and Actor- Network Theory: The Case <strong>of</strong> Physics, Technology and
Society Curriculum in Bahrain", University <strong>of</strong> British Columbia.
Rhodes, J. (2009) " A Strategic Framework for Rural Micro-Enterprise Development: The Integration <strong>of</strong> Information
Communication Technology (ICT), E-Commerce, Marketing, and Actor-Network Theory", PGDT, Vol 8,
pp 48-69.
Rogers, E. (1983) Diffusion <strong>of</strong> Innovations, Third edition, Free Press, London.
155

Ahmed Elsetouhi and Ibrahim Elbeltagi
Rohrbeck, R., Steinh<strong>of</strong>f, F. and Perder, F. (2010) “Sourcing Innovation from your Customer: How Multinational
Enterprises Use Web Platforms for Virtual Customer Integration”, Technology Analysis & Strategic Management,
Vol 22, No. 2, pp 117-131.
Roos, G. and Roos, J. (1997) "Measuring your Company's Intellectual Performance", Long Range Planning, Vol
30, No. 3, pp 413-426.
Srivastava, M. (2007) “Friends or Neighbors? The Effects <strong>of</strong> Inter-firm Networks and Clusters on Technological
Innovations in <strong>the</strong> U.S. Semiconductor Industry”, Virginia Polytechnic Institute and State University.
Stewart, T. (1997) “Intellectual Capital: The New Wealth <strong>of</strong> Organizations”, Doubleday, New York.
Subramaniam, M. and Youndt, M. (2005) “The Influence <strong>of</strong> Intellectual Capital on <strong>the</strong> Types <strong>of</strong> Innovative Capabilities",
Academy <strong>of</strong> Management Journal, Vol 48, No.3, pp 450-463.
Torres, M. (2006) " A Procedure to Design a Structural and Measurement Model <strong>of</strong> Intellectual Capital: An Exploratory
Study", Information& Management, Vol 43, No. 5, pp 617-626. Trott, P.(2005) Innovation Management
New Product Development, Third Edition, Pearson Education Limited, England.
Tushman, M. and Anderson, P. (1986) “Technological Discontinuities and Organizational Environments”, Administrative
Science Quarterly, Vol 31, No. 3, pp 439-465.
West, M. and Farr, J. (1990) Innovation and Creativity at Work, John Wiley & Sons Ltd., England.
Wu, W., Chang, M. and Chen, C. (2008) “Promoting Innovation through <strong>the</strong> Accumulation <strong>of</strong> Intellectual Capital,
Social Capital, and Entrepreneurial Orientation”, R&D Management, Vol 38, No. 3, pp 265- 77.
Yang, C. and Lin, C. (2009) “Does Intellectual Capital Mediate <strong>the</strong> Relationship between HRM and Organizational
Performance? Perspective <strong>of</strong> a Healthcare Industry in Taiwan”, The International Journal <strong>of</strong> Human Resource
Management, Vol 20, No. 9, pp 1965-1984.
Yang, C., Marlow, P. and Lu, C. (2009) “Assessing Resources, Logistics Service Capabilities, Innovation Capabilities
and <strong>the</strong> Performance <strong>of</strong> Container Shipping Services in Taiwan”, Int. J. Production Economics, Vol
122, No. 1, pp 4–20.
Young, D., Borland, R. and Coghill, K. (2010) " An Actor-Network Theory Analysis <strong>of</strong> Policy Innovation for
Smoke-Free Places: Understanding Change in Complex Systems", American Journal <strong>of</strong> Public Health, Vol
100, No. 7, pp 1208- 1217.
Zheng, W., Khoury, E. and Grobmeier, C. (2010)"How do Leadership and Context Matter in R&D Team Innovation?
A Multiple Case Study", Human Resource Development International, Vol 13, No. 3, pp 265-283.
156

The Strategies and Tactics <strong>of</strong> Patent Management and Their
Importance for Competitive Advantage
Albrecht Fritzsche 1 and Rebecca Geiger 2
1
Institute for Philosophy, TU Darmstadt, Germany
2
International Performance Research Institute gemeinnützige GmbH, Germany
a.m.fritzsche@gmx.net
rgeiger@ipri-institute.com
Abstract: In order to gain a better understanding <strong>of</strong> patenting activities, it is necessary to overcome <strong>the</strong> simplifications
<strong>of</strong> identifying a patent with a competitive advantage. Companies use patenting in many different ways for
different purposes. Based on <strong>the</strong> subsequent steps <strong>of</strong> rational problem solving, it is possible to establish a
framework <strong>of</strong> patent management that distinguishes <strong>the</strong> strategies <strong>of</strong> patenting and <strong>the</strong> tactical moves that are be
applied to pursue <strong>the</strong>m. Based on <strong>the</strong> review <strong>of</strong> current literature, four strategies and eleven tactical moves can be
identified. The distinction between strategies and tactics makes it easier to describe <strong>the</strong> role <strong>of</strong> patenting in <strong>the</strong>
knowledge society and <strong>the</strong> emerging market for intellectual property in <strong>the</strong> high tech industry. In particular, <strong>the</strong>
reference to <strong>the</strong> tactical moves in which companies make use <strong>of</strong> <strong>the</strong>ir patents can improve <strong>the</strong> methods to assess
<strong>the</strong> value that patents have for <strong>the</strong>ir owners.
Keywords: intellectual capital, intellectual property, procedurals in patent management, strategic and tactical
aspects <strong>of</strong> patent management
1. Introduction
In <strong>the</strong> last two decades, <strong>the</strong> annual number <strong>of</strong> patent registrations has tripled. This development has
proceeded similarly in all big industrial countries. While <strong>the</strong> sudden growth <strong>of</strong> patent registrations in <strong>the</strong>
mid-eighties in <strong>the</strong> United States <strong>of</strong> America can be explained by changes in <strong>the</strong> legislation that made
registrations easier (see e.g. Thurows 1997), <strong>the</strong> continuous augmentation throughout <strong>the</strong> last years is
an expression <strong>of</strong> a more fundamental economic development. Companies make more use <strong>of</strong> patents
than ever before and <strong>the</strong>y do so in ways that have until recently not been reflected in academic research.
Patents represent a considerable part <strong>of</strong> <strong>the</strong> documented technological knowledge in <strong>the</strong> world, which
includes <strong>the</strong> current state <strong>of</strong> <strong>the</strong> art. They also indicate new directions and trends in technological development;
various studies have shown that <strong>the</strong>re is a strong connection between intellectual property
rights and innovative power (Harh<strong>of</strong>f 2006, Kanwar/Evenson 2003, Hall 2007, Qian 2006, Frietsch et al.
2010). By patent management a company can both benchmark its R&D contributions with respect to its
competitors and realize competitive strategies in technological development.
Recent publications on <strong>the</strong> topic <strong>of</strong> patent management draw a detailed picture <strong>of</strong> <strong>the</strong> patenting activity
in different countries and industries. They also make clear that <strong>the</strong> motivation to register patents varies
quite a lot between different companies. So far, however, it has remained most unclear how this behaviour
should be administered and evaluated for its success. This paper suggests a framework that
allows a systematic approach to patenting in terms <strong>of</strong> rational problem solving.
2. Dimensions <strong>of</strong> patent management
2.1 Patents and intellectual capital
The term intellectual capital subsumes a variety <strong>of</strong> different intangible assets, including human capital,
structural capital, and relational capital (Sullivan 2000, Stewart 1997, Sveiby 1997, Maddocks/Beaney
2002, Edvinsson/Malone 1997, Skyrme 1998). Intellectual capital affects economic operations in many
different ways. For example, human capital – and to some extent also structural and relational capital –
determine <strong>the</strong> potential <strong>of</strong> a company for technical innovation. Patents, trademarks, design rights and
utility models are legal means to secure exclusive access to an innovation. With <strong>the</strong> existence <strong>of</strong> <strong>the</strong>se
rights, <strong>the</strong> innovation turns into property. Patents enable a company to exploit it without having to share
it with <strong>the</strong> competition. In models <strong>of</strong> market dynamics, <strong>the</strong> economic effect <strong>of</strong> patents is usually described
as a temporary monopoly that allows <strong>the</strong> company to setup higher prices; making innovative
activity more pr<strong>of</strong>itable (see Arrow 1962, Nordhaus 1969). In that sense, patents are one way for a
company to get a pay<strong>of</strong>f from <strong>the</strong>ir intellectual capital.
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Various studies, however, indicate that <strong>the</strong> relation between patenting, intellectual capital and competitive
advantage is actually much more complicated. Patents do not necessarily imply an advantage
on <strong>the</strong> market. The exclusively owned technology can relate to products on <strong>the</strong> market in many different
ways. Most <strong>of</strong> <strong>the</strong> times, a single patent is only relevant for a very specific part <strong>of</strong> a product or a
manufacturing process. O<strong>the</strong>r companies can <strong>the</strong>refore develop different solutions. In many cases, <strong>the</strong>
competitors own o<strong>the</strong>r patents which refer to o<strong>the</strong>r parts <strong>of</strong> a product, or <strong>the</strong>y may even pr<strong>of</strong>it from <strong>the</strong>
explication <strong>of</strong> <strong>the</strong> innovation in <strong>the</strong> patent catalogue for fur<strong>the</strong>r inventions (Levin et al. 1987, Harabi
1995, Sattler 2003). In such cases, o<strong>the</strong>r mechanisms <strong>of</strong> protection, for example shorter times to
market, <strong>the</strong> control <strong>of</strong> resources, complex designs or secrecy can be more effective and efficient than
patents (Levin et al. 1987, Harabi 1995, Sattler 2003, Hipp 2006). In addition, infringements are a
common phenomenon that causes significant problems for <strong>the</strong> owners <strong>of</strong> patents, making <strong>the</strong> effort for
patenting ra<strong>the</strong>r futile (see e.g. Feinberg/Rousslang (1990), Mansfield et al. (1981), Lerner (1995)).
Never<strong>the</strong>less, it remains a fact that <strong>the</strong> interest in patents is rising. In order to understand this phenomenon,
<strong>the</strong> patenting activities in <strong>the</strong> companies require fur<strong>the</strong>r attention.
2.2 Patenting practice
Many authors have recently studied <strong>the</strong> way how companies make practical use <strong>of</strong> patenting. Rahn
(1994) focuses on <strong>the</strong> patenting behaviour in Japan and emphasizes <strong>the</strong> similarities between fighting
for a competitive advantage and warfare. As a consequence, <strong>the</strong> author approaches <strong>the</strong> usage <strong>of</strong>
patents in terms <strong>of</strong> military strategy. Rahn argues from <strong>the</strong> perspective <strong>of</strong> a patent attorney and distinguishes
various different strategies to accomplish <strong>the</strong>se goals. Ernst (1995) studies patenting activities
in <strong>the</strong> German mechanical engineering industry and <strong>the</strong>ir relationship to company performance.
The paper distinguishes systematic patenting activities according to a general policy and selective
patenting <strong>of</strong> specific inventions and highlights <strong>the</strong> difference between national and international patenting.
Granstrand (1999) gives a complete overview <strong>of</strong> intellectual property management and its
economic impact, including an explication <strong>of</strong> different patenting policies and strategies that can be
applied in pursuing <strong>the</strong>m. These strategies mostly refer to <strong>the</strong> way how several patents can be combined
to have a stronger effect on <strong>the</strong> competition. Granstrand also discusses strategies to react to <strong>the</strong>
patenting activity <strong>of</strong> <strong>the</strong> competitors. Cohen et al. (2002) present <strong>the</strong> results <strong>of</strong> a comparative study
among American and Japanese companies about <strong>the</strong> different functions attributed to patenting. The
paper is mainly interested in showing <strong>the</strong> effects <strong>of</strong> patenting on <strong>the</strong> development and distribution <strong>of</strong>
knowledge in <strong>the</strong> industry. Shapiro (2001) studies how patents interfere with <strong>the</strong> innovative activities in
various high-tech industries and <strong>the</strong> licensing activities between different companies (on that topic see
also Burr 2004). Shapiro coins <strong>the</strong> term "patent thicket" to emphasise <strong>the</strong> problem that each product can
be affected by a multitude <strong>of</strong> patents from many o<strong>the</strong>r companies. As a consequence, co-operative
behaviour is necessary to avoid a complete deadlock <strong>of</strong> innovation in <strong>the</strong> industry. Burr et al. (2007)
provide ano<strong>the</strong>r overview <strong>of</strong> all aspects <strong>of</strong> patent management, distinguishing <strong>of</strong>fensive and defensive
as well as sporadic and comprehensive patenting activities and patent licensing.
3. A framework <strong>of</strong> patenting behaviour
3.1 Patents as instruments
The current state <strong>of</strong> research makes clear that it is necessary to distinguish patenting as an act from its
purpose. The registration <strong>of</strong> a patent is not identical to <strong>the</strong> protection <strong>of</strong> a product against competitors; it
is an <strong>of</strong>ficial claim <strong>of</strong> possession concerning an innovation which exerts a legal restriction on <strong>the</strong> potential
<strong>of</strong> o<strong>the</strong>rs to make use <strong>of</strong> this innovation. The protection <strong>of</strong> a product against competition is a
potential effect <strong>of</strong> this restriction. The extent <strong>of</strong> this protection depends on <strong>the</strong> relation between <strong>the</strong>
innovation and <strong>the</strong> product. If <strong>the</strong> innovation is strongly connected to <strong>the</strong> product, <strong>the</strong> patent can be an
effective instrument to protect it. However, it only makes sense to use <strong>the</strong> patent as an instrument for
that purpose if it is also efficient. If <strong>the</strong> costs for <strong>the</strong> registration and <strong>the</strong> enforcement <strong>of</strong> <strong>the</strong> patent are
too high, its protective effect is worthless. Never<strong>the</strong>less, it might still be useful to register <strong>the</strong> patent
because it also serves o<strong>the</strong>r purposes.
For a concise understanding <strong>of</strong> <strong>the</strong> way how companies make use <strong>of</strong> patenting, it is <strong>the</strong>refore necessary
to address <strong>the</strong> different dimensions <strong>of</strong> instrumental action, including <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> instrument,
<strong>the</strong> purpose to which it is used and <strong>the</strong> conditions <strong>of</strong> application that define its efficiency. If this is done,
it becomes possible to review <strong>the</strong> outcome <strong>of</strong> <strong>the</strong> patenting activity with respect to its original intentions
and to draw conclusions about its success.
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3.2 Organizational principles <strong>of</strong> rational action
The framework <strong>of</strong> patent management presented in this paper is based on <strong>the</strong> assumption that <strong>the</strong>
instrumental usage <strong>of</strong> patents is part <strong>of</strong> a rational problem solving process. Fur<strong>the</strong>rmore, we assume
that <strong>the</strong> problem that motivates patenting can generally be described as gaining competitive advantage.
Rational problem solving is a systematic activity that involves several subsequent steps. The general
literature about problem solving describes <strong>the</strong>se steps in different ways (see e.g. Davidson/Sternberg
2003, p 5, or Dörner/Dietrich 1989, pp 67). All approaches, however, refer in some way to (1) <strong>the</strong>
recognition <strong>of</strong> <strong>the</strong> problem, (2) <strong>the</strong> review <strong>of</strong> <strong>the</strong> possible alternatives to act, (3) <strong>the</strong> description <strong>of</strong> <strong>the</strong>
operation to realize <strong>the</strong>m, (4) its execution, and (5) <strong>the</strong> review <strong>of</strong> <strong>the</strong> results. The principles <strong>of</strong> rational
problem solving have also been adopted by management and organization <strong>the</strong>ory. In this context, <strong>the</strong>
basic steps <strong>of</strong> <strong>the</strong> process are usually referred to as (1) forecasting , (2) planning, (3) organizing, (4)
leading, and (5) controlling; ano<strong>the</strong>r popular description <strong>of</strong> <strong>the</strong> steps is given by <strong>the</strong> terms (1) goal, (2)
strategy, (3), tactics, (4) operation, and (5) evaluation (see Fayol 1966, Daft 1983, and Scholl 2001, pp
10, pp 14).
3.3 Organizational principles <strong>of</strong> rational action
Considering competitive advantage as <strong>the</strong> overall goal, <strong>the</strong> protection <strong>of</strong> a product has to be understood
as one strategy to accomplish that. It is tempting to proceed from <strong>the</strong> definition <strong>of</strong> <strong>the</strong> strategy directly to
<strong>the</strong> operation <strong>of</strong> registering a patent. However, <strong>the</strong> tactical move in between must not be forgotten.
Before <strong>the</strong> registration <strong>of</strong> a certain patent can take place, it is first necessary to make a choice about <strong>the</strong>
patent to register as <strong>the</strong> right means to protect <strong>the</strong> product. According to our framework, patent management
<strong>the</strong>refore can be expressed in <strong>the</strong> following way:
Table 1: Patent management as a problem solving process
Topic Application to Patents Operation
1. Goal Competitive Advantage Problem Definition
2. Strategy e.g. Product Protection Possible Alternatives
3. Tactics e.g. Use patent as instrument Operational Description
4. Operation e.g. Patent Registration Execution
5. Evaluation e.g. Assess Pr<strong>of</strong>itability Review
4. A framework <strong>of</strong> patenting behaviour
4.1 Literature references to patenting procedurals
Table 2 gives a short overview <strong>of</strong> some representative literature about patent management. The term
strategy appears in various publications, but it is mostly applied in a ra<strong>the</strong>r colloquial sense to all activities
that involve patents. In order to avoid misunderstandings, we <strong>the</strong>refore use <strong>the</strong> terms procedurals
and intentions instead. A review <strong>of</strong> <strong>the</strong> literature yields <strong>the</strong> following results:
Table 2: References to strategies in literature about patent management
Author Procedural Context
Rahn
(1994)
Ernst
(1995)
Granstrand
Strategic Patent Setting
Combination <strong>of</strong> patents
and standards
Strategy <strong>of</strong> patent nets
(Flooding)
Buy licenses
Licensing and
Cross-Licensing
Patent pool Strategy
Combination <strong>of</strong> Patent and
Trademark
Technological leaders attack competitors by blockade setting, technological
standards are set on <strong>the</strong> market in order to expand <strong>the</strong> own
market share.
Specific, clearly focussed technological applications cover a certain
technological field.
Development <strong>of</strong> <strong>the</strong> needed technology for production is no longer
possible or not intended (ex: electronic and optical industry), but
access to foreign technology is needed.
Revenues through licensing, avoidance <strong>of</strong> lawsuits.
In cases in which products are a trademark at <strong>the</strong> same time, enforce
<strong>the</strong> own trademark and brand reputation
Selective patenting High concentration on specific technological fields and technological
applications (ex: SME mechanical manufacturing with low patenting
Internationally oriented
patenting
„Ad hoc blocking“ and „Inventing
around“
activities)
Patents in various technological fields and technological applications
(ex: mechanical manufacturing)
Protection <strong>of</strong> an innovation in specific applications
Minimize R&D costs
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Author Procedural Context
(1999) Strategic Patent Setting Blockade <strong>of</strong> competitors by bordering a specific field <strong>of</strong> technology
Flooding or Blanketing Systematic built-up <strong>of</strong> patent portfolios
In field <strong>of</strong> new technologies with high uncertainty concerning <strong>the</strong>
future economic development.
Fencing Blockade <strong>of</strong> certain R&D directions for competitors.
Different technological solutions that lead to a similar product/application
are patented.
Surrounding A competitive strategic patent is surrounded by a few smaller, less
important patents that collectively hinder <strong>the</strong> application <strong>of</strong> <strong>the</strong> strategic
patent.
Force <strong>the</strong> competitor to realize access to his/her technology.
Combination Protection and enforcement <strong>of</strong> <strong>the</strong> own competitive position by combining
<strong>the</strong> o<strong>the</strong>r procedurals above.
Shapiro Cross Licenses Each partner still is free to compete both in designing its products
(2001)
without fear <strong>of</strong> infringement and in pricing its products without <strong>the</strong>
burden <strong>of</strong> a per unit royalty due to <strong>the</strong> o<strong>the</strong>r.
Patent Pools and Package Two or more parties control patents necessary to make a given
Licenses
product (ex: manufacturing, aircraft industry)
(Corporative) Standard Standard setting organizations typically require that participants
Setting
agree to license all patents (example: telecommunication).
Cohen et
Patenting Measure R&D performance and review R&D activity
al. (2002)
Setting up one's own patent in opposition to ano<strong>the</strong>r to prevent infringement
accusations
Enhance reputation
Licensing Licensing revenue
Cross licensing Use in negotiations
Discrete and complex
Prevent blocking and copying
products
Enhance reputation
Burr
(2004)
Burr et al.
(2007)
Licensing Entrance to international markets
Generate financial resources
Exploit a given technology
Overcome bottlenecks in production capacities.
Offensive strategies Access to new markets
To hinder and deter competitors systematically
Protection <strong>of</strong> <strong>the</strong> own technological and competitive position
In technological fields that constitute <strong>the</strong> core competence <strong>of</strong> a
company and for which future growth is important
Defensive strategies Avoid claims <strong>of</strong> a third party
Protect <strong>the</strong> own freedom <strong>of</strong> action
Border (new) markets
In technological fields that constitute <strong>the</strong> core competence <strong>of</strong> a
company and for which future growth is important
Patent volume strategy Increase <strong>the</strong> reputation, differentiation from competitors
(<strong>of</strong>fensive or defensive)
Border new markets
Strategic Patent Setting
Protection <strong>of</strong> <strong>the</strong> most important own technologies
(<strong>of</strong>fensive or defensive)
Licensing
(<strong>of</strong>fensive or defensive)
4.2 The strategic perspective on patent management
Generate revenues and consequently financial resources
Promote <strong>the</strong> diffusion <strong>of</strong> <strong>the</strong> concerned technology that consequently
might lead to standard setting
Receive access to technologies <strong>of</strong> <strong>the</strong> licensee
Exploitation <strong>of</strong> unused patents
Avoidance <strong>of</strong> lawsuits
If competitive advantage is <strong>the</strong> ultimate goal <strong>of</strong> all patenting activity, it follows that <strong>the</strong> strategies <strong>of</strong>
patent management address <strong>the</strong> ways how a company establishes and secures its position on <strong>the</strong>
market. The review <strong>of</strong> <strong>the</strong> literature allows <strong>the</strong> distinction <strong>of</strong> four different approaches:
The company claims technical leadership. It uses patenting to control <strong>the</strong> innovative activity on <strong>the</strong>
whole market. The competition is forced to follow <strong>the</strong> direction <strong>of</strong> product development in <strong>the</strong>
company.
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The company finds itself in a position equal or weaker than <strong>the</strong> competition. It uses patenting to
disrupt <strong>the</strong> innovative activity in <strong>the</strong> o<strong>the</strong>r companies. At <strong>the</strong> same time, it secures its own intellectual
property.
The company concentrates on a specific niche <strong>of</strong> <strong>the</strong> market. It avoids direct competition. Instead, it
co-operates with o<strong>the</strong>r companies by developing complementary products and services.
The company focuses on licensing. It <strong>of</strong>fers patents on innovations that play an important role for
research and development in o<strong>the</strong>r companies, ei<strong>the</strong>r by contributing to a new technical solution or
by claiming rights on an innovative characteristic <strong>of</strong> an existing product.
Fur<strong>the</strong>r on, we refer to (1) technical leadership, (2) aggressive competition, (3) claiming niches and (4)
licensing as <strong>the</strong> four strategies <strong>of</strong> patent management.
Internal functions <strong>of</strong> patenting are not considered in this framework. Cohen et al. (2002) and Hall et al.
(2000) show that patents are also used for performance measurement in research and development.
There is no doubt that performance measurement can also contribute to gaining a competitive advantage,
both as a means to organize innovative activities and to encourage <strong>the</strong> employees. However,
patents can only serve as a performance indicator if <strong>the</strong>y have ano<strong>the</strong>r positive effect for <strong>the</strong> company
as a claim <strong>of</strong> possession to <strong>the</strong> outside. In that sense, internal functions <strong>of</strong> patenting should ra<strong>the</strong>r be
considered as reflections on external functions patenting.
4.3 The tactical perspective on patent management
Having clarified <strong>the</strong> strategies <strong>of</strong> patent management, it is now necessary to discuss how <strong>the</strong>y are
pursued from a tactical perspective. As mentioned before, it is necessary to make a distinction between
<strong>the</strong> tactical move itself and its instrumental value. Tactical moves are not necessarily exclusive to one
strategy. Registering a patent for a basic innovation that is fundamental for <strong>the</strong> development <strong>of</strong> <strong>the</strong>
whole industry, for example, is useful for technical leadership and aggressive competition as well as for
licensing. In addition, <strong>the</strong> activity <strong>of</strong> <strong>the</strong> tactical move must not be mixed up with <strong>the</strong> expected effect. An
enhanced reputation or a stronger position in negotiations is clearly an effect, while fencing or surrounding
<strong>the</strong> patents <strong>of</strong> <strong>the</strong> competition by one's own patents describes an activity. The tactical moves
that can be derived from <strong>the</strong> review <strong>of</strong> <strong>the</strong> literature are presented in <strong>the</strong> following table.
Table 3: The tactics <strong>of</strong> problem solving
Activity Effect
1. Offering licensed access to pat- Control <strong>of</strong> technical development, influence on competitive activity,
ented invention
financial revenue, enhanced reputation.
2. Mutual cross licensing <strong>of</strong> patents Involvement in technical progress, mutual dependency, shared
with o<strong>the</strong>rs
costs.
3. Establishing patent pools with Involvement in technical progress, shared costs, better communica-
free access to all contributors
tion with o<strong>the</strong>rs.
4. Standard setting by free access Control <strong>of</strong> technical development, influence on competitive activity,
to patented content
enhanced reputation.
5. "Ad hoc" blockade <strong>of</strong> competition
Specific protection <strong>of</strong> an innovation
for a single product
6. Registering a patent for a basic
innovation
7. Flooding an area <strong>of</strong> technical
development with numerous
patents
8. Registering patents that work as
a fence in certain directions <strong>of</strong>
technical development
9. Surrounding <strong>the</strong> patents <strong>of</strong> <strong>the</strong>
competitors by one's own such
that <strong>the</strong>y cannot be exploited
Exclusion <strong>of</strong> o<strong>the</strong>rs from technical development, reduction <strong>of</strong> competitive
activity, enhanced reputation, increased value <strong>of</strong> <strong>the</strong> com-
pany
Disruption <strong>of</strong> technical development in o<strong>the</strong>r companies, reduction <strong>of</strong>
competitive activity, enhanced reputation, increased value <strong>of</strong> <strong>the</strong>
company
Exclusion <strong>of</strong> o<strong>the</strong>rs from technical development, reduction <strong>of</strong> competitive
activity
Blocking <strong>the</strong> technical development <strong>of</strong> a competitor
10. Hybrid tactical moves and o<strong>the</strong>r
means <strong>of</strong> protection
Combination <strong>of</strong> o<strong>the</strong>r effects
The literature on patent management allows different conclusions about <strong>the</strong> applicability <strong>of</strong> <strong>the</strong> tactical
moves in pursuing a specific strategy. Table 4 compares <strong>the</strong> opinions <strong>of</strong> <strong>the</strong> various authors, as far as it
was possible to extract this from <strong>the</strong>ir arguments.
161

Table 4: Applicability <strong>of</strong> tactical moves
Albrecht Fritzsche and Rebecca Geiger
Tactical Move 1 2 3 4 5 6 7 8 9 10
Technical Leadership z x, z x, y, v x, y x, y
Aggressive Competition x, y, v y y x, y
Claiming Niches v, t x x, z z y v y y
Licensing x, v z z
x – Rahn (1994) y – Granstrand (1999) z – Shapiro (2001) y – Burr et al. (2007) t – Burr (2004)
5. Implications for competitive advantage
5.1 The contextual background <strong>of</strong> patent trade
It is important to understand that <strong>the</strong> awareness <strong>of</strong> <strong>the</strong> different effects that patents can have does not
only enable a systematic approach to patent management; it also has consequences for <strong>the</strong> assessment
<strong>of</strong> <strong>the</strong> patent value. Based on <strong>the</strong> patent strategies <strong>the</strong>y pursue and <strong>the</strong> tactical moves <strong>the</strong>y apply,
companies can express very specific interest in <strong>the</strong> acquisition <strong>of</strong> patents and realise it ei<strong>the</strong>r by internal
research and development, external consulting, purchase <strong>of</strong> licenses or <strong>the</strong> takeover <strong>of</strong> o<strong>the</strong>r companies.
Evans/Wurster (1997) have described <strong>the</strong> emergence <strong>of</strong> such activities as a consequence <strong>of</strong> <strong>the</strong>
transformation <strong>of</strong> business transactions towards an economy <strong>of</strong> information. According to Monk (2009),
this development is still in an early stage that can be compared to <strong>the</strong> situation <strong>of</strong> financial derivates in
<strong>the</strong> early nineteen-eighties. The biggest restraining force <strong>of</strong> <strong>the</strong> development is <strong>the</strong> problem that it is
difficult to say how much a single patent is actually worth. For that reason, intermediaries with high
expertise in legal, economic and technical questions play an important role for patent trade.
The previous reflections in this paper suggest that <strong>the</strong> meaning <strong>of</strong> a patent for competitive advantage
unfolds itself in <strong>the</strong> context <strong>of</strong> patenting strategies and tactics. It is impossible to estimate what a
company would be willing to pay for <strong>the</strong> possession <strong>of</strong> a patent without knowing if <strong>the</strong> company wants to
use it for trading licenses, claming a niche, interfering with <strong>the</strong> competition or protecting its position as
technical leader. In addition, it is necessary to find out how <strong>the</strong> patent contributes to <strong>the</strong> tactical moves
that a company may apply. As we have seen, many <strong>of</strong> <strong>the</strong>se moves involve a number <strong>of</strong> different
patents. The reference to a certain market value only seems to make sense for a patent which is so
fundamental that possessing it means a tactical move that applies to all four strategies.
5.2 Patents and competitive instruments
The value <strong>of</strong> a patent is usually expressed by indicators like <strong>the</strong> number <strong>of</strong> citations, renewals and
claims, <strong>the</strong> number <strong>of</strong> contributors, <strong>the</strong> places where it is registered or <strong>the</strong> route in which it was subsequently
registered in different locations (see e.g. Frietsch et al. 2010). These indicators have proven
to be helpful to estimate <strong>the</strong> innovative power <strong>of</strong> certain companies and regions. The separate assessment
<strong>of</strong> single patents, however, raises questions which can hardly answered by <strong>the</strong>se indicators.
For example, it remains unclear how strong <strong>the</strong> protection is that <strong>the</strong> patent can exert, both in terms <strong>of</strong>
efficiency and effectiveness. There is good reason to assume that <strong>the</strong> situation would become much
easier if <strong>the</strong> evaluation referred to <strong>the</strong> tactical moves <strong>of</strong> patenting instead <strong>of</strong> <strong>the</strong> patents <strong>the</strong>mselves. In
contrast to <strong>the</strong> patents, <strong>the</strong> tactical moves are already expressed in instrumental terms. The effect <strong>the</strong>y
are supposed to have is clearly defined and it is possible to make comparisons between one tactical
move and ano<strong>the</strong>r.
If all this is true, <strong>the</strong> emerging market for patents ra<strong>the</strong>r seems to be a market for protective instruments
that involve patents and that can be applied as tactical moves in pursuing a certain patenting strategy.
For <strong>the</strong> patent intermediaries, it is <strong>the</strong>refore ra<strong>the</strong>r important to select patents carefully according to <strong>the</strong>
strategies <strong>of</strong> <strong>the</strong>ir customers. For tactical moves like fencing and surrounding o<strong>the</strong>r patents, it is also
necessary to create bundles <strong>of</strong> different patents and possibly o<strong>the</strong>r protective measures. These bundles
show that it is less important to clarify a certain technical innovation than it is to clarify what can or
cannot be done with it. In that sense, <strong>the</strong> tactical moves refer back to a more general kind <strong>of</strong> intellectual
capital than what is expressed in <strong>the</strong> description <strong>of</strong> <strong>the</strong> patent. Patenting presents itself as a sophisticated
behaviour. It requires expertise from both R&D and marketing departments.
162

6. Conclusion
Albrecht Fritzsche and Rebecca Geiger
At first sight, it all sounds very easy: Companies apply for patents, trademarks etc. in order to improve
<strong>the</strong>ir position on <strong>the</strong> market. If a company owns a patent on a certain technical innovation, <strong>the</strong> competition
is not allowed to make use <strong>of</strong> it. Without competition, <strong>the</strong> company can assume <strong>the</strong> role <strong>of</strong> a
monopolist who can increase <strong>the</strong> prices for a product. In practice, however, <strong>the</strong> situation has proven to
be much more complicated. Patenting requires specific strategic expertise.
In <strong>the</strong> last two decades, various authors have studied <strong>the</strong> ways how companies apply <strong>the</strong>ir patents. A
qualitative content analysis <strong>of</strong> <strong>the</strong> relevant literature reveals a huge number <strong>of</strong> different procedurals in
patent management. In comparison, <strong>the</strong> description <strong>of</strong> <strong>the</strong>se procedurals is ra<strong>the</strong>r inhomogeneous. For
a systematic approach, we <strong>the</strong>refore suggest a taxonomy which distinguishes strategic and tactical
aspects <strong>of</strong> patent management. The notion <strong>of</strong> strategy refers to <strong>the</strong> intended effects <strong>of</strong> <strong>the</strong> patent
management on <strong>the</strong> position <strong>of</strong> <strong>the</strong> company on <strong>the</strong> market and its relation to <strong>the</strong> competition. In contrast
to that, <strong>the</strong> tactics <strong>of</strong> patent management address <strong>the</strong> specific activities <strong>of</strong> patenting that are applied
to translate <strong>the</strong> strategy into action. The literature review leads to <strong>the</strong> distinction <strong>of</strong> at least four
different strategies and ten different tactics <strong>of</strong> patent management. Every strategy allows different tactical
approaches. Various tactics, on <strong>the</strong> o<strong>the</strong>r hand, can serve different strategic intentions.
Considering <strong>the</strong> manifold <strong>of</strong> strategies and tactics in patent management, it seems inappropriate to
establish a direct relation between patents and <strong>the</strong> position <strong>of</strong> a company on <strong>the</strong> market. The instruments
to establish certain kinds <strong>of</strong> monopolies are not <strong>the</strong> specific rights <strong>of</strong> ownership on a single innovation,
but <strong>the</strong>ir combination in <strong>the</strong> application <strong>of</strong> different tactical moves. In order to understand <strong>the</strong>
dynamics <strong>of</strong> patenting in <strong>the</strong> knowledge society and <strong>the</strong> emerging market for intellectual property in <strong>the</strong>
high tech industry, it is <strong>the</strong>refore important to study both <strong>the</strong> strategies and tactical moves <strong>of</strong> <strong>the</strong>
companies involved as ano<strong>the</strong>r form <strong>of</strong> intellectual capital.
References
Arrow, K (1962): "Economic Welfare and <strong>the</strong> Allocation <strong>of</strong> Resources for Invention" In: Nelson, Richard (ed.): The
Date and Direction <strong>of</strong> Inventive Activity. Princeton University Press, Princeton, pp 609–625.
Arundel, A. (2001) “The relative effectivenes <strong>of</strong> patents and secrecy for appropriation”, Research Policy, Vol. 30,
No. 4, pp 611-624.
Bessen, J. and Meurer, M. J. (2008) “Do Patents Perform Like Property?”, Boston University School <strong>of</strong> Law,
Working Paper Series, Law and Economics Working Paper N° 08-08.
Bottani, A. C. (2010) “Intellectual Property as a Kind <strong>of</strong> Metaproperty”, The Monist, Vol. 93, No. 3, pp 395-413.
Cohen, W. M., Goto, A., Nagata, A., Nelson, R. R. and Walsh, J. P. (2002) „R&D spillovers, patents and <strong>the</strong> incentives
to innovate in Japan and <strong>the</strong> United States“, Research Policy, Vol. 31, pp 1349-1367.
Cohen, W. M., Nelson, R. R. and Walsh, J. R. (2000) Protecting Their Intellectual Assets. Appropriability Conditions
and Why U.S. Manufacturing Firms Patent (or Not) National Bureau <strong>of</strong> Economic Research Working Paper
7552.
Daft, R. L. (1983) Organization <strong>the</strong>ory and design. The West series in management. West Pub. Co., St. Paul.
Davidson, J. E., and Sternberg, R. J. (2003) The psychology <strong>of</strong> problem solving. Cambridge University Press, New
York.
Dörner, D. (1989) Die Logik des Misslingens. Strategisches Denken in komplexen Situationen. Rowohlt, Reinbeck.
Edvinsson, L., Malone, M.S. (1997) Intellectual Capital: Realizing your Company’s True Value by Finding Its
Hidden Roots. Harper Business, New York.
Evans, P.B. and Wurster, T. S. (1997) "Strategy and <strong>the</strong> new economics <strong>of</strong> information", Harward Business Review,
75, pp 58-67.
Falvey, R., Foster, N. and Greenaway, D. (2004): Intellectual Property Rights and Economic Growth. Research
Paper 2004/12. University <strong>of</strong> Nottingham, Nottingham.
Fayol, H. (1966) Administration industrielle et générale - prévoyance organization - commandement, coordination -
contrôle. Dunod, Paris.
Feinberg, R. M. and Rousslang, D. J. (1990) “The Economic Effect <strong>of</strong> Intellectual Property Right Infringements”,
Journal <strong>of</strong> Business, Vol. 63, No. 1, pp 79-90.
Frietsch, R., Schmoch, U., van Looy, B., Walsh, J. P., Devroede, R., Du Plessis, M., Jung, T., Meng, Y., Neuhäusler,
P., Peeters, B., Schubert, T. (2010): The Value and Indicator Function <strong>of</strong> Patents. Studien zum
deutschen Innovationssystem. EFI, Berlin.
Ginarte, J. Carlos and Park, W. G. (1997) “Determinants <strong>of</strong> patent rights. A corss-national study”, Research Policy,
Vol. 26, No. 3, pp 283-301.
Gould, D. M. and Gruben, W. C. (1996) “The role <strong>of</strong> intellectual property rights in economic growth”, Journal <strong>of</strong>
Development Economics, Vol. 48, No. 2, pp 323-350.
Grossman, G and E. Helpman (1991) Innovation and Growth in <strong>the</strong> Global Economy, MIT Press, Cambridge,
Massachusetts.
163

Albrecht Fritzsche and Rebecca Geiger
Hall, B. H. (2007) “Patents and Patent Policy”, OxREP article, Dezember 2007,
http://elsa.berkeley.edu/~bhhall/papers/BHH07_OxREP_patents.pdf
Hall, B. H., Jaffe, A. and Trajtenberg, M. (2000) Market Value and Patent Citation: A First Look. NBER Working
Paper, No. 7741.
Harabi, N. (1995) “Appropriability <strong>of</strong> technical innovation: an empirical analysis”, Research Policy, Vol. 24, pp
981-992.
Harh<strong>of</strong>f, D. (2006) „Patente – Segen oder Fluch für Innovationen?“, zfbf Sonderheft, Vol. 54, pp 86-109.
Henkel, J. (2004) Open-Source-Aktivitäten von Unternehmen – Innovationen in kollektiven Prozessen. Habilitationsschrift
Universität München.
Hipp, C. (2006) “Strategies for <strong>the</strong> management <strong>of</strong> Intellectual Property Rights in Service-Intensive Companies”.
Full paper presented at <strong>the</strong> Annual Academy <strong>of</strong> Management <strong>Conference</strong> 2006, selected for <strong>the</strong> Best Paper
Award <strong>Proceedings</strong> 2006, August 11th-16th, 2006, Atlanta, USA.
Hussinger, K. (2006) “Is Silence Golden? Patents Versus Secrecy at <strong>the</strong> Firm Level”, Economic <strong>of</strong> Innovation and
New Technology, Vol. 15, No. 8, pp 735-752.
Kanwar, S., Evenson, R. (2003) “Does Intellectual Property Protection Spur Technological Change?”, Oxford
Economic Papers, Vol. 55, No. 2, pp 235-264, http://www.econ.yale.edu/growth_pdf/cdp831.pdf
Lerner, J. (1995) “Patenting in <strong>the</strong> Shadow <strong>of</strong> Competitors”, Journal <strong>of</strong> Law and Economics, Vol. 38, No. 2, pp
463-495.
Lerner, J. (2000) 150 Years <strong>of</strong> Patent Protection. National Bureau <strong>of</strong> Economic Research Working Paper No. 7478.
Lerner, J. (2002) “150 Years <strong>of</strong> Patent Protection”, American Economic Review Papers and <strong>Proceedings</strong>, Vol. 92,
No. 2, pp 221-225.
Levin, R. C., Klevorick, A. K., Nelson, R. R. and Winter, S. G. (1987) “Appropriating <strong>the</strong> returns from industrial
research and development”, Brookings Papers on Economic Activity, Vol. 3, pp 783-820.
Maddocks, J., Beaney, M. (2002) “See <strong>the</strong> invisible and intangible”, Knowledge Management, March 2002, pp
16-17.
Mansfield, E., Schwartz, M. and Wagner, S. (1981) “Imitation Costs And Patents: An Empirical Study”, The Economic
Journal, Vol. 91, pp 907-918.
Monk, A. H. B. (2009) "The emerging markets for intellectual property: drivers, restrainers, and implications"
Journal <strong>of</strong> Economic Geography 9, pp 469-491.
Nordhaus, W. (1969): Invention, Growth & Welfare: A <strong>the</strong>oretical treatment on technological change. MIT Press.
Ostergard Jr., R. L. (2000) “The Measurement <strong>of</strong> Intellectual Property Rights Protection”, Journal <strong>of</strong> International
Business Studies, Vol. 31, No. 2, pp 349-360.
Pitkethly, R. (2006) UK Intellectual Property Awareness Survey 2006. UK Intellectual Property Office, The Institute
<strong>of</strong> Intellectual Property, London. http://www.ipo.gov.uk/ipsurvey.pdf.
Qian, Y. (2006) “Do National Patent Laws Stimulate Innovation in a Global Patenting Environment? A
Cross-Country Analysis <strong>of</strong> Pharmaceutical Patent Protection, 1978-2002”. Working Paper, later The Review
<strong>of</strong> Economics and Statistics, Vol. 89, No. 3, pp 436-453.
Rammer, C. (2002) Patente und Marken als Schutzmechanismen für Innovationen. Studien zum deutschen Innovationssystem
Nr. 11-2003. Zentrum für Europäische Wirtschaftsforschung - ZEW, Mannheim.
Romer, P. M. (1990) “Endogenous Growth and Technical Change,” Journal <strong>of</strong> Political Economy, 99, pp 807-827.
Sattler, H. (2003) “Appropriability <strong>of</strong> Product Innovations. An Empirical Analysis for Germany”, International Journal
<strong>of</strong> Technology Management, Vol. 26, pp 502-516.
Scholl, A. (2001) Robuste Planung und Optimierung: Grundlagen – Konzepte und Methoden – Experimentelle
Untersuchungen. Physika, Heidelberg.
Skyrme, D. J. (1998) “Valuing Knowledge: Is it Worth it?” Managing Information, Vol 8, No. 3,
http://www.skyrme.com/pubs/im0398.htm.
Stewart, T. A. (1997) Intellectual Capital - The New Wealth <strong>of</strong> Organizations. Crown Business, New York et al.
Sullivan, P. H. (2000) Value-driven Intellectual Capital. John Wiley & Sons, New York.
Sveiby, K. E. (1997) "The Intangible Asset Monitor", Journal <strong>of</strong> Human Resource Casting and Accounting, Vol. 2,
No. 1.
Thurow, L. C. (1997) “Needed: A new system <strong>of</strong> intellectual property rights”, Harvard Business Review, Vol. 75, pp
95-103.
164

Intangible Assets and Value Creation <strong>of</strong> a Company:
Russian and UK Evidence
Tatiana Garanina and Yana Pavlova
Graduate School <strong>of</strong> Management, Saint-Petersburg State University, Russia
garanina@gsom.pu.ru
pavlova.bm2010@edu.gsom.pu.ru
Abstract: The paper is devoted to <strong>the</strong> question <strong>of</strong> Value-Based Management (VBA) and <strong>the</strong> role <strong>of</strong> Intangible
Assets (IA) in value creation <strong>of</strong> a company. The main research objective is to define <strong>the</strong> impact <strong>of</strong> fundamental
value <strong>of</strong> both tangible and intangible assets <strong>of</strong> a company on market value <strong>of</strong> its assets. As a general approach,
<strong>the</strong> method based on residual operating income (REOI) model as a variant <strong>of</strong> fundamental value <strong>of</strong> equity model
is used herein for IA evaluation. Developed econometric model is tested on <strong>the</strong> data <strong>of</strong> Russian and UK
companies which are listed on Russian Trade System and London Stock Exchange respectively. In <strong>the</strong> focus <strong>of</strong>
<strong>the</strong> research <strong>the</strong>re is both <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> sampled companies as a whole as well as divided into five
aggregated industries: mechanical engineering, extractive industry, power engineering, communication services,
and metallurgy. The main directions for fur<strong>the</strong>r research in this field are outlined.
Keywords: intangible assets, intellectual capital, valuation, residual operating income, fundamental value
1. Introduction
Rapid technological advancement, deregulation and globalization have forced companies to go
through <strong>the</strong> process <strong>of</strong> reinventing. That means that <strong>the</strong>y should develop new advantages while
undermining strategic advantages <strong>of</strong> <strong>the</strong>ir competitors within an increasingly intensive competitive
environment.
Research in <strong>the</strong> field <strong>of</strong> intellectual capital (IC) involves <strong>the</strong> finding for “understanding <strong>the</strong> roots <strong>of</strong> a
company’s value, <strong>the</strong> measurement <strong>of</strong> <strong>the</strong> hidden dynamic factors that underlie <strong>the</strong> visible
company…” [Edvinsson, Malone, 1997, p.11]. In today’s knowledge-based economy, two <strong>of</strong> <strong>the</strong> most
important “hidden dynamic factors” in an organization are knowledge and know how which are
created by and stored in its people (human capital), relations (relationship capital) and organizational
information technology systems and processes (organizational capital). The main findings <strong>of</strong> IC
research suggest that it is <strong>the</strong> leveraging <strong>of</strong> <strong>the</strong>se three components that allow an organization to
create and sustain a competitive advantage [Edvinsson, Malone, 1997; Stewart, 1997; Stam 2010].
The issue <strong>of</strong> IA contribution to increasing a company’s value has been raised by many researchers.
[Edvinsson, Malone, 1997, p. 11] stated that analyzing a company’s intellectual capital helps seeing
<strong>the</strong> “roots <strong>of</strong> company value creation”. [Lev, 2003] continuously stresses that intangible assets are
“major drivers <strong>of</strong> company growth and value in most economy sectors”.
Practical research does prove <strong>the</strong> idea.
As [Kozyrev, Makarov, 2003, p. 59] point out, “…according to Charles Handy, <strong>the</strong> value <strong>of</strong> a
corporation’s intellectual capital is usually three to four times bigger than all its tangible assets. In
1996, L. Edvinsson already considered that data outdated. He estimated that <strong>the</strong> ratio for most
companies at 5:1 up to 16:1. In 1996–2001, <strong>the</strong> importance <strong>of</strong> intellectual capital was still growing. In
o<strong>the</strong>r words, value <strong>of</strong> contemporary companies is mostly defined by <strong>the</strong>ir IC”.
The growing importance <strong>of</strong> IA is well illustrated by Interbrand’s research represented in [Doyle, 2000,
p.298]. The research positively proves that for contemporary companies, a major source <strong>of</strong> prosperity
and most important resource is nei<strong>the</strong>r physical capital nor material assets—it is <strong>the</strong> intellectual
capital.
The increasing gap between market and book value <strong>of</strong> companies spurred reflections on <strong>the</strong>
importance <strong>of</strong> intangible assets and <strong>the</strong> way <strong>the</strong>y are measured.
As Figure 1 shows, <strong>the</strong> value <strong>of</strong> intangible assets is understated while <strong>the</strong> premium market is huge.
165

S&P 500 Market Cap ($ billions)
14,000
12,000
10,000
8,000
6,000
4,000
2,000
-
Tatiana Garanina and Yana Pavlova
Components <strong>of</strong> S&P 500® Market Capitalization
Market Premium
Intangible Book Value
Tangible Book Value
1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005
Figure 1: Market capitalization <strong>of</strong> companies from <strong>the</strong> S&P 500 [source: Ned Davis Research, Inc.]
Planning to achieve a certain goal, management must assess company’s current state, determine <strong>the</strong>
gap between it and <strong>the</strong> desired future state, and finally form a sequence <strong>of</strong> actions needed to address
this gap what again proves <strong>the</strong> actuality <strong>of</strong> this paper. A company can develop not only investment
strategies, but strategies <strong>of</strong> increasing production, strategic M&A with <strong>the</strong> knowledge about intangible
assets.
In this article <strong>the</strong> main aim <strong>of</strong> <strong>the</strong> research is to define <strong>the</strong> impact <strong>of</strong> fundamental value <strong>of</strong> both
tangible and intangible assets on <strong>the</strong> market value <strong>of</strong> assets on two markets – developed (case <strong>of</strong>
companies from <strong>the</strong> UK market) and emerging (case <strong>of</strong> companies from <strong>the</strong> Russian market).The
conclusions will be made both on <strong>the</strong> whole sample <strong>of</strong> <strong>the</strong> companies under consideration, as well as
from <strong>the</strong> point <strong>of</strong> <strong>the</strong>ir belonging to a certain field. But before presenting <strong>the</strong> results <strong>of</strong> <strong>the</strong> research
carried out by <strong>the</strong> authors, <strong>the</strong> following questions will be raised and discussed: 1)<strong>the</strong> problem <strong>of</strong>
defining Intangible Assets and connection <strong>of</strong> this concept with such categories as “Intellectual capital”,
“Intangibles”, “Knowledge assets”, etc, 2) <strong>the</strong> question <strong>of</strong> Intangible assets evaluation models. Upon
consideration <strong>of</strong> <strong>the</strong> above mentioned problems, <strong>the</strong> authors formulate <strong>the</strong>ir personal position.
The structure <strong>of</strong> <strong>the</strong> paper is <strong>the</strong> following. First <strong>the</strong> main approached to definition <strong>of</strong> <strong>the</strong> main
concepts are introduced, <strong>the</strong>n <strong>the</strong> method which is chosen for evaluation Intangible Assets in <strong>the</strong>
paper is represented (method <strong>of</strong> Calculated Intangible Value), <strong>the</strong> research model <strong>the</strong> main
hypo<strong>the</strong>sis are formulated with providing statistical information about <strong>the</strong> sample. At <strong>the</strong> end <strong>of</strong> <strong>the</strong>
paper <strong>the</strong> main results and directions for fur<strong>the</strong>r research are highlighted.
2. The approaches to intangible assets and intellectual capital definition
There exist various approaches to defining <strong>the</strong> Intangibles, Intangible Assets and Intellectual Capital.
Some authors consider <strong>the</strong>se terms to be synonyms, while <strong>the</strong> o<strong>the</strong>rs still separate <strong>the</strong>m from each
o<strong>the</strong>r. Apart from that, a number <strong>of</strong> authors do not <strong>of</strong>fer any definition, but only separate <strong>the</strong> basic
components, being a part <strong>of</strong> <strong>the</strong> concepts referred above. Without claiming <strong>the</strong> completeness, lets us
examine <strong>the</strong> basic approaches to defining Intangible Assets and Intellectual Capital. At that, we shall
firstly give <strong>the</strong> approaches to <strong>the</strong> definitions <strong>of</strong> <strong>the</strong> concepts, and afterwards consider <strong>the</strong> composition
and structure <strong>of</strong> Intangible Assets (Intellectual Capital).
According to <strong>the</strong> opinion <strong>of</strong> B. Lev, to which <strong>the</strong> authors <strong>of</strong> this paper subscribe, <strong>the</strong> terms Intangible
Assets, Knowledge Assets and Intellectual Capital are interchangeable owing to <strong>the</strong> fact that all three
terms are “widely used: Intangible Assets in accounting literature, Knowledge Assets – by
economists, Intellectual Capital – in management and law literature; and on <strong>the</strong> whole <strong>the</strong>y come to
<strong>the</strong> same: to <strong>the</strong> future benefits that are not embodied materially” [Lev, 2003].
166

Tatiana Garanina and Yana Pavlova
Hence, Intangible Assets, or Intellectual Capital, are defined by B.Lev as “non-physical sources <strong>of</strong>
value (claims to future benefits) generated by innovation (discovery), unique organizational designs,
or human resource practices”. Intangible Assets, as defined in [Lönnqvist, Mettänen, 2002], are nonmaterial
sources <strong>of</strong> creating a company’s value, based on <strong>the</strong> employees capabilities, organizations’
resources, <strong>the</strong> way <strong>of</strong> operating and relations with <strong>the</strong> shareholders. In [Lönnqvist, Mettänen, 2002],
as in [Lev, 2003], <strong>the</strong> terms Intellectual Capital and Intangible Assets are suggested for
interchangeable usage.
In [Starovic, Marr, 2003], a widespread approach is described, under which Intellectual Capital (or
Intangibles) is a broader concept than Intangible Assets. In this sense, Intangible Assets are only a
part <strong>of</strong> Intellectual Capital acknowledged as <strong>the</strong> assets in a company’s bookkeeping and accounting
records.
The authors assume that narrowing <strong>of</strong> <strong>the</strong> Intangible Assets concept only to <strong>the</strong> assets acknowledged
in accounting is unjustified. Such opinion is a result <strong>of</strong> confusing two different problems. Firstly, what
an asset is in general, and secondly, which assets can be acknowledged in accounting and which can
not. In view <strong>of</strong> <strong>the</strong> fact that under <strong>the</strong> asset is basically understood any possible future economic
benefit, obtained and controlled by a company, as a result <strong>of</strong> past transactions and events, <strong>the</strong>n all
<strong>the</strong> elements (tangible or intangible) coming within <strong>the</strong> above definition appear to be a company’s
assets.
It is quite ano<strong>the</strong>r matter, if <strong>the</strong>se elements match <strong>the</strong> criteria <strong>of</strong> recognition in bookkeeping and
accounting or not. Thus, according to [IFAC 38], “intangible asset is an identifiable non-financial
asset, having no physical form and serving for production usage or for providing <strong>the</strong> goods or
services, for leasing to o<strong>the</strong>rs or for administrative purposes.” The Russian accounting standards
[PBU 14/2000] supplement <strong>the</strong> enumerated criteria with a range <strong>of</strong> conditions for “recognition assets
by accounting and bookkeeping as intangible”.
Thus, <strong>the</strong> authors’ position may be summarized as follows. Any asset, belonging to a company or
controlled by it, having no physical or financial (in case <strong>of</strong> financial investment) form, but capable <strong>of</strong>
producing future economic benefits is an Intangible Asset. The aggregate <strong>of</strong> Intangible Assets <strong>of</strong> a
company may also be named Intellectual Capital, or Intangibles. At <strong>the</strong> same time, two subgroups
should be distinguished within Intangible Assets: recognized Intangible Assets and non-recognized
Intangible Assets in bookkeeping and accounting
3. Evaluation <strong>of</strong> intangible assets: The method <strong>of</strong> calculated intangible value
The Intangible Assets evaluation problem is immensely complicated and disputable. Apart from <strong>the</strong>
specific character <strong>of</strong> <strong>the</strong> evaluated subject (its intangibility), <strong>the</strong> difficulty <strong>of</strong> <strong>the</strong> problem is connected
with <strong>the</strong> fact that in this case <strong>the</strong> evaluation models do not only give <strong>the</strong> numerical evaluation, but also
in a certain way determine <strong>the</strong> essence <strong>of</strong> <strong>the</strong> evaluated subject. But it is clear that <strong>the</strong> problem is
really important in <strong>the</strong> century <strong>of</strong> knowledge-based economy when IA have become <strong>the</strong> most
important resources for a company and when <strong>the</strong>y need to be managed in <strong>the</strong> best way.
A great number <strong>of</strong> papers are devoted to <strong>the</strong> problem <strong>of</strong> Intangible Assets evaluation. The reviews <strong>of</strong>
various approaches to this kind <strong>of</strong> assets evaluation are presented in <strong>the</strong> works <strong>of</strong> [Andriessen,
Tiessen, 2000; Bontis, 2001; Luthy, 1998; Petty, Guthrie, 2000; Sveiby, 2002; Hang, Chang, 2008].
Besides, some Russian researchers also develop <strong>the</strong> above problem in <strong>the</strong>ir works [Kozyrev,
Makarov, 2003; Bukhvalov 2004а; 2004b]. The task <strong>of</strong> this paper does not include <strong>the</strong> detailed
analysis <strong>of</strong> all existing approaches; <strong>the</strong>refore we have chosen only one approach for this purpose.
As a general approach used herein for IA evaluation, we have chosen <strong>the</strong> method <strong>of</strong> Calculated
Intangible Value (CIV) <strong>of</strong>fered by T. Stewart [Stewart, 1995]. According to CIV, intangible value <strong>of</strong> a
company is determined as a difference between <strong>the</strong> company’s value (which, in its turn, is determined
by <strong>the</strong> book value <strong>of</strong> <strong>the</strong> company’s assets and discounted flow <strong>of</strong> residual operating income) and <strong>the</strong>
possessed value <strong>of</strong> its tangible assets (determined by <strong>the</strong> book value <strong>of</strong> <strong>the</strong>se assets and discounted
flow <strong>of</strong> residual earnings using <strong>the</strong> average industrial rate <strong>of</strong> return). This difference characterizes <strong>the</strong>
company’s capability to use <strong>the</strong> Intangible Assets in order to “outrun” <strong>the</strong> competitors in <strong>the</strong> industry
[Tan et al., 2007].
167

Tatiana Garanina and Yana Pavlova
This method was chosen due to several reasons. First <strong>of</strong> all, <strong>the</strong> method <strong>of</strong>fers $-valuations, what is
very useful when <strong>the</strong> main objective <strong>of</strong> <strong>the</strong> paper is to calculate <strong>the</strong> influence <strong>of</strong> IA on stock market
valuations. This method can also be used for comparisons between companies within <strong>the</strong> same
industry and it is good for illustrating <strong>the</strong> financial value <strong>of</strong> Intangible assets, a feature, which tends to
get <strong>the</strong> attention <strong>of</strong> <strong>the</strong> CEOs. Finally, because this method is build on long established accounting
rules it is easily communicated in <strong>the</strong> accounting pr<strong>of</strong>ession.
The calculation <strong>of</strong> Intangible Assets value in accordance with <strong>the</strong> chosen valuation method (CIV) is
based on <strong>the</strong> residual operating income (REOI) model as a variant <strong>of</strong> fundamental value <strong>of</strong> equity
model. Residual operating income is a net operating income <strong>of</strong> a company after cost deduction on all
company’s capital. In this case investments mean book value <strong>of</strong> net assets (NA) <strong>of</strong> a company.
Consequently, we take here <strong>the</strong> value <strong>of</strong> net operating income for <strong>the</strong> income, i.e. <strong>the</strong> value <strong>of</strong> income
before interest but after taxes (or earnings before interest – EBI) and we take <strong>the</strong> rate <strong>of</strong> weighed
average cost <strong>of</strong> all capital (WАСС) — kw for <strong>the</strong> required return.
As mentioned above, <strong>the</strong> basis for valuation in this paper is <strong>the</strong> REOI model:
V
REOI
E
j
REOI
∞
∞
BV
j
BV
= E0
+ ∑ = ⎢NA
+ ∑
j=
1 W ⎢
⎡
REOI
j
j
W
j
0
( 1+
k ) j=
1 ( 1+
k )
⎣
⎤
⎥ − D
⎥⎦
0
, (1)
where REOI
V E
— <strong>the</strong> fundamental value <strong>of</strong> equity according to <strong>the</strong> REOI model;
BV BV
E0
, NA0
, D0
— book value <strong>of</strong> equity, net assets and debt at <strong>the</strong> moment (respectively);
REOIj — residual operating income in year j. REOI variant is EVA (economic
added value);
kW — weighted average cost <strong>of</strong> capital (WACC)
The value in square brackets in <strong>the</strong> formula (1) is a fundamental value <strong>of</strong> assets according to <strong>the</strong>
REOI model (VA):
V
REOI
A
j
= NA
BV
0
+
∑ ∞
j=
1
REOI
j
j
W
( 1+
k )
. (2)
In technical annex at <strong>the</strong> end <strong>of</strong> <strong>the</strong> paper all assumptions and formula transformations are
represented in order to obtain fundamental values <strong>of</strong> all assets in general and tangible and intangible
assets in particula.
The fundamental value <strong>of</strong> assets formula may be presented as:
REOI ⎡ REOI ⎤ ⎡ REOI ⎤
= + = + +
VI
, (14)
⎣
⎦ ⎣ ⎦
REOI BV
BV
T
I
V A NAT
⎢NAT
⎥ ⎢ ⎥ = VT
+
kW
kW
kW
where fundamental value <strong>of</strong> a company’s assets can be divided into <strong>the</strong> fundamental value <strong>of</strong> tangible
assets (VT) and intangible assets (VI) as follows:
V
REOI
T
= NA
V
= NA
BV
T
BV
T
NA
+
BV
T
×
⎛ RONAIAVG
− k
×
⎜
⎜1+
⎝ kW
REOI
NA
( RONA − k )
k
W
W
IAVG
⎞
⎟ = NA
⎠
BV
T
W
RONA − RONA
=
RONA
×
k
W
REOI
I BV
IAVG
I = = T ×
. (4)
kW
kW
168
IAVG
,
(3)

3.1 The research model
Tatiana Garanina and Yana Pavlova
The model <strong>of</strong> <strong>the</strong> regression analysis which characterizes <strong>the</strong> relationship between <strong>the</strong> market-value
<strong>of</strong> assets and <strong>the</strong> fundamental value <strong>of</strong> tangible and intangible assets is analyzed in this research.
The market-value <strong>of</strong> a company’s assets can be characterized by such subordination:
P = P + P , (5)
M
A
M
E
M
D
where M M M
P , P , P – <strong>the</strong> market-value <strong>of</strong> assets, equity and debt <strong>the</strong>reafter.
A
E
D
Considering that <strong>the</strong> market-value <strong>of</strong> equity is market capitalization (Cap), and <strong>the</strong> market-value <strong>of</strong>
dept (D) is usually assumed as its book value, equation (5) can be rewritten as:
M
PA P
= Cap + D . (6)
The market-value <strong>of</strong> assets for <strong>the</strong> model calculation appointed as average weighted market
capitalization to <strong>the</strong> content <strong>of</strong> bids over a period <strong>of</strong> 2 nd quarter, which follows after <strong>the</strong> accounting
year, plus book value <strong>of</strong> debt to <strong>the</strong> end <strong>of</strong> <strong>the</strong> accounting period.
The tested model is a two-factor one which includes <strong>the</strong> influence <strong>of</strong> fundamental value <strong>of</strong> both
tangible and intangible assets upon <strong>the</strong> market-value <strong>of</strong> assets <strong>of</strong> a company:
M
A = 0 + μ1
× VT
+ μ2
× VI
μ + ε
where μ , μ 1 , μ 2
ε
1
0
1
, (M1)
- coefficients <strong>of</strong> <strong>the</strong> regression equation;
- random error.
The tested hypo<strong>the</strong>sis can be formulated as follows: <strong>the</strong> market value <strong>of</strong> assets <strong>of</strong> a company
depends on fundamental value <strong>of</strong> its tangible and intangible assets.
3.2 Statistical information
We have tested our hypo<strong>the</strong>sis for two samples <strong>of</strong> companies: Russian and UK. This helped us to
compare <strong>the</strong> results <strong>of</strong> evaluation for <strong>the</strong> emerging Russian market and <strong>the</strong> well developed UK
market.
The Russian sample includes companies that trade <strong>the</strong>ir shares within <strong>the</strong> Russian Trading System
(RTS). The final sample we have used includes 43 Russian companies. The companies have been
divided into five aggregated industries: mechanical engineering (incl. aircraft and automotive),
extractive industry (incl. oil holdings and oil-and-gas companies), power engineering,
telecommunications and metallurgy (ferrous and non-ferrous). For <strong>the</strong> research we used nonconsolidated
financial data <strong>of</strong> <strong>the</strong> sampled companies for 2001–2006.
One <strong>of</strong> <strong>the</strong> main problems <strong>of</strong> making this kind <strong>of</strong> research on <strong>the</strong> Russian market is <strong>the</strong> lack <strong>of</strong>
information. That is why only <strong>the</strong> mentioned five industries were chosen in order make <strong>the</strong> samples
comparable. For companies from o<strong>the</strong>r industries in Russia it is not possible to obtain financial
statements for <strong>the</strong> researched period as <strong>the</strong>y are not provided by companies. For both samples, first,
<strong>the</strong> model described above has been tested on <strong>the</strong> whole sample, <strong>the</strong>n separately on each industry.
For <strong>the</strong> second sample, companies which are operating in <strong>the</strong> UK and listed on <strong>the</strong> London Stock
Exchange were chosen to test <strong>the</strong> hypo<strong>the</strong>sis. The same five industries as for <strong>the</strong> Russian sample
were included in <strong>the</strong> sample: mechanical engineering, extractive industry, power engineering,
telecommunications and metallurgy. The sample size is 50 companies for <strong>the</strong> period from 2003 to
2007.
Data was obtained from <strong>the</strong> analytical reports submitted to <strong>the</strong> Lexis Nexis database.
169

Tatiana Garanina and Yana Pavlova
To keep <strong>the</strong> data homogeneous, <strong>the</strong> sample does not include financial intermediaries (banks and
financial institutions).
Primary data <strong>of</strong> <strong>the</strong> companies’ market capitalization has been found on London Stock Exchange
(www.londonstockexchange.com) and Russian Trade System Website (www.rts.ru). Our analysis has
used weighted averages for <strong>the</strong> second quarter.
A major problem is to define <strong>the</strong> weighted-average costs <strong>of</strong> capital (kW). Our research has taken
average RONA value for each industry as kW. This is also one <strong>of</strong> <strong>the</strong> assumptions and one <strong>of</strong> <strong>the</strong>
limitations <strong>of</strong> <strong>the</strong> study.
General statistical characteristics <strong>of</strong> <strong>the</strong> Russian sample are represented in Table 1.
Table 1: General statistical characteristics <strong>of</strong> <strong>the</strong> Russian sample
№ Name <strong>of</strong> <strong>the</strong> variables/characteristic Mean Mediana Standard deviation
1 Market-value <strong>of</strong> <strong>the</strong> assets
(mln.rub)
103 244 24 864 16 130
2 Fundamental value <strong>of</strong> tangible
assets (mln.rub.)
77 193 22 792 11 753
3 Fundamental value <strong>of</strong> intangible
assets (mln. rub.)
2 374 - 925 7 044
General statistical characteristics <strong>of</strong> <strong>the</strong> UK sample are represented in Table 2.
Table 2: General statistical characteristics <strong>of</strong> <strong>the</strong> UK sample
№ Name <strong>of</strong> <strong>the</strong> variables/characteristic Mean Mediana Standard deviation
1 Market-value <strong>of</strong> <strong>the</strong> assets (mln.
GBP)
10 696
452
29 140
2 Fundamental value <strong>of</strong> tangible
assets (mln. GBP)
4 089
14
66 825
3 Fundamental value <strong>of</strong> intangible
assets (mln. GBP)
1 556 5
89 033
The authors suppose that <strong>the</strong> market value <strong>of</strong> assets in <strong>the</strong> analyzed year is influenced by
fundamental values and respectively RONA <strong>of</strong> <strong>the</strong> previous year. By this fact <strong>the</strong> dependence
between market value <strong>of</strong> assets <strong>of</strong> <strong>the</strong> current year and fundamental values <strong>of</strong> tangible and intangible
assets, based on <strong>the</strong> parameters <strong>of</strong> <strong>the</strong> previous year was analyzed in <strong>the</strong> introduced model.
3.3 The main results <strong>of</strong> <strong>the</strong> research
First <strong>the</strong> results concerning <strong>the</strong> Russian sample are presented.
The 1 st stage <strong>of</strong> <strong>the</strong> research is an estimation <strong>of</strong> <strong>the</strong> regression equation for <strong>the</strong> whole sample <strong>of</strong> <strong>the</strong>
analyzed companies-emitters.
T-test is used for <strong>the</strong> analysis <strong>of</strong> significance <strong>of</strong> explanatory variables (Student criterion), and F-test
(Fisher criterion) is used for testing <strong>the</strong> models for adequacy.
The analysis <strong>of</strong> <strong>the</strong> two-factor model allows drawing <strong>the</strong> conclusion, in what degree each <strong>of</strong> <strong>the</strong>
independent parameters influence <strong>the</strong> dependent one. As <strong>the</strong> result <strong>of</strong> <strong>the</strong> test <strong>the</strong> following
regression equation is obtained for <strong>the</strong> period 2001 – 2006:
ˆ M
P = 3971,
695 + 1,0677×
V + 0,
1610×
V .
(7)
A
T
I
In this case <strong>the</strong> value <strong>of</strong> <strong>the</strong> coefficient <strong>of</strong> determination and adjusted coefficient <strong>of</strong> determination have
high values (0,7504 and 0,7369 respectively), what says about <strong>the</strong> tight relationship between <strong>the</strong>
analyzed variables. That means that in Russian conditions <strong>the</strong> market value <strong>of</strong> assets <strong>of</strong> companies
for 75,04% depends on <strong>the</strong> fundamental value <strong>of</strong> its tangible and intangible assets.
The following hypo<strong>the</strong>ses are formulated in order to test <strong>the</strong> significance <strong>of</strong> <strong>the</strong> explanatory variables,
which <strong>the</strong> model contains:
170

H
H
0
0
: μ =
1
: μ =
2
0,
0,
H
H
1
1
: μ ≠ 0
1
: μ ≠ 0
2
Tatiana Garanina and Yana Pavlova
As <strong>the</strong> test shows, null hypo<strong>the</strong>ses can be rejected on both explanatory variables and that means that
<strong>the</strong> market value <strong>of</strong> assets <strong>of</strong> Russian companies depends on fundamental value <strong>of</strong> both tangible and
intangible assets. The results <strong>of</strong> <strong>the</strong> analysis concerning <strong>the</strong> model are represented in Table 3.
Table 3: The results <strong>of</strong> testing <strong>the</strong> model (M1) for <strong>the</strong> Russian sample
№ Characteristic
The sample as
a whole
Mechanical
engineering
1 2 3 4
Model (М1)/VT; VI
5 6 7 8
*
1 Intercept
3 971,7
27
266,31
38
393,15
22
567,04
649,8642
12
388,19
2 Coefficient before <strong>the</strong> first
independent variable **
1,0677
(18,80)
0,7662
(2,98)
0,9756
(7,53)
1,8104
(16,61)
1,0654
(8,35)
1,2531
(8,35)
3 Coefficient before <strong>the</strong> second
independent variable **
0,1610
(20,02)
0,6469
(0,57)
0,0150
(2,07)
0,0675
(2,09)
0,3142
(4,64)
0,1855
(2,96)
4 t-critical 1,971 2,8073 2,0167 2,0017 2,0167 2,8073
5 F-statistics 55,49 1,44 13,15 76,27 26,48 16,57
6 Coefficients <strong>of</strong> determination
R 2
–R 2 0,850 0,327 0,675 0,950 0,828 0,847
–R 2 adj 0,837 0,310 0,634 0,945 0,801 0,816
After testing <strong>the</strong> two-factor model (M1) for <strong>the</strong> researched period in all <strong>the</strong> industries, except
mechanical engineering, a very close relationship between <strong>the</strong> analyzed variables was found.
Coefficient <strong>of</strong> determination in all <strong>the</strong> cases is more than 0,675. Null hypo<strong>the</strong>sis is rejected in all <strong>the</strong>
industries, again except mechanical engineering, that means that <strong>the</strong> market value <strong>of</strong> assets depends
on <strong>the</strong> fundamental value <strong>of</strong> tangible and intangible assets in all <strong>the</strong> researched branches.
We can make a conclusion that on <strong>the</strong> Russian market <strong>the</strong> influence <strong>of</strong> fundamental value <strong>of</strong> tangible
assets on <strong>the</strong> market value <strong>of</strong> assets <strong>of</strong> a company surpasses <strong>the</strong> influence <strong>of</strong> fundamental value <strong>of</strong>
intangible assets upon <strong>the</strong> same parameter.
Now <strong>the</strong> results concerning <strong>the</strong> UK sample will be presented.
The analysis <strong>of</strong> <strong>the</strong> two-factor model allows making <strong>the</strong> conclusion, in what degree each <strong>of</strong> <strong>the</strong>
independent parameters influence <strong>the</strong> dependent one. As <strong>the</strong> result <strong>of</strong> <strong>the</strong> test <strong>the</strong> following
regression equation is obtained:
ˆ M
P = 9815 + 0 ,20763×
V + 0,
02024×
V .
(8)
A
T
I
The coefficient <strong>of</strong> determination equals 0,197. It is small enough, that is primarily due to <strong>the</strong> fact that
this indicator is <strong>the</strong> average one for <strong>the</strong> industry. It means that for UK companies fundamental value
<strong>of</strong> tangible and intangible assets explains <strong>the</strong> market value for 20% (to compare with <strong>the</strong> Russian
market where this figure is nearly 75,04%). Fur<strong>the</strong>r regression analysis for each industry displays
more detailed information.
* Tested at 5% significance level
** t-statistics is shown in paren<strong>the</strong>ses
** t-statistics is shown in paren<strong>the</strong>ses
171
Extractive industry
Power engineering
Telecommunications
Metallurgy

Tatiana Garanina and Yana Pavlova
The results <strong>of</strong> <strong>the</strong> analysis concerning <strong>the</strong> UK market are represented in Table 4.
Table 4: The results <strong>of</strong> testing <strong>the</strong> model (M1) for <strong>the</strong> UK sample
№ Characteristic
The sample as
a whole
1 2 3 4 5 6 7 8
Model (М1)/VT; VI *
1 Intercept
9 815
Mechanical engineering
137,79
Extractive industry
818,06
Power engineering
10 789
Telecommunications
324
Metallurgy
154,8
2 Coefficient before <strong>the</strong> first
independent variable **
0,44
(5,25)
1,49
(7,20)
0,56
(21,87)
0,14
(1,52)
5,53
(15,84)
0,85
(55,03)
3 Coefficient before <strong>the</strong> second
independent variable **
0,21
(4,68)
1,38
(5,6)
0,43
(6,68)
0,03
(0,88)
0,3
(9,7)
0,83
(62,3)
4 t-critical 3,9 1,86 1,86 1,86 1,86 1,86
5 F-statistics 17,98 31,63 287 2,46 181,14 626
6 Coefficients <strong>of</strong> determination
R 2
–R 2
–R 2 adj
0,23
0,19
0,74
0,67
The results <strong>of</strong> <strong>the</strong> test show that <strong>the</strong> model is significant, as both <strong>of</strong> its factors are. Null hypo<strong>the</strong>sis is
rejected in all <strong>the</strong> industries. That means that <strong>the</strong> market value <strong>of</strong> assets depends on <strong>the</strong> fundamental
value <strong>of</strong> tangible and intangible assets in all <strong>the</strong> researched branches. In <strong>the</strong> metallurgy industry
market value <strong>of</strong> assets is explained by fundamental values <strong>of</strong> both types <strong>of</strong> assets by almost 100%.
Extractive industry and telecommunications are characterized by a high influence <strong>of</strong> fundamental
value <strong>of</strong> tangible and intangible assets on companies’ value. The model, which was tested for power
engineering proved to be insignificant in <strong>the</strong> UK market. In this case we can not make any
conclusions. Probably, all <strong>the</strong> results could be better for explanation if <strong>the</strong> sample were bigger.
All in all, based on <strong>the</strong> data obtained, changes in market value <strong>of</strong> assets <strong>of</strong> companies are explained
in <strong>the</strong> Russian market by 75%, while <strong>the</strong> UK market only by 20% by <strong>the</strong> fundamental value <strong>of</strong> tangible
and intangible assets. But it should be mentioned that <strong>the</strong>se figures are based on a sample <strong>of</strong> 5
branches. The main problem in realization <strong>of</strong> this kind <strong>of</strong> research on <strong>the</strong> Russian market is <strong>the</strong>
shortage <strong>of</strong> statistical information. A bigger number <strong>of</strong> companies-emitters match <strong>the</strong> necessary
parameters <strong>of</strong> sample in o<strong>the</strong>r industries, but <strong>the</strong>ir reporting is not publicly available.
If to speak about <strong>the</strong> results obtained in different industries in general, <strong>the</strong> UK market has appeared to
be less predictable than <strong>the</strong> Russian one. We should not forget about some limitations <strong>of</strong> <strong>the</strong> study.
We have a bit different samples – different amount <strong>of</strong> companies and also <strong>the</strong>re are differences in <strong>the</strong>
periods <strong>of</strong> research, but according to <strong>the</strong> results obtained all <strong>the</strong> models and variables are valuable
what allows us to make <strong>the</strong> following conclusions.
The implicit connection was observed in <strong>the</strong> mechanical engineering industry in <strong>the</strong> Russian market
between <strong>the</strong> explained and explanatory variables, while in <strong>the</strong> UK it was power engineering. A very
obvious correlation between market value <strong>of</strong> assets and fundamental value <strong>of</strong> tangible and intangible
* Tested at 5% significance level
** t-statistics is shown in paren<strong>the</strong>ses
** t-statistics is shown in paren<strong>the</strong>ses
172
0,95
0,95
0,15
0,09
0,93
0,92
0,98
0,97

Tatiana Garanina and Yana Pavlova
assets was identified in <strong>the</strong> metallurgy industry on <strong>the</strong> data <strong>of</strong> <strong>the</strong> Russian market, which was also
confirmed by <strong>the</strong> data <strong>of</strong> <strong>the</strong> UK market.
4. Conclusion
Intangible Assets are a company’s “weightless wealth” that helps it to obtain real pr<strong>of</strong>it. Every
company should understand that nowadays paying much attention to Value-based Management in
general and to Intangible Assets especially (as <strong>the</strong>y are <strong>the</strong> key drivers <strong>of</strong> value creation in <strong>the</strong>
economy <strong>of</strong> <strong>the</strong> XXI century) may help to create and develop its core competences and thus yield
competitive advantage on <strong>the</strong> market.
This question is discussed in different publications, where it is said about <strong>the</strong> problem that <strong>the</strong> most
important resources <strong>of</strong> a company, which are Intangible Assets, are <strong>of</strong>ten not reflected in companies’
balance-sheets [Edvinsson, Mallone, 1997; Sveiby, 1997]. That is why a new approach for obtaining a
fundamental value <strong>of</strong> intangible assets on <strong>the</strong> base <strong>of</strong> residual operating income is developed in <strong>the</strong>
paper. It helps to get <strong>the</strong> value <strong>of</strong> those intangibles which are not shown on <strong>the</strong> balance sheets <strong>of</strong>
companies. It was decided to test a hypo<strong>the</strong>sis and to compare results <strong>of</strong> influence <strong>of</strong> fundamental
value <strong>of</strong> tangible and intangible assets on market value <strong>of</strong> assets on two markets: <strong>the</strong> emerging
Russian market and <strong>the</strong> well-developed UK market.
For <strong>the</strong> research a two-factor model has been developed. The research helped to find out that,
indeed, <strong>the</strong>re is a connection between <strong>the</strong> selected indicators, but if to look at all <strong>the</strong> industries, <strong>the</strong>
connection is not strong enough. The strongest relationship was observed in <strong>the</strong> metallurgy and it was
very poor in <strong>the</strong> mechanical engineering for both markets.
The tested econometric model shows that on both markets (<strong>the</strong> UK, and <strong>the</strong> Russian one) tangible
assets still play a more important role in value creation <strong>of</strong> companies if to use <strong>the</strong> chosen method <strong>of</strong>
evaluation. Of course <strong>the</strong> method has some limitations due to <strong>the</strong> assumptions represented in <strong>the</strong>
Technical annex, but <strong>the</strong> method is very useful for obtaining $-valuation <strong>of</strong> Intangible assets for
comparing different companies and industries between each o<strong>the</strong>r. The approach highlighted in <strong>the</strong>
paper may be used by managers in order to understand what role Intangible Assets play in
company’s value creation and also to understand whe<strong>the</strong>r <strong>the</strong>ir company overplays rivals or not.
The method can also be used for external investors who may compare companies <strong>the</strong>y want to invest
in from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> Intangible assets. In this case investors need only external financial
reports what makes this approach very easy to use.
The fur<strong>the</strong>r research in this field will develop not only in <strong>the</strong> direction <strong>of</strong> testing <strong>the</strong> researched models
for sustainability as statistical information accumulated, but also in <strong>the</strong> direction <strong>of</strong> developing and
testing o<strong>the</strong>r models <strong>of</strong> Intangible Assets valuation. Moreover, <strong>the</strong> question <strong>of</strong> Intangible Assets
structure demands <strong>the</strong> fur<strong>the</strong>r specification, and also <strong>the</strong> problem <strong>of</strong> extracting separate elements <strong>of</strong>
Intangible Assets from <strong>the</strong>ir aggregate value needs to be solved.
5. Technical annex
In this annex all <strong>the</strong> assumptions and formulas transformation are presented for obtaining
fundamental values <strong>of</strong> tangible and intangible assets.
Here, <strong>the</strong> residual operating income equals <strong>the</strong> residual earnings after deducting <strong>the</strong> cost <strong>of</strong> invested
capital:
BV
REOI j = NOPAT j − kW
× NA j−1
( t)
, (1a)
where NOPAT — net operating pr<strong>of</strong>it after taxes (also EBI – earnings before interest),
calculated according to <strong>the</strong> formula:
NOPAT = NI + i × 1−
, (2a)
where NI — net income
i
t
— interest
— income tax rate according to <strong>the</strong> income statement
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Tatiana Garanina and Yana Pavlova
If in expression formula (2) we presume that REOI value is constant within infinite research period,
(REOI = const), <strong>the</strong>n model (2) may be presented as:
REOI
= 0 . (3a)
k
REOI BV
V A NA +
W
The made assumption complies with <strong>the</strong> allowance <strong>of</strong> linear information dynamics (LID) that has been
formulated by J.Ohlson [Ohlson, 1995]. LID is defined as <strong>the</strong> linear stochastic process, expressing
time changes and correlation <strong>of</strong> accounting and non-accounting variables. LID gives forecast for
future expected residual earnings value, resting on <strong>the</strong> actual value <strong>of</strong> accounting variables and o<strong>the</strong>r
information at present time.
Let us divide <strong>the</strong> book value <strong>of</strong> net assets into two constituents: tangible assets (NAT) and intangible
assets (NAI). The upper index BV means that <strong>the</strong> assets are taken according to <strong>the</strong>ir book value:
BV BV
NA NAT
+
= NA . (4a)
BV
I
Let us presume that intangible assets are not reflected in <strong>the</strong> balance sheet at all, or <strong>the</strong>ir part in <strong>the</strong>
book value is small enough to be neglected. Then, expression (4a) transforms as follows:
BV BV
NA = NAT
. (5a)
If accepting <strong>the</strong> presumption (5a), model (3a) turns into:
REOI BV REOI
V A = NAT
+ . (6a)
k
W
Hence, <strong>the</strong> REOI defines <strong>the</strong> effect obtained by a company from both tangible and intangible assets.
The main problem lies in dividing <strong>the</strong> general effect into constituent factors. In order to solve <strong>the</strong>
problem, we shall set up <strong>the</strong> following interconnected assumptions.
Assumption 1. The companies referring to <strong>the</strong> same industry are characterized by approximately
similar structure <strong>of</strong> assets. Therefore we may presume that one monetary unit invested into tangible
assets gives <strong>the</strong> same return throughout all <strong>the</strong> companies <strong>of</strong> <strong>the</strong> industry.
Assumption 2. The intra-branch differences in return <strong>of</strong> companies are explained only by exclusive
intangible assets <strong>of</strong> each company.
If to accept <strong>the</strong> mentioned assumptions, <strong>the</strong>n:
The return on tangible assets is <strong>the</strong> same for all companies and equals <strong>the</strong> average industry
return rate;
The return on intangible assets is <strong>the</strong> difference between <strong>the</strong> actual return <strong>of</strong> a company and
average return in industry. In this sense, <strong>the</strong> effect <strong>of</strong> intangible assets on general return rate may
be ei<strong>the</strong>r positive (if a company’s return rate prevails <strong>the</strong> average industry return rate), or negative
(if opposite).
From <strong>the</strong> above, we draw two principal conclusions:
The fundamental value <strong>of</strong> a company’s equity may be ei<strong>the</strong>r positive or zero (if <strong>the</strong> average
industry return is larger than or equals null);
The fundamental value <strong>of</strong> intangible assets may be ei<strong>the</strong>r positive or negative, if <strong>the</strong> average
industry return is non-negative.
Accepting <strong>the</strong> above presumptions, we shall distinguish in <strong>the</strong> REOI model <strong>the</strong> effects induced by
tangible and intangible assets. For that, we shall re-arrange <strong>the</strong> expression (3a) taking into account
<strong>the</strong> presumption (5a) as follows:
174

W
Tatiana Garanina and Yana Pavlova
REOI = NOPAT − k × NA ± RONA × NA , (7a)
BV
T
IAVG
where RONAIAVG — industry average return on net assets.
In <strong>the</strong> result <strong>of</strong> <strong>the</strong> re-arrangement we get:
BV
BV
BV
[ NOPAT − RONA × NA ] + [ RONA × NA − k NA ]
REOI = IAVG T
IAVG T W × T . (8a)
BV
T
Granting (3a), expression (8a) may be rewritten as follows:
I
T
BV
BV
[ NA × ( RONA − RONA ) ] + NA × ( RONA k )
T
BV
T
BV
T
IAVG
W
IAVG
IAVG
[ ]
REOI = − . (9a)
T
The expression in <strong>the</strong> first square brackets <strong>of</strong> formula (11a) may be interpreted as residual
operational income generated by intangible assets (REOII); <strong>the</strong> expression in <strong>the</strong> second square
brackets – as residual operational income generated by tangible assets (REOIT):
( RONA RONA )
REOI = NA × −
, (10a)
( RONA k )
REOI = NA × − . (11a)
References
Andriessen, D. and Tiessen, R. (2000) Weightless Weight – Find your real value in a future <strong>of</strong> intangible assets,
Pearson Education, London.
Bontis, N. (2001) “Assessing knowledge assets: a review <strong>of</strong> <strong>the</strong> models used to measure intellectual capital”,
International Journal <strong>of</strong> Management Reviews, Vol. 3, No. 1, pp 215-257.
Brooking, A. (1996) Intellectual Capital. International Thomson Business Press, London.
Bukhvalov A.V. (2004a) “Using Real Options in Management: An Introduction”, The Russian journal <strong>of</strong>
management, Vol. 2, No. 1, pp 3–32.
Bukhvalov, A.V. (2004b) “The <strong>the</strong>ory <strong>of</strong> a firm and <strong>the</strong> <strong>the</strong>ory <strong>of</strong> corporate governance”, Bulletin <strong>of</strong> Saint-
Petersburg State University. Management, No. 4, pp 99–117.
Doyle P. (2000) “Valuing marketing's contribution”, <strong>European</strong> Management Journal, Vol.18, No. 2, pp 233–245.
Edvinsson, L. and Malone, M. (1997) Intellectual Capital: Realizing Your Company’s True Value by Finding its
Hidden Brainpower. HarperBusiness, New York.
Huang, H.C. and Chang, C.W. (2008) “Embedded ties and <strong>the</strong> acquisition <strong>of</strong> competitive advantage”, Journal <strong>of</strong>
Intellectual Capital, Vol. 9, No. 1, pp. 105-121.
IFAC. (1998) Measurement and Management <strong>of</strong> Intellectual Capital.
Kozyrev, A.N. and Makarov, V.L. (2003) Intangible assets and intellectual property valuation, RIC TS VS RF.
Lev, B. (2003) Intangibles: Management, Measurement, and Reporting. Cwinto-Consalting, Moscow.
Lönnqvist, A., Mettänen, P. (2002) Criteria <strong>of</strong> Sound Intellectual Capital Measures. <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 2 nd
International Workshop on Performance Measurement, Hanover, June 6-7.
Luthy, D. (1998). Intellectual capital and its measurement, [on-line], http://www3.bus.osakacu.ac.jp/apira98/archives/htmls/25.htm
Ned Davis research, [on-line], www.ndr.com
Ohlson, J. (1995) Earnings, Book Values, and Dividends in Security Valuation, Contemporary Accounting
Research, Vol. 11, No. 2, pp 661 — 687.
Petty, R. and Guthrie, J. (2000) “Intellectual capital literature overview: measurement, reporting and
management”, Journal <strong>of</strong> Intellectual Capital, Vol. 1, No. 2, pp 155-176.
Rechtman, Y. (2001) Accounting Treatment <strong>of</strong> Intangible Assets. [on-line], http://hometown.aol.com/
rechtman/acc692.htm
Ståhle, P. and Grönroos, M. (1999) Knowledge Management (Tietopääoma Yrityksen Kilpailutekijänä). WSOY,
Porvoo.
Stam, C. (2010). Ideas and Things: Understanding <strong>the</strong> Dynamic Dimensions <strong>of</strong> Intellectual Capital. Proc. ECIC
2010, Lisbon.
Starovic, D., Marr, B. (2003) Understanding corporate value: managing and reporting intellectual capital. Technical
Report. Chartered Institute <strong>of</strong> Management Accountants (CIMA).
Stewart, T. (1995) “Trying to grasp <strong>the</strong> intangible”, Fortune Magazine, pp 52-69.
Sveiby K. (2002) “The "Invisible" Balance Sheet”, [on-line], http://www.sveiby.com/Portals/0/articles
/InvisibleBalance.html
Tan, H.P., Plowman, D. and Hancock, P. (2007) “Intellectual Capital and Financial Returns <strong>of</strong> Companies”,
Journal <strong>of</strong> Intellectual Capital, Vol. 9, No.1, pp 79-95.
175
IAVG
W

Impact <strong>of</strong> Investment in Human Capital on <strong>the</strong> Business
Value
Lidia García-Zambrano, Arturo Rodríguez-Castellanos and José Domingo
García-Merino
University <strong>of</strong> <strong>the</strong> Basque Country, Spain
lidia.garcia@ehu.es
arturo.rodriguez@ehu.es
josedomingo.garcia@ehu.es
Abstract: At present, it is known that intangible resources, or intellectual capital, are <strong>the</strong> drivers <strong>of</strong> economic
growth. One <strong>of</strong> its components is <strong>the</strong> human resources. Human resources are <strong>the</strong> main source <strong>of</strong> knowledge <strong>of</strong>
firms, and it is considered a critical resource, maybe <strong>the</strong> most important one (Johanson, 2005; Marr and Roos,
2005). For this reason, its management and its development are crucial to increase <strong>the</strong> value <strong>of</strong> <strong>the</strong> firm. The
objective <strong>of</strong> this paper is to analyse <strong>the</strong> influence that <strong>the</strong> training expenses have over <strong>the</strong> total value <strong>of</strong> <strong>the</strong>
intangibles. From <strong>the</strong> business management, <strong>the</strong> expenditure on training are an investment. It has been selected
a sample <strong>of</strong> <strong>the</strong> main Spanish companies, those that are included into IBEX-35 (<strong>the</strong> main index <strong>of</strong> reference <strong>of</strong>
<strong>the</strong> Spanish Stock Exchange, made up <strong>the</strong> 35 companies with more liquidity on <strong>the</strong> Spanish Stock Exchange),
and it has been analysed <strong>the</strong> relationship between <strong>the</strong> investment into human resources and <strong>the</strong> total value <strong>of</strong>
intangibles. The variable “expenditure on training” is a flow variable, ga<strong>the</strong>rs <strong>the</strong> investment done during a period
<strong>of</strong> time, while <strong>the</strong> variable “value <strong>of</strong> intangibles” is a stock variable, collects <strong>the</strong> total value <strong>of</strong> investment done
until a period <strong>of</strong> time. The value <strong>of</strong> intangibles in a particular time will be collected because <strong>of</strong> <strong>the</strong> investments
done into this intangible minus <strong>the</strong> depreciation suffered by <strong>the</strong>se investments. For this, it has been recollected
data about “expenditure on training” variable <strong>of</strong> <strong>the</strong> sample during <strong>the</strong> period 2006-2008; and <strong>the</strong> “value <strong>of</strong>
intangibles” variable in 2009, trying <strong>of</strong> analysing its relationship. From this, it obtains a positive relationship
between both variables, that is, <strong>the</strong> investment on training <strong>of</strong> employees generates increases on future intangible
value <strong>of</strong> <strong>the</strong> firm. The results are similar using different rates <strong>of</strong> depreciation on <strong>the</strong> investment <strong>of</strong> training. It is
significant that <strong>the</strong> analysis has been done during period <strong>of</strong> bear market. This conclusion reinforces <strong>the</strong> strategic
value <strong>of</strong> human resources during times <strong>of</strong> crisis.
Keywords: intellectual capital, human capital, expenditure on training, depreciation, business value
1. Introduction
It is widely accepted that intangible resources are those that generate economic growth in many
economic sectors. Investing in intangibles is <strong>the</strong> path that companies must follow to consolidate <strong>the</strong>ir
competitive position and ensure long-term growth. Recent studies (García-Merino et al., 2009;
García-Zambrano, 2010; Rodríguez-Castellanos et al., 2010) show how <strong>the</strong> companies that believe it
is important to invest in intangible resources obtain better economic results that those that do not.
Marshall (1890) already recognised <strong>the</strong> importance <strong>of</strong> knowledge as a significant resource and a
powerful production factor. However, <strong>the</strong> interest in measuring and managing intangibles, in particular
those due to knowledge −"intellectual capital"−, did not emerge until <strong>the</strong> mid 1990s, when models
began to be developed (Edvinsson, 1997; Edvinsson & Malone, 1997). Factors that contributed to
increasing <strong>the</strong> importance <strong>of</strong> intangibles in <strong>the</strong> company have been, on <strong>the</strong> one hand, <strong>the</strong> increasing
business competences driven by <strong>the</strong> globalisation <strong>of</strong> <strong>the</strong> markets and, on <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> advent
<strong>of</strong> <strong>the</strong> information technologies, whose greatest exponent is <strong>the</strong> Internet boom.
Today’s society is noted <strong>the</strong> knowledge-based society. Knowledge is <strong>the</strong> main strategic resource that
is capable in itself <strong>of</strong> generating new knowledge. Therefore, intangible resources have become <strong>the</strong>
competitiveness base for any company, as <strong>the</strong>ir ownership provides <strong>the</strong> company with <strong>the</strong> opportunity
to generate sustainable competitive advantage and increases <strong>the</strong> value <strong>of</strong> <strong>the</strong> company.
Numerous authors acknowledge that knowledge is <strong>the</strong> main value source <strong>of</strong> corporate intangible
resources (Johanson, 2005; Marr & Ross, 2005). Given <strong>the</strong> rapidity at which <strong>the</strong> required skills and
knowledge change and <strong>the</strong> employees being considered as an essential competitive resource to
obtain a lasting competitive advantage (Guerrero & Sire, 2001), training is one <strong>of</strong> <strong>the</strong> essential factors
that determine <strong>the</strong> efficiency <strong>of</strong> <strong>the</strong> organisations.
176

Lidia García-Zambrano et al.
Therefore, this paper is focused exclusively on <strong>the</strong> influence <strong>of</strong> employee training in business value.
The aim is to highlight, in <strong>the</strong> Spanish case, <strong>the</strong> impact <strong>of</strong> investment on Human Capital, and more
specifically expenditure on training, on <strong>the</strong> corporate intangible value.
A model is put forward that analyses <strong>the</strong> impact <strong>of</strong> <strong>the</strong> accumulated investment in training on <strong>the</strong>
value <strong>of</strong> <strong>the</strong> company’s intangibles.
The paper is structured as follows: <strong>the</strong> second section justifies <strong>the</strong> key role <strong>of</strong> intangible resources in
business competitiveness based on Resource Based View. In <strong>the</strong> third section, a review is performed
<strong>of</strong> <strong>the</strong> key role <strong>of</strong> intellectual capital, one <strong>of</strong> whose component is human capital, regarding <strong>the</strong>
business value. This is followed, in section four, by a review <strong>of</strong> <strong>the</strong> literature that considers Human
Capital and <strong>the</strong> investments made in it, and <strong>the</strong> value <strong>of</strong> <strong>the</strong> company. The methodology used is
subsequently set out. The results obtained are contained in section six and <strong>the</strong> paper ends with <strong>the</strong>
conclusions.
2. Resource based view: Intellectual capital as a source <strong>of</strong> competitive
advantage
Resource Based View has been a decisive contribution to strategic management. This emerged after
years <strong>of</strong> domination <strong>of</strong> Industrial Organisation (Porter, 1980, 1985) where <strong>the</strong> competitive advantage
<strong>of</strong> companies was exclusively justified by <strong>the</strong>ir belonging to specific economic sectors and <strong>the</strong> position
maintained <strong>the</strong>rein.
However, <strong>the</strong> empirical evidence doesn’t fully support this <strong>the</strong>ory. At <strong>the</strong> same time, different authors
noted that companies have or control a wide variety <strong>of</strong> resources and combinations <strong>of</strong> <strong>the</strong>m
(capabilities) that are essential for <strong>the</strong> company to be able to operate. These resources have
intrinsically different levels <strong>of</strong> efficiency, some <strong>of</strong> which are superior to o<strong>the</strong>rs. Therefore, companies
endowed with superior resources will have a greater likelihood <strong>of</strong> better perform, provided that <strong>the</strong>
cost <strong>of</strong> acquiring <strong>the</strong>m is lower than <strong>the</strong> value obtained as <strong>the</strong> result <strong>of</strong> <strong>the</strong> competitive advantage
generated by those resources (Barney, 1986, 2001). This is <strong>the</strong> origin <strong>of</strong> Resource Based View.
There are different names for <strong>the</strong>se resources that are so fundamental: “critical
resources”(Wernerfeld, 1984), “strategic factors” (Barney, 1986), etc.
Amit & Shoemaker (1993) highlighted five characteristics that differentiate <strong>the</strong>m: inimitable, rare,
valuable, non-transferable and non-substitutable. We have added durability to <strong>the</strong> aforementioned
characteristics.
Intangible resources are those that, lacking a financial or physical form, and being constructed by <strong>the</strong>
company over time, combine all <strong>the</strong>se requirements with more facility, and <strong>the</strong>refore become more
frequently <strong>the</strong> key factor <strong>of</strong> business competitiveness (Lev, 2001). This statement is particularly
applicable to <strong>the</strong> intangible resources based on knowledge, that is, to intellectual capital.
The information society requires new competitive mechanisms, fundamentally based on intangible
resources. Therefore, intangibles, according to Cañibano et al. (2004), have become an area <strong>of</strong> huge
interest not only to academics, but also to managers. Intangibles are <strong>the</strong> elements that guarantee <strong>the</strong>
success <strong>of</strong> a 21 st -century organisation, and enable a company to build up sustainable competitive
advantages.
According to Sánchez (2003), intellectual capital is <strong>the</strong> combination <strong>of</strong> intangible resources or
intangibles <strong>of</strong> an organisation, including personal knowledge, capacity for learning and adapting,
relations with customers and suppliers, brands, internal processes, R&D capacity, etc., that,
irrespective <strong>of</strong> whe<strong>the</strong>r <strong>the</strong>y are reflected on <strong>the</strong> financial statements, are directly or indirectly
controlled by that organisation and generate or will generate future value for <strong>the</strong> company, so that
<strong>the</strong>y can underpin sustained competitive advantage.
When grouping and classifying <strong>the</strong> elements which make up <strong>the</strong> intellectual capital, we find
differences and <strong>the</strong>re are also differences in <strong>the</strong> terminology used. Despite this, <strong>the</strong>re is a certain
consensus about <strong>the</strong> three components or basic dimensions: Human Capital, Structural Capital and
Relational Capital (Stewart, 1997; Cañibano et al., 1999; Sullivan, 1999; Brennan & Cornell, 2000;
Petty & Guthrie, 2000; Sánchez et al., 2000; Roos et al., 2001; Bontis, 2002; Ordóñez, 2002; Bueno,
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Lidia García-Zambrano et al.
2003; Palacios-Marqués & Garrigós-Simon, 2003; Kauffman & Schneider, 2004; Boedker et al., 2005;
Marr & Roos, 2005).
There are numerous papers that consider that intangibles, and investments in intangibles, determine
<strong>the</strong> pr<strong>of</strong>itability <strong>of</strong> <strong>the</strong> companies (Grabowski & Mueller, 1978 and Ravenscraft & Scherer 1982).
Odagiri (1983) studied <strong>the</strong> link that exists between <strong>the</strong> stock <strong>of</strong> technological intangible assets,
calculated according to expenditure on R&D and patent rights, and <strong>the</strong> results <strong>of</strong> <strong>the</strong> company. He
finds that <strong>the</strong> relationship between those variables varies according to <strong>the</strong> technological endeavour <strong>of</strong>
<strong>the</strong> companies. Those companies with research intensity over <strong>the</strong> average show a significant and
positive relationship between innovation and results.
Within <strong>the</strong> intangibles, those based on knowledge, that is, intellectual capital, have also been widely
studied, where <strong>the</strong>y are related to <strong>the</strong> creation <strong>of</strong> value in <strong>the</strong> company, (Rodríguez et al., 2006)
3. Human capital: Concept and value creation
As has been previously stated, it is one <strong>of</strong> <strong>the</strong> components <strong>of</strong> intellectual capital and <strong>the</strong>refore linked
to obtaining sustainable competitive advantage and performance (Alamar, 2007). Fernández et al.
(1998) Johanson (2005) and Marr & Roos (2005) consider that it is <strong>the</strong> dimension that provides
greater value for <strong>the</strong> company.
There are many definitions put forward in relationship to this concept that are more or less widely
accepted. The widely-held view that “our employees are our most valuable resource” is an oversimplification
<strong>of</strong> <strong>the</strong> idea <strong>of</strong> human capital. Human capital refers to <strong>the</strong> value <strong>of</strong> <strong>the</strong> knowledge <strong>of</strong> <strong>the</strong>
employees that create wealth for <strong>the</strong> company.
Human capital designates <strong>the</strong> quantity <strong>of</strong> valuable and useful knowledge accumulated by <strong>the</strong>
individual in his training. It includes <strong>the</strong> innate capacity and talent, along with training and acquired
qualifications.
Therefore, human capital includes <strong>the</strong> strategic intangible resources incorporated in <strong>the</strong> individuals.
Human capital is <strong>the</strong> set <strong>of</strong> productive capabilities that an individual acquires by accumulation <strong>of</strong>
specific or general knowledge (Becker, 1967). Therefore, it is an intangible resource supported by an
individual that can be accumulated and be used simultaneously in different operations.
The rapid advances in technologies that occur every day make it increasingly more necessary to have
employees with more knowledge, more skills to carry out <strong>the</strong> work and with more talent. Therefore,
companies require employees with competencies, attitudes and mental agility that enable <strong>the</strong>m to
work within a technological environment (Bontis, 2002). This importance, according to Edvinsson &
Malone (1999), is mainly due to <strong>the</strong> fact that a lack <strong>of</strong> an appropriate human dimension will negatively
condition <strong>the</strong> o<strong>the</strong>r activities <strong>of</strong> <strong>the</strong> company that create value for <strong>the</strong> latter. Pérez (2000) considers
human capital as <strong>the</strong> individual knowledge and skills <strong>of</strong> <strong>the</strong> members <strong>of</strong> <strong>the</strong> organisation that enable
its productivity and its contribution to generating value for <strong>the</strong> company to be increased.
In an isolated way, <strong>the</strong>re are a significant number <strong>of</strong> empirical studies that have shown <strong>the</strong> positive
relationship between Human Capital and results (Landau, 1983; Baumol et al., 1989; Barro, 1991;
Mankiw, et al. 1992; García, et al. 2010,Aaker, 1989; Dierick & Cool,, 1989; Erikson & Jacobson,
1992; Hall, 1992 and 1993; Chauvin & Hirschey, 1993; Boer, 1994; Lusch & Harvey, 1994; Bean,
1995; Schuman et al., 1995; Klette, 1996; White & Miles, 1996; Bukowitz & Petrash, 1997).
Danvila (2005) notes <strong>the</strong> strategic importance <strong>of</strong> <strong>the</strong> training <strong>of</strong> employees as a factor to generate
human capital, which involves obtaining sustainable competitive advantages that result in better
business results. His analysis finds that a great emphasis on training leads to better business
performance and a higher degree <strong>of</strong> customer loyalty. Fur<strong>the</strong>rmore, it has been shown that <strong>the</strong>
strategy influences <strong>the</strong> effect that training has on <strong>the</strong> performance.
Yang & Lin (2009) established a link between <strong>the</strong> human resources management practices and
organisational performance.
Some studies that relate investment in training and <strong>the</strong> results and business value are set out by
Danvila (2005).
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Lidia García-Zambrano et al.
However, investments in employee training do not generate immediate returns, but ra<strong>the</strong>r an
adaptation period is required before those investments are reflected in better performance.
O<strong>the</strong>r studies show that <strong>the</strong> value <strong>of</strong> <strong>the</strong> intangibles reflects part <strong>of</strong> <strong>the</strong> investments in intangibles in
previous periods. The Human Capital stock is <strong>the</strong> accumulated investment with a depreciation rate <strong>of</strong>
between 15% and 20% (Lev & Sougiannis, 1999; Baruch et al., 2005).
Therefore, <strong>the</strong> following hypo<strong>the</strong>sis is advanced:
H1: Investment in employee training positively impacts <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles <strong>of</strong> <strong>the</strong>
companies.
4. Methodology
4.1 Designing <strong>the</strong> research, population, sample and variables
The study has focused on Spanish companies quoted on <strong>the</strong> Spanish Stock Market and specifically
those that are quoted on <strong>the</strong> IBEX-35.
A simple linear regression was performed to establish whe<strong>the</strong>r or not <strong>the</strong> relationship advanced in <strong>the</strong>
hypo<strong>the</strong>sis exists.
The data needed to conduct <strong>the</strong> study were obtained from <strong>the</strong> CNMV (Spanish Stock Market
Commission), as well as from <strong>the</strong> websites <strong>of</strong> <strong>the</strong> different companies.
The variables used in <strong>the</strong> study were as follows: logarithm <strong>of</strong> <strong>the</strong> value <strong>of</strong> <strong>the</strong> company's intangibles
and logarithm <strong>of</strong> <strong>the</strong> accumulated investment in <strong>the</strong> training <strong>of</strong> <strong>the</strong> employees.
The value <strong>of</strong> <strong>the</strong> intangibles was calculated as <strong>the</strong> difference between <strong>the</strong> market value <strong>of</strong> <strong>the</strong>
company and <strong>the</strong> book value equity, with <strong>the</strong> latter calculated as <strong>the</strong> difference between <strong>the</strong> total
assets and liabilities.
On <strong>the</strong> o<strong>the</strong>r hand, data were collected about <strong>the</strong> investment in employee training, as <strong>the</strong> main
variable covering investment in Human Capital (Ordiz Fuertes, 2002; Bukowitz & Petrash, 1997; Koch
& McGrath, 1996). The accumulated investment in training was obtained by means <strong>of</strong> <strong>the</strong> summary <strong>of</strong>
<strong>the</strong> expenditure on training in <strong>the</strong> three periods prior to moment t, depreciated by a percentage. The
depreciation rate used varied between 15% and 30%.
The figures obtained were submitted to a normality test, using χ 2 test. Given that <strong>the</strong> variables were
not normal, <strong>the</strong> logarithm <strong>of</strong> each <strong>of</strong> <strong>the</strong> variables, which did present normality, was used for <strong>the</strong>
analysis.
Regarding <strong>the</strong> size bias, <strong>the</strong> initial variables were divided by <strong>the</strong> logarithm <strong>of</strong> “Net Amount <strong>of</strong> <strong>the</strong>
Turnover” to alleviate that problems, as suggested by o<strong>the</strong>r previous studies (Lev & Sougiannis,
1999).
Table 1 sets out <strong>the</strong> technical details <strong>of</strong> <strong>the</strong> study:
Table 1: Technical details <strong>of</strong> <strong>the</strong> study
Sample 35 companies belonging to <strong>the</strong> IBEX-35
Data collection source CNMV and company websites
Data type
Expenditure on training, capitalization, value
<strong>of</strong> <strong>the</strong> intangibles
Data analysis technique Simple linear regression
Schedule September 2010
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Lidia García-Zambrano et al.
4.2 Proposed model: Relationship between human capital investment and intangible
value
As performed by Lev et al. (2005), a simple linear regression model was put forward that relates <strong>the</strong>
investment in Human Capital, through <strong>the</strong> training <strong>of</strong> <strong>the</strong> employees, and <strong>the</strong> intangible value <strong>of</strong> <strong>the</strong>
company. This enabled us to test whe<strong>the</strong>r investing in Human Capital really increase <strong>the</strong> intangible
value <strong>of</strong> <strong>the</strong> company.
j, t
( Human CapitalInvestmentj,
t ) εt
Intangible Value = f
+
[1]
As has been discussed, <strong>the</strong>re is a lag effect <strong>of</strong> <strong>the</strong> investments in Human Capital on <strong>the</strong> value <strong>of</strong> <strong>the</strong>
intangibles; that is, <strong>the</strong> value <strong>of</strong> <strong>the</strong> intangibles <strong>of</strong> company j in time period t will not only be influenced
by <strong>the</strong> investments performed in period t−1, but <strong>the</strong>y will also be influenced, although to a lesser
extent, by <strong>the</strong> outgoings in k previous years. An accumulative annual depreciation rate was used to
consider this effect. Different depreciation rates <strong>of</strong> 15%, 20% and 30% were used. Three lags were
taken as <strong>the</strong> depreciation rate <strong>of</strong> 30% did not allow previous effects to be considered.
Previous studies considered similar depreciation rates. García et al. (2008) find <strong>the</strong> average life <strong>of</strong> a
core competency was between 3 and 5 years. We likewise took 15% as a depreciation rate, chosen
by o<strong>the</strong>r authors (Lev et al., 2005). Previous literature also considered that investment in training has
a life that ranges between two years (Leonard, 1971; Hirschey y Weygandt, 1985) to seven years
(Sougiannis, 1994; Ballester et al., 2003).
Given that <strong>the</strong>re is a time lapse between <strong>the</strong> moment <strong>of</strong> performing <strong>the</strong> investment in training and <strong>the</strong>
results obtained, <strong>the</strong> investment in year t has not been considered but ra<strong>the</strong>r <strong>the</strong> investment in
previous years.
We considered period t as year 2009 and periods 2006, 2007 and 2008 (taking a 3 lag structure) as
investments in training <strong>of</strong> <strong>the</strong> employees, with <strong>the</strong>ir relevant depreciations.
Therefore, <strong>the</strong> proposed model would be as follows:
3
LogVI ⎛ t Log GFt
-i
) α ⎞
= f
( 1 i ) ε t
LogINCV ⎜
⎜∑
− +
t i 1 LogINCV 100 ⎟
⎝ = t ⎠
Where:
VIt is <strong>the</strong> value <strong>of</strong> <strong>the</strong> intangibles <strong>of</strong> that company.
GFt-i is <strong>the</strong> value <strong>of</strong> <strong>the</strong> spending on training during <strong>the</strong> three years prior to <strong>the</strong> current year t.
α: Applied depreciation percentage. (α = 15, 20, 30).
INCVt: Net Turnover <strong>of</strong> year t
εt: Random error in t.
Therefore, equation [2] includes <strong>the</strong> lag impact <strong>of</strong> <strong>the</strong> expenditure on training <strong>of</strong> <strong>the</strong> employees, which
thus does not consider <strong>the</strong> impact <strong>of</strong> <strong>the</strong> current investment (period in t) on training on <strong>the</strong> future value
<strong>of</strong> <strong>the</strong> value <strong>of</strong> <strong>the</strong> intangibles <strong>of</strong> <strong>the</strong> company, but ra<strong>the</strong>r <strong>the</strong> costs or expenditure performed in <strong>the</strong>
three years prior to t. It should also be pointed out that α indicates <strong>the</strong> deprecation percentage
(accumulated year after year) <strong>of</strong> <strong>the</strong> training costs.
5. Results
In order to check <strong>the</strong> aforementioned hypo<strong>the</strong>sis, a simple linear regression was performed to verify if
<strong>the</strong> company that invests in training for <strong>the</strong>ir employees sees <strong>the</strong> value <strong>of</strong> <strong>the</strong>ir intangibles increase.
In <strong>the</strong> following tables, we can see <strong>the</strong> descriptive statistics, <strong>the</strong> results <strong>of</strong> <strong>the</strong> regression and <strong>the</strong>
goodness <strong>of</strong> fit test for each <strong>of</strong> <strong>the</strong> depreciation rates used, 15%, 20% and 30%, respectively.
180
[2]

Lidia García-Zambrano et al.
Table 2: Impact <strong>of</strong> <strong>the</strong> investment in training on <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles, descriptive
statistics: α = 15%
Descriptive statistics
N Minimum Maximum Average
Standard
deviation
Intangible Value Log 09 35 8,41 10,78 9,4534 0,60011
15% depreciation training
costs accumulated log
35 11,723 19,638 15,31570 1,808914
Table 3: Impact <strong>of</strong> <strong>the</strong> investment in training on <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles, linear regression: α
= 15%
Coefficients
Model
Linear
regression
Non-standardised
Coefficients
Standardised
coefficients
B Standard error Beta
t Sig.
(Constant) 7,250 0,823 8,804 0,000
Training costs accumulated
log
Dependent variable: Intangible Value Log 09
Table 4: Goodness <strong>of</strong> fit test α =15%
0,145 0,054 0,461 2,696 0,012
Model Summary
Model R R squared R squared corrected Standard error <strong>of</strong> <strong>the</strong> estimate
0,461 0,212 0,183 0,54244
Predictor variables: (Constant, training costs accumulated log
Therefore, <strong>the</strong> regression model resulting from <strong>the</strong> analysis is as follows:
3
t t i
ε t
t
1
~
Log VI
⎛ LogGF
⎞
−
= 7,250 + 0,
145
( 1 0,
15i)
+
LogINCV
⎜
⎜∑
−
LogINCV ⎟
⎝ i= t ⎠
Table 5: Impact <strong>of</strong> <strong>the</strong> investment in training on <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles, descriptive
statistics: α = 20%
Descriptive statistics
N Minimum Maximum Average Standard deviation
Intangible Value Log 09 35 8,41 10,78 9,4534 0,60011
Training costs accumulated
log
35 10,05 16,83 13,1462 1,53939
Table 6: Impact <strong>of</strong> <strong>the</strong> investment in training on <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles, linear regression: α
= 20%
Coefficients
Model
Linear
regression
Non-standardised
Coefficients
Standardised
coefficients
B Standard error Beta
t Sig.
(Constant) 7,214 0,829 8,699 0,000
Training costs
accumulated log
Dependent variable: Intangible Value Log 09
0,171 0,063 0,464 2,720 0,011
181

Table 7: Goodness <strong>of</strong> fit test α =20%
Lidia García-Zambrano et al.
Model Summary
Model R R squared R squared corrected Standard error <strong>of</strong> <strong>the</strong> estimate
0,462 0,213 0,184 0,54213
Predictor variables: (Constant, training costs accumulated log
The resulting model is as follows:
3
t t i
ε t
t
i 1
t
~
Log VI
⎛ LogGF ⎞
−
= 7,214 + 0,
171
(1 0,2i) +
LogINCV
⎜
⎜∑
−
LogINCV ⎟
⎝ =
⎠
Table 8: Impact <strong>of</strong> <strong>the</strong> investment in training on <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles, descriptive
statistics: α = 30%
Descriptive statistics
N Minimum Maximum Average Standard deviation
Intangible Value Log 09 35 8,41 10,78 9,4534 0,60011
Training costs accumulated log 35 6,71 11,23 8,8071 1,01161
Table 9: Impact <strong>of</strong> <strong>the</strong> investment in training on <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles, linear regression: α
= 30%
Coefficients
Model
Non-standardised
Coefficients
Standardised
coefficients
B Standard error Beta
t Sig.
Linear regression (Constant) 7,118 0,846 8,412 0,000
Training costs
accumulated log
Dependent variable: Intangible Value Log 09
Table 10: Goodness <strong>of</strong> fit test α =30%
0,267 0,096 0,472 2,779 0,010
Model Summary
Model R R squared R squared corrected Standard error <strong>of</strong> <strong>the</strong> estimate
0,466 0,217 0,188 0,54072
Predictor variables: (Constant, training costs accumulated log
The regression model resulting from <strong>the</strong> analysis is as follows:
3
t t i
ε t
t
i 1
t
~
Log VI
⎛ LogGF
⎞
−
= 7,118 + 0,
267
(1 0,30i) +
LogINCV
⎜
⎜∑
−
LogINCV ⎟
⎝ =
⎠
Except to case α =30%, total value <strong>of</strong> intangibles is less than accumulated expenses on training (table
2, 5 and 8). That seems mean a lack <strong>of</strong> efficiency <strong>of</strong> training investments. But we have to consider <strong>the</strong>
crisis period when stock market capitalization was low. We understand <strong>the</strong> comparative between
<strong>the</strong>se two variables is not suitable.
The beta <strong>of</strong> model for <strong>the</strong> three cases studied is positive and, at <strong>the</strong> same time, statistically significant
at 5%. This means that <strong>the</strong> investment in training positively affects <strong>the</strong> value <strong>of</strong> <strong>the</strong> intangibles <strong>of</strong> <strong>the</strong>
company. This result, set out in tables 3, 6 and 9, includes how investing in Human Capital has a
positive impact on <strong>the</strong> intangible value <strong>of</strong> <strong>the</strong> company, and, <strong>the</strong>refore means that <strong>the</strong> value <strong>of</strong> <strong>the</strong>
company increases. We consider also in tables 4, 7 and 10 <strong>the</strong> R 2 determination coefficient that
shows <strong>the</strong> goodness <strong>of</strong> <strong>the</strong> adjustment, according to <strong>the</strong> depreciation rate applied. In <strong>the</strong> three cases,
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Lidia García-Zambrano et al.
it is around 0.2, being statistically significant. This value increases when we increase α, that means
<strong>the</strong> recent expenses on training affect strongly to total value <strong>of</strong> firm.
This results is similar to o<strong>the</strong>r studies (Novales, 2008), which a priori means that <strong>the</strong> goodness <strong>of</strong> fit
test is a little weak, in such a way that <strong>the</strong> variations that <strong>the</strong> endogenous variable experiments is only
explained by a 20% by <strong>the</strong> exogenous variable. However, if we look at o<strong>the</strong>r studies Novales (2008),
this result does not mean that <strong>the</strong> model is not valid or reliable, but ra<strong>the</strong>r that it may be due to <strong>the</strong>
sample is too small or that one or two residuals are too high and cause a relatively low value <strong>of</strong> <strong>the</strong>
coefficient <strong>of</strong> determination. Therefore, we have deemed it convenient to study <strong>the</strong> correlations
between <strong>the</strong> investments in training during <strong>the</strong> three years studied and <strong>the</strong> intangible value <strong>of</strong> <strong>the</strong>
companies. Table 11,shows <strong>the</strong> aforementioned correlations.
Table 11: Correlation between <strong>the</strong> logarithm <strong>of</strong> <strong>the</strong> intangibles in 2009 and <strong>the</strong> logarithm <strong>of</strong> spending
on training in 2008, 2007 and 2006
08 training
costs log
Intangible Value Log 09 Pearson Correlation 0,487 **
07 training
costs log
06 training
costs log
0,401 * 0,410 *
Sig. (bilateral) 0,007 0,031 0,027
As can be seen, <strong>the</strong> correlation between <strong>the</strong> variable “investment <strong>of</strong> training” and <strong>the</strong> value <strong>of</strong> <strong>the</strong>
intangibles in 2009 is positive, which means that <strong>the</strong>re is a relationship between <strong>the</strong> investment in
training and <strong>the</strong> intangible value <strong>of</strong> <strong>the</strong> company, a relationship that is positive and strong and,
according to <strong>the</strong> model studied, is statistically significant at 5%.
It should also be mentioned that <strong>the</strong> most recent spending on training has a greater impact on <strong>the</strong>
intangible value <strong>of</strong> <strong>the</strong> company. This means that <strong>the</strong> highest depreciation rates chosen for <strong>the</strong>
analysis result in a greater impact <strong>of</strong> <strong>the</strong> most recent spending on <strong>the</strong> intangible value <strong>of</strong> <strong>the</strong>
companies. This can be seen in Tables 3, 6 and 9, respectively.
In all <strong>the</strong> cases studied, investment in training <strong>of</strong> <strong>the</strong> employees has a positive correlation with <strong>the</strong>
future value <strong>of</strong> <strong>the</strong> intangibles.
We can <strong>the</strong>refore accept <strong>the</strong> proposed hypo<strong>the</strong>sis.
6. Conclusions
The importance attributed to <strong>the</strong> intangible resources is <strong>of</strong> increasing interest, which encourages
researchers to turn to knowledge and <strong>the</strong>ir management. It is undeniable that <strong>the</strong> companies are
aware <strong>of</strong> <strong>the</strong> existing widespread concern regarding knowledge about <strong>the</strong>ir intangibles, as <strong>the</strong>y need
guarantees for <strong>the</strong>ir external funding and to improve <strong>the</strong>ir internal management, while financial
statement do not currently provide all <strong>the</strong> necessary information about <strong>the</strong> intangibles.
This paper seeks to establish <strong>the</strong> importance that investment in Human Capital has, and more
specifically expenditure on training, and its impact on <strong>the</strong> corporate intangible value, in <strong>the</strong> Spanish
case.
The results show that <strong>the</strong>re is a positive relationship, and at <strong>the</strong> same time statistically significant,
between <strong>the</strong> investment in employee training, and <strong>the</strong> future value <strong>of</strong> <strong>the</strong> intangibles <strong>of</strong> <strong>the</strong>
companies. The results show that relationship exists in all <strong>the</strong> cases studied, using depreciation <strong>of</strong>
15%, 20 and 30%. This means that investing in Human Capital, and more specifically, in training <strong>the</strong>
employees, increases <strong>the</strong> value <strong>of</strong> <strong>the</strong> company.
Therefore, Human Capital, reflected through <strong>the</strong> “investment in employee training” variables is one <strong>of</strong>
<strong>the</strong> most important dimensions <strong>of</strong> Intellectual Capital to create intangible value in <strong>the</strong> company.
Besides, this influence is higher on <strong>the</strong> case <strong>of</strong> recent expenses <strong>of</strong> employees; that means, <strong>the</strong> impact
in training investment on intangible value <strong>of</strong> organizations seems run out quickly. Also, <strong>the</strong> total value
<strong>of</strong> intangibles is less than accumulative training investment in cases <strong>of</strong> α = 15% and 20%. That means
apparently a lack <strong>of</strong> efficiency <strong>of</strong> training investment. But we have to take into account <strong>the</strong> variable
used: stock market capitalization. In 2009 stock market prices had been descended strongly. For this
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Lidia García-Zambrano et al.
reason, we understand <strong>the</strong> comparative between <strong>the</strong>se values is not appropriate to measure <strong>the</strong>
efficiency <strong>of</strong> investment. Companies that invested more into training employees during prosperity
times, valued better into Stock Market in 2009. That means investors have valued better effort to build
Human Capital.
One <strong>of</strong> <strong>the</strong> possible lines <strong>of</strong> future research is to expand <strong>the</strong> selected sample and include <strong>European</strong>
companies quoted on <strong>the</strong> stock market. We could likewise see <strong>the</strong> degree <strong>of</strong> impact that <strong>the</strong> o<strong>the</strong>r two
dimensions <strong>of</strong> Intellectual Capital, Relational and Structural Capital, have on <strong>the</strong> intangible value <strong>of</strong>
<strong>the</strong> company, and <strong>the</strong>refore, on <strong>the</strong> business value overall.
References
Aaker, D.A. (1989) “Managing assets and skills: <strong>the</strong> key to a sustainable competitive advantage” California
Management Review, Vol 31, No. 2, pp 91-106.
Alamar, E. M. (2007) Capital Intelectual y resultados empresariales en las empresas de servicios pr<strong>of</strong>esionales
de España. Doctoral Thesis, Complutense University <strong>of</strong> Madrid, Madrid.
Amit, R. and Schoemaker, P. (1993) “Strategic assets and organizational rent”, Strategic Management Journal,
Vol 14, pp 33-46.
Ballester, M., García-Ayuso, M. and Livnat, J. (2003) “The economic value <strong>of</strong> <strong>the</strong> R&D intangible asset”,
<strong>European</strong> Accounting Review, Vol 12, No. 4, pp 605-633.
Barney, J. B. (1986) “Strategic factor markets: expectations, luck and business strategy”, Management Science,
Vol 32, No. 10, pp 1231-1241.
Barney, J. B. (1991) “Firm resources and sustained competitive advantage”, Journal <strong>of</strong> Management, Vol 17, No.
1, pp 99-120.
Barney, J. (2001) “Is <strong>the</strong> Resource-based View a useful perspective for Strategic Management Research? Yes”,
Academy <strong>of</strong> Management Review, Vol 26, pp 41-56.
Baruch, L., Sarath, B. and Sougiannis, T. (2005) “R&D Reporting Biases and Their Consequeences”,
Contemporary Accounting Research, Vol 22, No. 4, pp 977-1026.
Barro, R. (1991) "Economic Growth in a Cross Section <strong>of</strong> Countries", Quarterly Journal <strong>of</strong> Economics, Vol 6, No.
2, pp 407-43.
Baumol, W., Batey, S.A. and Wolf, E (1989) Productivity and American Leadership: <strong>the</strong> Long View. Boston (MA):
The MIT Press.
Bean, A.S. (1995) “Why some R&D organizations are more productive than o<strong>the</strong>rs.” Research-Technology
Management, Vol 38, No. 1, pp 25-29.
Becker, G.S. (1967) Human capital and <strong>the</strong> personal distribution <strong>of</strong> income, Ann Arbor (Michigan): University <strong>of</strong>
Michigan Press.
Boedker, C., Guthrie, J. and Cuganesan, S. (2005) “An integrated framework for visualising intellectual capital”,
Journal <strong>of</strong> Intellectual Capital, Vol 6, No. 4, pp 510-527.
Boer, F.P. (1994) “Linking R&D to growth and shareholder value”, Research-Technology Management, Vol 37,
No. 3, pp 16-22.
Bontis, N. (2002) National Capital Intellectual Index: intellectual capital development in <strong>the</strong> Arab region, (Ontario):
Institute for Intellectual Capital Research.
Brennan, N. and Cornell, B. (2000) “Intellectual Capital: current issues and policy implications”. Paper presented
at <strong>the</strong> 23º <strong>Conference</strong> on <strong>the</strong> Annual <strong>European</strong> Accounting Association, Munich, 29-31 March 2000.
Bueno Campos, E. (2003) “El capital social en la sociedad del conocimiento: estado del arte y evidencia
empírica”, XIII <strong>Conference</strong> <strong>of</strong> ACEDE.
Bukowitz, W.R. and Petrash, G.P. (1997) “Visualizing, measuring, and managing knowledge”, Research-
Technology Management, Vol 40, No. 4, pp 24-31.
Cañibano, L., García-Ayuso, M. and Sánchez, M. P. (1999) “La relevancia de los intangibles para la valoración y
la gestión de empresas: revisión de la literatura”, Revista Española de Financiación y Contabilidad, No.
100, extra, pp 17-88.
Cañibano, L. and Sánchez, M. P. (2004) “Medición, gestión e información de intangibles: lo más nuevo”,
Medición, Control y Gestión de los Intangibles, Vol 1, pp 99-139.
Chauvin K.W. and Hirschey, M. (1993) “Advertising, R&D expenditures, and <strong>the</strong> market value <strong>of</strong> <strong>the</strong> firm”,
Financial Management, Vol 22, No. 4, pp 345-357.
Danvila del Valle, I. (2005) La generación de capital humano a través de la formación, un análisis de su efecto
sobre los resultados empresariales, Doctoral Thesis, Complutense University <strong>of</strong> Madrid, Madrid.
Dierick, I. and Cool, K. (1989) “Asset stock accumulation and sustainability <strong>of</strong> competitive advantage”
Management Science, Vol 35, No. 12, pp 1504-1513.
Edvinsson, L. (1997) “Developing intellectual capital at Skandia”, Long Range Planning, Vol 30, No. 3, pp 266-
373.
Edvinsson, L. and Malone, M. (1997) Intellectual Capital. New York: Harper.
Edvinsson, L. and Malone, M.S. (1999) El capital intelectual: como identificar y calcular el valor de los recursos
intangibles de su empresa, Barcelona: Gestión 2000.
Erickson, G. and Jacobson, R. (1992) “Gaining comparative advantage through discretionary expenditures: <strong>the</strong>
returns to R&D and advertising”, Management Science, Vol 38, No. 9, pp 1264-1279.
184

Lidia García-Zambrano et al.
Fernández, E., Montes, J. and Vázquez, C. (1998) “Tipología e Implicaciones Estratégicas de los Recursos
Intangibles. A view based on The Theory <strong>of</strong> The Resources”, Revista Asturiana de Economía, Vol 11, pp
159-182.
García, D., Rodríguez, A., Arregui, G. and Vallejo, B. (2008) “Importancia y valoración de los intangibles: la
percepción de los directivos”, Estudios de Economía Aplicada, Vol 26, No. 3, pp 27-55.
García, D., Arregui, G. and García, L. (2009) “La valoración financiera de los intangibles y los resultados
empresariales”, in Rodrigues, S. (ed)) Creativity and Survival <strong>of</strong> <strong>the</strong> firm under uncertainty, pp 41-63,
<strong>European</strong> Academic Publishers, Italy.
García-Merino, D., Arregui-Ayastuy, G., Rodríguez-Castellanos, A. and García-Zambrano, L. (2010) “The
intangibles’ mindset <strong>of</strong> CFO’s and corporate performance”. Knowledge Management Research & Practice,
forthcoming.
García-Zambrano, L. (2010) Recursos intangibles, su valoración financiera, y los resultados empresariales.
Dissertation for <strong>the</strong> Diploma <strong>of</strong> Advanced Studies in Finance and Marketing. Bilbao: University <strong>of</strong> <strong>the</strong>
Basque Country.
Guerrero, S. and Sire, B. (2001) “Motivation to train from <strong>the</strong> workers perspective: example <strong>of</strong> French
companies”, International Journal <strong>of</strong> Human Resource Management, Vol 12, No. 6, pp 988-1004.
Gravowski, H. and Mueller, D. (1978) “Industrial research and development, intangible capital stocks and firm
pr<strong>of</strong>it rates”, Bell Journal <strong>of</strong> Economics, Vol 9, No. 2, pp 328-343.
Hall, R. (1992) “The strategic analysis <strong>of</strong> intangible resources”, Strategic Management Journal, Vol 13, No. 2, pp
135-144.
Hall, R. (1993) “A framework linking intangible resouces and capabilitites to sustainable competitive advantage”,
Strategic Management Journal, Vol 14, No. 5, pp 607-618.
Hirchey, M. and Weygandt, J.J. (1985) “Amortization Policy for Advertisisng and Research and Development
Expenditures”, Journal <strong>of</strong> Accounting Research, Vol 23, pp 326-335.
Johanson, U. (2005) “A Human Resource perspective on Intellectual Capital”. In Marr, B. (Eds), Perspective on
Intellectual Capital. Multidisciplinary insights into management, measurement and reporting, Oxford:
Butterworth Heinemann, pp 96-105.
Kaufmann, L. and Schneider, Y. (2004) “Intangibles: a syn<strong>the</strong>sis <strong>of</strong> current research”, Journal <strong>of</strong> Intellectual
Capital, Vol 5, No. 3, pp 366-388.
Klette, T.J. (1996) “R&D, scope economies, and plant performance”, Journal <strong>of</strong> Economics, Vol 27, No. 3, pp
502-522.
Koch, M. and McGrath, R. (1996) “Improving Labour Productivity: Human Resource Management Policies do
Master”, Strategy <strong>of</strong> Management Journal, Vol 17, pp 335-355.
Landau, D. (1983) "Government Expenditure and Economic Growth: a Cross-Country Study", Sou<strong>the</strong>rn
Economic Journal, January, pp 783-92.
Leonard, W.N. (1971) “Research and Development in Industrial Growth”, Journal <strong>of</strong> Political Economy, Vol 79,
No. 2, pp 232-256.
Lev, B. (2001) Intangibles- Management, measuring and reporting. Washington, DC: The Brooking Institution.
Lev, B. and Sougiannis, T. (1999) “Penetrating <strong>the</strong> Book-to-Market black-box: The R&D effect”, Journal <strong>of</strong>
Business Finance and Accounting, Vol 26, No. 3,4, pp 419-449.
Lev, B., Sarath, B. and Sougiannis, T. (2005) “R&D Reporting Biases and Their Consequences”, Contemporary
Accounting Research, Vol 22, No. 4, pp 977-1026.
Lusch, R.F. and Harvey, M.G. (1994) “The case for an <strong>of</strong>f-balance sheet controller”, Sloan Management Review,
Vol 35, No. 2, pp 101-105.
Mankiw, G., Romer, D. and Weil, D. (1992) "A Contribution to <strong>the</strong> Empirics <strong>of</strong> Economic Growth", Quartely
Journal <strong>of</strong> Economics, Vol 1, pp 407-37.
Marr, B. and Roos, G. (2005) “A Strategy perspective <strong>of</strong> intellectual capital”. In Marr, B. (Ed), Perspectives <strong>of</strong>
Intellectual Capital. Multidisciplinary insights into management, measurement and reporting, Boston, MA:
Elsevier, pp 28-41.
Novales, A. (2008) La bondad de ajuste del modelo de regresión lineal simple, Investigación Research,
Complutense University, Madrid.
Odagiri, H. (1983) “R&D expenditures, royalty payments, and sales growth in Japanese manufacturing
corporations”, The Journal <strong>of</strong> Industrial Economics, Vol 32, No. 1, pp 61-71.
Ordiz fuertes, M. (2002) “Prácticas de alto rendimiento en recursos humanos: concepto y factores que motivan
su adopción”, Cuadernos de Economía y Dirección de la Empresa, Vol 12, pp 247-266.
Palacios-Marqués, D. and Garrigós-Simón, F.J. (2003) “Validating and measuring IC in <strong>the</strong> biotechnology and
telecommunication industries”, Journal <strong>of</strong> Intellectual Capital, Vol 4, No. 3, pp 332-347.
Perez-Bustamante, G. (2000) “Capital intelectual e innovación en conocimiento”. Paper presented at X Congreso
Nacional de ACEDE: Integración Económica, Competitividad y Entorno Institucional de la Empresa, Oviedo,
September 2000.
Pfeffer, J. and Salancik, G.R. (1978) The external control <strong>of</strong> organizations, New York: Harper and Row.
Porter, M. (1979) “How Competitive Forces Shape Strategy”, Harvad Business Review, New York, pp 102-116.
Porter, M. E (1985) "Technology and Competitive Advantage", Journal <strong>of</strong> Business Strategy, Vol 5, No. 3, pp 60-
78.
Ravenscraft, D and Scherer, F. (1982) “The lag structure <strong>of</strong> returns to research and development”, Applied
Economics, Vol 14, No. 6, pp 603-620.
185

Lidia García-Zambrano et al.
Rodriguez, A., Ranguelov, S. and García, J. D. (2006) “Intangible resources and value creation in firms: a
review”. In Kilsberg, B.; Mercado, C. (eds.): Los límites de la Responsabilidad Social de la Empresa.
Responsabilidad Social de la Empresa, Universidad y Desarrollo. Buenos Aires: Academia Europea de
Dirección y Economía de la Empresa, University <strong>of</strong> Buenos Aires and Rey Juan Carlos University, pp 489-
496.
Rodríguez-Castellanos, A., García-Merino, J. D. and García-Zambrano, L. (2010) “Conocimiento organizacional,
recursos intangibles y resultados empresariales”. In Maximsev, I. A., Krasnoproshin, V. V. and Prado-
Román, C. (Eds.): Global Financial & Business Networks and Information Management Systems. Madrid:
<strong>European</strong> Academic Publishers, pp. 23-42 (CD format).
Roos, G., Bainbridge, A. and Jacobsen, K. (2001) “Intellectual Capital as a strategic tool”, Strategic & Leadership,
Vol 29, No. 4, pp 21-26.
Sánchez, P., Chamichade, C. and Olea, M. (2000) “Management <strong>of</strong> intangibles: an attempt to build a <strong>the</strong>ory”,
Journal <strong>of</strong> Intelectual Capital, Vol 1, No. 4, pp 188-209.
Sánchez Medina, A.J (2003) Modelo para la medición del capital intelectual de territorios insulares: una
aplicación al caso de Gran Canaria, Thesis, Complutense University <strong>of</strong> Madrid. Chapter 1 (El Capital
Intelectual: una revisión).
Schumann, P.A. (1995): “Measuring R&D performance.” Research & Technology Management, Vol 38, No. 3, pp
45-54.
Sougiannis, T. (1994) “The accounting Based-Valuation <strong>of</strong> Corporate R&D”, Accounting Review, Vol 69, No. 1,
pp. 44-68.
Stewart, T.A. (1997) Intellectual Capital: The new Wealth <strong>of</strong> Organizations. New York: Doubleday.
Sullivan, P.H. (1999) “Pr<strong>of</strong>iting from intellectual capital”, Journal <strong>of</strong> Knowledge Management, Vol 3, No. 2, pp
132-142.
Yang, C. and Lin, C. (2009) “Does intellectual capital mediate <strong>the</strong> relationship between HRM and organizational
performance? Perspective <strong>of</strong> a healthcare industry in Taiwan”, International Journal <strong>of</strong> Human Resource
Management, Vol 20, No. 9, pp 1965-1984.
Wernerfelt, A. (1984) “A resource based view <strong>of</strong> <strong>the</strong> firm”, Strategic Management Journal, Vol 5, No. 2, pp 171-
180.
White, J.B. and Miles, M.P. (1996) “The financial implications <strong>of</strong> advertising as an investment”, Journal <strong>of</strong>
Advertising Research, Vol 36, No. 4, pp 43-52.
186

The Relationship Between Gross Domestic Product (GDP)
and Hidden Wealth During <strong>the</strong> years 2000-2009: An
International Study
Víctor Raúl López Ruiz, José Luis Alfaro Navarro and Domingo Nevado Peña
University Of Castilla-La Mancha, Spain
Victor.Lopez@uclm.es
JoseLuis.Alfaro@uclm.es
Domingo.Nevado@uclm.es
Abstract: In this paper we showed that it is possible to measure <strong>the</strong> development and management <strong>of</strong>
knowledge in a country using indicators <strong>of</strong> intellectual capital that consider non visible assets not included by <strong>the</strong>
Gross Domestic Product. Using this idea, we obtained a measure <strong>of</strong> <strong>the</strong> intellectual capital for 72 countries
selected in function <strong>of</strong> <strong>the</strong> information available in <strong>the</strong> years 2000, 2005 and 2008. These measures allows us to
verify <strong>the</strong> hypo<strong>the</strong>sis that knowledge acts as a divergent factor <strong>of</strong> wealth, that is, that rich countries are richer in
knowledge and manage it more efficiently than poor countries. Thus, in a global economy, intellectual capital
circulates in opposite sense to development, that is, from poor to rich countries. We showed as national
intellectual capital anticipates economic crisis before than GDP because <strong>of</strong> real GDP averages increase in all
years considered whereas national intellectual capital back down in last year analysed. Moreover, we used a
data panel model with common coefficients to emphasize more important factor in economic crisis in order to
know elements where governments have to act to surpass <strong>the</strong> crisis phenomena.
Keywords: growth economic, intellectual capital, panel data international models, divergent factor
1. Introduction
In a knowledge society, competitive advantage shifts from material and financial assets to intangible
assets. This is due to several factors, including human capital, research, development and innovation
(R&D&I), quality and <strong>the</strong> environment. These factors have become influential in recent times where
economic and social growths are concerned. In short, hidden wealth or intellectual capital is becoming
one <strong>of</strong> <strong>the</strong> main driving forces behind growth.
Hence, measures related to GDP that take into account negative externalities and <strong>the</strong> impact <strong>of</strong>
economic activity on <strong>the</strong> environment scholars have been proposed in order to obtain a more
comprehensive measure that is directly related to social wellbeing. Some examples worth highlighting
include <strong>the</strong> Index <strong>of</strong> Sustainable Economic Welfare (ISEW) proposed by Daly and Cobb (1989) and
<strong>the</strong> research by Chen and Dahlman (2005), Corrado et al. (2006), Montañez (2008) and Pulido (2008,
2009), which studies intangibles and <strong>the</strong>ir contribution to economic development.
All <strong>of</strong> <strong>the</strong> above indicate <strong>the</strong> need to establish a measure <strong>of</strong> intellectual capital in order to gain insight
into <strong>the</strong> relative advantage that some countries or regions have over o<strong>the</strong>rs in order to develop
policies to guide future economic development. For this reason, this paper analyses <strong>the</strong> relationship
between intellectual capital and economic growth, considering aspects that are beyond <strong>the</strong> scope <strong>of</strong>
GDP. In this sense, intellectual capital can usually be divided into technological or structural capital
and human capital (also is divided into human, relational and structural capitals). These components
make it possible to elaborate and estimate an indicator <strong>of</strong> intellectual capital for a territory, capable <strong>of</strong>
analysing <strong>the</strong> progress made in terms <strong>of</strong> <strong>the</strong> society <strong>of</strong> information and comparing it.
We analyses a panel data in 2000 years for an international scene. We study dynamic relationship
between GDP and intangibles components or hidden wealth with a macroeconometric model.
Specifically, it is a panel data model with fixed effects, where is estimated <strong>the</strong> relationship between
GDP and proxies variables <strong>of</strong> hidden wealth. These are generated as syn<strong>the</strong>sis <strong>of</strong> variables reduced
by principal component analysis (PCA) techniques. The method used to develop such indices is
inspired by <strong>the</strong> intangible accounting management models implemented in enterprises by Edvinsson
and Malone (1997), Kaplan and Norton (1997), and López y Nevado (2002).
The contribution <strong>of</strong> this paper is to show that it is possible to measure <strong>the</strong> development and
management <strong>of</strong> knowledge in a country using a monetary measure <strong>of</strong> intellectual capital. Using this
new proposal as a basis, we established following hypo<strong>the</strong>sis: knowledge acts as a divergent factor <strong>of</strong>
wealth, that is, that rich countries are richer in knowledge and manage it more efficiently than poor
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Víctor Raúl López Ruiz et al.
countries. Thus, in a global economy, intellectual capital circulates in opposite sense to development,
that is, from poor countries to rich countries.
2. Methods to measure national intellectual capital
First <strong>of</strong> all, it is necessary to establish <strong>the</strong> concept that we are going to study: intellectual capital <strong>of</strong>
nations. Bradley (1997) considers that <strong>the</strong> country‟s intellectual capital is its ability to transform
knowledge and intangible resources into wealth. Edvinsson and Stenfelt (1999) perceive intellectual
capital as <strong>the</strong> value <strong>of</strong> ideas generated by <strong>the</strong> union between human and structural capital, which
allows knowledge to be produced and shared. According to Malhotra (2000), <strong>the</strong> definition would
involve a set <strong>of</strong> hidden assets that explain <strong>the</strong> growth <strong>of</strong> a country and <strong>the</strong> added value <strong>of</strong>
stakeholders. Therefore, this perception <strong>of</strong> intellectual capital, methodologically speaking, completes
<strong>the</strong> definition <strong>of</strong> <strong>the</strong> value <strong>of</strong> a country‟s production. That is, its value would coincide with <strong>the</strong> value <strong>of</strong>
hidden or immaterial production stemming from factors such as <strong>the</strong> development <strong>of</strong> its inhabitants,
quality <strong>of</strong> life and wellbeing and technical progress. This definition <strong>of</strong> intellectual capital will be used in
this research considering aspects o<strong>the</strong>r than <strong>the</strong> simple value <strong>of</strong> production.
In <strong>the</strong> literature, <strong>the</strong> approaches to and indicators <strong>of</strong> intellectual or intangible capital at
macroeconomic level can be divided into two large groups:
1) Models specifically aimed at measuring and managing <strong>the</strong> intellectual capital <strong>of</strong> nations or
regions that have been adapted from company management systems, particularly those based on
<strong>the</strong> Skandia Navigator. Among <strong>the</strong>se, it is worth highlighting Rembe (1999) for Sweden, López et
al. (2008) for <strong>the</strong> <strong>European</strong> Union 25 (regional level), Lin and Edvinsson (2008) for 40 countries,
or Schiuma et al. (2008) for Italian regions.
2) Competitiveness analysis and o<strong>the</strong>r studies related to establishing national or regional
indicators. In this case, information systems use <strong>the</strong> aggregate level directly as a starting point.
Examples include „<strong>European</strong> Scoreboard‟ by <strong>the</strong> <strong>European</strong> Commission from 2000, Atkinson
(2002) for <strong>the</strong> United States, Chen and Dahlman (2005) assesses <strong>the</strong> effects <strong>of</strong> knowledge on
economic growth using an array <strong>of</strong> indicators that span 92 countries for <strong>the</strong> period 1960 to 2000,
<strong>the</strong> research by World Bank (2006) on 120 countries, or Ståhle and Bounfour (2008) analysis that
includes data for 51 countries for <strong>the</strong> period 2000 to 2005.
After studying <strong>the</strong> various approaches, we decided to use a method that involved transferring <strong>the</strong>
classification <strong>of</strong> intangible assets, used by Nevado and López (2002) and López and Nevado (2006),
in models at company level to macroeconomic level, making any necessary adjustments. We <strong>the</strong>reby
establish some visible intangible assets and some hidden ones. The latter are <strong>the</strong> basis for <strong>the</strong> main
models, such as <strong>the</strong> Skandia Navigator, Integrated Analysis and Balanced Scorecard, in <strong>the</strong> territories
in order: to obtain tools for managing intellectual capital and not confine <strong>the</strong> research to merely
measurement and evaluation.
In this approach, national intellectual capital is defined as an immaterial element that generates future
benefits and which can be controlled by <strong>the</strong> State. However, within <strong>the</strong> current framework <strong>of</strong> national
accounts, <strong>the</strong>re are few items that can be defined as such, except for education and innovation and
development costs. These expenses are an ongoing reference to <strong>the</strong> intellectual capital <strong>of</strong> a country
(traditional analysis). However, even when <strong>the</strong>ir definition is changed to investment, <strong>the</strong>y remain
insufficient, as a series <strong>of</strong> capitals that would complete <strong>the</strong> picture are omitted. It is <strong>the</strong>se
uncontrollable, non separable capitals that must be studied fur<strong>the</strong>r in order to measure <strong>the</strong>m and, in
turn, exert control over <strong>the</strong>m, consider <strong>the</strong>ir relationship to GDP, <strong>the</strong> potential wealth <strong>the</strong>y entail, as
well as ascertaining whe<strong>the</strong>r or not this new wealth is more disperse than <strong>the</strong> wealth measured
traditionally by means <strong>of</strong> production value.
Therefore, <strong>the</strong> intellectual capital <strong>of</strong> a country is made up <strong>of</strong> visible, separable and controllable assets,
in <strong>the</strong> sense that <strong>the</strong> government is able to control <strong>the</strong>m in some way (for example, by means <strong>of</strong>
Budget) and hidden, non separable and uncontrollable assets, which have an enormous potential for
future wealth, but which <strong>the</strong> government is unable to control entirely. The structures for measuring
intangible capitals are summarised in Figure 1, which includes several capitals in each group. While
<strong>the</strong> majority <strong>of</strong> research carried out at macroeconomic level to date focuses on <strong>the</strong> use <strong>of</strong> visible
capitals, in this case emphasis is placed on hidden capitals, including human, structural and non
explicit capitals.
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Víctor Raúl López Ruiz et al.
The main difference is that hidden asset (intellectual capital) approach cannot be observed directly,
using indicators instead to estimate <strong>the</strong> generators <strong>of</strong> a country‟s wealth. For example, <strong>the</strong> traditional
approach uses expenditure on education per inhabitant as a visible asset for human talent. However,
in <strong>the</strong> hidden asset approach talent is <strong>the</strong> result <strong>of</strong> a combination <strong>of</strong> indicators <strong>of</strong> human resources,
using expenditure on education per inhabitant, but also <strong>the</strong> activity and literacy rates. The result
determines both investment (accountable expenditure) and how well it has been used or level <strong>of</strong>
efficiency and combination. The main limitation <strong>of</strong> this approach is <strong>the</strong> difficulty involved in obtaining
all <strong>the</strong> necessary information, a problem that is overcome at microeconomic level by conducting
surveys. The advantage is that <strong>the</strong> results, despite <strong>the</strong> aforementioned shortfall, is more relevant and
more accurately represents <strong>the</strong> asset being measured. Finally, this approach allows measuring and
valuating national intellectual capital, in agree with Andriessen (2004), who demonstrates that
measurement is not enough, that valuation is paramount in leveraging intangibles for strategic benefit.
I
N
T
A
N
G
I
B
L
E
C
A
P
I
T
A
L
S
Visible:
separable and
controllable
Hidden:
non separable
and
uncontrollable
Education expenditure / innabitant
Investment in R&D / GDP
Human: Knowledge, skill,
development.
Structural
Process
Relational
Image
Innovation and Development
Social and Environmental
Non explicit (unavailable,
synergies,…)
Figure 1: Structures for measuring intangible capitals (source: own elaboration)
TRADITIONAL
APPROACH
INTELLECTUAL
CAPITAL
APPROACH
3. A panel data model to estimate national intellectual capital or hidden wealth
Using this conceptual framework as a basis, an integrated ad hoc model is designed on a global
scale. This is based on models <strong>of</strong> firm intellectual capital management and <strong>the</strong> competitiveness
analysis, under <strong>the</strong> <strong>the</strong>oretical and conceptual view <strong>of</strong> national intangible capital as an „invisible value‟
<strong>of</strong> that space. Finally, for this transfer, besides <strong>the</strong> model, a method is incorporated to determine <strong>the</strong>
national intellectual capital. Changes in reporting systems made in <strong>the</strong> microeconomic approach must
undoubtedly be transferred to <strong>the</strong> reporting systems for national accounts, as regards intellectual
capital.
In accordance with considerations made in o<strong>the</strong>r models, in <strong>the</strong> first place, it is worth establishing <strong>the</strong>
vision <strong>of</strong> a country and its activities, projects and intangible capitals as a whole by means <strong>of</strong> a
National Index <strong>of</strong> Intellectual Capital (NIIC). In order to do so, it is necessary to identify <strong>the</strong> indicator
for each and allocate <strong>the</strong>m to <strong>the</strong> capitals already defined.
Following this method, two large groups <strong>of</strong> capital are identified: human and structural or non human
capitals 1 . Structural capital, due its very nature, will undergo <strong>the</strong> most changes in <strong>the</strong> case <strong>of</strong> nations.
Apart from <strong>the</strong>se two groups, a set <strong>of</strong> capitals that are not contemplated due to identification errors,
lack <strong>of</strong> information or not being included among those listed above, are added under <strong>the</strong> category <strong>of</strong>
non explicit capitals (equation 1).
1 We don‟t use traditional division in three components: human, relational and structural. We think that relational or trade is a
part <strong>of</strong> structural capital, according our definition. See more in López and Nevado (2002, 2006).
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Víctor Raúl López Ruiz et al.
NIIC = Human + Structural + Non Explicit (1)
Human capital encompasses knowledge, skills and personal development towards achieving
objectives (equation 2). It also includes cultural values, national labour market conditions and
resource inflows from workers abroad.
Human = Knowledge + Skill + Development (2)
On <strong>the</strong> o<strong>the</strong>r hand, structural capital covers several intangibles related to <strong>the</strong> socio-economic
framework <strong>of</strong> a country, namely <strong>the</strong> non human structure that enables a country generate future
benefits: business structure, burocracy, image, international market share, technology, innovation and
sustainability. This capital has been divided into:
Process capital, which focuses generally on a country‟s private sector structure. More specifically,
it measures information and management systems, bureaucracy and also organisational
structures.
Relational or trade capital, which captures <strong>the</strong> quality <strong>of</strong> <strong>the</strong> balance <strong>of</strong> trade.
Marketing or image capital, which contemplates a country‟s domestic and foreign image and
international relations.
Research, development and innovation capital (R&D&i), which explicitly measures innovation,
research and development possibilities through investment and how efficiently existing resources
are exploited.
Social and environmental capital (SE), which is determined by <strong>the</strong> social commitment <strong>of</strong> <strong>the</strong> social
welfare state in relation to <strong>the</strong> quality <strong>of</strong> life <strong>of</strong> its inhabitants, toge<strong>the</strong>r with action related to <strong>the</strong>
environment and sustainable development.
Structural = Processes + Customer + Image + R&D&i + SE (3)
Finally, non explicit capital, as explained above, completes <strong>the</strong> picture provided by integrated model,
assuming variable estimation errors, omission <strong>of</strong> relationships, synergies and/or intangible capitals
and data unavailability. This variable is, never<strong>the</strong>less, non observable and becomes less relevant
when rest <strong>of</strong> capitals is explained adequately. Next stage <strong>of</strong> this research is to establish indicators
scorecard (Table 1) in order to be able to determine intangibles included in equations 2 and 3. In this
sense, following intellectual capital approach, first column defines <strong>the</strong> intangibles to be estimated as
generators <strong>of</strong> long term benefits. Then, we justify each <strong>of</strong> <strong>the</strong>se generators or intangibles in
<strong>the</strong>oretical terms. Finally, overcoming <strong>the</strong> main problem related to obtaining information, two types <strong>of</strong>
indicators are used: absolute indicators (AI), in monetary terms, and efficiency indicators (EI), in a
percentage scale. In order to obtain <strong>the</strong> latter, when <strong>the</strong> variable does not have a percentage scale,
variables have been rescaled assigning 100 to <strong>the</strong> highest value and 0 to <strong>the</strong> lowest. As a result, all
<strong>the</strong> variables generated by <strong>the</strong> indicators have values ranging from 0 to 100 (minimum and
maximum). That is, <strong>the</strong> maximum must coincide with <strong>the</strong> highest score obtained by <strong>the</strong> country with
<strong>the</strong> highest value in <strong>the</strong> sample for <strong>the</strong> year in question, whereas <strong>the</strong> minimum will coincide with <strong>the</strong>
countries that record <strong>the</strong> lowest scores.
Table 1: Scorecard for national intangibles
Intangibles Theoretical justification
Knowledge
Skill
Development
Reporting and Management
systems
Indicators
Absolute (AI) Efficiency (EI)
Human Capital
Education expenditure
Qualifications
Capital formation
Internal human capital
(UNESCO)
Literacy index (adjusted gross
school enrolment) (UNESCO)
Motivation and
employability
Non residential wage
mass and remittances.
Activity rate (UN)
Excess employability
Human capital
exported Adjusted migration (ONU)
Process Capital
System/structure quality Capitalisation/Market
value over resident
190
Adjusted firm start-up time
GDP Ranking

Organisational structure Level <strong>of</strong> management:
technology
Intangibles Theoretical justification
Client Portfolio
Image and International
Institutional Relations
Innovation, Research and
Development
Social and Environmental
Responsibility
Víctor Raúl López Ruiz et al.
firms as <strong>of</strong> 31st
December
Relational or Trade Capital
Product brand name
quality
Line index: adjusted mobile and
land lines/inhabitant
Indicators
Internet users per 100
inhabitants
Absolute (AI) Efficiency (EI)
Trade balance in goods
and services
Marketing or Image Capital
Internal image
External image
Foreign direct
investment
Research, Development and Innovation Capital
Level <strong>of</strong> innovation and
development Investment in R&D&i
Technological level
(UNESCO)
Social and Enviornmental Capital
Environment
Sustainability
Quality <strong>of</strong> life, welfare
society
Health expenditure
(WHO)
Source: own elaboration. Note: Sources in brackets if not WBG.
High Technology Export Index
1-Development aid index
GDP Ranking
Life Expectancy Index
Travel and Tourism
Infrastructure Index (WEF)
Line Index: adjusted mobile
and land lines/inhabitant
Internet users per 100
inhabitants
CO2 emissions per capita
Hectares <strong>of</strong> green
areas/habitant
Life Expectancy Index
Access to health system in
rural areas
Access to water
The latter filter book expenditure included by <strong>the</strong> national government in <strong>the</strong> budget or its market
value, according to <strong>the</strong> objective efficiency recorded and equation 4 below. Expense filtering was
inspired by <strong>the</strong> process presented for Skandia Navigator by Edvinsson and Malone (1997), later
modified in Integrated Analysis method by López and Nevado (2006).
C
m
c 1
AI
c
EI c
(4)
Where human or structural capitals (C) are estimated by one or more absolute indicators m, filtered
by k efficiency indicators and syn<strong>the</strong>sized into only one indicator, weighted in accordance with a
subjective weighting w. The procedure followed to allocate weights to efficiency indicators is based on
<strong>the</strong> development <strong>of</strong> a principal component analysis (PCA) that makes it possible to assign weights to
each indicator highly objectively. More specifically, bearing in mind that it is impossible to directly
assign weights to each efficiency indicator, we proceeded to transform <strong>the</strong>m into <strong>the</strong> same number <strong>of</strong>
principal components (PC) as indicators available:
PC
ic
k
i 1
u x
i
i
Where ui are <strong>the</strong> characteristic vectors <strong>of</strong> each principal component and xi <strong>the</strong> variables used to make
<strong>the</strong> efficiency indicators. Once <strong>the</strong>se components have been obtained, we proceeded to build one
indicator <strong>of</strong> efficiency by weighting each component in accordance with <strong>the</strong> percentage <strong>of</strong> variance
retained by each.
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EI
c
k
i 1
w PC
i
ic
Víctor Raúl López Ruiz et al.
Where w is <strong>the</strong> percentage <strong>of</strong> variance retained by each component (a total <strong>of</strong> k, <strong>the</strong> same number as
variables). Hence, equation 4 would be transformed into:
C
c
m
1
AI
c
k
i 1
w
i PCic
As a result, following a similar procedure to that proposed by Alfaro and López (2008), we can obtain
efficiency indicators, to filter <strong>the</strong> absolute indicators, which are far from being as subjective as <strong>the</strong>
person performing <strong>the</strong> analysis due to being based on a widely used technique in economics, namely
principal component analysis.
The need for scores from absolute indicators at this level is a problem that if solved would improve <strong>the</strong>
estimation. As a result <strong>of</strong> <strong>the</strong>se limitations, a scorecard is designed, which includes an open system <strong>of</strong>
variables to estimate intangible capitals on a national scale. Never<strong>the</strong>less, <strong>the</strong> proposed method
always allows efficiency or relative indexes to be comparable, whereas absolute indexes and <strong>the</strong> final
values <strong>of</strong> intangibles may only be compared in relative terms (GDP per capita). In this sense, we have
estimated <strong>the</strong> national intellectual capital per capita at constant prices to analyse <strong>the</strong> relationships
with real economic growth and compare <strong>the</strong> evolution in years considered.
4. National intellectual capital components
Using <strong>the</strong> information from <strong>the</strong> World Bank (2010) as our main source, we proceeded to apply <strong>the</strong>
proposed model to 72 countries with information referring to 2000, 2005 and 2008 except in some
cases where <strong>the</strong> most recent data available were used. The countries were chosen depending on <strong>the</strong>
availability <strong>of</strong> information for <strong>the</strong> majority <strong>of</strong> variables considered, as <strong>the</strong>re were not enough data from
<strong>the</strong> sources mentioned to be able add more countries. We must remember that in order to syn<strong>the</strong>size
<strong>the</strong> efficiency indicators under consideration into one indicator for each kind <strong>of</strong> capital, weightings
have been allocated according to <strong>the</strong> variance weight <strong>of</strong> <strong>the</strong>ir principal components. Moreover we
have calculated a monetary value <strong>of</strong> each component <strong>of</strong> <strong>the</strong> national intellectual capital. Human and
Structural capital (as sum <strong>of</strong> process, relational, marketing, R&D&I and social capitals) for each
countries considered in this paper are showed in <strong>the</strong> table 2.
Table 2: Human and structural capital per capita at constant dollars
Human
Structural
Capital
Capital
2000 2005 2008 2000 2005 2008
Average 567.590 797.804 937.767 10973.439 13793.110 11089.892
Log (Std. Deviation) 2,848 3,006 3,074 4,495 4,549 4,500
Variation Coefficient 1.243 1.271 1.264 2.850 2.566 2.854
%GDP 5,33 5,57 5,48 103,06 96,38 64,81
Source: Own elaboration. Results detailed by country in appendix.
The results show that <strong>the</strong> difference between <strong>the</strong> rich and poor countries is high when we consider
<strong>the</strong> structural capital because <strong>the</strong> variation coefficient that measures <strong>the</strong> dispersion in <strong>the</strong> date is
bigger in this capital. This situation can be seen also using <strong>the</strong> log <strong>of</strong> standard deviation.
Moreover if we analyse <strong>the</strong> values <strong>of</strong> this coefficient we can see that in <strong>the</strong> human capital <strong>the</strong>
variations in this three years are smaller. Therefore, in structural capital we can advance <strong>the</strong>
economic crisis because <strong>the</strong> difference between rich and poor countries reduces in <strong>the</strong> expansive
period between 2000 and 2005 and increase in <strong>the</strong> beginning <strong>of</strong> crisis in 2008. This situation can be
detected also in <strong>the</strong> average value with a continuous increase in human capital in years considered
but with two different situations in <strong>the</strong> structural capital: an increase between 2000 and 2005 and a
decrease in 2005-2008.
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Víctor Raúl López Ruiz et al.
If we consider <strong>the</strong> importance <strong>of</strong> structural capital in intellectual capital, <strong>the</strong>n it is easy assuring that
intellectual capital will have a similar behaviour than structural capital. Moreover, <strong>the</strong> results show that
relevance <strong>of</strong> this capital, in terms <strong>of</strong> GDP, have been reduced in 32.7% between 2005 and 2008.
Whereas human capital is stable, in terms <strong>of</strong> GDP. The structural capital had a strong fall in 2008
what allows considering this factor as one <strong>of</strong> <strong>the</strong> most important elements <strong>of</strong> <strong>the</strong> economic crisis
beginning in 2008.
5. National intellectual capital and gross domestic product
One interesting aspect in <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> national intellectual capital is to consider relationship with
Gross Domestic Product (GDP). Several studies consider <strong>the</strong> existence <strong>of</strong> a positive relationship
between <strong>the</strong>se measures but we are going to verify this affirmation and to analyse <strong>the</strong> evolution <strong>of</strong>
<strong>the</strong>se relationships in <strong>the</strong> years considered. Table 3 shows <strong>the</strong> values <strong>of</strong> <strong>the</strong> intellectual capital and
GDP per capita at constant dollars. Moreover, in <strong>the</strong> appendix appear <strong>the</strong> detailed results by country
in order to compare.
Table 3: Intellectual capital and GDP per capita at constant dollars
Intellectual
Capital
GDP
2000 2005 2008 2000 2005 2008
Average 11,541.031 14,590.920 12,027.659 10,647.750 14,310.734 17,111.416
% GDP 108.389 101.958 70.290
Correlation with GDP 0.675 0.737 0.670
Beta Convergence --
-0.068
(-2.583)
Source: Own elaboration. (NS: Non Significant).
-0.156
(-5.456)
--
0.034
NS
-0.001
NS
The results confirm <strong>the</strong> existence <strong>of</strong> a positive relationship between <strong>the</strong> traditional measure used in
economic (GDP) and <strong>the</strong> measure proposed in this paper that considers <strong>the</strong> non visible wealth
(intellectual capital). Fur<strong>the</strong>rmore, in <strong>the</strong> expansive period <strong>the</strong> correlation between this measurements
increase in a 9.2% but <strong>the</strong> crisis period (2008) had made that <strong>the</strong> correlation between <strong>the</strong>se measures
is reduced at <strong>the</strong> same levels <strong>of</strong> 2000.
When we analyse <strong>the</strong> average values <strong>of</strong> <strong>the</strong>se measurements in <strong>the</strong> years considered we can see
that intellectual capital was capable to detect <strong>the</strong> existence <strong>of</strong> <strong>the</strong> crisis period before that GDP. The
average in national intellectual capital shows a reduction in 2008 whereas GDP increases in all years
considered.
Fur<strong>the</strong>rmore, as we anticipated in <strong>the</strong> previous section, <strong>the</strong> intellectual capital is identified as a
divergence for <strong>the</strong> economic growth. In order to verify this we have realised a beta convergence
analysis whose results appear in table 3. These show <strong>the</strong> absence <strong>of</strong> convergence in terms <strong>of</strong> GDP
for periods 2000-2005 and 2000-2008 since <strong>the</strong> equations show non significant convergence
coefficients along with very low determination coefficients. On <strong>the</strong> contrary, in terms <strong>of</strong> intellectual
capital appear values for <strong>the</strong> beta coefficients negatives and significant, being more important for
period 2000-2008. Therefore, <strong>the</strong> intellectual capital are a divergent factor in <strong>the</strong> economic growth <strong>of</strong>
<strong>the</strong> decade, that is to say, exist more difference between <strong>the</strong> poor and rich countries when
considering this measurement.
Finally, we have made a study on <strong>the</strong> relationship between GDP and <strong>the</strong> different components from
intellectual capital to determine factors with greater relevance in <strong>the</strong> economic growth.
We have used a data panel model with common coefficients whose results appear in table 4. In
regression 1, <strong>the</strong> explanatory variable is human capital showing like more important factor in terms <strong>of</strong>
elasticity <strong>the</strong> qualification <strong>of</strong> <strong>the</strong> inhabitants <strong>of</strong> <strong>the</strong> country. In regression 2, <strong>the</strong> structural components
like explanatory factor <strong>of</strong> <strong>the</strong> growth are introduced. The more relevant results in terms <strong>of</strong> elasticity
are for; Social and Environmental and Research, Development and Innovation capitals. Moreover, in
<strong>the</strong> regression 3 two variables are included as explanatory, capital structural and human, with all <strong>of</strong>
<strong>the</strong>se components. The results are significant for both, although, are more relevant in terms <strong>of</strong>
elasticity for <strong>the</strong> human capital.
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Víctor Raúl López Ruiz et al.
Table 4: Panel data relationships between intellectual capital components and GDP (per capita at
constant dollars)
Components
Qualifications
Motivation and
employability
Excess employability
Process
Relational
External and internal
Image
Research,
Development and
Innovation
Social and
Environmental
R 2
Regression 1:Human
Capital
Coefficient
(Elasticity)
15.54272
(0.804)
18.44895
(0.056)
T-Stat
49.15132
12.60838
Regression 2: Structural
Capital
Coefficient
(Elasticity)
0.083239
(0.047)
1.670248
(0.062)
0.050209
(0.0096)
9.360531
(0.114)
T-Stat
3.925446
5.644141
2.247112
3.800079
Regression 3: Intellectual
Capital
Coefficient
(Elasticity)
14.67855
(0.803)
0.056509
(0.048)
14.22958
(0.555)
14.34199
0.936433 0.937913 0.943563
Source: Own elaboration. Pooled Least Squares. Total panel observations: 216 (3x72).
6. Conclusions
T-Stat
43.84944
5.543384
GDP has traditionally been used to measure national economic development. However, in <strong>the</strong> current
knowledge economy, o<strong>the</strong>r factors have a great influence on growth and do not appear to be captured
by GDP. In this research, we have made an estimation <strong>of</strong> <strong>the</strong> national intellectual capital in monetary
terms. It allows comparing results obtained for different years. Moreover we have estimate <strong>the</strong> value
<strong>of</strong> this capital for each main component <strong>of</strong> it: human and structural capital.
In valuation <strong>of</strong> national intellectual capital we have used an objective weighting (applying a princiapal
componenet analysis) in <strong>the</strong> elaboration <strong>of</strong> efficiency indexes for each component that allow to obtain
unbiased efficiency indicators.
The more important results can be summarizing as:
First <strong>of</strong> all, national intellectual capital is a divergence factor in terms <strong>of</strong> economic growth in <strong>the</strong>
2000 decade, <strong>the</strong>refore if we use this measure <strong>of</strong> wealth in a nation <strong>the</strong> difference between
countries will be higher.
Second, <strong>the</strong> intellectual capital allows anticipating <strong>the</strong> economic crisis beginning in 2000. In this
sense, we can emphasize <strong>the</strong> important <strong>of</strong> <strong>the</strong> structural capital in <strong>the</strong> economic situation in 2008.
It shows that governments have to make more attacks in <strong>the</strong>se aspects.
Finally, when we analyses each components <strong>of</strong> <strong>the</strong>se capitals we can obtain that <strong>the</strong> more
relevant factors in <strong>the</strong> economic growth are <strong>the</strong> human capital and within <strong>the</strong>m <strong>the</strong> qualification <strong>of</strong>
its inhabitants. In structural capital are Social and Environmental (SE) and Research,
Development and Innovation (R&D&I) more important factors.
7. Appendix 1
Table 2: Details: Human and structural capital per capita at constant dollars
Country
Human
Structural
Capital
Capital
2000 2005 2008 2000 2005 2008
Argentina 353.879 105.513 156.935 1733.046 662.123 447.331
Armenia 17.785 43.510 95.607 31.632 58.841 134.982
Australia 1139.616 1439.686 1764.437 12662.248 21984.754 16919.565
Austria 1388.202 1952.066 2400.163 4731.839 19475.706 10314.690
Belgium 1422.765 2101.469 2588.146 25175.212 19687.283 15744.644
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Víctor Raúl López Ruiz et al.
Country
Human
Capital
Structural
Capital
Bolivia 55.633 55.382 67.072 98.578 102.225 112.301
Brazil 149.202 135.745 233.260 396.342 660.161 754.862
Bulgaria 53.860 131.148 167.060 113.406 555.115 835.766
Chile 175.121 180.304 217.058 1698.798 3529.334 2659.771
China 23.810 43.693 78.320 149.497 269.172 709.930
Colombia 85.300 102.041 131.293 163.485 442.796 634.897
Costa Rica 178.032 155.555 161.299 432.660 256.936 314.814
Croatia 172.212 385.762 485.560 535.561 1727.491 3247.862
Cyprus 660.678 1208.693 1635.588 3290.089 5192.538 6503.323
Czech Republic 207.250 453.787 716.495 807.876 3044.522 3544.037
Denmark 2526.224 3612.241 4313.870 21286.094 27039.296 18072.733
Egypt. Arab Rep. 61.088 39.628 40.648 140.121 292.728 248.507
El Salvador 66.154 96.088 124.369 166.547 279.873 314.125
Estonia 218.587 427.084 576.609 744.025 2502.196 1438.515
Finland 1398.093 2281.335 2778.712 40453.530 31429.210 22373.884
France 1290.721 1843.896 2238.737 14401.738 18494.134 15297.509
Georgia 15.552 28.482 56.706 35.454 103.309 172.111
Germany 1043.883 1475.120 1850.213 11959.283 12982.296 12216.150
Greece 467.736 766.948 1022.626 5204.691 6669.898 4624.862
Hong Kong SAR. China 927.400 1185.369 1083.071 73318.562 92493.744 147111.604
Hungary 224.807 461.658 542.630 664.332 1936.244 3239.990
Iceland 1850.950 3417.784 2501.873 13922.647 65407.779 10542.946
India 14.187 16.551 18.566 34.779 104.154 121.540
Indonesia 17.037 23.025 33.786 63.938 79.147 69.969
Ireland 1121.384 1935.715 2496.013 21185.666 16033.556 9931.877
Israel 1358.669 1149.136 1635.493 7874.165 10352.475 10661.158
Italy 843.610 1182.274 1345.586 9270.297 9141.751 5648.678
Jamaica 182.695 143.578 156.178 575.185 1712.848 691.703
Japan 1351.885 1347.354 1460.808 17964.277 27722.913 20622.005
Kazakhstan 38.357 47.601 76.870 120.466 305.298 748.409
Korea. Rep. 423.670 623.181 666.526 2689.114 8879.509 5451.126
Kyrgyz Republic 8.824 20.573 39.289 6.630 17.760 31.534
Latvia 167.644 276.159 382.697 240.422 779.651 632.063
Lithuania 192.915 348.674 490.241 282.221 1703.628 966.405
Luxembourg 2982.872 3583.919 5175.282 237809.660 265558.741 216250.095
Malaysia 200.269 297.259 220.350 2556.661 4225.216 3612.219
Mauritius 144.333 166.864 156.271 542.493 699.834 810.942
Mexico 272.287 273.565 279.917 595.206 778.196 646.497
Mongolia 21.614 27.155 36.396 23.479 23.523 55.128
Morocco 52.390 94.813 123.244 127.719 399.968 771.511
Ne<strong>the</strong>rlands 1218.734 1905.737 2429.637 31437.134 27978.451 17351.743
New Zealand 920.267 1606.195 1395.906 3805.844 7328.451 4486.284
Norway 2483.049 3921.874 4452.013 17667.880 36965.611 25447.471
Pakistan 5.177 7.784 10.477 19.086 73.855 34.613
Panama 176.592 157.110 202.402 597.068 1069.091 1191.136
Paraguay 67.347 29.807 45.457 78.150 39.633 45.539
Peru 70.412 72.255 101.777 129.798 474.370 674.102
Poland 224.529 394.288 568.930 451.636 1415.589 1450.004
Portugal 727.484 914.703 1083.130 3604.436 4020.269 3981.966
Romania 41.781 60.075 109.519 65.333 240.185 230.173
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Víctor Raúl López Ruiz et al.
Country
Human
Capital
Structural
Capital
Russian Federation 47.798 81.736 95.589 328.912 1107.104 702.027
Saudi Arabia 445.789 515.165 572.756 1853.639 9861.696 4365.164
Slovak Republic 189.251 352.260 500.276 369.332 916.070 1187.558
Slovenia 617.440 769.641 957.701 1040.958 2514.652 3531.143
South Africa 166.471 200.051 169.124 1549.542 3706.001 2079.376
Spain 668.681 1046.141 1170.660 6421.450 11623.968 9945.127
Sweden 2006.794 2637.036 2971.707 30702.241 35517.204 23688.319
Switzerland 1830.449 2789.632 3191.565 84242.221 90241.228 78937.427
Thailand 89.724 91.177 133.225 300.182 740.829 627.232
Tunisia 135.545 184.998 226.279 173.607 212.139 370.038
Turkey 91.878 59.981 63.840 435.021 395.866 251.383
Uganda 5.860 10.573 11.391 12.881 9.695 12.317
Ukraine 26.526 60.124 63.050 46.735 177.019 121.675
United Kingdom 1166.591 1859.523 1971.078 31465.112 34408.884 17895.123
United States 1701.137 1922.995 2052.759 36572.206 35979.674 23223.265
Uruguay 167.504 99.283 142.950 420.173 266.035 367.825
Zambia 4.457 4.332 4.177 17.391 22.440 19.652
Source: own elaboration
Table 3: Details: Intellectual capital and GDP per capita at constant dollars
Country
Intellectual
Capital
GDP
2000 2005 2008 2000 2005 2008
Argentina 2086.925 767.637 604.267 7693.923 2790.565 3169.702
Armenia 49.417 102.350 230.590 621.483 1314.768 2700.219
Australia 13801.863 23424.440 18684.002 21768.043 28600.689 35447.378
Austria 6120.041 21427.772 12714.853 23865.458 33986.964 43110.318
Belgium 26597.977 21788.752 18332.790 22623.278 32237.125 39850.401
Bolivia 154.211 157.607 179.372 1009.677 856.121 1008.173
Brazil 545.544 795.906 988.122 3701.472 2974.478 4454.318
Bulgaria 167.266 686.263 1002.826 1563.200 2834.029 4079.304
Chile 1873.920 3709.639 2876.829 4877.875 5476.447 6525.545
China 173.308 312.866 788.250 949.182 1466.170 2388.945
Colombia 248.785 544.837 766.190 2364.753 2417.571 3206.437
Costa Rica 610.692 412.491 476.113 4056.728 2891.517 3037.263
Croatia 707.773 2113.253 3733.422 4817.071 8302.336 11428.629
Cyprus 3950.767 6401.231 8138.911 11844.153 17715.254 22594.539
Czech Republic 1015.126 3498.309 4260.533 5521.189 10609.101 17032.531
Denmark 23812.318 30651.537 22386.603 29992.941 42673.512 51424.564
Egypt. Arab Rep. 201.209 332.356 289.155 1422.733 870.999 1105.033
El Salvador 232.701 375.961 438.494 2209.159 2431.338 2687.762
Estonia 962.612 2929.280 2015.125 4144.381 8410.037 11342.198
Finland 41851.623 33710.545 25152.596 23530.124 35845.284 46453.144
France 15692.459 20338.031 17536.245 22547.792 31938.276 38736.443
Georgia 51.006 131.791 228.817 644.387 1073.936 1699.635
Germany 13003.166 14457.416 14066.363 23114.233 32170.201 40315.368
Greece 5672.427 7436.846 5647.488 11500.648 18692.473 24137.733
Hong Kong SAR. China 74245.962 93679.113 148194.674 25374.515 30416.880 34584.879
Hungary 889.140 2397.902 3782.620 4689.608 8250.051 10149.182
Iceland 15773.597 68825.563 13044.819 30951.203 44372.908 33040.041
India 48.966 120.705 140.106 452.969 599.872 701.463
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Víctor Raúl López Ruiz et al.
Country
Intellectual
Capital
GDP
Indonesia 80.976 102.172 103.755 803.882 827.131 953.833
Ireland 22307.050 17969.271 12427.890 25383.856 41424.725 49461.843
Israel 9232.833 11501.612 12296.651 19836.098 18080.474 24806.650
Italy 10113.907 10324.025 6994.264 19269.022 26421.536 30898.139
Jamaica 757.879 1856.426 847.880 3479.057 2567.615 2246.339
Japan 19316.162 29070.267 22082.813 36789.220 38231.781 42322.516
Kazakhstan 158.823 352.899 825.279 1229.003 2109.759 2781.176
Korea. Rep. 3112.784 9502.691 6117.652 11346.665 15143.831 15737.602
Kyrgyz Republic 15.454 38.333 70.823 278.659 375.028 499.372
Latvia 408.067 1055.810 1014.760 3302.305 5370.178 7577.923
Lithuania 475.136 2052.301 1456.647 3267.355 6969.226 10118.935
Luxembourg 240792.532 269142.660 221425.377 46456.624 69915.262 88025.675
Malaysia 2756.930 4522.475 3832.569 4029.874 4647.290 5889.830
Mauritius 686.826 866.698 967.213 3861.039 3813.566 4477.118
Mexico 867.493 1051.761 926.413 5934.982 5331.084 5572.036
Mongolia 45.093 50.678 91.524 455.881 526.169 689.038
Morocco 180.109 494.782 894.755 1284.229 1857.187 2379.622
Ne<strong>the</strong>rlands 32655.868 29884.188 19781.381 24179.856 34094.192 43163.389
New Zealand 4726.111 8934.646 5882.190 13192.959 23680.336 21994.326
Norway 20150.929 40887.484 29899.484 37472.371 55436.229 65621.353
Pakistan 24.263 81.639 45.090 535.576 531.443 545.020
Panama 773.660 1226.201 1393.538 3938.083 4420.561 5658.135
Paraguay 145.497 69.440 90.996 1321.674 768.327 1211.878
Peru 200.210 546.625 775.879 2049.302 2510.912 3540.994
Poland 676.165 1809.877 2018.933 4454.080 7075.709 11381.036
Portugal 4331.921 4934.972 5065.095 11016.221 15019.444 18124.408
Romania 107.114 300.260 339.693 1650.966 1698.823 2459.734
Russian Federation 376.710 1188.840 797.616 1775.141 2438.190 3436.864
Saudi Arabia 2299.428 10376.861 4937.921 9128.113 9757.888 10022.451
Slovak Republic 558.582 1268.330 1687.834 5326.060 9176.892 13709.929
Slovenia 1658.398 3284.292 4488.844 9998.994 13632.169 18606.476
South Africa 1716.012 3906.051 2248.499 3019.947 3725.285 3187.302
Spain 7090.132 12670.109 11115.787 14421.941 21404.531 26073.412
Sweden 32709.035 38154.240 26660.025 27688.893 37562.845 44272.625
Switzerland 86072.670 93030.860 82128.992 34787.104 48610.520 59246.779
Thailand 389.906 832.006 760.457 1968.428 2399.283 3194.140
Tunisia 309.151 397.137 596.317 2033.071 2540.660 3063.100
Turkey 526.900 455.846 315.222 4010.972 2196.438 2471.303
Uganda 18.741 20.268 23.709 253.480 247.856 308.752
Ukraine 73.260 237.144 184.726 635.709 1019.842 1189.212
United Kingdom 32631.703 36268.407 19866.201 25089.446 33300.984 34899.793
United States 38273.343 37902.668 25276.024 34605.843 37441.400 38417.902
Uruguay 587.677 365.318 510.775 6914.363 3608.104 5053.541
Zambia 21.849 26.772 23.829 309.318 243.215 319.305
Source: own elaboration
References
Andriessen, D. (2004): Making Sense <strong>of</strong> Intellectual Capital: Designing a Method for <strong>the</strong> Valuation <strong>of</strong> Intangibles.
Elsevier Butterworth-Heinemann.
Alfaro, J. L. and López V. R. (2008): “El capital estructural tecnológico como medida de crecimiento económico
regional”, Estudios de Economía Aplicada, 26(3), 57-72.
197

Víctor Raúl López Ruiz et al.
Atkinson, R. D. (2002): “The 2002 State New Economy Index: benchmarking economic transformation in <strong>the</strong>
states”, The Progressive Policy Institute. http://www.neweconomyindex.org/states/2002/ (accessed 5
november 2010)
Bradley, K. (1997): “Intellectual capital and <strong>the</strong> new wealth <strong>of</strong> nations. Business”, Strategy Review, 8(1), 53-62.
Chen, D. H. C. and Dahlman, C. J. (2005): “The Knowledge Economy, <strong>the</strong> KAM Methodology and World Bank
Operations (October 19)”. World Bank Institute Working Paper No. 37256.
Corrado, C., Hulten, C. and Sichel, D. (2006): “Intangible capital and economic growth”, NBER Working Paper nº
11948, National Bureau <strong>of</strong> Economic Research, Cambridge, M.A.
Daly, H. and Cobb, J. (1989): For <strong>the</strong> common good, Beacon press, Boston.
Edvinsson, L. and Malone, M. S. (1997): Intellectual Capital, Harper Business, New York.
Edvinsson, L. and Stenfelt, C. (1999): “Intellectual capital <strong>of</strong> nations for future wealth creation”, Journal <strong>of</strong> Human
Resource Costing and Accounting, 4 (1), 21-33.
Kaplan, R. S. and Norton, D. P. (1997): Cuadro de mando integral, Gestión 2000, Barcelona.
Kuznets, S. (1955): “Economic Growth and Income inequality”, American Economic Review, 45 (1), 1-28.
Lin, C. YY. and Edvinsson, L. (2010): National intellectual capital: a comparison <strong>of</strong> 40 countries. NY: Springer.
Lin, C. YY. and Edvinsson, L. (2008): “National intellectual capital: comparison <strong>of</strong> <strong>the</strong> Nordic countries”, Journal
<strong>of</strong> Intellectual Capital, 9(4), 525-545.
López, V. R. and Nevado, D. (2006): Gestione y controle el valor integral de su empresa, Diaz de Santos,
Madrid.
Malhotra, Y. (2000): “Knowledge assets in <strong>the</strong> global economy: Assessment <strong>of</strong> national intellectual capital”,
Journal <strong>of</strong> Global Information Management, 8 (3), 5-15.
Montañez, M. (2008): Una aproximación a la medición del capital intangible y su contribución al crecimiento: una
aplicación al caso español. Instituto L.R. Klein, UAM, Diploma de Estudios Avanzados.
Nevado, D. and López, V. R. (2002): El capital intelectual: valoración y medición, Prentice-Hall, Madrid.
Pulido, A. (2008): “Medición del capital intangible a escala macroeconómica y su contribución al crecimiento”,
XXII Reunión Asepelt, Barcelona.
Pulido, A. (2009): “Una comparativa internacional en la medición del capital intangible de países”, Revista de
Economía Mundial, 23, 245-262.
Rembe, A. (1999): Invest in Sweden: Report 1999, Halls Offset AB, Stockholm.
Schiuma, G., Lerro, A. and Carlucci, D. (2008): “The Knoware tree and <strong>the</strong> regional intellectual capital index: an
assessment within Italy”, Journal <strong>of</strong> intellectual capital, 9(2), 283-300.
Ståhle, P. and Bounfour, A. (2008): “Understanding dynamics <strong>of</strong> intellectual capital <strong>of</strong> nations”, Journal <strong>of</strong>
intellectual capital, 9 (2), 164-177.
World Bank (2006): Where is <strong>the</strong> wealth <strong>of</strong> nations? Measuring Capital for <strong>the</strong> 21st Century. The International
Bank for Reconstruction and Development / The World Bank.
http://siteresources.worldbank.org/INTEEI/214578-1110886258964/20748034/All.pdf (accessed 5
november 2010).
World Bank (2010): World Development Indicators 2010. Washington, D.C., available at http://data.worldbank.org
(accessed 5 november 2010).
198

Academic Satisfaction as an Amplifier <strong>of</strong> <strong>the</strong>
Organizational Intellectual Capital
Maria de Lourdes Machado and Odília Gouveia
CIPES - Center for Research in Higher Education Policies, Matosinhos,
Portugal
lmachado@cipes.up.pt
odilia@cipes.up.pt
Abstract: Purpose – The academic staff can, with appropriate support, build a national and international
reputation for <strong>the</strong>mselves and <strong>the</strong> institution in <strong>the</strong> pr<strong>of</strong>essional areas, in research and in publishing. Such a
pr<strong>of</strong>ile may have an impact on <strong>the</strong> quality <strong>of</strong> a higher education institution and <strong>the</strong>refore in <strong>the</strong> organizational
intellectual capital. Moreover <strong>the</strong> performance <strong>of</strong> academic staff as teachers, researchers and managers
determines much <strong>of</strong> <strong>the</strong> student success and has an impact on student learning. We will discuss an ongoing
study on academic satisfaction and its impact as an amplifier <strong>of</strong> <strong>the</strong> organizational intellectual capital within <strong>the</strong>
Portuguese higher education institutions. Research questions: What is <strong>the</strong> impact <strong>of</strong> academic satisfaction as an
amplifier <strong>of</strong> <strong>the</strong> organizational Intellectual Capital? Does satisfaction <strong>of</strong> academics play a role in <strong>the</strong> quality <strong>of</strong>
higher education institutions? Design/methodology/approach – In terms <strong>of</strong> methodology, a quantitative and
qualitative approach is being developed for this project. Results – This ongoing study aims to answer <strong>the</strong>
research questions above in order to help Portuguese higher education institutions (HEIs) to identify <strong>the</strong>
determinants for recruitment and retention <strong>of</strong> academic staff, to attract academic talents and to assist institutions
to assess <strong>the</strong>ir competitive position. The realization <strong>of</strong> this study is providing a diverse range <strong>of</strong> information on
multiple dimensions <strong>of</strong> <strong>the</strong> faculty job in higher education, in particular dimensions <strong>of</strong> satisfaction, as well as
dimensions <strong>of</strong> <strong>the</strong> academic career and <strong>the</strong> pr<strong>of</strong>essional context in which it is exercised.
Keywords: academics, job satisfaction, intellectual capital, higher education
1. Introduction
Throughout history, academic institutions have sought to respond to <strong>the</strong> demands <strong>of</strong> endlessly
changing and evolving environmental conditions. However in <strong>the</strong> 21 st century, a number <strong>of</strong> significant
factors are changing <strong>the</strong> higher education landscape. Today, higher education institutions (HEIs) are
challenged to interpret <strong>the</strong> vital needs <strong>of</strong> contemporary society, to live in <strong>the</strong> market environment, to
be innovative, as well as to develop <strong>the</strong> internal structures to meet <strong>the</strong>ir new missions. These major
shifts are forcing HEIs to proactively be positioned to seize opportunities and confront threats in an
increasingly competitive environment.
In Europe, <strong>the</strong> three greatest challenges are expansion, diversification and massification (Sporn,
1999). Addressing <strong>the</strong>se challenges has meant finding ways to align organizational capacities with
environmental demands and opportunities (Amaral and Maassen, 2002; Sadlak, 1999). At <strong>the</strong> same
time, <strong>the</strong>re are clear signals <strong>of</strong> <strong>the</strong> influence <strong>of</strong> <strong>the</strong> market in <strong>the</strong> higher education sector (Jongbloed,
2004). As noted by Newman and Couturier (2002, 1) after researching market forces in higher
education worldwide for two years, “…<strong>the</strong> market has arrived in higher education. There is no turning
back.”
In uncertain times <strong>the</strong> academic staff is a key resource within higher education institutions and has a
major role in achieving <strong>the</strong> objectives <strong>of</strong> <strong>the</strong> institution (Noordin and Jus<strong>of</strong>f, 2009). The role <strong>of</strong> <strong>the</strong>
academic staff is crucial organizational intellectual capital. The academic pr<strong>of</strong>ession is <strong>the</strong> „productive
workforce‟ <strong>of</strong> higher education institutions, <strong>the</strong> key organizations in society serving <strong>the</strong> generation,
preservation and dissemination <strong>of</strong> knowledge. The academic pr<strong>of</strong>ession is extremely important in a
society <strong>of</strong>ten characterized as a „knowledge society‟, both in being responsible for <strong>the</strong> improvement <strong>of</strong>
systematic general knowledge and in providing its apex for many pr<strong>of</strong>essional areas (Cavalli and
Teichler, 2010).
In this context, <strong>the</strong> academic staff can, with appropriate support, build a national and international
reputation for <strong>the</strong>mselves and <strong>the</strong> institution in <strong>the</strong> pr<strong>of</strong>essional areas, in research and in publishing
(Capelleras, 2005). Such a pr<strong>of</strong>ile may have an impact on <strong>the</strong> quality <strong>of</strong> a higher education institution
and <strong>the</strong>refore in <strong>the</strong> organizational intellectual capital. Fur<strong>the</strong>rmore, <strong>the</strong> performance <strong>of</strong> academic staff
as teachers, researchers and managers determines much <strong>of</strong> <strong>the</strong> student success and has an impact
on student learning.
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Maria de Lourdes Machado and Odília Gouveia
We will discuss an ongoing study on academic satisfaction and its impact as an amplifier <strong>of</strong> <strong>the</strong>
organizational intellectual capital within <strong>the</strong> Portuguese higher education institutions. The study is
being funded by <strong>the</strong> Foundation for Science and Technology, and is being held in <strong>the</strong> Center for
Research <strong>of</strong> Higher Education Policies, in Portugal. This study will collect both quantitative and
qualitative data from both public and private higher education in Portugal.
The specific research questions are as follows:
RQ1: What is <strong>the</strong> impact <strong>of</strong> academic satisfaction as an amplifier <strong>of</strong> <strong>the</strong> organizational Intellectual
Capital?
RQ2: Does satisfaction <strong>of</strong> academics play a role in <strong>the</strong> quality <strong>of</strong> higher education institutions?
2. Conceptual foundation
2.1 Brief overview <strong>of</strong> <strong>the</strong> Portuguese higher education and academic career
To better understand <strong>the</strong> context <strong>of</strong> Portuguese higher education and <strong>the</strong> development <strong>of</strong> <strong>the</strong>
academic career a historical perspective is adopted in this study.
Higher education in Portugal is diverse and its nature had changed significantly over <strong>the</strong> past 40
years. The number and types <strong>of</strong> institutions has increased dramatically. Today, Portuguese higher
education (PHE) is organized into public and non-public higher education. Both under public and
private higher education, <strong>the</strong>re are universities, polytechnic institutes and „o<strong>the</strong>r schools‟.
Meanwhile, growth in <strong>the</strong> number <strong>of</strong> academic staff in Portuguese‟s higher education is evident. In <strong>the</strong>
90s academic staff <strong>of</strong> <strong>the</strong> public system knew a major expansion, particularly in <strong>the</strong> newborn state
polytechnic subsystem. Indeed, between 1993 and 2004, <strong>the</strong> number <strong>of</strong> pr<strong>of</strong>essors in public university
education increased by 1.3 (from 10,009 in 1993 to 12,549 in 2004). In <strong>the</strong> same period <strong>the</strong> group <strong>of</strong>
pr<strong>of</strong>essors in polytechnic institutes grew by 2, 5 (from 3110 in 1993 to 7,892 in 2004) (OCES, 2005a;
OCES, 2005b).
The weight <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essional group "Academic Staff" in 2008 is a very significant in relation to o<strong>the</strong>r
pr<strong>of</strong>essional groups, representing <strong>the</strong> majority <strong>of</strong> employees in each <strong>of</strong> <strong>the</strong> higher education
subsystems. The academic staff represents over two thirds <strong>of</strong> <strong>the</strong> total staff in <strong>the</strong> entire system.
(DGES - Direcção-Geral do Ensino Superior, 2008).
Most academic staff in higher education belongs to public institutions <strong>of</strong> higher education, is male
dominated although this statistic supremacy is decreasing; is aged between 30 and 50 years, and are
<strong>of</strong> Portuguese nationality. On <strong>the</strong> distribution <strong>of</strong> 35 380 pr<strong>of</strong>essors in higher education in 2008, it is
noted that:
70% (24,728) are in public higher education institutions, <strong>of</strong> which 41% (14,466) belong to
universities and 29% (10,262) to polytechnics;
30% (10652) are in private higher education institutions, <strong>of</strong> which 18% (6,519) belong to
universities and 12% (4133) to polytechnics.
With respect to <strong>the</strong> age structure <strong>of</strong> <strong>the</strong> academic staff, it appears that faculty is aging (<strong>the</strong> % <strong>of</strong>
pr<strong>of</strong>essors with less than 40 years decreased from 48% in 2001 to 37% in 2008). Moreover it‟s
interesting to note that female academic staff is less aged than male academic staff.
With respect to <strong>the</strong> higher degree <strong>of</strong> <strong>the</strong> academic staff, <strong>the</strong> number <strong>of</strong> pr<strong>of</strong>essors with a doctoral
degree increased from 9,465 in 2001 to 14,205 in 2008, representing an increase <strong>of</strong> 50%.
The distribution <strong>of</strong> academics inside scientific areas shows <strong>the</strong> same similarities along <strong>the</strong> years in <strong>the</strong>
period <strong>of</strong> analysis (2001- 2008). However, this hints that <strong>the</strong>re are still some differences in disciplinary
paths. In all years, <strong>the</strong> area with more pr<strong>of</strong>essors is Social Sciences, Business and Law. The scientific
areas with less pr<strong>of</strong>essors are General Programmes and Agriculture (GPEARI, 2010).
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Maria de Lourdes Machado and Odília Gouveia
2.2 Push-pull factors influencing <strong>the</strong> academic job satisfaction
Research, reveals that <strong>the</strong> concept <strong>of</strong> job satisfaction is a complex collection <strong>of</strong> variables that interact
in a myriad <strong>of</strong> ways. Moreover according to Seifert and Umbach (2008) job satisfaction is an important
factor as a predictor <strong>of</strong> intention to remain or leave <strong>the</strong> higher education sector.
There is a belief that pecuniary factors are determinant to job satisfaction. However salary alone is
rarely <strong>the</strong> most important mover in faculty decisions to leave, as defended by Caplow and McGee,
1958; Gartshore, Hibbard and Stockard, 1983; Johnsrud and Rosser, 2002; Matier, 1990; Smart,
1990; Toombs and Marlier, 1981 (all in Ambrose, Huston and Norman 2005).
Verhaegen (2005) analyzed <strong>the</strong> recruitment and retention <strong>of</strong> academic talent, as important factors for
<strong>the</strong> success and competitiveness <strong>of</strong> a business school. He indicates four principal flow drivers‟ factors
from both recruitment and retention perspective: 1) academic freedom; 2) research time; 3)
geographic location <strong>of</strong> <strong>the</strong> school and 4) opportunities for pr<strong>of</strong>essional development. The lower
important factors for faculty were institutional factors, specifically reputation <strong>of</strong> <strong>the</strong> school,
innovativeness and progressiveness <strong>of</strong> <strong>the</strong> school and international orientation. (Please see Table 1
below).
Table 1: Categories and factors used in <strong>the</strong> survey
Categories Factors
The school‟s culture and values Academic freedom
Stimulating peer community
Participation in decision-making processes
Identification with school‟s mission and strategy
Availability <strong>of</strong> resources for new initiatives
Innovativeness and progressiveness <strong>of</strong> <strong>the</strong> school
The school‟s reputation and position Reputation <strong>of</strong> <strong>the</strong> school in <strong>the</strong> academic community
Reputation <strong>of</strong> <strong>the</strong> school in <strong>the</strong> business community
Prestige/reputation <strong>of</strong> <strong>the</strong> department/discipline
Composition <strong>of</strong> <strong>the</strong> program portfolio
International orientation <strong>of</strong> <strong>the</strong> school
Partners in <strong>the</strong> school‟s network
Conditions <strong>of</strong> employment Remuneration
Career opportunities
Job security
Non-financial reward systems
Resources for pr<strong>of</strong>essional activities
Opportunities for sideline activities or additional jobs
Personal and pr<strong>of</strong>essional development Balance between work and life
Opportunities to work with people outside <strong>the</strong> school
Opportunities and facilities for family
Opportunities for personal growth and development
Opportunities for pr<strong>of</strong>essional development
Opportunities to pursue cross-disciplinary scholarship
Teaching climate Teaching time
Recognition <strong>of</strong> teaching achievements
Availability <strong>of</strong> teaching support
Availability <strong>of</strong> teaching facilities
Quality <strong>of</strong> students
Participation in executive education
Research climate Research time
Recognition <strong>of</strong> research achievements
Financial resources for research
Availability <strong>of</strong> research support
Availability <strong>of</strong> research facilities
Research climate within <strong>the</strong> school
Work environment Geographic location <strong>of</strong> <strong>the</strong> school
Necessity to speak local language
Pr<strong>of</strong>essional opportunities for partner
Campus quality
Office quality
Competency <strong>of</strong> administrative staff and support services
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Source: Verhaegen, P. (2005). Academic talent: Quo vadis? Recruitment and retention <strong>of</strong> faculty in
<strong>European</strong> business schools. Journal <strong>of</strong> Management Development, 24(9), 807-818.
These results “[...] could not only help <strong>the</strong> school in identifying its main bottlenecks in <strong>the</strong> recruitment
and retention <strong>of</strong> academic talent, but it can also help <strong>the</strong> school to assess its competitive position and
identify its unique selling points and help to design an effective pr<strong>of</strong>iling strategy” (Verhaegen, 2005,
815).
A study based on academics from 14 countries (Australia, Brazil, Chile, USA, UK, Germany, Israel,
Hong Kong, The Ne<strong>the</strong>rlands, Korea, Japan, Russia, Sweden and Mexico) (Boyer et al. 1994, in
Ssesanga and Garrett 2005) suggested that <strong>the</strong> academic satisfaction was greatly influenced by <strong>the</strong>
courses taught and <strong>the</strong>ir relationships with <strong>the</strong>ir colleagues.
The “International Study on <strong>the</strong> Academic Pr<strong>of</strong>ession” (Altbach, 1996; Enders and Teichler, 1995,
1997; all in Enders 1999) examined <strong>the</strong> academic pr<strong>of</strong>ession in four <strong>European</strong> countries (Western
Germany, <strong>the</strong> Ne<strong>the</strong>rlands, Sweden and England), Japan and <strong>the</strong> U.S. Academics criticized
negatively some areas such as <strong>the</strong> resources for <strong>the</strong>ir work and <strong>the</strong> teaching-related work load; junior
academic staff in diverse countries considered problems <strong>of</strong> job security and lack <strong>of</strong> opportunities for
career advancement.
For instance Küskü (2001) analyzed <strong>the</strong> satisfaction level <strong>of</strong> <strong>the</strong> academic staff <strong>of</strong> a state university in
Istanbul find out that <strong>the</strong> most important factors were “Pr<strong>of</strong>essional Satisfaction” and “Institutional Job
Satisfaction” followed by “Colleague Competition Level Satisfaction” and “Colleague Relations
Satisfaction”.
Clery (2002) give us information about <strong>the</strong> National Survey <strong>of</strong> Postsecondary Faculty (NSOPF), a
survey <strong>of</strong> college and university faculty members carried out by <strong>the</strong> U.S. Department <strong>of</strong> Education.
The vast majority <strong>of</strong> faculty members were satisfied with <strong>the</strong>ir jobs. The participants were most
satisfied with <strong>the</strong> autonomy <strong>the</strong>y had to decide <strong>the</strong> content <strong>of</strong> <strong>the</strong>ir own courses and least satisfied
with <strong>the</strong>ir salaries. Part-time faculty members expressed more satisfaction than <strong>the</strong>ir full-time
counterparts, appearing to be desirable <strong>the</strong> flexibility <strong>of</strong> part-time work.
Santhapparaj and Alam (2005) in <strong>the</strong>ir study in Malasia concluded that pay, promotion, working
condition and support <strong>of</strong> research had positive effect on job satisfaction and, contrary to this, fringe
benefits and support <strong>of</strong> teaching had negative effect on this satisfaction.
Ward and Sloane (2000) found three factors which influence overall job satisfaction: a) opportunities
to use <strong>the</strong>ir own initiative; b) <strong>the</strong> relationship with <strong>the</strong>ir colleagues and c) <strong>the</strong> actual work. Moreover
<strong>the</strong> authors found that <strong>the</strong> least influencing factors were promotion prospects and salary.
Stevens (2005) analyses <strong>the</strong> job satisfaction <strong>of</strong> academics using a dataset <strong>of</strong> over two thousand
academics from ten English higher education institutions states that <strong>the</strong>re are three separate set <strong>of</strong>
factors which determine <strong>the</strong> job satisfaction <strong>of</strong> academics: 1) <strong>the</strong> non-pecuniary elements <strong>of</strong> <strong>the</strong> job –
relations with <strong>the</strong> manager, being able to use <strong>the</strong>ir own initiative, <strong>the</strong> hours <strong>the</strong>y work; relations with
colleagues and physical work conditions -; 2) <strong>the</strong> pecuniary elements <strong>of</strong> <strong>the</strong> job - salary and total
earnings -; and 3) longer term prospects - promotion prospects and job security.
Moreover <strong>the</strong>re are several studies founding that job stress influences <strong>the</strong> employees‟ job satisfaction
and <strong>the</strong>ir performance (Stamps and Piedmonte, 1986; Cooper et al., 1989; Vinokur-Kaplan, 1991;
Fletcher and Payne, 1980; Landsbergis, 1988; Terry et al., 1993; Cummins, 1990; all in Ahsan,
Abdullah, Fie and Alam 2009).
However, many <strong>of</strong> <strong>the</strong> previous studies were conducted in countries such as US, Japan and some
<strong>European</strong> countries (UK, Germany, The Ne<strong>the</strong>rlands and Sweden). This study intends to explore <strong>the</strong>
factors that impact Portuguese academic careers. In so doing, we hope that we can identify <strong>the</strong>
contributing factors satisfaction or (dis)satisfaction and <strong>the</strong>refore influencing and amplifying
Intellectual capital.
2.3 Academic satisfaction and <strong>the</strong> organizational intellectual capital
Nerdrum and Erikson (2001, 127) define “intellectual capital as individuals‟ complementary capacity to
generate added value and thus create wealth”. OECD (1999, in Nerdrum and Erikson 2001: 127)
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Maria de Lourdes Machado and Odília Gouveia
defines intellectual capital as `”<strong>the</strong> economic value <strong>of</strong> two categories <strong>of</strong> intangible assets <strong>of</strong> a
company'', that is, organizational and human capital.
Higher education colleges, institutes and universities are among <strong>the</strong> oldest institutions in <strong>the</strong> world.
Throughout time, academic institutions have sought to respond to <strong>the</strong> demands <strong>of</strong> endlessly changing
and evolving environmental conditions <strong>of</strong> society (Altbach, 2004; Castells, 2001). Moreover, <strong>the</strong>
academy‟s contribution to scientific and technological advancements is premier and unparalleled in all
<strong>of</strong> recorded history (Gibbons, 1998; Guruz, 2003).
Higher education institutions represent <strong>the</strong> most meaningful symbol <strong>of</strong> intellectual, economical,
cultural and social life <strong>of</strong> <strong>the</strong> community in general. Besides, and according to Amiri et al (2010, 98-
99), “…<strong>the</strong> competitive advantage <strong>of</strong> organizations is based on <strong>the</strong> ability to exploit knowledge
resources”. Moreover, <strong>the</strong> authors stressed “Today, intellectual capital (IC) is widely recognized as
<strong>the</strong> critical source <strong>of</strong> true and sustainable competitive advantage. Knowledge is <strong>the</strong> basis <strong>of</strong> IC and is
<strong>the</strong>refore at <strong>the</strong> heart <strong>of</strong> organizational capabilities”. Thus, <strong>the</strong> intellectual capital is one <strong>of</strong> <strong>the</strong> most
important aspects <strong>of</strong> <strong>the</strong> competitiveness <strong>of</strong> an institution <strong>of</strong> higher education. Besides, Ulrich (1998,
in Nerdrum and Erikson 2001) conceptualized intellectual capital as a multiplicative function <strong>of</strong>
competence and commitment.
An important constituent group within higher education institutions is <strong>the</strong> faculty or academic staff.
The academic staff is a key resource that has a major role to continuously generate and grow
knowledge and <strong>the</strong>refore contributing to a competitive advantage <strong>of</strong> <strong>the</strong> institution. Academia is an
institution charged with <strong>the</strong> discovery and dissemination <strong>of</strong> knowledge in our society. So, it´s
important to have high quality staff, in particular, academic staff, with high intellectual capital.
Job satisfaction is part <strong>of</strong> intellectual capital as pointed out by Amiri et al. (2010, 100) “Employees‟
attitude is <strong>the</strong> s<strong>of</strong>t part <strong>of</strong> IC, including <strong>the</strong>ir motivation for work and satisfaction from work.”
According to Jones; Meadow and Sicilia (2009) higher education institutions establish strategic plans
to achieve <strong>the</strong>ir goals. Never<strong>the</strong>less, <strong>the</strong>se plans may be successful only if <strong>the</strong> needed resources are
available. One <strong>of</strong> <strong>the</strong> most valuable resources <strong>of</strong> higher education institutions are <strong>the</strong> expertise <strong>of</strong> its
faculty and staff; its intellectual capital. “Therefore, if a university effectively measures and manages
<strong>the</strong>se valuable resources, it can more effectively create and deploy strategies to achieve its goals”
(Jones, Meadow and Sicilia, 2009, 113).
In this context, this study aims to identify <strong>the</strong> determinants <strong>of</strong> satisfaction or dissatisfaction <strong>of</strong>
academic staff in Portuguese higher education institutions, in order to help higher education
institutions management to promote academic job satisfaction and, as consequence, to improve
organizational intellectual capital.
3. Methodology
This study is being conducted in both public and private Portuguese higher education institutions.
Several methodologies are being utilized to ga<strong>the</strong>r <strong>the</strong> data and information needed for this study: 1)
quantitative survey data ga<strong>the</strong>ring, 2) qualitative interview data ga<strong>the</strong>ring and 3) qualitative document
examination. The sample is <strong>the</strong> all universe <strong>of</strong> faculty members including all sub-groups (pr<strong>of</strong>essor,
researcher, part-time, full-time, etc.), and institutional type <strong>of</strong> Portuguese higher education institutions
(public-private, university-polytechnic, etc.). All quantitative data collected will be placed in a
comprehensive database reflecting a national sample <strong>of</strong> academic staff members. The database and
its subsequent analyses will be performed with <strong>the</strong> Statistical Package for <strong>the</strong> Social Sciences
(SPSS). O<strong>the</strong>r findings will yield qualitative results relating to human resources management policies,
practices and related factors affecting <strong>the</strong> development <strong>of</strong> careers.
4. Implications
This ongoing study aims to answer <strong>the</strong> research questions already referred in order to help
Portuguese higher education institutions (HEIs) and <strong>the</strong>ir leadership to identify <strong>the</strong> determinants for
recruitment and retention <strong>of</strong> academic staff, to attract academic talents and to assist institutions to
assess <strong>the</strong>ir competitive position. Fur<strong>the</strong>rmore, <strong>the</strong> realization <strong>of</strong> this study aims to provide a diverse
range <strong>of</strong> information on multiple dimensions <strong>of</strong> <strong>the</strong> faculty job in higher education, in particular
dimensions <strong>of</strong> satisfaction, as well as dimensions <strong>of</strong> <strong>the</strong> academic career and <strong>the</strong> pr<strong>of</strong>essional context
in which it is exercised. From a practical point <strong>of</strong> view, <strong>the</strong> findings from this project should heighten
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Maria de Lourdes Machado and Odília Gouveia
awareness, sensitivity and dialogue regarding <strong>the</strong> important issues that need to be addressed to
promote and maintain job satisfaction within <strong>the</strong> ranks <strong>of</strong> <strong>the</strong> academic staff. Once data have been
collected, analyzed and interpreted, it will be compiled in documents for dissemination and
distribution. Feedback will be sent to <strong>the</strong> respondents and <strong>the</strong> institutions in order <strong>the</strong>y can use results
to shape policies and change, promoting <strong>the</strong> organizational intellectual capital.
At all moments <strong>of</strong> <strong>the</strong> study, we will keep in mind that satisfaction is inextricably tied to <strong>the</strong>
organizational intellectual development (Amiri et al, 2010), in order to help higher education
institutions to promote excellence and productivity, because <strong>the</strong> concept <strong>of</strong> IC can be used as a
strategic management framework and competitive tool for institutions (Secundo, Margherita, Elia,
Passiante, 2010).
References
Ahsan, N., Abdullah, Z., Fie, D. Y. G. and Alam, S. S. (2009) A Study <strong>of</strong> Job Stress on Job Satisfaction among
University Staff in Malaysia: Empirical Study, <strong>European</strong> Journal <strong>of</strong> Social Sciences, Vol.8, No. 1, pp. 121-
131.
Altbach. P. G. (2004) Globalisation and <strong>the</strong> university: Myths and realities in an unequal world, Tertiary Education
and Management, Vol. 10, No. 1, pp. 3-25.
Amaral, A. and Maassen, P. (2002). Preface. In A. Amaral, G. Jones and B. Karseth (Eds.), Governing higher
education: National perspectives on institutional governance, Dordrecht, NE: Kluwer Academic Publishers.
Ambrose, S., Huston, T. and Norman, M. (2005) A Qualitative Method for Assessing Faculty Satisfaction,
Research in Higher Education, Vol. 46, No. 7, pp. 803-830.
Amiri, A. N.; Jandghi, G; Alvani, S. M.; Hosnavi, R. and Ramezan, M. (2010) Increasing <strong>the</strong> Intellectual Capital in
Organization: Examining <strong>the</strong> Role <strong>of</strong> Organizational Learning, <strong>European</strong> Journal <strong>of</strong> Social Sciences, Vol. 14,
Nº 1, pp 98-108.
Capelleras, J. (2005) Attitudes <strong>of</strong> Academic Staff Towards <strong>the</strong>ir Job and Organization: an empirical assessment,
Tertiary Education and Management, Vol. 11, No. 2, pp. 147-166.
Castells, M. (2001) The new global economy. In J. Muller, N. Cloete and S. Badat (Eds.), Challenges <strong>of</strong>
globalisation: South African debates with Manuel Castells (pp. 2-21), Cape Town, SA: Maskew Miller
Longman.
Cavalli, A. and Teichler, U. (2010) The Academic Pr<strong>of</strong>ession: A Common Core, a Diversified Group or an
Outdated Idea?, <strong>European</strong> Review, Vol. 18, Supplement No. 1, pp. S1–S5.
Clery, S. (2002) Faculty Satisfaction. Research Center Update, National Education Association, Washington, DC.
Higher Education Research Center, Washington.
DGES - Direcção-Geral do Ensino Superior (2008) Indez 2008. Direcção-Geral do Ensino Superior, Lisbon.
Enders, J. (1999) Crisis? What Crisis? The Academic Pr<strong>of</strong>essions in <strong>the</strong> "Knowledge" Society, Higher Education,
Vol. 38, No. 1, pp. 71-81.
Gibbons, M. (1998) “Higher education relevance in <strong>the</strong> 21 st century”, Paper read at <strong>the</strong> UNESCO World
<strong>Conference</strong> on Higher Education, Paris, France.
GPEARI (2010) Docentes do Ensino Superior [2001 a 2008], Gabinete de Planeamento, Estratégia, Avaliação e
Relações Internacionais, Ministério da Ciência, Tecnologia e Ensino Superior, Lisbon.
Guruz, K. (2003) “Higher education in <strong>the</strong> global knowledge economy”. Paper read at <strong>the</strong> CMU Assembly, Bari,
Italy.
Jones, N.; Meadow, C. and Sicilia, M. (2009) Measuring Intellectual Capital in Higher Education, Journal <strong>of</strong>
Information & Knowledge Management (JIKM), Vol. 8, No. 2, pp 113-136.
Jongbloed, B. (2004) “Creating public-private dynamics in higher education funding: A discussion <strong>of</strong> three
options”. Paper read at <strong>the</strong> 17 th Annual <strong>Conference</strong> <strong>of</strong> <strong>the</strong> Consortium <strong>of</strong> Higher Education Researchers,
Enschede, The Ne<strong>the</strong>rlands.
Knight, P. and Harvey, L. (1999) The use <strong>of</strong> a staff satisfaction survey at <strong>the</strong> University <strong>of</strong> Central England in
Birmingham, Perspectives: Policy and Practice in Higher Education, Vol. 3, No. 2, pp. 56-62.
Küskü, F. (2001) Dimensions <strong>of</strong> Employee Satisfaction: A State University Example, METU Studies in
Development, Vol, 28, No. 2, pp. 399-430.
Nerdrum, L. and Erikson, T. (2001) Intellectual capital: a human capital perspective, Journal <strong>of</strong> Intellectual
Capital, Vol. 2, No. 2, pp.127 – 135.
Newman, F. and Couturier, L. (2002) “Trading Public Good in <strong>the</strong> Higher Education Market,” The Observatory on
Borderless Higher Education, London.
Noordin, F. and Jus<strong>of</strong>f, K. (2009) Levels <strong>of</strong> Job Satisfaction amongst Malaysian Academic Staff, Asian Social
Science, Vol. 5, No. 5, pp. 122-128.
OCES - Observatório da Ciência e do Ensino Superior (2005a) Evolução Por Categoria do Pessoal Docente do
Ensino Superior Politécnico Público: 1993 a 2004. Observatório da Ciência e do Ensino Superior, Lisbon.
OCES - Observatório da Ciência e do Ensino Superior (2005b) Evolução Por Categoria do Pessoal Docente do
Ensino Superior Universitário Público: 1993 a 2004. Observatório da Ciência e do Ensino Superior, Lisbon.
Sadlak, J. (1999) Globalization and concurrent challenges for higher education. In P. Scott (Ed.), The
globalization <strong>of</strong> higher education, The Society for Research into Higher Education and Open University
Press.
204

Maria de Lourdes Machado and Odília Gouveia
Santhapparaj, A. S. and Alam, S. S. (2005) Job satisfaction among academic staff in private universities in
Malaysia, Journal <strong>of</strong> Social Sciences, Vol. 1, No. 2, pp. 72-76.
Secundo, G.; Margherita, A.; Elia, G. and Passiante, G. (2010) Intangible assets in higher education and
research: mission, performance or both?, Journal <strong>of</strong> Intellectual Capital, Vol. 11, No. 2, pp. 140-157.
Seifert, T. A. and Umbach, P. D. (2008) The Effects <strong>of</strong> Faculty Demographic Characteristics and Disciplinary
Context on Dimensions <strong>of</strong> Job Satisfaction, Research in Higher Education, Vol. 49, No. 4, pp. 357-381.
Sporn, B. (1999) Adaptive university structures: An analysis <strong>of</strong> adaptation to socio-Economic Environments <strong>of</strong> US
and <strong>European</strong> Universities, London, Jessica Kingsley Publishers.
Ssesanga, K. and Garrett, R. M. (2005) Job satisfaction <strong>of</strong> University academics: Perspectives from Uganda,
Higher Education, Vol. 50, No. 1, pp. 33-56.
Stevens, P. A. (2005) The job satisfaction <strong>of</strong> English academics and <strong>the</strong>ir intentions to quit academe, National
Institute <strong>of</strong> Economic and Social Research, London.
Verhaegen, P. (2005) Academic talent: Quo vadis? Recruitment and retention <strong>of</strong> faculty in <strong>European</strong> business
schools, Journal <strong>of</strong> Management Development, Vol. 24, No. 9, pp. 807-818.
Ward, M. E. and Sloane, P. J. (2000) Non-pecuniary Advantages Versus Pecuniary Disadvantages: Job
Satisfaction Among Male and Female Academics in Scottish Universities, Scottish Journal <strong>of</strong> Political
Economy, Vol. 47, No. 3, pp. 273-303.
205

Intellectual Capital and Corporate Performance
Agnes Maciocha
Dublin Institute <strong>of</strong> Technology, Institute <strong>of</strong> Art, Design and Technology, Ireland
amaciocha@dit.ie
Agnes.MacIocha@iadt.ie
Abstract: In this paper we <strong>of</strong>fered a new approach towards analysis <strong>of</strong> Intangible Assets. The conceptual
framework <strong>of</strong> our research was based on taxonomy proposed by Contractor [2000] and we focused our study on
intangible assets that formed uncodified human capital. The aim <strong>of</strong> this research was to discriminate <strong>the</strong> most
crucial intangible assets that were absolutely indispensible in <strong>the</strong> organisational value creation. On <strong>the</strong> basis <strong>of</strong>
questionnaire tool we constructed Information Table according to Pawlak [1982]. Next we applied Rough Sets
method to analyse our data. The choice <strong>of</strong> <strong>the</strong> data analysis technique was determined by numerous advantages
associated with Rough Sets that weren’t so obvious in turn when considering traditional statistical methods.
Consequently we obtained a set <strong>of</strong> intangible assets that were absolutely necessary in <strong>the</strong> organisational value
creation process. This set was form by 14 different indicators that embraced aspects related to training,
competencies and culture. Nearly all <strong>of</strong> <strong>the</strong>m had qualitative character. In relation to training, apart from <strong>the</strong>
training’s frequency and quality, such aspects as knowledge dissemination and evaluation <strong>of</strong> <strong>the</strong> need for a
training were highlighted. Despite <strong>of</strong> being underlined in <strong>the</strong> area <strong>of</strong> Training, <strong>the</strong> aspect <strong>of</strong> cooperation was also
emphasized in <strong>the</strong> area <strong>of</strong> Competencies. In that section, apart from <strong>the</strong> requirement <strong>of</strong> particular knowledge
necessary in each position, <strong>the</strong> importance <strong>of</strong> s<strong>of</strong>t skills like motivation, team building and cooperation was
stressed out. In <strong>the</strong> organisational culture area <strong>of</strong> importance were two elements: <strong>the</strong> level <strong>of</strong> freedom when
performing duties and <strong>the</strong> degree to which management attends to employee’s problems. Consequently, we can
conclude that despite belonging to various sections, all <strong>the</strong> crucial intangible assets stressed <strong>the</strong> absolute
importance <strong>of</strong> active participation <strong>of</strong> employees in <strong>the</strong> organisational decision making. This constitutes a clear
evidence <strong>of</strong> <strong>the</strong> important role <strong>of</strong> Intellectual Capital in <strong>the</strong> corporate value creation.
Keywords: intellectual capital, intangible assets, rough sets, measurement
1. Introduction
Globalization <strong>of</strong> economic activity increasingly sophisticated and demanding consumers as well as
recent, significant advances in Information Technology caused substantial changes in <strong>the</strong> perception
<strong>of</strong> corporate value creation process. Introduction <strong>of</strong> <strong>the</strong> internet based technologies into business
milieu resulted in an obsolescence <strong>of</strong> <strong>the</strong> traditional factors <strong>of</strong> competitive advantage (such as land,
labour or capital). Consequently, inherent in <strong>the</strong> new media opportunities switched <strong>the</strong> attention into
new, less tangible, harder to imitate by rivals, and thus more sophisticated drivers <strong>of</strong> corporate
performance. Intangible Assets and consequently, Intellectual Capital become a buzz words in <strong>the</strong>
academic and business setting. Numerous conferences, articles and debates were and still are
focused on this phenomenon. Never<strong>the</strong>less, despite <strong>of</strong> serious problems inherent in <strong>the</strong> valuation and
measurement <strong>of</strong> intangibles, scholars still search for new, better methods and models. Consequently,
this paper aims at providing a new outlook on intangibles and <strong>the</strong>ir impact on <strong>the</strong> corporate
performance.
2. Intellectual capital: Definitions and measurement problems
Despite <strong>of</strong> much interest and research in <strong>the</strong> area <strong>of</strong> Intellectual Capital (IC) [Dumay, 2009], [O’Regan
et.al. 2001]; [Sriram, 2008], [Maciocha, 2007a], [Liu et.al, 2009]; [Lee, Guthrie, 2010]; [Choong, 2008];
[Tan et.al. 2008] <strong>the</strong> non-agreement <strong>of</strong> <strong>the</strong> academic community related to <strong>the</strong> definition <strong>of</strong> a firm’s
collection <strong>of</strong> intangible resources is still present in a scientific and pr<strong>of</strong>essional milieu. Characterised
by different scientific and pr<strong>of</strong>essional background, managers, accountants and information science
researchers propose different descriptions <strong>of</strong> IC [Marks, 2001], [Dzinkowski, 2000] [Bontis, Serenko,
2009] [Andriessen, 2004] [Allard, 1997] [Miller, 1999] [Huang, 1998] [Sveiby, 1997]. Apart from <strong>the</strong>
above problem, <strong>the</strong> perusal <strong>of</strong> <strong>the</strong> literature reveals also that IC notion is used interchangeably with
o<strong>the</strong>r terms such as intangible assets, knowledge assets, organisational knowledge, strategic
capabilities, information assets and so on [Kasiewicz, 2006], [Perechuda, 2006], [Arvidsson, 2003],
[Martinez , 2006] [Tovstiga Tulugurova 2009] [Lonnqvist @@] [Peng 2007] Choong [2009] [Soler and
Celestino 2007] [Sveiby, 1997] [Lev, 2001] [Ortiz, 2009]; [Choong, 2008].
Such situation triggers serious difficulties for empirical research, especially in <strong>the</strong> areas <strong>of</strong>
measurement and valuation <strong>of</strong> Intellectual Capital. The IC measurement difficulty is well explained by
Contractor [2000].
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Agnes Maciocha
By taking into account <strong>the</strong> scope <strong>of</strong> control over <strong>the</strong> particular elements and <strong>the</strong> possibility to separate
<strong>the</strong>m from <strong>the</strong> o<strong>the</strong>r intangibles he distinguishes three types <strong>of</strong> organisational intangible assets(fig. 1):
Formally registered assets – formally registered Intellectual Property Rights
Defined in more broader terms - intellectual assets embracing <strong>the</strong> above-mentioned formally
registered Intellectual Property Rights plus unregistered organizational knowledge codified in form
<strong>of</strong> drawings, s<strong>of</strong>tware, database, blueprints, formulae and written trade secrets
Uncodified human and organizational capital. In this group, <strong>the</strong> literature on management
includes also such constituents as company reputation, customer loyalty, network links and o<strong>the</strong>r
‘goodwill’ type items.
(I) Intellectual Property
(Registered)
Patents
Brands
Copyrights
Etc.
(II) Intellectual Assets (Uregistered but Codified)
Drawings
S<strong>of</strong>tware
Blueprints
Written Trade Secrets
Data Bases
Formulae
Recipes
(III) Intellectual Capital
(Uncodified Human and Organizational Capital)
Collective Corporate Knowledge
Individual Employee Skills and Knowledge
‘Know-how”
Organizational Culture
Customer Satisfaction
Figure 1: Intangible assets taxonomy (source: [Contractor, 2000])
He explains that as we move fur<strong>the</strong>r from level I towards level II and consequently III – <strong>the</strong>
discrimination and thus valuation <strong>of</strong> <strong>the</strong>se assets becomes more difficult and becomes nearly
impossible when dealing with uncodified human and organisational capital – <strong>the</strong> third type <strong>of</strong>
intangible assets. This also relates to <strong>the</strong> spectrum <strong>of</strong> <strong>the</strong> IC definition that was mentioned earlier on.
As we deal with first level <strong>of</strong> intangibles – <strong>the</strong>y are much easier to define and thus valuate, however
<strong>the</strong>y constitute only a fraction <strong>of</strong> all organisational intangibles. As we try to define <strong>the</strong> remaining
assets we need to use much broader definition and thus it is harder to provide any correct and valid
measurement method.
3. Rough sets
Introduced in early 1980’s by Pawlak [1982], <strong>the</strong> Rough Sets Theory involved methods for knowledge
discovery and data mining [Beynon et.al. 2001]. As such it provided a relatively new technique <strong>of</strong>
reasoning from vague and imprecise data [Goh, Law 2003] and attracted <strong>the</strong> attention <strong>of</strong> number <strong>of</strong>
researchers and practitioners [Daubie 2002], [Ahn et al. 2000], [Bose 2006], [Tseng, Huang 2007]. It
was widely used in various areas ranging from finance [Dimitras et al. 1999], [Maciocha & Kisielnicki
2009], [Maciocha, 2007b], [Kyoung-jae & Ingoo 2001], [McKee 2000], [Beynon & Peel 2001] [Francis
et al. 2002] [Shyng, Tzeng 2007] tourism [Goh & Law 2003] marketing [Beynon et al. 2001] production
[Gento & Redondo 2003], [Lee 2002] and medicine, [Hassanien 2003] to just name a few.
Although somewhat similar to statistical probability <strong>the</strong>ory and o<strong>the</strong>r s<strong>of</strong>t approaches, such as fuzzy
sets, <strong>the</strong> rough sets approach is significantly different. Fuzzy sets are useful for handling imprecision
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Agnes Maciocha
when objects in a data set do not exclusively belong to a single category. In turn, rough sets are
useful when ‘‘<strong>the</strong> classes into which <strong>the</strong> objects are to be classified are imprecise, but can
never<strong>the</strong>less be approximated with precise (crisp) sets’’.
Fur<strong>the</strong>rmore, <strong>the</strong> main advantage <strong>of</strong> rough sets <strong>the</strong>ory is that it does not require any a priori
information about <strong>the</strong> probability distribution <strong>of</strong> <strong>the</strong> data or any knowledge about <strong>the</strong> grade <strong>of</strong>
membership in a class. It finds its use in ‘‘data reduction (elimination <strong>of</strong> superfluous data), discovery
<strong>of</strong> data dependencies, estimation <strong>of</strong> data significance, generation <strong>of</strong> decision (control) algorithms from
data, approximate classification <strong>of</strong> data, discovery <strong>of</strong> similarities or differences in data, discovery <strong>of</strong>
patterns in data, and discovery <strong>of</strong> cause–effect relationships [Hassanien 2003]. Fur<strong>the</strong>r text contains
a description <strong>of</strong> <strong>the</strong> steps involved in rough sets analysis.
3.1 Information system
The first step in a rough set analysis is to select data on <strong>the</strong> attributes <strong>of</strong> predefined objects [Pheng,
Hongbin, 2006]. Then, information is transformed into a coded information table. One attribute in
information table is designated as a decision attribute, and <strong>the</strong> rest <strong>of</strong> <strong>the</strong> attributes are called
condition attributes. Rows <strong>of</strong> this table correspond to objects (actions, alternatives, candidates,
patients, etc.) and columns correspond to attributes. To each pair (object, attribute) <strong>the</strong>re is
designated value - descriptor. Descriptors (placed in each row <strong>of</strong> <strong>the</strong> table) correspond to <strong>the</strong>
information about <strong>the</strong> equivalent object <strong>of</strong> a given decision situation.
3.2 Approximation <strong>of</strong> sets
As we mentioned earlier, <strong>the</strong> concept <strong>of</strong> rough sets is founded on <strong>the</strong> assumption that with every
object <strong>of</strong> <strong>the</strong> universe <strong>of</strong> discourse <strong>the</strong>re is associated some information (data, knowledge). Objects
characterised by <strong>the</strong> same information are indiscernible (similar) in view <strong>of</strong> available information about
<strong>the</strong>m [Slowinski et. al. 1997]. Created in this way <strong>the</strong> indiscernibility relation enables one to
characterize a collection <strong>of</strong> objects which in general are impossible to be accurately described by
means <strong>of</strong> <strong>the</strong> values <strong>of</strong> <strong>the</strong>ir sets <strong>of</strong> attributes, in terms <strong>of</strong> lower or upper approximation [Beynon et.al.
2001]. As a result, we can define a rough set as an approximate representation <strong>of</strong> a given crisp set in
terms <strong>of</strong> two subsets (lower and upper approximation) derived from a crisp partition defined on <strong>the</strong>
universal set involved [Beynon et.al. 2001], [Intana, Mukaidono 2002].
By <strong>the</strong> lower approximation <strong>of</strong> X we mean <strong>the</strong> set <strong>of</strong> all elements that are certainly in X, while <strong>the</strong>
elements in <strong>the</strong> upper approximation can possible be classified as X [Salonen, Nurmi 1999]. The
boundary region (BND) <strong>of</strong> a particular set (A) constitutes <strong>the</strong> difference between <strong>the</strong> upper and lower
approximation. If <strong>the</strong> boundary region <strong>of</strong> X is not empty (i.e. if <strong>the</strong> upper and lower approximations are
not identical) <strong>the</strong>n <strong>the</strong> set X is referred to as definable ('rough set') with respect to A; o<strong>the</strong>rwise, it is
called crisp [Pawlak 2000]. In sum, <strong>the</strong> indiscernibility relation is used to define basic operations in
rough sets:
Let P ⊆ Y and Y ⊆ U. The P-lower approximation <strong>of</strong> Y: P (Y), and <strong>the</strong> P-upper approximation <strong>of</strong> Y:
P (Y) are defined as follows:
3.3 Accuracy and quality <strong>of</strong> approximation
P Y = x ∈X : I p (x) ⊆ Y}
P Y =U X∈ Y Ip (x)
Using upper and lower approximation it is possible to define accuracy as well as quality <strong>of</strong>
approximation. These numbers are placed within [0, 1] interval. They define exactly how it is possible
to describe <strong>the</strong> examined set <strong>of</strong> objects using available information [Pawlak, Slowinski 1994].
Accuracy <strong>of</strong> approximation is closely related to <strong>the</strong> inexactness <strong>of</strong> a class, which is caused by <strong>the</strong>
occurrence <strong>of</strong> a boundary region <strong>of</strong> a set. In o<strong>the</strong>r words, lower accuracy <strong>of</strong> a set suggests a larger
borderline region [Goh, Law, 2003]. By definition, accuracy <strong>of</strong> approximation <strong>of</strong> Y is equal to <strong>the</strong> ratio
<strong>of</strong> numbers <strong>of</strong> objects belonging to <strong>the</strong> lower approximation <strong>of</strong> Y to <strong>the</strong> number <strong>of</strong> objects belonging
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Agnes Maciocha
(representing) <strong>the</strong> upper approximation <strong>of</strong> <strong>the</strong> set Y [Ahn et. al. 2000]. It expresses <strong>the</strong> possible
correct decision when classifying objects employing <strong>the</strong> attribute B. This ratio is defined as follows
[Gento, Redondo, 2003]:
α p(Y) =
where ‘card’ means cardinality <strong>of</strong> <strong>the</strong> particular set
card(
PY
)
card(
PY
)
Quality <strong>of</strong> approximation defines <strong>the</strong> ratio <strong>of</strong> all P-correctly sorted objects to all objects <strong>of</strong> a system
[McKee, 2000]. In o<strong>the</strong>r words, it expresses <strong>the</strong> percentage <strong>of</strong> objects, which can be correctly
classified to a particular class y employing attributes from <strong>the</strong> set P. The following indicator describes
quality <strong>of</strong> approximation <strong>of</strong> classification y by using attributes P [Tay, Shen 2002], [Slowinski et. al.
1997], [Wong, Chungb 2007]:
γ p (y) =
∑
card( PYi
)
card(
U )
where P ⊆ Q, and Q is finite set <strong>of</strong> attributes; Y ⊆ U, U is finite set <strong>of</strong> objects; P Yi is <strong>the</strong> P-upper
approximation <strong>of</strong> Yi; subsets Yi, i= 1, …., n are classes <strong>of</strong> classification y, and card(x) is <strong>the</strong> cardinality
<strong>of</strong> a set x.
When <strong>the</strong> value <strong>of</strong> this ration equals 1, <strong>the</strong> result <strong>of</strong> <strong>the</strong> classification is satisfactory. That means that
all elements <strong>of</strong> <strong>the</strong> set have been unambiguously classified to upper area (positive region), using <strong>the</strong>
set <strong>of</strong> attributes P [Meskens et. al. 2002]
3.4 Attribute reduction
Ano<strong>the</strong>r central matter in <strong>the</strong> research on <strong>the</strong> rough set <strong>the</strong>ory is knowledge reduction [Jiye, Zongben,
2002]. It is a process <strong>of</strong> finding <strong>the</strong> minimum number <strong>of</strong> indicators (attributes) that are important within
a database. The set <strong>of</strong> reduced indicators obtained is known as 'reduct' [Ahmad et. al. 2004]. Reduct
is <strong>the</strong>n defined as a subset R <strong>of</strong> <strong>the</strong> set <strong>of</strong> conditional attributes C such that [Pawlak, Skowron, 2007],
[Pawlak, 1991]:
γC(Q) = γR(Q)
Less formally we can say that reduced set <strong>of</strong> attributes R, R ⊆ Q, provides <strong>the</strong> same quality <strong>of</strong>
classification as <strong>the</strong> original set <strong>of</strong> attributes Q [Dimitras et.al.].
Collection <strong>of</strong> <strong>the</strong> most important attributes in <strong>the</strong> system is called core <strong>of</strong> <strong>the</strong> set. Core is <strong>the</strong> most
essential part <strong>of</strong> <strong>the</strong> set P, it can't be eliminated without disturbing <strong>the</strong> ability <strong>of</strong> approximating <strong>the</strong>
decision [Pawlak, Slowinski, 1994]. In o<strong>the</strong>r words, <strong>the</strong> core <strong>of</strong> <strong>the</strong> set is <strong>the</strong> intersection <strong>of</strong> <strong>the</strong> all
reducts in <strong>the</strong> set [Goh, Law, 2003], [Tay, Shen, 2002].
3.5 Attribute importance
Applying <strong>the</strong> concept <strong>of</strong> attribute reduction it is possible to determine <strong>the</strong> importance <strong>of</strong> analysed
attributes. The order <strong>of</strong> importance <strong>of</strong> success indicators is calculated based on <strong>the</strong> frequency <strong>of</strong>
occurrences in <strong>the</strong> sets <strong>of</strong> reducts obtained. In o<strong>the</strong>r words, <strong>the</strong> attributes that are present in more
reducts are more important than <strong>the</strong> attributes that are characterised by less frequent occurrence in
<strong>the</strong> reducts. Consequently, as we stated earlier on, attributes that form <strong>the</strong> core <strong>of</strong> <strong>the</strong> set are
absolutely indispensable, and thus are present in each reduct. Therefore <strong>the</strong>y are characterised by
100% occurrence in <strong>the</strong> reduct. We can say thus that <strong>the</strong> attributes that form <strong>the</strong> core <strong>of</strong> <strong>the</strong> set are
<strong>the</strong> most important and absolutely indispensable in <strong>the</strong> set.
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Agnes Maciocha
4. Presentation <strong>of</strong> <strong>the</strong> rough sets results
4.1 Research methodology
The conceptual framework <strong>of</strong> this research is based on <strong>the</strong> Intangible Assets taxonomy proposed by
Contractor [2000]. The main interest <strong>of</strong> this study is concerned with <strong>the</strong> third level <strong>of</strong> Intangible
Assets: namely Uncodified Human and Organizational Capital. It embraces such elements as
Collective Corporate Knowledge, Individual Employee Skills and Knowledge. In order to fully describe
this concept we analysed a number <strong>of</strong> different models used to measure and manage intangible
assets [Bontis, 2001], [Baruch 2001],[Sveiby 1997], [Andriessen, 2002], [Brooking, 1996], [Ulf, 1999],
[Dawson, 1994], [CG E&Y, 2000], [Nally, 2000]. As most <strong>of</strong> <strong>the</strong>m emphasized <strong>the</strong> role <strong>of</strong> human
resources in corporate value creation, we decided to focus on this aspect <strong>of</strong> <strong>the</strong> intellectual capital.
After <strong>the</strong> literature review we distinguished <strong>the</strong> following areas <strong>of</strong> interest:
Communication (11 attributes)
Competencies (10 attributes)
Organizational Culture (9 attributes)
Training (7 attributes)
Motivation (12 attributes)
Each <strong>of</strong> <strong>the</strong> following areas was described by <strong>the</strong> set <strong>of</strong> indicators (intangible assets) incorporated
from such models as Balanced Scorecard, Kaplan & Norton [1992], Intangible Assets Monitor, Sveiby
[1997, 2000], Skandia Navigator, Edvinsson [2001], or Value Creation Index [CG E&Y, 2001].
Consequently, <strong>the</strong> research model’s structure consisted <strong>of</strong> 5 separate areas that were in turn
described by set <strong>of</strong> specific attributes (7-12). The values <strong>of</strong> <strong>the</strong> indicators (intangible assets) were
obtained by mans <strong>of</strong> questionnaire tool distributed among small and medium size companies located
in Warsaw - Poland during 2007-2008. Rough Sets approach was applied into <strong>the</strong> analysis <strong>of</strong> <strong>the</strong>
received data. The choice <strong>of</strong> such method was determined by numerous advantages that are
characteristics for Rough Sets as opposite to <strong>the</strong> traditional statistical methods [Maciocha, 2009]. As
this technique was proved to provide even better results than traditional statistical analysis [Slowinski
et.al. 1997) it seemed that application <strong>of</strong> this method to our data analysis was <strong>the</strong> best choice.
4.2 The data and <strong>the</strong> information table
Obtained through a questionnaire, data was entered into an input file in <strong>the</strong> Rose2Little. 129 objects
were described by 58 attributes that in turn formed 5 above mentioned areas. For data quality
analysis purpose we eliminated any objects that were characterised by incomplete information.
Consequently, 5 separate information tables (one for each area) were constructed. The level <strong>of</strong>
organisational financial performance (which was measured on five point – Likert skale: very bad, bad,
average, good, and very good) was represented by <strong>the</strong> decision attribute in each system.
4.3 Approximation <strong>of</strong> sets
The prediction accuracy was assessed based on <strong>the</strong> number <strong>of</strong> correctly classified cases.
Table1: Quality and accuracy <strong>of</strong> classification
SECTION
Quality Of
Classific
I– 0.9744
II 1.000
Accuracy Class
# <strong>of</strong>
Objects
Lower
Approxim
Upper
Approxim
1.000 (1) 1 1 1
1.000 (2) 2 2 2
1.000 (3) 19 19 19
0.9459 (4) 36 35 37
0.9048 (5) 20 19 21
1.000 (1) 1 1 1
1.000 (2) 2 2 2
1.000 (3) 19 19 19
1.000 (4) 36 36 36
1.000 (5) 20 20 20
210

SECTION
Quality Of
Classific
III 0.9744
IV 1.000
V 1.000
Agnes Maciocha
Accuracy Class
# <strong>of</strong>
Objects
Lower
Approxim
Upper
Approxim
1.000 (1) 1 1 1
1.000 (2) 2 2 2
1.000 (3) 19 19 19
0.9459 (4) 36 35 37
0.9048 (5) 20 19 21
1.000 (1) 1 1 1
1.000 (2) 2 2 2
1.000 (3) 19 19 19
1.000 (4) 36 36 36
1.000 (5) 20 20 20
1.000 (1) 1 1 1
1.000 (2) 2 2 2
1.000 (3) 19 19 19
1.000 (4) 36 36 36
1.000 (5) 20 20 20
Approximations <strong>of</strong> <strong>the</strong> decision classes are characterised in table 3. The quality <strong>of</strong> classification was
very high for all analysed areas (equal to one for areas II, IV, and V and 0.97 for areas I and III). We
can say thus that <strong>the</strong> attributes provided satisfactory discrimination between <strong>the</strong> five financial classes.
Similar situation is present in terms <strong>of</strong> <strong>the</strong> accuracy <strong>of</strong> <strong>the</strong> classification. Areas II, IV, and V were
perfectly approximated by <strong>the</strong> whole set <strong>of</strong> attributes – <strong>the</strong> accuracy <strong>of</strong> <strong>the</strong> classification for <strong>the</strong>m was
equal one. For <strong>the</strong> remaining areas <strong>the</strong> level <strong>of</strong> accuracy <strong>of</strong> <strong>the</strong> classification was however slightly
lower. This was especially visible in <strong>the</strong> area: I and III– in <strong>the</strong> class 4 and 5 where accuracy <strong>of</strong> <strong>the</strong>
classification was equal to 0.9459 and 0.9048 respectively.
4.4 Attribute’s reduction
Reduction <strong>of</strong> information table constitutes one <strong>of</strong> <strong>the</strong> most important steps in <strong>the</strong> Rough Sets Data
Analysis. Table 4 presents results <strong>of</strong> <strong>the</strong> reduction stage in our data analysis.
Table 2: Reducts – number, minimum and maximum length
Section # <strong>of</strong> reducts
Min
length
Max length
# <strong>of</strong> describing
attributes
I CULTURE 8 6 7 9
II – COMPETENCIES 2 7 7 8
III TRAINING 1 6 6 7
IV- MOTIVATION 184 5 7 12
V- COMMUNICATION 65 6 7 11
It depicts number <strong>of</strong> reducts that were obtained for each area as well as <strong>the</strong> minimum and maximum
length <strong>of</strong> <strong>the</strong> reducts. It is interesting to notice that <strong>the</strong>re was only one reduct for Training area and it
consisted <strong>of</strong> 6 attributes. It means that only 1 attribute in that area was redundant. For each area we
can observe significant reduction in terms <strong>of</strong> number <strong>of</strong> attributes placed in <strong>the</strong> reduct.
4.5 Core <strong>of</strong> <strong>the</strong> set
Table 3: Core <strong>of</strong> each set <strong>of</strong> attributes
SECTION I II III IV V
A1 A1 A1 - -
A3 A2 A2 - -
CORE:
ATTRIBUTE
A3 A3 - -
A5 A4 - -
A8 A5 - -
A9 A6 - -
The indispensible attributes – namely <strong>the</strong> core was found for three following areas: I - Culture, II –
Competencies and III – Training. In area <strong>of</strong> Culture <strong>the</strong> core consisted <strong>of</strong> two attributes A1 and A3
211

Agnes Maciocha
while in <strong>the</strong> remaining two areas 6 different attributes formed each core. The number and type <strong>of</strong>
attributes in each core are presented in table 3.
4.6 Attribute importance
With <strong>the</strong> intention to meet our research goal we needed to distinguish <strong>the</strong> most characteristic for
financial performance intangibles. After <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> core <strong>of</strong> <strong>the</strong> set we focused on finding <strong>the</strong>
relative frequency <strong>of</strong> occurrence <strong>of</strong> <strong>the</strong> attributes in <strong>the</strong> reducts. Table 4 presents attribute ranking in
terms <strong>of</strong> its relative frequency <strong>of</strong> occurrence in reducts. The highest relative frequency <strong>of</strong> attribute
occurrence in <strong>the</strong> reduct is represented by 100% and is accredited to <strong>the</strong> core <strong>of</strong> <strong>the</strong> set. In o<strong>the</strong>r
words, <strong>the</strong>se attributes represent <strong>the</strong> most important, indispensable attributes that cannot be removed
from <strong>the</strong> set without affecting <strong>the</strong> quality <strong>of</strong> accuracy <strong>of</strong> approximation. Table 4 describes each area
attributes that were characterised by at least 50% frequency <strong>of</strong> occurrence in <strong>the</strong> reducts. Next, all
<strong>the</strong>se attributes were ranked from <strong>the</strong> highest frequency <strong>of</strong> occurrence in <strong>the</strong> reducts towards <strong>the</strong>
smallest regardless <strong>of</strong> <strong>the</strong> area <strong>the</strong>y belonged to.
Table 4: Ranking <strong>of</strong> <strong>the</strong> most important attributes (above 50% <strong>of</strong> occurrence in <strong>the</strong> reducts)
#
COMPETENCIE
MOTIVA COMMUNI
CULTURE
TRAINIG
S
TION
CATION
Attribut
e
%
Frequen
cy
Attribut
e
%
Freque
ncy
Attribut
e
%
Frequen
cy
Attribut
e
%
Freque
ncy
Attribut
e
%
Freque
ncy
1 A1 100.0 A1 100.0 A1 100.00 A5 66.30 A10 81.54
2 A3 100.0 A2 100.0 A2 100.00 A3 56.52 A5 78.46
3 A8 75.00 A3 100.0 A3 100.00 A8 54.35 A3 63.08
4 A4 62.50 A5 100.0 A4 100.00 A4 63.08
5 A6 62.50 A8 100.0 A5 100.00 A11 63.08
6 A7 62.50 A9 100.0 A6 100.00
7 A5 62.50
This ranking is presented in table no. 5 and it forms two clusters.
Table 5: The most important attributes and <strong>the</strong>ir meaning
#
RA
NK
ATTRI
BUTE
%
FREQU
ENCY
CODIFICATION SECTION
1 1 A1 100.00 To who is training directed TRAINIG
2 1 A2 100.00 Existence <strong>of</strong> training program related to
improvement <strong>of</strong> skills in team management towards
managers in
TRAINIG
3 1 A3 100.00 Existence <strong>of</strong> duty to give relation from attended
training
TRAINIG
4 1 A4 100.00 Number <strong>of</strong> training days per year TRAINIG
5 1 A5 100.00 Employee's judgment <strong>of</strong> need for training TRAINIG
6 1 A6 100.00 Contribution <strong>of</strong> <strong>the</strong> provided training to <strong>the</strong>
improvement <strong>of</strong> <strong>the</strong> employee's qualifications
TRAINIG
7 1 A1 100.00 Managers' competencies in general COMPETENCIES
8 1 A2 100.00 Level <strong>of</strong> managers' competencies in <strong>the</strong>ir position COMPETENCIES
9 1 A3 100.00 Supervisor's ability to motivate subordinates COMPETENCIES
10 1 A5 100.00 Supervisors' competencies in team building COMPETENCIES
11 1 A8 100.00 Coworkers' competencies in terms <strong>of</strong> <strong>the</strong> position COMPETENCIES
12 1 A9 100.00 Level <strong>of</strong> cooperation between employees COMPETENCIES
13 1 A1 100.00 Level <strong>of</strong> autonomy for employees when performing
<strong>the</strong>ir duties
CULTURE
14 1 A3 100.00 Degree to which management attends to
employees' problems
CULTURE
15 2 A10 81.54 level <strong>of</strong> exploitation <strong>of</strong> database COMMUNICATION
16 3 A5 78.46 Frequency <strong>of</strong> internet usage COMMUNICATION
17 3 A8 75.00 support for knowledge sharing behaviour CULTURE
18 3 A5 66.30 quality <strong>of</strong> <strong>the</strong> benefits package <strong>of</strong>fered by <strong>the</strong>
organization
MOTIVATION
Representing absolute essential intangibles (characterised by 100% <strong>of</strong> occurrence in <strong>the</strong> reducts), <strong>the</strong>
first cluster consists <strong>of</strong> various intangibles related to <strong>the</strong> training aspects (nearly 45%), competencies
212

Agnes Maciocha
(nearly 45%) and culture (2%). In relation to <strong>the</strong> Training area, apart from <strong>the</strong> training frequency and
quality <strong>the</strong> important aspects were related to <strong>the</strong> dissemination <strong>of</strong> <strong>the</strong> training knowledge by
employees attended <strong>the</strong> training as well as employee’s judgment <strong>of</strong> <strong>the</strong> need for a given training.
What is also important is <strong>the</strong> fact that <strong>the</strong> manager’s competencies in team management were not
only highlighted in <strong>the</strong> Training area, but also in <strong>the</strong> Competencies section. Consequently, in <strong>the</strong>
Competencies section apart from possessing characteristic to <strong>the</strong> position knowledge, it is important
for managers to develop and exhibit so called s<strong>of</strong>t skills: ability to motivate subordinates and build
good work team. This last aspect was also highlighted in <strong>the</strong> level <strong>of</strong> cooperation between employees.
In terms <strong>of</strong> Culture two aspects turned out to be crucial. The first related to <strong>the</strong> level <strong>of</strong> autonomy for
employees when performing <strong>the</strong>ir duties. The second in turn, focused on <strong>the</strong> degree to which
management attends to employee’s problem. The second group <strong>of</strong> assets consist <strong>of</strong> 4 attributes, <strong>of</strong>
which 2 were related to <strong>the</strong> communication, one to culture, and one to motivation. We need to
remember however, that being important <strong>the</strong>se assets didn’t turn out to be absolutely indispensible in
creation <strong>of</strong> organisational value.
5. Conclusions and recommendations
In this paper we proposed a new approach towards intangible assets’ data analysis. We base our
investigation on <strong>the</strong> empirical data ga<strong>the</strong>red through questionnaire tool distributed among polish
companies. The aim <strong>of</strong> our analysis was to discriminate between those intangible assets that are
significant in <strong>the</strong> corporate value creation process and those that are irrelevant and thus redundant.
The result <strong>of</strong> our research was a set <strong>of</strong> intangibles that constituted <strong>the</strong> most important drivers <strong>of</strong>
corporate value. These attributes represented three <strong>of</strong> <strong>the</strong> five analysed areas: Training,
Competencies and Culture. However it is necessary to say that <strong>the</strong> first two section constituted more
than 70% <strong>of</strong> <strong>the</strong> group. We hope that this research will be <strong>of</strong> assistance to <strong>the</strong> companies that are
investing significant money in <strong>the</strong> effective management <strong>of</strong> <strong>the</strong>ir intangibles and will enable <strong>the</strong>m to
gain competitive advantage. On <strong>the</strong> o<strong>the</strong>r hand <strong>the</strong>se results will also constitute a foundation for a
fur<strong>the</strong>r empirical investigation.
References
Ahmad F., Hamdan A.R., Bakar A.A., “Determining Success Indicators <strong>of</strong> E-Commerce Companies Using Rough
Set Approach”, The Journal <strong>of</strong> American Academy <strong>of</strong> Business , Cambridge, September 2004
Ahn B., Cho S., Kim Y.,The integrated methodology <strong>of</strong> rough set <strong>the</strong>ory and artificial neural network for business
failure prediction, Expert Systems with Applications, 18, 2000.
Allard S., Trott K., „Card World’s New Capital”, USBanker, Apr 1997
Andriessen D.,The Financial Value Of Intangibles, Searching For The Holy Grail, Paper Presented At The 5th
World Congress On The Management Of Intellectual Capital, Hamilton, Ontario, Canada, January 16-18,
2002.
Arvidsson S., „Demand and Supply <strong>of</strong> Information on Intangibles: The Case <strong>of</strong> Knowledge-Intense Companies”,
PhD Dissertation, Department <strong>of</strong> Business Administration, Finance, Lund University, 2003
Barron E., Byard D., Kile B., Riedl J., “High technology intangibles and analysts’ forecasts”, Journal <strong>of</strong> Accounting
Research, Vol. 40, No.2, 2002
Baruch L., Intangibles: Management, Measurement, and Reporting, Washingthon DC: Brookings Institute Press,
2001.
Bassi, Laurie J., “Harnessing <strong>the</strong> power <strong>of</strong> intellectual capital”, Training & Development, Vol. 51, Issue 12,
December 97
Beynon M. J., Peel M. J. “Variable precision rough set <strong>the</strong>ory and data discretisation: an application to corporate
failure prediction”, Omega 29, 2001
Beynon M., Curry B., Morgan P., “Knowledge discovery in marketing - an approach through Rough Set Theory”,
<strong>European</strong> Journal <strong>of</strong> Marketing, Vol. 35 No 7/8, 2001.
Bontis N., “Assessing knowledge assets: a review <strong>of</strong> <strong>the</strong> models used to measure intellectual capital”,
International Journal <strong>of</strong> Management Reviews, Vol. 3, Issue 1, Mar 2001
Bontis N., Serenko A., “A casual model <strong>of</strong> human capital antecedents and consequents in <strong>the</strong> financial services
industry”, Journal <strong>of</strong> Intellectual Capital, Vol. 10, No.1, 2009
Bose I., “Deciding <strong>the</strong> financial health <strong>of</strong> dot-coms using rough sets”, Information & Management 43, 2006
Brooking A., Motta E.,A Taxonomy <strong>of</strong> Intellectual Capital and a Methodology for Auditing It, 17th Annual National
Business <strong>Conference</strong> , McMaster University, Hamilton, Ontario, Canada, January 24-26, 1996.
Bukowitz W., Petrash G., “Visualizing, Measuring and Managing Knowledge”, Research Technology
Management, 08956308, Vol. 40, Issue 4, Jul/Aug 1997
Bukowitz, Wendi R., „Visualizing, Measuring and Managing Knowledge”, Research Technology Management,
08956308, Vol. 40, Issue 4, Jul/Aug 97
CG E&Y, “Measuring <strong>the</strong> Future: The Value Creation Index” Cap Gemini Ernst& Young Center For Business
Innovation Report , 2000.
213

Agnes Maciocha
Choong K., “Intellectual Capital: definitions, categorization and reporting models”, Journal <strong>of</strong> Intellectual Capital,
Vol. 9., No. 4, 2008
Contractor F., „Valuing Corporate Knowledge and Intangible Assets: Some General Principles”, Knowledge and
Process Management Vol. 7 Nr 4, 2000
Daubie M, Levecq P., Meskens N., “A comparison <strong>of</strong> <strong>the</strong> rough sets and recursive partitioning induction
approaches: An application to commercial loans”, International Transaction in Operational Research 9,
2002
Dawson C., “Human Resource Accounting: From Prescription to Description, Management Decision”, Vol. 32,
No. 6, 1994.
Dimitras A, Slowinski R., Susmaga R., Zopounidis C., “Business failure prediction using rough sets”, <strong>European</strong>
Journal <strong>of</strong> Operational Research 114, 1999.
Dobija D., „Pomiar i sprawozdawczość kapitału intelektualnego przedsiębiorstwa”, WSPiZ, Warszawa 2003
Dumay J., “Reflective discourse about intellectual capital: research and practice”, Journal <strong>of</strong> Intellectual Capital,
Vol. 10, No. 2, 2009
Dzinkowski R., „Assessing <strong>the</strong> risk <strong>of</strong> ideas”, Canadian Banker, Second Quarter, Vol. 107, Issue 2, 2000
Dzinkowski R., „The measurement and management <strong>of</strong> intellectual capital: An introduction”, Management
Accounting, Febr 2000
Edvinsson L., Malone M., “Kapital Intelektualny”, Wydawnictwo Naukowe PWN, Warszawa 2001
Francis E.H.Tay, Lixiang S., “Economic and Financial prediction using rough sets model”, <strong>European</strong> Journal <strong>of</strong>
Operational Research, 141, 2002
Gento A. M., Redondo A., “Rough sets and maintenance in a production line”, Expert Systems, November 2003,
Vol. 20, No. 5
Goh C., Law R., “Incorporating <strong>the</strong> rough sets <strong>the</strong>ory into travel demand analysis”, Tourism Management, Vol.
24, 2003
Hassanien A., “Intelligent Data Analysis Of Breast Cancer Based On Rough Set Theory”, International Journal on
Artificial Intelligence Tools, Vol. 12, No. 4, 2003.
Huang C., Lu<strong>the</strong>r R., Tayles M., “An evidence-based taxonomy <strong>of</strong> intellectual capital”, Journal <strong>of</strong> Intellectual
Capital, Vol. 8, No. 3, 2007
Huang K., „Capitalizing on Intellectual Assets”, IBM System Journal, Vol. 37, Issue 4, 1998
IAS 38, par 11, „International Financial Reporting Standards (IFRSs) including International Accounting
Standards (IASs) and Interpretations as at 1 January 2005”, International Accounting Standards Board,
2005
Intana R., Mukaidono M., “Generalization <strong>of</strong> Rough sets and its applications in information”, Intelligent Data
Analysis, No. 6, IOS Press, 2002
International Federation <strong>of</strong> Accountants, “The Measurement and Management <strong>of</strong> Intellectual Capital”, IFAC, New
York, NY, 1998
Jiye Liang , Zongben Xu,The algorithm on knowledge reduction in incomplete information systems, International
Journal <strong>of</strong> Uncertainty, Fuzziness and KnowledgeBased Systems, Vol. 10, No 1, 2002
Kamath B., “Intellectual capital and corporate performance in Indian pharmaceutical industry”, Journal <strong>of</strong>
Intellectual Capital, Vol. 9, No.4, 2008
Kaplan R., Norton D., “The balanced scorecard - measures that drive performance”, Harvard Business Rev., 70
(1), 1992
Kasiewicz S. Rogowski W., Kicińska M., “Kapitał Intelektualny”, Oficyna Ekonomiczna, Kraków 2006
Koening M., “Education for Knowledge Management”, Information Services & Use, Vol. 19, Issue 1, 1999
Kurz P., “Intellectual capital management and value maximization”, Technology, Law and Insurance, No 5,2000
Kyoung-jae K., Ingoo H., “The extraction <strong>of</strong> trading rules from stock market data using rough sets”, Expert
Systems, Vo.18, No.4, September 2001
Lee L., Guthrie J., “Visualising and measuring intellectual capital in capital markets: a research method”, Journal
<strong>of</strong> Intellectual Capital, Vol. 11, No. 1, 2010
Lev B., „Intangibles – Management, Measurement, and Reporting”, Brookings Institution Press, Washington, D.C,
2001
Lewis B., Asce P., „Do you own any Intellectual Capital – What’s it worth?”, Journal <strong>of</strong> Management in
Engineering , March/April 2000/9
Lia Y., Zhang C., Swan J., “An information filtering model on <strong>the</strong> Web and its application in Job Agent”,
Knowledge-Based Systems 13, 2000
Liu D., Tseng K., Yen S., “The incremental impact <strong>of</strong> intellectual capital on value creation”, Journal <strong>of</strong> Intellectual
Capital, Vol. 10, No. 2, 2009
Lonnqvist A., Kianto A., Sillapaa V., “Using intellectual capital management for facilitating organizational change”,
Journal <strong>of</strong> Intellectual Capital, Vol. 10, No. 4, 2009
Maciocha A., “Intellectual Capital Versus Intangible Assets - <strong>the</strong> Differences and Similarities”, conference
proceedings, IC-Congress 2007, INHOLLAND University <strong>of</strong> pr<strong>of</strong>essional education, Haarlem, The
Ne<strong>the</strong>rlands, 3-4 May 2007; a
Maciocha A., Kisielnicki J., “Intangible Assets <strong>of</strong> <strong>the</strong> Polish Telecommunication Sector – Rough Set Approach”,
Lecture Notes in Computer Science No. 5656, Transactions on Rough Sets; Special issue, Vol. X, 2009
Maciocha A., Kisielnicki J., “Kapital Intelektualny problemy pomiaru - studium na przykladzie sektora
telekomunikacji”, Zeszyty Naukowe Politechniki Warszawskiej, Warszawa 2007;b
Marks P., “A knowledge –turns odyssey”, Computer –Aided Engineering, Vol. 20, Issue 1, Jan 2001
214

Agnes Maciocha
Martinez-Torres M., “A Procedure to design a structural and measurement model <strong>of</strong> Intellectual Capital: An
exploratory study”, Information and Management 43, 2006
McKee T., “Developing a Bankruptcy Prediction Model via Rough Sets Theory”, International Journal <strong>of</strong> Intelligent
Systems in Accounting, Finance & Management , 9, 2000
Meskens N., Levecq P., Lebon F., “Multivariate analysis and rough sets: Two aprroaches for s<strong>of</strong>tware-quality
analysis”, International Transaction in Operational Research , 9, 2002
Miller W., “Building <strong>the</strong> ultimate resource”, Management Review, Vol. 88, Issue 1, Jan 1999
Mouritsen Jan, “Intellectual capital and <strong>the</strong> capital market: <strong>the</strong> circulability <strong>of</strong> intellectual capital”, Accounting,
Auditing &Accountability Journal, Vol. 16 No. 1, 2003,
Nally D., “Reinwenting Corporate Reporting”, PriceWaterhauseCoopers' report, May 2000
O’Regan P., O’Donnel D., Heffernan M., “Recognition and management <strong>of</strong> intellectual resources: preliminary
evidence from indigenous Irish high-technology firms”, Journal <strong>of</strong> <strong>European</strong> Industrial Training, 25/2/3/4,
2001
OECD, “Guidelines and instructions for OECD symposium”, presented at International Symposium Measuring
Reporting Intellectual Capital: Experiences, Issues, and Prospects, OECD, Amsterdam, 1999
Ortiz M., “Analysis and valuation <strong>of</strong> intellectual capital according to its context”, Journal <strong>of</strong> Intellectual Capital, Vol.
10, No.3, 2009
Pawlak Z., “Rough set approach to knowledge-based decision support”, <strong>European</strong> Journal <strong>of</strong> Operational
Research, 99,
Pawlak Z., “Rough sets and decision analysis”, INFOR, Vol. 38, No 3, Aug. 2000
Pawlak Z., “Rough Sets”, Informational Journal <strong>of</strong> Information and Computer Sciences 11(5), 1982
Pawlak Z., “Rough sets and decision analysis, Rough Sets: Theoretical Aspects <strong>of</strong> Reasoning About Data”,
Dordrecht: Kluwer Academic Publishers,1991.
Pawlak Z., Skowron A., “Rudiments <strong>of</strong> rough sets”, Information Sciences, No.177, 2007
Pawlak Z., Slowinski R., “Decision Analysis Using Rough Sets”, International Transaction Operational Research
Vol. 1, No. 1, 1994.
Peng T., Pike S., Roos G., “Intellectual capital and performance indicators: Taiwanese healthcare sector”,
Journal <strong>of</strong> Intellectual Capital, Vol. 8, No. 3, 2007
Perechuda K., “Zarządzanie wiedzą w przedsiębiorstwie”, Wydawnictwo Naukowe PWN, Warszawa 2005
Pheng L.S., Hongbin J., “Analysing ownership, locational and internalization advantages <strong>of</strong> Chinese construction
MNCs using rough sets analysis”, Construction Management and Economics, No. 24, November 2006,
Pheng L.S., Hongbin J., “Analysing ownership, locational and internalization advantages <strong>of</strong> Chinese construction
MNCs using rough sets analysis”, Construction Management and Economics, No. 24, November 2006,
1149116
Richards D., Compton P., “An alternative verification and validation technique for an alternative knowledge
representation and acquisition technique”, Knowledge- Based Systems, 12, 1999
Salonen H., Nurmi H., “Theory and Methodology. A note on rough sets and common knowledge events”,
<strong>European</strong> Journal <strong>of</strong> Operational Research, 112, 1999
Sharma S, “Counting my knowledge”, Knowledge Management, Nov 2001
Shyng J., Wang F., Tzeng G., Wu, “Rough Set Theory in analyzing <strong>the</strong> attributes <strong>of</strong> combination values for <strong>the</strong>
insurance market” Expert Systems with Applications 32, 2007
Slowinski R., Zopounidis C., Dimitras A., “Prediction <strong>of</strong> company acquisition in Greece by means <strong>of</strong> <strong>the</strong> rough set
approach”, <strong>European</strong> Journal <strong>of</strong> Operational Research, Vol. 100, 1997
Smith E., “The role <strong>of</strong> tacit and explicit knowledge in <strong>the</strong> workplace” Journal <strong>of</strong> Knowledge Management, Vol. 5,
No 4, 2001, pp311-321
Soler L., Celestino D., “Evaluating <strong>the</strong> scope <strong>of</strong> IC in firms’ value”, Journal <strong>of</strong> Intellectual Capital, Vol. 8, No.3,
2007
Sriram R., “Relevance <strong>of</strong> intangible assets to evaluate financial health”, Journal <strong>of</strong> Intellectual Capital, Vol. 9, No.
3, 2008
Stewart, T.A., “Intellectual Capital: The New Wealth <strong>of</strong> Organizations:, Doubleday/Curency, New York, 1997
Sveiby K., “The Invisible Balance Sheet: Key indicator for accounting control and valuation <strong>of</strong> know-how
companies”, The Konrad Group, Suecia, 2000
Sveiby K., “The New Organizational Wealth - Managing & Measuring Intangible Assets”, Berret Koehler, 1997.
Tan H., Plowman D., Hancoock P., “The evolving research on intellectual capital”, Journal <strong>of</strong> Intellectual Capital,
Vol. 9, No. 4, 2008
Tay F., Shen L., “Economic and Financial prediction using rough sets model Computing, Artificial Intelligence and
Information Technology”, <strong>European</strong> Journal <strong>of</strong> Operational Research, 141, 2002
Tovstiga G., Tulugurova E., “Intellectual capital practices; a four region comparative study”, Journal <strong>of</strong> Intellectual
Capital, Vol. 10, No. 1, 2009
Tseng Tzu-Liang (Bill), Huang Ch, “Rough set-based approach to feature selection in customer relationship
management” Omega 35,2007
Turyna J., “Standardy rachunkowości – MSR – US GAAP – Polskie ustawodawstwo”, Diffin, Warszawa 2003
Ulf J., “Why <strong>the</strong> concept <strong>of</strong> human resource costing and accounting does not work; A lesson form seven Swedish
cases”, Personnel Review, Vol. 28, No1/2, 1999.
Wong Jinn-Tsai, Chungb Yi-Shih, “Rough set approach for accident chains exploration, Accident Analysis and
Prevention”, Vol. 39, 2007
215

The Influence <strong>of</strong> Human Capital in Achieving Corporate
Performance
Anca Mândruleanu
Academy <strong>of</strong> Economic Studies, Bucharest, Romania
anca.mandruleanu@fabiz.ase.ro
Abstract: It is hardly surprising that linking corporate performance to Intellectual Capital can help increase
employees’ productivity, attain superior reliability, build organizational commitment to quality, create leaders, set
goals, create incentives and achieve superior innovation. The organizational management is responsible for
transforming <strong>the</strong> influence <strong>of</strong> Human Capital, one main component <strong>of</strong> <strong>the</strong> Intellectual Capital, in an increase <strong>of</strong>
<strong>the</strong> corporate performance. This paper analysis <strong>the</strong> perception <strong>of</strong> some Romanian stakeholders regarding <strong>the</strong>
influence <strong>of</strong> Human Capital over <strong>the</strong> corporate performance. All <strong>the</strong> stakeholders are in an exchange relationship
with <strong>the</strong> company, <strong>the</strong>y supply <strong>the</strong> organization with important resources and, in exchange, each expects its
interests to be satisfied. In <strong>the</strong>ory, an efficient firm succeeds in achieving both <strong>the</strong> stakeholders’ expectations and
an increased corporate performance. This article will disseminate <strong>the</strong> results obtained from a research
concerning <strong>the</strong> Romanian business environment, more precisely <strong>the</strong> role <strong>of</strong> <strong>the</strong> stakeholders over <strong>the</strong> corporate
performance. A company cannot always satisfy <strong>the</strong> claims and <strong>the</strong> expectations <strong>of</strong> all stakeholders. The goals <strong>of</strong>
different groups may conflict and, in practice, few companies have <strong>the</strong> financial resources to manage all <strong>the</strong>
stakeholders. Often companies must choose. To do so, companies must identify <strong>the</strong> most important
stakeholders’ influence and give <strong>the</strong> highest priority to pursuing strategies that satisfy <strong>the</strong>ir needs. Stakeholders’
impact analysis can enable a company to identify <strong>the</strong> stakeholders most critical to its financial growth. Typically,
<strong>the</strong> analysis follows <strong>the</strong>se steps: identify <strong>the</strong> stakeholders, identify <strong>the</strong>ir interests and concerns, analyze <strong>the</strong>
claims stakeholders are likely to make on <strong>the</strong> organization, identify <strong>the</strong> stakeholders who are <strong>the</strong> most important
from <strong>the</strong> company’s perspective, identify <strong>the</strong> resulting strategic challenges.
Keywords: corporate performance, management’s perception, Romanian business environment, stakeholders
1. Introduction
Multibusiness companies consists <strong>of</strong> businesses, many <strong>of</strong> which could exist independently and a
corporative hierarchy <strong>of</strong> managers, functions and staff. It is <strong>the</strong> company’s hierarchy, that we refer to
as <strong>the</strong> Human Capital, which is responsible for making corporate strategy decisions. It is <strong>the</strong>
stakeholder who decides what new business to support, what acquisitions to make and whe<strong>the</strong>r to
form joint ventures or alliances. It determines <strong>the</strong> structure <strong>of</strong> <strong>the</strong> corporation, defines budgeting and
capital expenditures processes and sets <strong>the</strong> tone for corporative values and attitudes. The Human
Capital <strong>of</strong> a company has <strong>the</strong> potential to both create and destroy significant amounts <strong>of</strong> value: it can
ensure <strong>the</strong> increase or decrease <strong>of</strong> <strong>the</strong> corporate growth and renewal, identify or miss development
opportunities, expand or isolate <strong>the</strong> business.
The issue <strong>of</strong> determining a valid role for <strong>the</strong> Human Capital in <strong>the</strong> organization is now on <strong>the</strong> agenda
<strong>of</strong> many companies. It has become a topic <strong>of</strong> central importance for managers who are eager to
improve <strong>the</strong> corporate performance. It is a matter <strong>of</strong> increasing debate among stakeholders, who are
no longer prepared to remain passive. If performance is unsatisfactory, corrective steps are now being
taken more rapidly.
The paper presents <strong>the</strong> perception <strong>of</strong> <strong>the</strong> Romanian stakeholders concerning <strong>the</strong>ir influence over <strong>the</strong>
corporate performance. They represent <strong>the</strong> Human Capital, one <strong>of</strong> <strong>the</strong> three components <strong>of</strong> <strong>the</strong>
Intellectual Capital, and it is very interesting to see <strong>the</strong> bound and <strong>the</strong> connections between <strong>the</strong>
Human Capital and <strong>the</strong> corporate performance in <strong>the</strong> Romanian business environment.
2. Corporate performance
The primary wealth creation takes place at <strong>the</strong> business level and all <strong>the</strong> internal stakeholders must
work toge<strong>the</strong>r to create value. The first test is <strong>the</strong>refore whe<strong>the</strong>r <strong>the</strong>y create any value in <strong>the</strong> business.
Successful stakeholders create significant value. Managers do so by realizing specific performance
improvement opportunities that exist in <strong>the</strong> business, for example: apply tighter controls, facilitate <strong>the</strong>
sharing <strong>of</strong> complex know-how, streng<strong>the</strong>n <strong>the</strong> organizational culture, involve <strong>the</strong> employees in <strong>the</strong>
procedures <strong>of</strong> obtaining <strong>the</strong> final organizational goals and create awareness about this, encourage
innovation and so on. Not only large companies, but now also small and mid-sized ones must grow
internationally in order to gain market shares. This has become necessary because markets in <strong>the</strong>
industrial countries are highly saturated. Often, market growth is only possible abroad. Development
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<strong>of</strong> new market potential has thus become an important success factor in order to succeed in <strong>the</strong>
framework <strong>of</strong> global markets (Hill, 2007).
The employee <strong>of</strong> <strong>the</strong> future must think and act corporate. Today more than ever, future oriented
businesses are dependent on innovations, development <strong>of</strong> new ideas, products and technologies.
Organizations require employees, whose competences trigger <strong>the</strong> modernization processes, making
<strong>the</strong> firm more competitive. In addition to this, it is <strong>the</strong> need for team work among all workers, reduction
<strong>of</strong> unnecessary hierarchies, and a networked, cybernetic thinking. However, in order to make an
optimal use <strong>of</strong> <strong>the</strong>se capabilities, it is advisable to analyze one’s abilities and weak points. It is
important to reflect on one’s strength. Many people possess remarkable knowledge and skills, most <strong>of</strong>
which remain unused because <strong>the</strong>ir readiness to perform suffers due to lack <strong>of</strong> positive mental
attitude to <strong>the</strong>ir tasks. A positive mental attitude is however <strong>the</strong> needed ingredient for
accomplishments and results (Goold, 1994). Many firms that were used to successes in <strong>the</strong> past are
now confronted with hard strong competition that threatens to squeeze <strong>the</strong>m out <strong>of</strong> business. They
hardly have any chance to prevail in such a competitive environment.
This makes it clear that it is hardly possible to make pr<strong>of</strong>its using old concepts until future problems
are resolved. It is only outstanding companies who have always recognized human potentials as
future resources that must be cultivated and deliberately promoted. In <strong>the</strong> future, finances and
machinery will become passive merchandise, while human capital, perceived as investment, will be
<strong>the</strong> active source. This strong source can be fully used in <strong>the</strong> business environment only through <strong>the</strong>
inclusion <strong>of</strong> highly motivated people. Human potential is <strong>the</strong> bridge between <strong>the</strong> demising industrial
age and <strong>the</strong> emerging information age. Contentment and motivation <strong>of</strong> <strong>the</strong> employees play a major
role in <strong>the</strong> success <strong>of</strong> a business. Expectation attitude <strong>of</strong> employees focuses more and more towards
self-actualization on <strong>the</strong> labor world (Griffin, 2006).
3. Human Capital in Romanian business environment
In order to study <strong>the</strong> perception and <strong>the</strong> influence <strong>of</strong> Human Capital over <strong>the</strong> corporate performance in
<strong>the</strong> Romanian companies and to discover <strong>the</strong> awareness <strong>of</strong> <strong>the</strong> Romanian managers and employees
on this topic, a research was conducted using both qualitative and quantitative methods.
The study is based on two hypo<strong>the</strong>ses:
Hypo<strong>the</strong>sis 1a: The Romanian managers consider that <strong>the</strong> Human Capital <strong>of</strong> <strong>the</strong> company has an
important influence in increasing <strong>the</strong> corporate performance.
Hypo<strong>the</strong>sis 1b: The Romanian managers do not consider that <strong>the</strong> Human Capital <strong>of</strong> <strong>the</strong> company has
an important influence in increasing <strong>the</strong> corporate performance.
Hypo<strong>the</strong>sis 2a: The Romanian managers know <strong>the</strong> strategic objectives <strong>of</strong> <strong>the</strong> company and do <strong>the</strong>
best in achieving organizational competitive advantage.
Hypo<strong>the</strong>sis 2b: The Romanian managers do not know <strong>the</strong> strategic objectives <strong>of</strong> <strong>the</strong> company and are
not very involved in achieving organizational competitive advantage.
The population is formed by <strong>the</strong> total number <strong>of</strong> corporations that act in <strong>the</strong> Romanian business
environment. In <strong>the</strong> last years, <strong>the</strong> corporations proved to be an engine <strong>of</strong> <strong>the</strong> economies <strong>of</strong> <strong>the</strong> most
important countries from <strong>the</strong> <strong>European</strong> Union. The corporations are <strong>the</strong> pioneers <strong>of</strong> <strong>the</strong> knowledge
economy, <strong>the</strong> first who emphasize on knowledge, knowledge workers, teamwork, <strong>the</strong> importance <strong>of</strong>
intangible assets and all <strong>the</strong>ir present characteristics show that <strong>the</strong>y are still capable <strong>of</strong> playing <strong>the</strong>
same important role in future. This is <strong>the</strong> most important reason for which <strong>the</strong> corporations acting in
<strong>the</strong> Romanian market were analyzed. Thus, a sample <strong>of</strong> 50 companies was used, important players in
<strong>the</strong> Romanian business environment, with a number <strong>of</strong> managers ranging from 1 and 15 and a
number <strong>of</strong> employees ranging from 50 to 850.
Several criteria were settled from <strong>the</strong> beginning, when choosing <strong>the</strong> companies: <strong>the</strong> organization
should have at least one Romanian manager and <strong>the</strong> company should have at least 50 employees
(<strong>the</strong> number <strong>of</strong> employees should range between 50 and 1000). In order for <strong>the</strong> research to be
significant, <strong>the</strong> geographical distribution and <strong>the</strong> industry <strong>of</strong> <strong>the</strong> companies were also taken into
account, so companies from every region <strong>of</strong> <strong>the</strong> country and from many fields <strong>of</strong> activity were chosen.
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From <strong>the</strong> total population <strong>of</strong> almost 450, sample <strong>of</strong> almost 50 managers was used and <strong>the</strong> main
criteria were age, <strong>the</strong> period <strong>of</strong> time worked within <strong>the</strong> company, <strong>the</strong> seniority in that industry, <strong>the</strong>
studies. Average age was 42.5. All <strong>of</strong> <strong>the</strong>m (100%) had higher education. They were predominately
seniors in <strong>the</strong> field <strong>of</strong> work (more than 10 years) and <strong>the</strong>y had been with <strong>the</strong>ir current organization on
an average <strong>of</strong> 7.85 years.
The quantitative research was part <strong>of</strong> a larger survey on <strong>the</strong> role <strong>of</strong> management as an integrator over
<strong>the</strong> organizational Intellectual Capital. Participants were asked to participate in a 20 minutes, online
(web-based) survey. Participants were informed that results would be used for research purposes.
The scalar questionnaire applied had five questions concerning <strong>the</strong> main macro-variable corporate
performance and contained statements similar to <strong>the</strong> followings:
Are <strong>the</strong> employees actively involved in elaborating targets?
Could most staff list <strong>the</strong> organization’s goals relevant to <strong>the</strong>ir activity and are <strong>the</strong>y familiar with <strong>the</strong>
plans to achieve in <strong>the</strong>ir own areas?
Is <strong>the</strong> organizational and information processing highly essential to <strong>the</strong> firm’s strategy?
Is <strong>the</strong> management style employee-oriented? Does <strong>the</strong> delegation <strong>of</strong> tasks, authority and
responsibility prevail?
Is <strong>the</strong>re a high-level conformity <strong>of</strong> employee’s and firm’s expectations with one ano<strong>the</strong>r?
The questions used to investigate <strong>the</strong> employees’ awareness regarding <strong>the</strong> strategic objectives (from
<strong>the</strong> management’s point <strong>of</strong> view) and <strong>the</strong> role and <strong>the</strong> importance <strong>of</strong> <strong>the</strong> corporation performance,
were created and adjusted during a focus group with specialists in <strong>the</strong> management <strong>the</strong>ory and
representatives <strong>of</strong> <strong>the</strong> business environment. The final addressed questionnaire is considered to
contain items that lead to relevant results in determining <strong>the</strong> role and <strong>the</strong> importance <strong>of</strong> <strong>the</strong> Human
Capital for <strong>the</strong> company’s performance.
In <strong>the</strong> conducted qualitative research, <strong>the</strong> focus was on interviews. The research consists on an
exploratory component, detailed 30 minutes interviews with six managers chosen from <strong>the</strong> selected
organizations. They have a relevant experience in managing a company in <strong>the</strong> Romanian business
environment. They were interviewed individually, with <strong>the</strong> clear goal <strong>of</strong> identifying <strong>the</strong>ir perception
concerning <strong>the</strong> role and <strong>the</strong> importance <strong>of</strong> <strong>the</strong> success factors in <strong>the</strong> company’s performance. The
interviews were informal and conversational. After presenting <strong>the</strong> field <strong>of</strong> interest, <strong>the</strong>y were asked to
identify <strong>the</strong> first five characteristics that <strong>the</strong>y consider to be relevant for <strong>the</strong> corporate performance.
4. Interpretations and results
These are <strong>the</strong> answers <strong>of</strong> <strong>the</strong> interviewed managers (Figure 1):
Manager 1 Manager 2 Manager 3 Manager 4 Manager 5 Manager 6
Qualified
employees
Clear
goals
Specific
business
concept for
target market
Price Goals
Technological
advance
Figure 1: Managers’ answers
Good objectives Qualified
employees
Product quality Having
experience
Orientation Strategic
options
Geographical
proximity to <strong>the</strong>
customer
Employees’
awareness
Goals Fundamental
market
knowledge
Purpose Clear direction Clear future
plans
Price Product quality Responsibility
Goals
Investments Goals Well known
objectives
Early market
entry
Technological
advance
Qualified
employees
Interpreting <strong>the</strong>ir answers, we can notice that three out <strong>of</strong> four managers related <strong>the</strong> company’s
performance to that <strong>of</strong> Human Capital. More than that, three <strong>of</strong> <strong>the</strong>m mention precisely that efficiency
involves <strong>the</strong> employees’ qualification, because in order to have performance, it is very important for all
<strong>the</strong> workers to be familiar with <strong>the</strong> plans <strong>the</strong>y have to achieve in <strong>the</strong>ir own areas. All <strong>the</strong> managers
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state that performance involves goals, objectives or plans and some <strong>of</strong> <strong>the</strong>m consider that <strong>the</strong> vision
<strong>of</strong> <strong>the</strong> company reflects predictability, direction, a good image in <strong>the</strong> future that can lead to
performance. Also, three managers mention that <strong>the</strong> price and <strong>the</strong> quality <strong>of</strong> <strong>the</strong> products and
services <strong>of</strong>fered directly influence <strong>the</strong> performance <strong>of</strong> <strong>the</strong> organization.
The Romanian managers are aware <strong>of</strong> <strong>the</strong> importance <strong>of</strong> <strong>the</strong> change in value. Intensification in <strong>the</strong>
standards <strong>of</strong> quality <strong>of</strong> life and self-actualization has become a generally declared goal. The higher
need for recognition than possession has become <strong>the</strong> strongest moving force for human performance.
Whereas economic principles made specialization in areas <strong>of</strong> activity essential in <strong>the</strong> past, <strong>the</strong>
situation has been reversed through technologically influenced new orientation structure (Hill, 2007).
Decentralization <strong>of</strong> decision making, creation <strong>of</strong> clear and manageable units, adoption <strong>of</strong> actionoriented
working groups, streng<strong>the</strong>ning <strong>the</strong> ability <strong>of</strong> self-control and <strong>the</strong> integration <strong>of</strong> <strong>the</strong> different
working areas are <strong>the</strong> starting points for <strong>the</strong> present and <strong>the</strong> future. Fur<strong>the</strong>rmore, only such firms
where employees recognize <strong>the</strong> fact that <strong>the</strong>ir performance at work not only contributes to <strong>the</strong> overall
development <strong>of</strong> <strong>the</strong> company, but also to personal development, will be successful.
Concerning <strong>the</strong> quantitative research, data presented below were analyzed in SPSS program, with
identifying information removed. The survey consisted <strong>of</strong> a series <strong>of</strong> questions presented above on
<strong>the</strong> Human Capital’s influence in increasing <strong>the</strong> corporate performance. Measures used in this study
included <strong>the</strong> demographic items (year <strong>of</strong> birth) and <strong>the</strong> geographical distribution. The descriptive
statistics for <strong>the</strong> variable that describe <strong>the</strong> macro-variable Mission and Vision is presented in Table 1.
In Table 1, N represents <strong>the</strong> total number <strong>of</strong> <strong>the</strong> participating managers (50), Min equals 1 and Max
equals 5 represent <strong>the</strong> minimum and <strong>the</strong> maximum values that <strong>the</strong>ir answers range between (1
represents totally disagree and 5, totally agree). The fourth column (Mean) represents <strong>the</strong> mean <strong>of</strong>
<strong>the</strong> answers and varies between 3,81 and 4,39. The majority <strong>of</strong> <strong>the</strong> answers’ means is close to <strong>the</strong>
maximum value (5), except for one variable that have a value less than 4. The Standard Deviation
(column 4) has values less than 1 that means that <strong>the</strong> managers have similar opinions concerning <strong>the</strong>
organizational Human Capital.
Table 1: Descriptive statistics for managers
Descriptive Statistics
N Min Max Mean Standard
deviation
Q1. Active involvement 50 1 5 4,18 ,829
Q2. Ability to recognize <strong>the</strong> strategy change 50 1 5 4,23 ,875
Q3. Information processing and firm’s strategy 50 1 5 4,29 ,845
Q4. Employee-oriented style 50 1 5 4,39 ,891
Q5. Employee’s and firm’s expectations 50 1 5 3,81 ,718
More and more people are joining <strong>the</strong> list <strong>of</strong> future innovators. Innovations are not restricted only to
products but also strongly reflected on markets, target groups and processes. Existing concepts are
being questioned and changed. Innovation flourishes in an environment <strong>of</strong> trust and <strong>of</strong> positive
attitude towards it both by employees and employers. It evolves in humans heads. Here, <strong>the</strong> need to
apply both sides <strong>of</strong> <strong>the</strong> brain is very important. While <strong>the</strong> left side <strong>of</strong> <strong>the</strong> brain logically, analytically,
rationally, linearly, consistently and conservatively processes sensory impressions, <strong>the</strong> right side
operates integrally. It creatively and imaginatively uses experiences acquired from <strong>the</strong> left side. The
“logical” left and “creative” right sides must be simultaneously activated in order to achieve <strong>the</strong> best
possible innovations.
Analyzing <strong>the</strong> Reliability Statistics, <strong>the</strong> value <strong>of</strong> Cronbach’s Alpha is 0.824, more than 0.7, <strong>the</strong>
minimum value that shows <strong>the</strong> relevance <strong>of</strong> <strong>the</strong> obtained answers. We can conclude that <strong>the</strong> answers
are relevant and correctly correlated.
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In Table 2, <strong>the</strong>re are two main aspects for this research: <strong>the</strong> values <strong>of</strong> <strong>the</strong> first column (Scale Mean <strong>of</strong>
Item deleted) and <strong>the</strong> values <strong>of</strong> <strong>the</strong> last column (Cronbach’s Alpha if Item deleted). Taking into
account <strong>the</strong> values obtained, we notice that item Q4 has <strong>the</strong> strongest correlation with <strong>the</strong> scale,
meaning it has a major role in this analysis. The weakest correlation with <strong>the</strong> scale belongs to <strong>the</strong> item
Q2. Thus, we can conclude that <strong>the</strong> organizations have a management style oriented towards <strong>the</strong>
employees. The management delegates tasks, authority and responsibility and <strong>the</strong>y realize that
empowering <strong>the</strong> employees is one <strong>of</strong> <strong>the</strong> best methods <strong>of</strong> increasing corporate performance. Still, not
all <strong>the</strong> managers are convinced that <strong>the</strong>ir philosophy is well understood in <strong>the</strong> company and that most
staff can list <strong>the</strong> organization’s goals relevant to <strong>the</strong> activity and is familiar with <strong>the</strong> plans to achieve in
<strong>the</strong>ir own areas. In Table 2, we can also notice <strong>the</strong> value <strong>of</strong> <strong>the</strong> last column Cronbach’s Alpha if Item
is deleted. The values are less than <strong>the</strong> value <strong>of</strong> 0.824, previously obtained. Thus, we can conclude
that all <strong>the</strong> items that were initially selected are relevant for <strong>the</strong> present study. This value shows us
that removing any <strong>of</strong> <strong>the</strong> selected items means a loss <strong>of</strong> information in analyzing <strong>the</strong> results. In
addition, <strong>the</strong> Significance from <strong>the</strong> ANOVA table equals zero, which means that <strong>the</strong> analysis is
significant at any level.
Table 2: Items statistics for managers
Items Statistics
Scale Mean if Item
Deleted
Scale
Variance if
Item Deleted
Corrected
Item
Total
Correlation
Q1. Active involvement 17,66 6,519 ,678 ,783
Q2. Ability to recognize <strong>the</strong> strategy
change
16,09 5,875 ,578 ,756
Q3. Information processing and firm’s
strategy
16,43 6,124 ,581 ,813
Q4. Employee-oriented style 17,91 6,321 ,601 ,805
Q5. Employee’s and firm’s expectations 16,72 6,498 ,512 ,797
Going back to <strong>the</strong> initial hypo<strong>the</strong>ses, after analyzing <strong>the</strong> data, we can conclude that both hypo<strong>the</strong>ses
are valid and we can state that in <strong>the</strong> analyzed Romanian companies, <strong>the</strong> managers consider that <strong>the</strong>
Human Capital <strong>of</strong> <strong>the</strong> company has an important influence in increasing <strong>the</strong> corporate performance
and <strong>the</strong>y know <strong>the</strong> strategic objectives <strong>of</strong> <strong>the</strong> company and do <strong>the</strong> best in achieving organizational
competitive advantage. In addition, <strong>the</strong> organizational and information processing is essential to <strong>the</strong>
firm’s strategy; still, a better understanding <strong>of</strong> <strong>the</strong> management philosophy by <strong>the</strong> staff <strong>of</strong> <strong>the</strong> company
is needed. This will lead to a better match between <strong>the</strong> employees’ needs and aspirations and <strong>the</strong>
company’s performance.
5. Conclusions
Romanian managers do believe that encouraging <strong>the</strong> development <strong>of</strong> Human Capital is essential,
because this will lead to an increase <strong>of</strong> <strong>the</strong> corporate performance. Each employee, irrespective <strong>of</strong> his
position or place in <strong>the</strong> organization and aside from pr<strong>of</strong>essional and personal qualifications, requires
more and more entrepreneurial capabilities. This must be made conscious to each employee. It is not
in just a company where I am working, it is my company (Griffin, 2006). Organizations that expect this
positive entrepreneurial thinking from his employees must provide stress-free working environment in
which <strong>the</strong>y can optimally apply <strong>the</strong>ir creative potentials and not be hindered by existing barriers.
Moreover, it is a bigger and wider area <strong>of</strong> responsibility which is being transferred over to <strong>the</strong>
employees as it is being expected <strong>of</strong> <strong>the</strong>m to take self-conscious actions. They must be able to act
and react as rational individuals and not just like subordinates. Nowadays, each employee must
assume bigger responsibility when dealing with customers. This is <strong>the</strong> reason why corporate and
entrepreneurial competences are being demanded <strong>of</strong> each employee.
Managers understand <strong>the</strong> importance <strong>of</strong> Human Capital and <strong>the</strong>y are willing to create an
organizational culture that encourages <strong>the</strong> flow <strong>of</strong> information and knowledge within <strong>the</strong> company and
to facilitate <strong>the</strong>ir creation. An effective leader has to focus attention on organizational culture, in
relation to <strong>the</strong> shared beliefs, values and expectations <strong>of</strong> <strong>the</strong> people in <strong>the</strong> organization.
220

Acknowledgments
Anca Mândruleanu
We would like to acknowledge <strong>the</strong> support received from UEFISCSU ROMANIA through PNII
research project ID_1812/2008
References
Andriessen, D. (2004) Making sense <strong>of</strong> Intellectual Capital: designing a method for <strong>the</strong> valuation <strong>of</strong> intangibles,
Elsevier Butterworth – Heinemann, pp. 60 – 69
Bart, C., Baetz, M. (1998) The relationship between mission statements and firm performance: an exploratory
study, Journal <strong>of</strong> Management Studies 35, p. 82
Business Week (1999) p. 12, http://www.businessweek.com
Debowski, S. (2006) Knowledge management. John Wiley & Sons Australia: Sydney.
Dess, G.G., Lumpkin, G.T. Eisner, A.B. (2006) Strategic management. Text and cases. 2nd edition. Boston:
McGraw-Hill Irvin.
Firer, S., Williams, S. M. (2003) Intellectual capital and traditional measures <strong>of</strong> corporate performance, Journal <strong>of</strong>
Intellectual Capital, 4, 348-360.
Goold, M., Campbell, A., Alexander, M. (1994) Corporate Level Strategy, John Wiley & Sons, New York, pp. 19-
67
Griffin, R.W., Moorhead, G. (2006) Fundamentals <strong>of</strong> organizational behavior. Houghton Mifflin Company: Boston,
pp. 178-179.
Hill, C., Jones, G. (2007) Strategic Management, Houghton Mifflin Company, Seventh Edition, New York, p.16
King, W. R., Cleland, D.I. (1979) Strategic Planning and Policy, New York, Van Nostrand Reinhold, p. 124.
Mândruleanu, A. (2010) The Romanian managerial perception <strong>of</strong> <strong>the</strong> organizational mission and vision,
International <strong>Conference</strong> on Business Excellence, October 2010, ISBN 978-973-1747-22-4, pp. 267-270.
Peters, T., Waterman, R. (1982) In search <strong>of</strong> excellence. Lessons from America’s best-run companies. London:
HarperCollinsBusiness, p. 173.
Robbins, S.P., DeCenzo, D.A. (2005). Fundamentals <strong>of</strong> management. Essential concepts and applications,
International Edition. Pearson Education: New Jersey.
Roos, J., Roos, G., Edvinson, L., Dragonetti, N. (1997) Intellectual capital. Managing in <strong>the</strong> new business
landscape. Macmillan:London.
Tung, R., Aycan Z., (2008) Key success factors and indigenous management practices in SMEs in emerging
economies, Journal <strong>of</strong> World Business; Oct2008, Vol. 43 Issue 4, pp. 381-384.
Youndt, M. A., Subramaniam, M. and Snell, S. A. (2004) Intellectual capital pr<strong>of</strong>iles:An examination <strong>of</strong>
investments and returns, Journal <strong>of</strong> Management Studies, 41, 335-361.
Zheng, W. (2005) The Impact <strong>of</strong> Organizational Culture, and Strategy on Knowledge Management Effectiveness
and Organizational Effectiveness, University <strong>of</strong> Minnesota, pp.143-186
221

Eliciting Tacit Knowledge From a Domain <strong>of</strong> Physical Skill
Peter Marshall and Damian Gordon
Dublin Institute <strong>of</strong> Technology, Ireland
pjmarshall@hotmail.com
damian.gordon@dit.ie
Abstract: Knowledge Acquisition (KA) can be seen as a form <strong>of</strong> requirements ga<strong>the</strong>ring where a process is
undertaken to ensure that <strong>the</strong> knowledge engineer fully captures <strong>the</strong> s<strong>of</strong>tware requirements <strong>of</strong> customers before
<strong>the</strong> design process commences. It involves a range <strong>of</strong> approaches that enable knowledge engineers to capture
<strong>the</strong> key knowledge that exists within <strong>the</strong> customers and <strong>the</strong>ir organisation (including <strong>the</strong> processes, procedures,
and documentation). Whilst <strong>the</strong> use <strong>of</strong> automated methods can produce great insights, <strong>the</strong>se techniques are
limited to organisations where a high percentage <strong>of</strong> its organisational knowledge is codified electronically.
Despite <strong>the</strong> shift towards a digital infrastructure, most <strong>of</strong> an organisation‟s knowledge still resides tacitly in <strong>the</strong>
minds <strong>of</strong> its members. To fully exploit this knowledge <strong>the</strong> field <strong>of</strong> Knowledge Elicitation (KE) has been established
to facilitate <strong>the</strong> acquisition <strong>of</strong> knowledge from human sources. A limitation <strong>of</strong> <strong>the</strong> current literature is that <strong>the</strong>
techniques focus primarily on capturing knowledge associated with skills at a cognitive level whereas relatively
little research has been performed in capturing knowledge found in physical activities. In organisations, where
physical tasks are part <strong>of</strong> <strong>the</strong> daily routine, research into acquiring and being able to manage <strong>the</strong>se manual skills
is <strong>of</strong> great importance. This research aims to help bridge <strong>the</strong> gap by applying and modifying existing KE
techniques, traditionally used to acquire knowledge in cognitive tasks, to <strong>the</strong> acquisition <strong>of</strong> knowledge and skills
found in physical tasks. For <strong>the</strong> purpose <strong>of</strong> <strong>the</strong> research, KE techniques were applied to <strong>the</strong> acquisition <strong>of</strong>
knowledge found in <strong>the</strong> performance <strong>of</strong> Mixed Martial Arts (MMA) skills. The experiments were conducted using
an expert trainer in <strong>the</strong> field. A wide cross-section <strong>of</strong> KE techniques were selected in <strong>the</strong> elicitation process and
retrospectively analysed. From <strong>the</strong> analysis, <strong>the</strong> techniques were <strong>the</strong>n critically compared, from which,
techniques that supported <strong>the</strong> verbal articulation <strong>of</strong> procedural and strategic knowledge required to perform <strong>the</strong>se
martial art techniques, were identified. The results from <strong>the</strong> study not only have implications in <strong>the</strong> elicitation <strong>of</strong>
knowledge from <strong>the</strong> field <strong>of</strong> MMA but also in <strong>the</strong> acquisition <strong>of</strong> knowledge in o<strong>the</strong>r fields <strong>of</strong> physical endeavour.
Keywords: knowledge management, knowledge capture, knowledge acquisition, knowledge elicitation, mixed
martial arts
1. Background
One <strong>of</strong> <strong>the</strong> fundamental processes at <strong>the</strong> heart <strong>of</strong> Knowledge Management is Knowledge Acquisition
(KA). KA is defined as <strong>the</strong> process <strong>of</strong> acquiring knowledge from a problem domain. The techniques
used in KA allow knowledge to be collected from different knowledge sources which can be validated
and maintained (Cooke, 2003). These processes are focused on <strong>the</strong> collection, analysis, modelling
and validation <strong>of</strong> knowledge for knowledge engineering and knowledge management projects
(Gronau et al., 2005).
The task <strong>of</strong> performing <strong>the</strong> KA problem is certainly non trivial. The impediments associated with this
undertaking are commonly referred to as <strong>the</strong> Knowledge Acquisition Bottleneck. Wagner (2003)
classifies <strong>the</strong>se issues into three broad categories, narrow bandwidth (i.e. limited number <strong>of</strong> channels
in which knowledge can be acquired), acquisition latency (i.e. length <strong>of</strong> time taken from <strong>the</strong> creation <strong>of</strong>
knowledge to when knowledge is available and ready to be shared) and knowledge inaccuracies (i.e.
mistakes made in extraction <strong>of</strong> knowledge from knowledge sources). Given <strong>the</strong>se challenges, KA
consists <strong>of</strong> a set <strong>of</strong> processes that aim to address <strong>the</strong>se limitations by providing <strong>the</strong> knowledge
engineer with a set <strong>of</strong> light-weight, knowledge-level, easy-to-use techniques that allow <strong>the</strong> engineer to
quickly obtain knowledge from a range <strong>of</strong> sources, and cross-validate <strong>the</strong>m to ensure accuracy.
Turban and Aronson (1998) categorise KA techniques into three distinct groups. The first group are
known as <strong>the</strong> automated techniques. These methods use tools, such as data mining, neural networks,
fuzzy logic and genetic algorithms, to address problems associated with KA latency and KA accuracy
by reducing <strong>the</strong> time taken and expense incurred in <strong>the</strong> KA phase. Whilst <strong>the</strong> popularity <strong>of</strong> such
methods has increased significantly over <strong>the</strong> past 20 years, <strong>the</strong>se techniques are reliant on <strong>the</strong> quality
and availability <strong>of</strong> digital sources (e.g. organisational corpora, databases, etc). Ano<strong>the</strong>r fundamental
problem associated with <strong>the</strong>se techniques is <strong>the</strong> omission <strong>of</strong> human expertise from <strong>the</strong> modelling
process. A survey conducted in 2000 estimated that over 90 percent <strong>of</strong> organisational knowledge is
not codified but resides tacitly an organisations entities (Bonner, 2000). By eliminating <strong>the</strong>se sources
from <strong>the</strong> KA process, <strong>the</strong>y are decreasing <strong>the</strong> bandwidth significantly, impacting on <strong>the</strong> accuracy <strong>of</strong>
KA initiatives. To address this problem, Turban and Aronson (1998), identified a fur<strong>the</strong>r two types <strong>of</strong>
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Peter Marshall and Damian Gordon
KA techniques which incorporate human sources into <strong>the</strong> KA process, known as semi-automated and
manual KA techniques.
Semi-automated techniques support <strong>the</strong> KA process in one <strong>of</strong> two ways. The first way is by providing
human sources with tools that facilitate <strong>the</strong> creation <strong>of</strong> knowledge bases with minimal assistance from
knowledge engineers, thus reducing <strong>the</strong> effects <strong>of</strong> latency. An example <strong>of</strong> this is found in Marshall and
Bandar‟s (1999) work on <strong>the</strong> acquisition <strong>of</strong> medical terms from medical corpora. From <strong>the</strong>ir work, <strong>the</strong>y
were able to automate <strong>the</strong> extraction <strong>of</strong> candidate terms which were <strong>the</strong>n presented to a
lexicographer for validation. These types <strong>of</strong> tools improve <strong>the</strong> quality <strong>of</strong> acquired knowledge, through
explicit sources, by using an expert in <strong>the</strong> field, to validate results. The second type <strong>of</strong> semiautomated
techniques assists knowledge engineers to execute <strong>the</strong> KA activities in a more efficient
and effective manner by minimising time spent with <strong>the</strong> subject matter expert (SME); again
addressing issues <strong>of</strong> latency. Examples <strong>of</strong> <strong>the</strong>se types <strong>of</strong> tools, includes techniques such as
repository grid analysis whereby key attributes are identified and are weighted in <strong>the</strong> decision making
process. These techniques benefit from <strong>the</strong> use <strong>of</strong> human sources in <strong>the</strong> KA process <strong>the</strong>refore
increasing <strong>the</strong> bandwidth <strong>of</strong> knowledge sources. However Turban and Aronson (1998) sees <strong>the</strong>
adoption <strong>of</strong> <strong>the</strong>se tools as best suited to well-structured problems such as diagnosis and classification
but warns such techniques do not provide a deep understanding <strong>of</strong> <strong>the</strong> decision making process.
The final set, <strong>of</strong> KA techniques, are <strong>the</strong> manual methods (Turban and Aronson, 1998). These
techniques allow knowledge engineers to capture knowledge from both knowledge artefacts and
human sources in order to populate knowledge bases. In creating new knowledge from knowledge
artefacts, one way in which this can be achieved is a through a systematic review. These reviews
focus on summarising a body <strong>of</strong> literature by identifying, appraising, selecting and syn<strong>the</strong>sising
research evidence. From this, conclusions can be reached that are relevant to <strong>the</strong> questions being
asked. In academia, an example <strong>of</strong> this would be a literature review, in which, a body <strong>of</strong> work, is
reviewed; citing <strong>the</strong> current knowledge in <strong>the</strong> field. In terms <strong>of</strong> <strong>the</strong> KA bottleneck, dealing with only
explicit artefacts, greatly reduces <strong>the</strong> bandwidth <strong>of</strong> sources in which <strong>the</strong>se techniques operate and
eliminate <strong>the</strong> human resources from <strong>the</strong> KA task. To address this, a set <strong>of</strong> techniques which focus on
<strong>the</strong> acquisition <strong>of</strong> knowledge from human sources are required. The field <strong>of</strong> study revolving around
<strong>the</strong> acquisition <strong>of</strong> knowledge from human sources is known as Knowledge Elicitation (KE).
The KE toolkit comprises <strong>of</strong> a variety <strong>of</strong> techniques that aim to elicit knowledge human sources. In
using KE techniques, <strong>the</strong> knowledge engineer is able to access a richness <strong>of</strong> detail which cannot be
achieved using automated or semi-automated methods. Despite <strong>the</strong> potential benefits <strong>of</strong> KE
techniques, <strong>the</strong>se techniques are slow, expensive and are <strong>of</strong>ten subject to bias especially when
dealing with a single expert. Multiple sources can be employed to increase <strong>the</strong> accuracy <strong>of</strong> <strong>the</strong>
knowledge acquired by eliminating bias. However a significant price is paid in terms <strong>of</strong> latency, which
is also impacted by <strong>the</strong> associated with <strong>the</strong> depth <strong>of</strong> analysis required to externalise new knowledge.
Despite <strong>the</strong> problems associated, organisations who wish to externalise <strong>the</strong>ir knowledge must engage
in this process.
2. Knowledge acquisition for physical skills
From a review <strong>of</strong> literature <strong>of</strong> KE techniques, <strong>the</strong>re is little evidence that research has been conducted
in <strong>the</strong> acquisition <strong>of</strong> skill based knowledge. Whilst some authors made reference to <strong>the</strong> applicability <strong>of</strong>
KE techniques to <strong>the</strong> acquisition <strong>of</strong> knowledge in physical activities, little was actually shown. In order
to address this balance, <strong>the</strong> research in this paper aimed to test this hypo<strong>the</strong>sis. For <strong>the</strong> purposes <strong>of</strong>
<strong>the</strong> experiments, <strong>the</strong> procedural knowledge and strategic knowledge required to perform Mixed
Martial Arts (MMA) techniques were selected as <strong>the</strong> type <strong>of</strong> knowledge to be acquired.
MMA is a full contact combat sport that allows a wide variety <strong>of</strong> fighting techniques, from both
traditional and non-traditional martial arts, to be used in competition. The rules permit athletes to
combine striking and grappling techniques, whilst fighting from a standing position as well as on <strong>the</strong>
ground. This allows martial artists from different backgrounds to compete on an equal playing field.
The sport <strong>of</strong> MMA is a relatively new discipline which has evolved from traditional martial arts.
Whereas <strong>the</strong> early MMA practitioners trained exclusively in one art (e.g. Wrestling, Boxing, Karate,
etc.), today's modern mixed martial artists have had to embrace techniques taken from various
fighting disciplines. Fighters who are unable to successfully combine techniques from a wide range <strong>of</strong>
disciplines are at a distinct disadvantage.
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Peter Marshall and Damian Gordon
MMA schools are not unlike any o<strong>the</strong>r organisation; <strong>the</strong>y have an abundance <strong>of</strong> knowledge in all
aspects <strong>of</strong> <strong>the</strong>ir business. Knowledge is required at a high level in strategic decision making, as well
as everyday administrative tasks; all <strong>the</strong> way through to <strong>the</strong> grassroots coaching <strong>of</strong> its athletes. The
relatively recent commercialisation <strong>of</strong> sport has seen <strong>the</strong> potential financial gains increase. With so
much at stake, organisations must look at ways in which organisational knowledge can be exploited in
order to gain a competitive advantage. As <strong>the</strong> sport evolves, old organisational models have been
replaced by new ones. Sports managers and coaches must look at <strong>the</strong> wealth <strong>of</strong> knowledge with
exists both internally and externally to <strong>the</strong>ir organisations and find ways to harness it in order to
benefit <strong>the</strong> athletes, <strong>the</strong> teams, <strong>the</strong> coaching staff and <strong>the</strong> organisation (Toohey, Halbwirth 2004).
When considering <strong>the</strong> coaching dimension <strong>of</strong> <strong>the</strong>se organisations, difficulties arise in <strong>the</strong> acquisition <strong>of</strong>
this knowledge, when <strong>the</strong> student fails to pick up <strong>the</strong> various nuances required to accurately model
<strong>the</strong> tacit knowledge <strong>of</strong> <strong>the</strong> instructor. The difference between a student‟s knowledge and that <strong>of</strong> <strong>the</strong>
expert‟s level is known as <strong>the</strong> “zone <strong>of</strong> proximal development” (Vygotsky, 1978). The hypo<strong>the</strong>sis for
our research is that elicitation techniques from <strong>the</strong> field <strong>of</strong> knowledge management can help reduce
this gap, by exposing <strong>the</strong> tacit knowledge <strong>of</strong> an expert. To achieve that aim, <strong>the</strong> following objectives
were established. The first was to conduct a series <strong>of</strong> experiments in which KE techniques, found in
<strong>the</strong> literature review, would be applied to <strong>the</strong> acquisition <strong>of</strong> MMA techniques. The results <strong>of</strong> <strong>the</strong>se
experiments would be presented and critically analysed. From this <strong>the</strong> conclusions will be drawn and
future work in <strong>the</strong> terms <strong>of</strong> <strong>the</strong> research will be identified.
3. Methodology
The MMA organisation in this study is Team Ryano in Dublin. Team Ryano is a MMA academy that
coaches students to compete in MMA competitions. Knowledge is a key asset extensively used in all
aspects <strong>of</strong> its business. Instructors from different disciplines use <strong>the</strong>ir knowledge to teach skills, help
<strong>the</strong>ir athletes apply strategies during competitions and improve <strong>the</strong>ir performance. The athletes
<strong>the</strong>mselves use this knowledge to acquire new and improve existing skills. The organisation benefits
from <strong>the</strong> collective knowledge <strong>of</strong> <strong>the</strong> group in tasks as diverse as scouting to providing dietary
guidance for <strong>the</strong>ir athletes. This knowledge provides <strong>the</strong> organisation with a competitive advantage
which has led to success on both national and international level.
The core service <strong>of</strong> Team Ryano is to teach students skills required for participation in <strong>the</strong> various
martial arts that are taught. In analysing <strong>the</strong> acquisition <strong>of</strong> knowledge in Team Ryano, <strong>the</strong>re exists
many informal channels in which knowledge is acquired (e.g. socialisation between its group
members, internalisation <strong>of</strong> knowledge artefacts). However for <strong>the</strong> most part, knowledge is acquired at
an individual and group level through <strong>the</strong> use <strong>of</strong> <strong>the</strong> traditional apprenticeship model (Vygotsky,
1978). In this model, students acquire techniques and strategies in <strong>the</strong> sport specific courses, through
an observation phase, a coaching phase and through practice.
The experiments were conducted at <strong>the</strong> Team Ryano‟s training facility in Dublin. The following steps
were performed.
3.1 Selecting valuable knowledge
The first task is <strong>the</strong> identification <strong>of</strong> valuable knowledge. The selection process is a key consideration
at <strong>the</strong> onset <strong>of</strong> KE activities. There is little point in eliciting knowledge that could be easily found online
or in textbooks, journals, reports, etc. (Okafor & Osuagwu, 2006). In rapidly changing domains, <strong>the</strong>
selection process is fur<strong>the</strong>r complicated when elicited knowledge becomes redundant before it has
been made explicit and distributed (ibid).
For <strong>the</strong> experiments, two very different martial arts techniques were selected that were used not only
by <strong>the</strong> MMA group but also by <strong>the</strong> Brazilian Jiu Jitsu (BJJ) group within <strong>the</strong> organisation. The first
technique is a throw in Judo known as Tai-Otoshi; a throw used to take an opponent down to <strong>the</strong>
ground. The Tai-otoshi can be employed by all weight categories. The throw is highly versatile in that
it can be performed direct attack or can be employed in combination with o<strong>the</strong>r throws as part <strong>of</strong> a
strategy to take an opponent to <strong>the</strong> ground. Whilst more extensively used in Judo and BJJ, it has
been successfully employed in MMA. The second technique that was selected was <strong>the</strong> arm-bar. This
technique aims to hyperextend <strong>the</strong> elbow joint which can result in muscle, tendon and ligament
damage, even dislocation, or bone fractures, if <strong>the</strong> opponent does not submit at <strong>the</strong> point <strong>of</strong>
application. This technique is perhaps <strong>the</strong> most versatile <strong>of</strong> all <strong>the</strong> submission techniques and can be
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Peter Marshall and Damian Gordon
employed in numerous ways. By choosing two significantly different techniques it is possible to test
how suitable <strong>the</strong> different KE techniques are in different contexts during <strong>the</strong> elicitation phase.
3.2 Selecting knowledge sources
The next task is to select an appropriate knowledge source for <strong>the</strong> experiments. Because <strong>of</strong>
difficulties associated with <strong>the</strong> availability <strong>of</strong> multiple experts in <strong>the</strong> field, a single source was used. In
selecting in an expert for <strong>the</strong> study, it was essential that <strong>the</strong> expert selected has <strong>the</strong> two
characteristics identified previously for an expert coach i.e. playing experience and teaching
experience (Schempp, 2000). Andy Ryan, <strong>the</strong> head coach <strong>of</strong> Team Ryano, agreed to be <strong>the</strong> SME in
<strong>the</strong> experiments. Whilst <strong>the</strong> use <strong>of</strong> a single source has been identified as risk for bias, Andy‟s
extensive knowledge <strong>of</strong> <strong>the</strong> Judo, BJJ and MMA provides a rich source <strong>of</strong> knowledge. In using <strong>the</strong>
head coach <strong>of</strong> Team Ryano, who has over thirty years experience in <strong>the</strong> field, it is possible to fully
encapsulate <strong>the</strong> knowledge contained in <strong>the</strong> two techniques.
3.3 Initial demonstrations <strong>of</strong> knowledge
As a means <strong>of</strong> evaluating <strong>the</strong> experiments, <strong>the</strong> SME was recorded performing an initial demonstration
<strong>of</strong> <strong>the</strong> two MMA techniques. The demonstrations focused on <strong>the</strong> knowledge typically delivered during
a demonstration <strong>of</strong> knowledge in <strong>the</strong> observation phase <strong>of</strong> a class and served as <strong>the</strong> benchmark for
which <strong>the</strong> generated protocols <strong>of</strong> <strong>the</strong> KE sessions were compared against.
3.4 Selecting <strong>of</strong> KE techniques
In selecting appropriate techniques for KE, Cooke (2003) observed that “no technique is guaranteed
to result in a complete and accurate representation <strong>of</strong> an expert's knowledge” and that selecting KE
techniques was an empirical and iterative process. No single KE technique can extract an expert‟s
knowledge in its entirety; however each is capable <strong>of</strong> providing rich information relating to concepts,
relations, facts, rules, and strategies relevant to <strong>the</strong> domain in question (ibid).
As stated in <strong>the</strong> goals section, <strong>the</strong> aim was to elicit strategic and procedural knowledge <strong>of</strong> techniques
in MMA. The KE techniques were selected based on <strong>the</strong> following criteria. Techniques selected to
acquire procedural knowledge required to respect <strong>the</strong> order <strong>of</strong> steps in which <strong>the</strong>y were performed.
From <strong>the</strong> standpoint <strong>of</strong> strategic knowledge, it was important that <strong>the</strong> KE technique provided <strong>the</strong> SME
with <strong>the</strong> a series <strong>of</strong> scenarios in which <strong>the</strong> various environmental variables could be identified in order
to understand <strong>the</strong> decision making processes and conditions required in order to successfully perform
<strong>the</strong>se techniques can be performed. O<strong>the</strong>r considerations when selecting <strong>the</strong> techniques is that <strong>the</strong>
elicitation <strong>of</strong> knowledge is from a single expert in <strong>the</strong> field. The selection process is fur<strong>the</strong>r
complicated due to <strong>the</strong> physical nature <strong>of</strong> <strong>the</strong> knowledge being demonstrated. Techniques such as
card sorting and repository grids are more difficult to implement given <strong>the</strong> constraints <strong>of</strong> <strong>the</strong> field.
3.4.1 Output - input - middle interview
The first KE technique selected was based on <strong>the</strong> Output-Input-Middle (OIM) interview technique
(Becerra-Fernandez et al., 2004). In performing this task, <strong>the</strong> Knowledge Engineer asks <strong>the</strong> SME to
establish <strong>the</strong> goals <strong>of</strong> <strong>the</strong> skill being elicited (i.e. outputs). Next, <strong>the</strong> SME identifies <strong>the</strong> environmental
variables which trigger a solution (i.e. inputs). The final step was to determine <strong>the</strong> procedural steps
between <strong>the</strong> inputs and <strong>the</strong> outputs (i.e. <strong>the</strong> middle). For <strong>the</strong> purposes <strong>of</strong> <strong>the</strong>se experiments a
modified version was used which allowed <strong>the</strong> SME to perform a physical demonstration <strong>of</strong> each step
to illustrate <strong>the</strong> output, input and middle elements <strong>of</strong> <strong>the</strong>ir knowledge. From this technique, <strong>the</strong> aim
was to elicit procedural knowledge <strong>of</strong> <strong>the</strong> steps required to perform <strong>the</strong> techniques, strategic
knowledge in terms <strong>of</strong> <strong>the</strong> environmental conditions in which <strong>the</strong> technique can be performed and
goal knowledge in terms <strong>of</strong> <strong>the</strong> purpose for <strong>the</strong> utilisation <strong>of</strong> <strong>the</strong> technique.
3.4.2 Commentary technique
The next KE technique was <strong>the</strong> Commentary method. In this task, <strong>the</strong> SME provides a running
commentary <strong>of</strong> a typical task performed in <strong>the</strong> problem domain. This protocol can be employed in one
<strong>of</strong> two different ways (Hannu and Pallab, 2000), ei<strong>the</strong>r concurrently (i.e. providing commentary whilst
<strong>the</strong> task is being performed) or retrospectively (i.e. after <strong>the</strong> task has been performed). In <strong>the</strong>
retrospective approach, <strong>the</strong> SME is shown a protocol <strong>of</strong> task behaviour, and asked to provide
commentary on <strong>the</strong> thinking processes in performance <strong>of</strong> <strong>the</strong> task. This can occur ei<strong>the</strong>r through self-
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reporting or as means <strong>of</strong> critiquing <strong>the</strong> performance <strong>of</strong> o<strong>the</strong>rs. An advantage <strong>of</strong> <strong>the</strong> retrospective
approach is that video can be paused or run at slow speed to allow time for <strong>the</strong> SME to provide full
explanation <strong>of</strong> <strong>the</strong> decision making processes involved. This is particularly useful in dynamic domains
(ibid). In <strong>the</strong>se experiments, <strong>the</strong> retrospective version is used. The SME will be presented with a
series <strong>of</strong> videos <strong>of</strong> <strong>the</strong> associated techniques being performed in a competition. The expert is <strong>the</strong>n
asked to provide a commentary, critiquing <strong>the</strong> techniques <strong>of</strong> o<strong>the</strong>rs as <strong>the</strong>y perform. To minimise <strong>the</strong>
impact <strong>of</strong> <strong>the</strong> knowledge acquisition bottleneck, demonstrations <strong>of</strong> technique will not recorded by <strong>the</strong>
knowledge engineer but randomly selected from examples <strong>of</strong> <strong>the</strong> techniques being successfully
performed from <strong>the</strong> Internet.
3.4.3 Triadic elicitation using video technology
Triadic elicitation is a KE technique used to capture <strong>the</strong> way in which an expert views <strong>the</strong> concepts in
a domain. Traditionally, a knowledge engineer populates an experimental set with concepts from <strong>the</strong>
domain under consideration during <strong>the</strong> KE session. Next <strong>the</strong> knowledge engineer presents three
random concepts within <strong>the</strong> set to SME. Upon presentation <strong>of</strong> <strong>the</strong>se concepts, <strong>the</strong> SME selects two <strong>of</strong>
<strong>the</strong> three that <strong>the</strong>y would consider <strong>the</strong> most similar and explain why. This differentiating factor will
identify a characteristic <strong>of</strong> <strong>the</strong> overall set <strong>of</strong> concepts being considered. In this research, a modified
version <strong>of</strong> this technique was presented in which <strong>the</strong> concepts from <strong>the</strong> field were replaced by video
variations <strong>of</strong> <strong>the</strong> MMA technique being performed in competition. As with <strong>the</strong> Commentary technique
detailed above, randomly selected videos found online will be used, thus making <strong>the</strong> experiment
repeatable as well as to minimise <strong>the</strong> effect <strong>of</strong> <strong>the</strong> knowledge acquisition bottleneck. Although <strong>the</strong>
traditional method <strong>of</strong> triadic elicitation does not elicit procedural knowledge, it was <strong>of</strong> interest to see
how <strong>the</strong> modified version exposed different types <strong>of</strong> knowledge during <strong>the</strong> KE sessions.
3.4.4 Cognitive walk-through
The Cognitive Walk-Through is a KE technique where <strong>the</strong> SME articulates <strong>the</strong>ir knowledge
concurrently whilst working through a problem or a task (Wright & Ayton, 1987). Similar to <strong>the</strong>
Commentary technique, this method is performed concurrently and enables knowledge engineers to
observe <strong>the</strong> thought process <strong>of</strong> <strong>the</strong> SME during <strong>the</strong> performance <strong>of</strong> <strong>the</strong> task. This is a powerful
technique in <strong>the</strong> identification <strong>of</strong> knowledge elements and steps. According to Ericsson and Simon
(1980), <strong>the</strong> concurrent verbalisation element provides a complete report <strong>of</strong> <strong>the</strong> knowledge being
demonstrated as no thought, feeling, or action is omitted from <strong>the</strong>ir account. In tasks where significant
cognitive effort is required, this method may interfere with <strong>the</strong> SME‟s performance. As a means <strong>of</strong>
negating this limitation, a retrospective variant can be employed where <strong>the</strong> SME provides a
commentary <strong>of</strong> <strong>the</strong>ir thought processes whilst observing <strong>the</strong>mselves performing <strong>the</strong> task. However
this variant does not provide <strong>the</strong> knowledge engineer direct access to <strong>the</strong> decision making process as
it happens. For <strong>the</strong> purpose <strong>of</strong> this research, <strong>the</strong> concurrent version <strong>of</strong> <strong>the</strong> technique was employed.
3.5 Analysis <strong>of</strong> captured knowledge
Once <strong>the</strong> KE sessions were completed, <strong>the</strong> next step was to analyse <strong>the</strong> produced protocol from <strong>the</strong>
KE sessions. For each technique, a transcript was produced from <strong>the</strong> resulting protocol. The next step
in will be to analyse <strong>the</strong> non-verbal articulations, <strong>the</strong> movements used by SME in <strong>the</strong> demonstration <strong>of</strong>
technique were articulated and <strong>the</strong>n merged. From this, <strong>the</strong> intersections from this produce a model <strong>of</strong>
<strong>the</strong> knowledge being demonstrated.
3.6 Metrics for comparison
Once <strong>the</strong> individual knowledge artefacts had been analysed <strong>the</strong> next step will be to compare <strong>the</strong>
different techniques against o<strong>the</strong>r. In this we can make interesting comparisons between <strong>the</strong> KE
elicitation techniques as well as <strong>the</strong> initial demonstration <strong>of</strong> technique. As described above two types
<strong>of</strong> knowledge were identified as being <strong>the</strong> aim <strong>of</strong> <strong>the</strong> elicitation sessions, procedural knowledge, in
terms <strong>of</strong> <strong>the</strong> steps required to perform <strong>the</strong> techniques, and strategic knowledge, in terms <strong>of</strong> <strong>the</strong>
situations <strong>of</strong> when <strong>the</strong> <strong>the</strong>se techniques could be performed. The following measures were extracted
from <strong>the</strong> elicitation sessions.
Procedural Knowledge articulated verbally
Procedural knowledge articulated non-verbally
Strategic knowledge articulated verbally
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Strategic knowledge articulated non-verbally
Peter Marshall and Damian Gordon
From <strong>the</strong>se findings, a series <strong>of</strong> graphs will be created as a means <strong>of</strong> comparison.
Procedural steps required to perform <strong>the</strong> arm-bar technique
Strategic knowledge found for <strong>the</strong> arm-bar technique
Procedural steps required to perform <strong>the</strong> tai-otoshi throw
Strategic knowledge found for <strong>the</strong> tai-otoshi throw
4. Results
The results are presented considering <strong>the</strong> two techniques (Arm-Bar and Tai-Otoshi) from <strong>the</strong>
perspectives <strong>of</strong> both Procedural knowledge and Strategic knowledge.
4.1 Elicitation <strong>of</strong> procedural knowledge for <strong>the</strong> Arm-Bar technique
The first comparison <strong>of</strong> elicited knowledge was <strong>the</strong> comparison <strong>of</strong> techniques in eliciting procedural
steps required to perform <strong>the</strong> arm bar technique. From <strong>the</strong> results in figure 1, <strong>the</strong> initial demonstration
<strong>of</strong> technique identified nine steps, six <strong>of</strong> which were articulated verbally and three non-verbally. The
cognitive walkthrough not only identified <strong>the</strong> nine steps but <strong>the</strong> steps were verbally identified. With <strong>the</strong>
OIM demonstration, only five <strong>of</strong> <strong>the</strong> nine steps were identified and only one <strong>of</strong> those articulated
verbally. The triadic elicitation and commentary methods failed to identify any <strong>of</strong> <strong>the</strong> steps.
Procedural Steps Identified
Verbal
Non Verbal
Results From Elicitation
0 2 4 6 8 10
Number <strong>of</strong> Steps
Identified
Cognitive WalkThrough
Triadic Elicitation
Commentary
OIM
Initial Demonstration
Figure 1: Comparison <strong>of</strong> verbal and non-verbal procedural steps elicited for <strong>the</strong> Arm Bar Technique
4.2 Elicitation <strong>of</strong> procedural knowledge for <strong>the</strong> Tai-Otoshi technique
The next comparison <strong>of</strong> elicited knowledge was <strong>the</strong> comparison <strong>of</strong> techniques in eliciting procedural
steps required to perform <strong>the</strong> tai-otoshi throw. From <strong>the</strong> results in figure 2, <strong>the</strong> initial demonstration <strong>of</strong>
technique identified seven steps, five <strong>of</strong> which were articulated verbally and two non-verbally. As can
be seen in <strong>the</strong> results, <strong>the</strong> initial demonstration was superior to <strong>the</strong> elicitation methods. In <strong>the</strong>
cognitive walkthrough, two were verbally identified and <strong>the</strong> o<strong>the</strong>r five, non-verbally. In <strong>the</strong> OIM
demonstration, four were identified and three non-verbally. Once again, <strong>the</strong> triadic elicitation and
commentary methods failed to identify any <strong>of</strong> <strong>the</strong> steps.
4.3 Elicitation <strong>of</strong> strategic knowledge for <strong>the</strong> Arm-bar technique
The third comparison <strong>of</strong> elicited knowledge was <strong>the</strong> comparison <strong>of</strong> techniques in eliciting strategic
knowledge required to perform <strong>the</strong> arm-bar technique. In <strong>the</strong> initial demonstration, three methods
were identified non-verbally. In <strong>the</strong> OIM method, two techniques were shown both <strong>of</strong> which were
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Peter Marshall and Damian Gordon
articulated. From <strong>the</strong> commentary method, we saw five different variations <strong>of</strong> <strong>the</strong> arm-bar being
applied. As <strong>the</strong> cognitive walkthrough was performed from <strong>the</strong> position <strong>of</strong> arm-bar application, it
<strong>of</strong>fered no strategic knowledge <strong>of</strong> when <strong>the</strong> arm-bar could be employed <strong>the</strong>refore it was eliminated
from this section <strong>of</strong> <strong>the</strong> results. The triadic elicitation method failed to identify any strategic knowledge.
Procedural
Steps
Identified
Verbal
Non Verbal
Results From Elicitation
0 2 4 6 8
Number <strong>of</strong> Steps Identified
Cognitive WalkThrough
Triadic Elicitation
Commentary
OIM
Initial Demonstration
Figure 2: Comparison <strong>of</strong> verbal and non-verbal procedural steps elicited for <strong>the</strong> Arm Bar Technique
Strategic Steps Identified
Verbal
Non Verbal
Results From Elicitation
0 1 2 3 4 5
Number <strong>of</strong> Steps
Identified
Cognitive WalkThrough
Triadic Elicitation
Commentary
OIM
Initial Demonstration
Figure 3: Strategic knowledge articulated during <strong>the</strong> initial demonstration <strong>of</strong> <strong>the</strong> Arm-Bar technique
4.4 Elicitation <strong>of</strong> strategic knowledge for <strong>the</strong> Tai-Otoshi technique
The final comparison <strong>of</strong> elicited knowledge was <strong>the</strong> comparison <strong>of</strong> techniques in eliciting strategic
knowledge required to perform <strong>the</strong> tai-otoshi technique. The initial demonstration identified two ways
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Peter Marshall and Damian Gordon
in which <strong>the</strong> throw could be performed using <strong>the</strong> non-traditional grips and traditional method grips.
The cognitive walkthrough and <strong>the</strong> OIM methods only generate one each. The commentary method
identified four.
Procedural Steps Identified
Verbal
Non Verbal
Results From Elicitation
0 1 2 3 4
Number <strong>of</strong> Steps
Identified
Cognitive WalkThrough
Triadic Elicitation
Commentary
OIM
Initial Demonstration
Figure 4: Strategic knowledge articulated during <strong>the</strong> initial demonstration <strong>of</strong> <strong>the</strong> Tai-Otoshi technique
5. Discussion
In selecting <strong>the</strong>se techniques, many <strong>of</strong> <strong>the</strong>m were adapted from <strong>the</strong>ir original use. This approach
provided much discussion during <strong>the</strong> experiment phase. In terms <strong>of</strong> <strong>the</strong> goals established at <strong>the</strong> onset
<strong>of</strong> our experiments, <strong>the</strong> triadic elicitation variation failed to elicit knowledge that aided <strong>the</strong> capture <strong>of</strong>
strategic or procedural knowledge pertaining to <strong>the</strong> techniques. The results from this technique served
more to detail <strong>the</strong> important factor a SME might consider when observing variations <strong>of</strong> <strong>the</strong> techniques
being performed. The findings from our experiments are <strong>of</strong> great interest but not in <strong>the</strong> context <strong>of</strong> <strong>the</strong>
goals established at <strong>the</strong> onset <strong>of</strong> our research. From our results, <strong>the</strong> cognitive walkthrough in <strong>the</strong> armbar
experiment was particularly successful in generating verbal articulations. The output-input-method
was less successful in <strong>the</strong> arm-bar demonstration as fewer steps were identified in terms <strong>of</strong> <strong>the</strong> steps.
The commentary elicitation provided a good source for <strong>the</strong> identification <strong>of</strong> strategic knowledge in
terms <strong>of</strong> when <strong>the</strong>se techniques can be employed. The results from this experiment are a useful tool
for practitioners in identifying situations in which techniques can be employed. One way in which <strong>the</strong>
commentary could have been improved would have been <strong>the</strong> inclusion <strong>of</strong> failed attempts in
performing <strong>the</strong> techniques. An initial investigation into acquiring <strong>the</strong>se types <strong>of</strong> techniques from online
sources was attempted. Finding examples <strong>of</strong> error in performance was difficult as it seemed that
practitioners are unwilling to post examples <strong>of</strong> poor technique. Extensive analysis <strong>of</strong> videos would
have been required in this task which would have resulted in a significant impact on <strong>the</strong> knowledge
acquisition bottleneck. It would have also made <strong>the</strong> experiments more difficult to repeat.
6. Conclusions and future work
The research performed serves as a good foundation in which future elicitation sessions in more <strong>of</strong>
<strong>the</strong> organisation knowledge can be externalised. In addition, it was evident in <strong>the</strong> elicitation sessions
that <strong>the</strong>se some <strong>of</strong> <strong>the</strong>se techniques were particularly versatile. It is envisaged that <strong>the</strong>se techniques
could be easily used in o<strong>the</strong>r sports and physical activity. Ano<strong>the</strong>r path for future work is <strong>the</strong> potential
for embedding <strong>the</strong> externalised knowledge in a format which could be easily distributed to <strong>the</strong> Team
Ryano community and beyond (e.g. an instructional video). Fur<strong>the</strong>r experiments will focus on eliciting
more <strong>of</strong> <strong>the</strong> organisation‟s tacit knowledge. The strategies and <strong>the</strong> techniques used at Team Ryano
are <strong>of</strong> great importance to <strong>the</strong> individuals within <strong>the</strong> club. In eliciting this knowledge and externalising
it, this format allows for knowledge to be easily distributed to all members <strong>of</strong> <strong>the</strong> groups. As more and
more students at Team Ryano rise from novice status to expert status, <strong>the</strong>re will be <strong>the</strong> opportunity to
use <strong>the</strong> group elicitation methods e.g. <strong>the</strong> de Bono Six Thinking Hats technique (DeBono 1985).
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These methods would bring a greater depth to <strong>the</strong> externalised knowledge by fostering <strong>the</strong> opinion <strong>of</strong>
all <strong>the</strong> participants leading to high quality knowledge artefacts.
Acknowledgements
We would like to thank Andy Ryan and Team Ryano for all <strong>the</strong>ir help and co-operation in conducting
<strong>the</strong> research.
References
Becerra-Fernandez, I., Gonzalez, A., & Sabherwal, R., 2004. Knowledge management: Challenges, solutions,
and technologies, (1st ed.). Upper Saddle River ,NJ: Prentice Hall
Bonner, D. 2000. Knowledge from Theory to Practice to Golden Opportunity, American Society for Training and
Development, September-October, 12-13.
Cooke, F. L. 2003. Maintaining Change: The Maintenance Function and <strong>the</strong> Change Process, New Technology,
Work and Employment
Davenport, T. H. Prusak, L. 1998. Working Knowledge: How Organizations Manage What They Know,
Cambridge, MA: Harvard Business School Press.
DeBono, E., 1985. Six Hats Thinking, Little, Brown and Co, Boston, MA
Ericsson, K.A., & Simon, H.A. (1980). Verbal Reports as Data. Psychological Review
Gronau, N. Korf, R. Müller, C. 2005. KMDL - Capturing, Analysing and Improving Knowledge-Intensive Business
Processes, Journal <strong>of</strong> Computer Science
Hannu, K. Pallab, P. 2000. A Comparison <strong>of</strong> Concurrent and Retrospective Verbal Protocol Analysis, American
Journal <strong>of</strong> Psychology
Marshall, P. Bandar, Z. 1999. Working Towards Connectionist Modelling <strong>of</strong> Term Recognition, Lecture Notes in
Computer Science, 1625, Springer Berlin / Heidelberg.
Okafor, E.C. & Osuagwu, C.C. 2006. The underlying issues in knowledge elicitation. InterdisciplinaryJournal <strong>of</strong>
Information, Knowledge, and Management
Scarborough, H. 1996. Business Process Re-Design: The Knowledge Dimension.
Toohey, K. and Halbwirth. S., 2004 „Sydney Olympic Games Case Study‟ in Allen, J et al, Festival and Special
Event Management <strong>3rd</strong> ed. Milton, Qld.: John Wiley and Sons
Turban, E. Aronson, J.E. 1998. Decision Support Systems and Intelligent Systems (5th edition), Upper Saddle
River, Prentice Hall.
Vygotsky, L.S. 1978. Mind and society: The development <strong>of</strong> higher psychological processes. Cambridge, MA:
Harvard University Press
Wagner, W. 2003. Knowledge Acquisition, Villanova University
Wright, G and Ayton, P. 1987, Eliciting and Modelling Expert Knowledge, Decision Support Systems
230

Innovation Strategy and Management Control: The Link
Between Knowledge Management and Management
Control Systems
Maurizio Massaro 1 , Roland Bardy 2 and Filippo Zanin 1
1
Udine University, Italy
2
Florida Gulf Coast University, USA
maurizio.massaro@uniud.it
rbardy@t-online.de
filippo.zanin@uniud.it
Abstract: In <strong>the</strong> light <strong>of</strong> <strong>the</strong> increasing complexity and intensity <strong>of</strong> competition <strong>the</strong>re is a growing sense that
innovation is a relevant key to continuously out perform competitors, to diversify, adapt and, even, re-invent <strong>the</strong>
organization. Understanding how enterprises manage <strong>the</strong> process for acquiring and sharing new knowledge has
emerged as an important stream <strong>of</strong> research for supporting <strong>the</strong> enterprises’ competition challenge. Likewise, <strong>the</strong>
literature recognizes that Management Control Systems (MCS) play an important role for supporting <strong>the</strong> “problem
finding” and “problem solving” process. Thus, MCS becomes a tool for producing knowledge. Focusing on <strong>the</strong>se
lines <strong>of</strong> research, <strong>the</strong> aims <strong>of</strong> this exploratory paper are to: i) identify such <strong>the</strong>oretical and statistically proven
clusters that describe where and how companies acquire, produce and select knowledge for sustaining
innovation strategies. A <strong>the</strong>oretical framework is adopted which encompasses <strong>the</strong> origin <strong>of</strong> knowledge (where)
and <strong>the</strong> knowledge creation process (how); ii) identify such <strong>the</strong>oretical and statistically proven clusters that
describe how companies use <strong>the</strong>ir MCS for producing knowledge and sustaining innovation strategies; iii) detect
and prove, within <strong>the</strong>se clusters, <strong>the</strong> existence <strong>of</strong> a link between MCS and knowledge management processes in
terms <strong>of</strong> coherence between how companies manage <strong>the</strong> knowledge process and how <strong>the</strong>y use MCS. In order to
have a wider perspective, <strong>the</strong> paper analyzes <strong>the</strong> knowledge management process during innovation processes.
The research is based on a survey conducted on a sample <strong>of</strong> 40 enterprises working in <strong>the</strong> North East <strong>of</strong> Italy
that carry out pertinent innovation processes. A structured questionnaire was delivered to <strong>the</strong> CEO <strong>of</strong> <strong>the</strong>
company, <strong>the</strong> Financial Manager and <strong>the</strong> Innovation Manager for a total amount <strong>of</strong> 120 questionnaires. The
managerial implications <strong>of</strong> this paper could be: i) to help managers in <strong>the</strong> development <strong>of</strong> tactical and operative
activities related to innovation strategies, in order to facilitate knowledge processes; ii) to <strong>of</strong>fer guidelines for
projecting more useful MCS in order to facilitate innovation processes.
Keywords: innovation, intellectual capital, knowledge management, management and control systems
1. Contextual framework and research questions
Scholars advise that to acquire a sustainable competitive advantage, companies must treat
knowledge as a strategic asset (Teece, 2000). Knowledge management (KM) thus becomes a
strategic task and <strong>the</strong> ability to link KM to strategy and competitive advantage is recognized as <strong>the</strong>
key to solving problems and exploiting opportunities in order to innovate companies’ business models
(Drew, 1999). Literature on this topic is quite extensive and it is not possible to identify a unique
definition <strong>of</strong> innovation and KM (Bardy, 2010) but some authors (Van de Ven and Engleman, 2004)
noted four basic perspectives emerging in studies <strong>of</strong> innovation strategies: human, contextual,
structural and process. The first focuses on making organizations more innovative by exploring new
knowledge ra<strong>the</strong>r than exploiting existing knowledge. The second emphasizes <strong>the</strong> creation and
management <strong>of</strong> a context that is appropriate for innovation. The third refers to a structural problem <strong>of</strong>
building an infrastructure across organizational boundaries for absorbing external knowledge. The
final perspective focuses on revealing <strong>the</strong> sequences <strong>of</strong> activities and transactions that are involved in
and which contribute to <strong>the</strong> constitution <strong>of</strong> new knowledge.
At <strong>the</strong> same time <strong>the</strong> influence <strong>of</strong> internal and external factors during innovation strategies has
attracted interest within <strong>the</strong> academic debate. Internal factors include organizational structures,
control and coordination mechanisms, communication channels, and organizational cultures. Early
studies noted that organic organizations were more effective than bureaucratic or mechanistic
organizations in innovation because <strong>the</strong> former were characterized as having flexible structures and
informal communication channels, which were important for sharing knowledge within an organization
(Butler, 1981). External factors refer to a set <strong>of</strong> contextual contingencies that have an effect on KM
and innovation activities. Van de Ven (2004) for instance, discussed <strong>the</strong> role <strong>of</strong> networks in
transferring knowledge across organizations, industries, and national boundaries while Cohen and
Levinthal (1990) emphasized <strong>the</strong> importance <strong>of</strong> absorptive capacity as <strong>the</strong> ability to recognize,
assimilate, and apply external knowledge. O<strong>the</strong>rs shed light on complementary assets as constituting
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Maurizio Massaro et al.
crucial factors for increasing <strong>the</strong> learning process in order to supplementing <strong>the</strong> effect <strong>of</strong> absorptive
capacity (Teece, 1987).
Our study centered on <strong>the</strong> role <strong>of</strong> KM during innovation strategies and using previous literature, we
tried to analyse <strong>the</strong> role <strong>of</strong> Management and Control Systems (MCS) as a blend <strong>of</strong> tools that support
<strong>the</strong> KM during innovation strategies processes within and across organizations. The connection
between Innovation and MCS is not quite clear (Bisbe, Otley, 2004) but seems to be related more to
<strong>the</strong> use <strong>of</strong> MCS than to <strong>the</strong> characteristics <strong>of</strong> a single tool (Henry, 2006). Indeed, <strong>the</strong> outcome <strong>of</strong> our
literature review shows that <strong>the</strong>re is more than one definition <strong>of</strong> MCS. Many textbooks adopt <strong>the</strong>
narrow definition <strong>of</strong> control: management activities are categorised separately as planning, control
and decision-making. Emmanuel et al. (1990) reject this approach and adopt a wider definition <strong>of</strong>
control which encompasses both planning and ensuring that plans are implemented for achieving
objectives. Thus, planning, control and decision-making are inextricably linked within <strong>the</strong> wider
conception <strong>of</strong> management control. Indeed <strong>the</strong> literature recognises that MCS could have two
complementary and interdependent roles (Ahrens and Chapman, 2004; Simons, 1994): i) <strong>the</strong>y can be
used to extend control over <strong>the</strong> attainment <strong>of</strong> organisational goals; ii) <strong>the</strong>y can also be used to enable
managers and employees to search for opportunities and solve problems. Scholars recognise that
this blend <strong>of</strong> aims requires a combination <strong>of</strong> multiple control systems that work toge<strong>the</strong>r (Otley, 1980),
and different levers <strong>of</strong> control (Simons, 1994).
Numerous prior studies have highlighted <strong>the</strong> importance <strong>of</strong> achieving a fit between a firm’s strategy
and its MCS (Chenhall, 2003; Langfield-Smith, 1997). Traditionally, <strong>the</strong> relationship between strategy
and MCS has been viewed as a passive one, suggesting that <strong>the</strong> MCS is an outcome <strong>of</strong> a firm’s
strategy. However, Hopwood (1987) and Dent (1990) recognised that <strong>the</strong> MCS might have a
proactive role in influencing strategy. Thus, <strong>the</strong> role <strong>of</strong> MCS and its impact on innovation processes
has emerged as an important research question (Shields, 1997) but few empirical studies address <strong>the</strong>
relationship among <strong>the</strong>se variables, especially considering SMEs. By focusing on this line <strong>of</strong> research,
we adopted an exploratory study that aims to investigate <strong>the</strong> relationships between <strong>the</strong> KM processes
adopted during innovation strategies and <strong>the</strong> use <strong>of</strong> MCS. Thus, our research questions are:
RQ1: How do enterprises manage knowledge in <strong>the</strong> specific process <strong>of</strong> innovation strategy?
RQ2: How do enterprises design and use MCSs in <strong>the</strong> specific process <strong>of</strong> innovation strategy?
RQ3: Is <strong>the</strong>re a link between KM processes adopted by <strong>the</strong> enterprises <strong>of</strong> <strong>the</strong> sample in <strong>the</strong>
specific process <strong>of</strong> innovation strategies and <strong>the</strong> use <strong>of</strong> MCSs?.
2. Methodology
A sample <strong>of</strong> 40 SMEs located in north-eastern Italy was drawn from a list <strong>of</strong> 200 manufacturing firms
supplied by local SMEs associations, which provided company names and contacts. The overall
selection criterion for creating <strong>the</strong> sample was <strong>the</strong> introduction <strong>of</strong> at least one new product by <strong>the</strong> firm
during <strong>the</strong> last three years and with expected costs for innovation strategies projects above 100.000
Euros. This enabled <strong>the</strong> selection <strong>of</strong> companies with an history <strong>of</strong> innovation and with relevant
innovation strategy projects.
Our research was conducted under <strong>the</strong> form <strong>of</strong> a knowledge audit where owner-managers were
interviewed in <strong>the</strong>ir role as “experts” (Ketchen and Shook, 1996). We adopt a multi-method, multicase
field research design to capture, in depth, <strong>the</strong> richness needed to investigate patterns <strong>of</strong> KM and
MCS-use within innovation strategies and <strong>the</strong> link between <strong>the</strong>m. Our multi-method design employs
qualitative and quantitative data collected through four main information sources: public data,
company reports and one semi-structured interview and a structured questionnaire. This
questionnaire was created based on <strong>the</strong> interviews and <strong>the</strong> o<strong>the</strong>r materials and sent to <strong>the</strong> CEO, <strong>the</strong>
CFO and <strong>the</strong> Research and Innovation Manager asking <strong>the</strong>m to rate <strong>the</strong>ir answers on a 1-7 Likert
scale.
To identify <strong>the</strong> KM processes involved in innovation strategies we refer to <strong>the</strong> knowledge model <strong>of</strong>
Holsapple and Jones (2004). Thus, <strong>the</strong> KM processes taken into consideration were: i) knowledge
acquisition: acquiring knowledge from external sources and making it suitable for subsequent use; ii)
knowledge generation: producing knowledge by ei<strong>the</strong>r discovery or derivation from existing
knowledge and making it suitable for subsequent use; iii) knowledge selection: selecting knowledge
generated and making it suitable for subsequent use. The variables we chose to characterise KM
were: i) knowledge origin or “where”: repositories <strong>of</strong> acquired, generated and selected knowledge; ii)
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knowledge creation process or “how”: ways <strong>of</strong> knowledge acquisition, generation and selection.
“Where” and ”How” were <strong>the</strong>n connected to acquisition, generation and selection for determining our
clusters.
“Where” and ”How” were also used to categorise <strong>the</strong> answers from <strong>the</strong> interviews as follows: i) 15
different ways <strong>of</strong> acquiring knowledge (7 “where” + 8 “how”); ii) 8 different ways <strong>of</strong> generating
knowledge (3 “where” + 5 “how”); iii) 8 different ways <strong>of</strong> selecting knowledge (3 “where” + 5 “how”). To
identify <strong>the</strong> use <strong>of</strong> MCS we refer to classifications suggested by previous research (Vandenbosch,
1999, Davila et al, 2009). The variable chosen to characterise <strong>the</strong> use <strong>of</strong> management control process
was <strong>the</strong> information use or “how”: ways <strong>of</strong> use <strong>of</strong> information drawn from MCS in <strong>the</strong> specific process
<strong>of</strong> innovation strategic decision-making. The open answers supplied by <strong>the</strong> owner-managers that we
interviewed were categorised by overlapping <strong>the</strong>se classifications recognizing 9 different uses <strong>of</strong>
MCS.
Cluster analyses have been used to classify firms into different groups based on <strong>the</strong>ir KM processes
and MCS-use. Some techniques based on <strong>the</strong> agglomeration coefficients have guided <strong>the</strong> selection <strong>of</strong>
final cluster solution: dendogram analysis; average silhouette index analysis; Tukey’s pair wise
comparison analysis. These approaches have been adopted in management control and in strategic
management field research (Ketchen and Shook, 1996; Gerdin and Greve, 2004; Henri, 2008). We
subsequently tested our results using k-means approaches and p.a.m. approaches (Kaufman and
Rousseeuw, 1990). To investigate <strong>the</strong> existence <strong>of</strong> a “coherent” link between KM processes and use
<strong>of</strong> MCS we use a Chi-Square Test (χ 2 ). To provide reassurance that <strong>the</strong> observed associations were
statistically robust, some control variables have been used. In particular we compare our results
considering: (i) environment uncertain; (iii) technology uncertain; (iiii) organization structure; iv)
organization size; v) strategy characteristics. Those variables have been selected since <strong>the</strong>y
represent common factors used in contingency-based management accounting research (Chenhall,
2003). In order to carry out <strong>the</strong>se tests One-Way-ANOVA-models have been employed for each
control variable.
3. Results
The cluster analysis led to <strong>the</strong> identification <strong>of</strong> distinct groups at <strong>the</strong> levels <strong>of</strong> KM processes and <strong>of</strong>
MCS-use, and <strong>the</strong> semi-structured interviews showed that distinct sources <strong>of</strong> knowledge and ways <strong>of</strong>
applying <strong>the</strong> knowledge are employed. The following paragraphs illustrate <strong>the</strong> results <strong>of</strong> our analysis.
3.1 Knowledge acquisition
The results <strong>of</strong> our analyses (see Table 1) reflect <strong>the</strong> presence <strong>of</strong> two groups that could be related to
<strong>the</strong> dimensions <strong>of</strong> <strong>the</strong> knowledge acquisition model discussed by Jordan and Jones (1997),
appropriately adapted to our sample companies. The groups are labeled as follows:
Cluster 1 “Focused”: Enterprises <strong>of</strong> this cluster use structured approaches as <strong>the</strong>ir knowledge
acquisition process. Great importance is given to pr<strong>of</strong>essional providers <strong>of</strong> knowledge such as
research centers and consultants as <strong>the</strong> main sources <strong>of</strong> acquisition. Suppliers <strong>of</strong> goods and
services are also important, even though less importance is given to <strong>the</strong>m than by <strong>the</strong> o<strong>the</strong>r
cluster. Preference is given to collaborative approaches, temporary management and access to
existing knowledge databases.
Cluster 2 “Opportunist”: Enterprises <strong>of</strong> this cluster mainly use economic actors <strong>of</strong> <strong>the</strong>ir value chain
(mostly suppliers, customers and sales network) in <strong>the</strong>ir knowledge acquisition process.
Techniques used to acquire knowledge are sparsely structured. A fair number <strong>of</strong> enterprises
recognizes <strong>the</strong> importance <strong>of</strong> <strong>the</strong> information given by competitors and gained from exhibitions,
fairs, meetings. Ample importance is given to <strong>the</strong> access <strong>of</strong> existing information available in
markets.
3.2 Knowledge generation
Our results (see Table 2) reflect <strong>the</strong> presence <strong>of</strong> two groups that could be related to <strong>the</strong> KM strategies
first identified by Zack (1999), adequately adapted to our sample companies. They are labeled as
follows:
Cluster1 “Aggressive Planners”: Enterprises <strong>of</strong> this cluster create specific cross-functional groups
to develop <strong>the</strong>ir research projects. A few <strong>of</strong> <strong>the</strong>m also feature an R&D group, which is usually not
233

Maurizio Massaro et al.
exclusive (researchers are usually assigned o<strong>the</strong>r tasks, too) but permanent and <strong>the</strong>y use
cooperative methods and target experimentations.
Cluster 2 “Conservative Searchers”: Enterprises <strong>of</strong> this cluster deploy a top down approach,
setting out from <strong>the</strong> top managers (who are mainly <strong>the</strong> owners), using methods such as learning
by doing, brainstorming and sometimes also self intuitive generation. The key variable is <strong>the</strong>
interaction between doing and learning, and research projects are not organized in advance.
Table 1: Knowledge acquisition clusters
Variables Centroids
Tukey's
Comparison
Cluster 1 Cluster 2 1-2
Where (1-7)
Research centres 6.35 3.71
***(see Note
below)
Consultants 6.39 4.95 ***
Districts organizations 3.42 2.49 ***
Competitors 2.81 4.49 ***
Customers 4.72 5.92 ***
Suppliers 4.42 6.08 ***
Sales networks
How (1-7)
3.54 5.57 ***
Benchmarking 5.14 2.54 ***
Collaborative learning 6.49 4.83 ***
Temporary managers and Job
***
mobility 6.49 4.40
Direct access to Knowledge
***
databases 5.54 6.40
External training 5.04 2.52 ***
Meetings and conventions 4.54 5.44 ***
Exhibitions and fairs 4.89 6.44 ***
Technical papers
Note: *p

Maurizio Massaro et al.
Cluster 1 “Entrepreneurs”: Enterprises belonging to this cluster restrict knowledge selection to top
managers, who must choose all <strong>the</strong> information <strong>the</strong>y need and search for knowledge bases.
Approaches used are less formalized; brainstorming and informal identification are among <strong>the</strong>
most used tools.
Cluster 2 “Team Workers”: Enterprises belonging to this cluster feature specific R&D groups
inside <strong>the</strong> organization. These groups, as in knowledge generation, may temporary be crossfunctional,
formed especially for overseeing <strong>the</strong> research projects, or stable R&D groups which
enjoy considerable autonomy. These groups apply formalized approaches in selecting <strong>the</strong>
relevant information, using both cooperative analysis approaches and experimental control.
Table 3: Knowledge selection clusters
Variables Centroids
Tukey's
Comparison
Cluster 1 Cluster2 1-2
Where (1-7)
R&D unit/ function 4.57 2.51
***(see Note
below)
Specific cross-functional groups 5.86 4.09 ***
TOP manager 3.38 6.09 ***
How (1-7)
Informal, intuitive selection 3.17 4.90 ***
Internal and external
brainstorming 4.45 6.47 ***
Standardization in knowledge
repositories 5.50 4.00 ***
Systematic, in depth and
focused analysis 5.93 3.78 ***
Cooperative analysis 6.57 4.53 ***
Note: *p

Maurizio Massaro et al.
autonomy <strong>of</strong> actors and structure <strong>of</strong> process. Using <strong>the</strong>se variables, we may infer that
opportunists do not require an interaction process and that <strong>the</strong>ir learning process is less
structured. This seems to justify a major propensity <strong>of</strong> opportunists to use a surveillance-machineapproach:
Having a more emergent approach on learning, <strong>the</strong> opportunists use MCS for focusing
on critical factors and mostly not for enabling discussion On <strong>the</strong> o<strong>the</strong>r hand, focused enterprises,
which have a more structured approach, develop a double-loop process in order to facilitate
debates inside internal and external groups and to increase <strong>the</strong> problem-focusing attitude.
Regarding <strong>the</strong> knowledge generation process, companies which belong to <strong>the</strong> cluster <strong>of</strong>
aggressive planners use a learning-machine-approach on MCS, and conservative searchers use
a surveillance-machine-approach. This empirical evidence comes close to what Henri (2006) said
about innovativeness. He has demonstrated that a more interactive use <strong>of</strong> MCS for fostering
dialog among employees could develop a more fluent information sharing process. This approach
seems to be related with <strong>the</strong> need to create an internal stimulus for breaking out <strong>of</strong> narrow search
routines, stimulating opportunity seeking and generation <strong>of</strong> ideas. O<strong>the</strong>r approaches which are
more conservative with regard to relating <strong>the</strong> generation process to a self intuitive approach,
seem to emphasize <strong>the</strong> need <strong>of</strong> focusing <strong>the</strong> actions on critical factors (Simons, 1994).
Companies <strong>of</strong> this cluster deploy a less structured way to verify <strong>the</strong> opportunities that <strong>the</strong>y
acquire, and <strong>the</strong>y have to develop <strong>the</strong> means to organize <strong>the</strong>ir transfer to operative plans.
Regarding <strong>the</strong> knowledge selection process, <strong>the</strong> “entrepreneurs” cluster is more inclined to a
problem-solving approach, and <strong>the</strong> “team-workers” cluster is more inclined to a surveillancemachine
approach. This empirical evidence seems to be related to earlier findings on <strong>the</strong> process
<strong>of</strong> cognition. A fair and balanced account <strong>of</strong> <strong>the</strong> various alternative approaches to cognition is not
on <strong>the</strong> agenda <strong>of</strong> this paper as <strong>the</strong>re is both a considerable overlap between <strong>the</strong>m (Patokorpi,
2009). But we can argue that, considering cognition as an activity in which information is
processed, <strong>the</strong> small number <strong>of</strong> people involved inside <strong>the</strong> entrepreneurs clusters usually adopt
tools that could help managers to clarify doubts and not for creating dialogue. Having a more
structured approach on knowledge selection, <strong>the</strong> “team-worker” cluster uses a more structured
approach for controlling <strong>the</strong> selection process focusing on critical factors.
Table 4: Knowledge selection clusters
Variables Centroids Tukey's Compar
How (1-7)
Enabling discussion, face to face
dialogue and debate across all
Cluster
1
Cluster
2
levels <strong>of</strong> organization 6.58 4.97 3.13
Focusing attention on strategic
uncertainties 6.67 5.18 2.91
Supporting creativity
Reducing complexity <strong>of</strong> <strong>the</strong>
6.50 4.74 3.07
strategy decision-making
Reducing time <strong>of</strong> <strong>the</strong> strategy
4.97 6.51 3.09
decision
Supporting problem solving and
3.03 6.59 5.09
finding
Tracking innovation process
3.22 6.49 5.02
toward goals
Focusing organization on critical
2.78 4.77 6.40
factors
Confirm understanding <strong>of</strong> <strong>the</strong>
4.06 5.05 6.56
business 2.86 5.13 6.53
Note: *p

Maurizio Massaro et al.
Table 5: MCS and KM relationships, expected and observed frequency
Variabile Cluster
Knwoledge Focused
acquisition
Opportunist
Knwoledge
generation
Knowledge
selection
Agressive Planner
Conservative search
Team Workers
Entrepreneurs
MCS-Use
Learning
Machine
14,63 (68%)
Problem Solving
Machine
11,25 (45%) 2,55 (12%)
2,25 (14%) 7,35 (54%)
Surveillance
Machine
3,53 (17%) 11,1 (59%)
13,8 (85%)
9,6 (41%)
The table only shows <strong>the</strong> positive difference between expected and observed frequency. The
numbers in brackets show <strong>the</strong> percentage rapport between <strong>the</strong> difference among expected and
observed frequency and observed frequency.
3.6 Control variables analysis
To provide reassurance that <strong>the</strong> observed associations were statistically robust, some control
variables have been used. In particular we analyze an ANOVA index considering:
Environment uncertainties asking <strong>the</strong> interviewed to respond in a scale <strong>of</strong> 1 (low = uncertain) to 7
(high = certain);
Technology uncertainties asking <strong>the</strong> interviewed to respond in <strong>the</strong> same 1-7 scale;
Organization structure considering <strong>the</strong> age <strong>of</strong> companies as a proxy <strong>of</strong> structure characteristics;
Size <strong>of</strong> <strong>the</strong> organization considering number <strong>of</strong> employees;
Strategy characteristics as dummy variable: 0 for cost reduction and 1 for differentiation
leadership.
Table 6 shows our statistical results. They indicate that <strong>the</strong>re is correlation among <strong>the</strong> control
variables and <strong>the</strong> observed variables in just a few cases. No correlation is verified for all observed
variables.
Table 6: Variables <strong>of</strong> control
Knowledge Knowledge Knowledge
MCS
Acquisition Generation Selection
Use
Environment uncertainties 0.786 0.413 0.086 0.589
Technology uncertainties 0.059 0.732 0.905 0.155
Organization 0.752 0.208 0.0076 ** 0.099
Size 0.647 0.0041 ** 0.000*** 0.446
Content <strong>of</strong> strategy 0.005 ** 0.990 0.255 0.496
Note: *p

Maurizio Massaro et al.
Chennal (2003) found several variables that influence <strong>the</strong> MCS-design and -use as: i) External
environment; ii) Technology; iii) Organizational structure; iv) Organizational size; v) Organizational
strategy; vi) National culture. Focusing on organizational structure, <strong>the</strong> author recognizes several
characteristics that could influence MCS-use, such as: <strong>the</strong> dimension <strong>of</strong> an organization, levels <strong>of</strong>
decentralization on strategic decision and leadership style. Our paper tries to enlarge this vision
considering <strong>the</strong> importance <strong>of</strong> <strong>the</strong> KM process encompassed in MCS-use. Empirical evidence seems
to confirm that different approaches to KM drive different usage <strong>of</strong> MCS which <strong>of</strong>fers a new
perspective on contingency <strong>the</strong>ory applied to MCS and KM. The operative applications <strong>of</strong> this study
could be several. Firstly, enterprises could review <strong>the</strong>ir use <strong>of</strong> MCS-tools by adapting <strong>the</strong>m in a
manner which facilitates <strong>the</strong> processes <strong>of</strong> knowledge acquisition, knowledge generation and <strong>the</strong>
knowledge selection. Secondly, as knowledge actors, controllers could work toge<strong>the</strong>r with o<strong>the</strong>r units
<strong>of</strong> <strong>the</strong>ir organization in order to produce information that could help in <strong>the</strong> innovation process.
Despite displaying corroborated empirical evidence, <strong>the</strong> study is not without limitations. The
geographical limitation <strong>of</strong> <strong>the</strong> sample and <strong>the</strong> relatively small number <strong>of</strong> enterprises may have
influenced <strong>the</strong> statistical analyses. Several factors like national culture and relatively similar
perception recorded from enterprises, could have had an influence on our statistical evidence. Indeed,
we are conscious that KM processes do not necessary lend <strong>the</strong>mselves to knowledge creation
because we need to understand <strong>the</strong> ecology <strong>of</strong> <strong>the</strong> system, named by <strong>the</strong> authors <strong>the</strong> “ Ba” (Nonaka
and Konno,1998). Moreover even though <strong>the</strong> Chi-Square Test exhibits a strong relationship between
MCS-use and KM-approaches clusters, we are not able to identify <strong>the</strong> direction. Our statistics have
not indicated if <strong>the</strong> KM approaches influence MCS-use or if it is <strong>the</strong> opposite. Regarding this, we did
not consider any variable indicating performance. These limitations could be <strong>the</strong> topic <strong>of</strong> fur<strong>the</strong>r
studies in this research field .
6. Conclusion
Based on <strong>the</strong> above arguments, <strong>the</strong> main findings <strong>of</strong> this research are, in relation to <strong>the</strong> three
research questions: verification <strong>of</strong> how <strong>the</strong> companies included in our sample deploy <strong>the</strong>ir KM process
considering <strong>the</strong> phases <strong>of</strong>
Knowledge acquisition (where we find two main approaches: focused approaches and
opportunists approaches);
Knowledge generation (where we find two main approaches: aggressive planners and
conservative searchers);
Knowledge selection (where we find two main approaches: entrepreneurs and team workers).
We verified how <strong>the</strong> sample companies use <strong>the</strong>ir MCS and we found three different approaches:
learning-machine, problem-solving-machine, surveillance-machine.
Finally, we verified how <strong>the</strong> companies <strong>of</strong> our sample link MCS-use and KM approaches. Our results
indicated a statistically relevant relationship among <strong>the</strong> approaches. Our analyses seem to <strong>of</strong>fer a
way for a wider application <strong>of</strong> <strong>the</strong> contingency <strong>the</strong>ory applied to <strong>the</strong> MCS-use.
The operative application <strong>of</strong> <strong>the</strong>se researches in <strong>the</strong> field could help managers to facilitate <strong>the</strong>
innovation strategies process and to create a more fluent practice <strong>of</strong> information sharing.
5. References
Ahrens, T. and Chapman, C.S. (2004) “Accounting for Flexibility and Efficiency: A Field Study <strong>of</strong> Management
Control Systems in a Restaurant Chain”, Contemporary Accounting Research, Vol 21, No.2, pp 271-301.
Argyres, N. and Silverman, B. (2004) “R&D, Organization Structure, and <strong>the</strong> Development <strong>of</strong> Corporate
Technological Knowledge”, Strategic Management Journal, Vol 25, No. 8/9, pp 929-958.
Bardy, R. (2010) “Comparative supply Chain Performance”, Knowledge and Process Management, Vol.17, No.2,
pp95-110.
Bisbe G., Otley D. (2004) “The effects <strong>of</strong> <strong>the</strong> interactive use <strong>of</strong> management control systems on product
innovation”, Accounting, Organization and Society, Vol.29, No.8, pp 709-737.
Butler, R.J. (1981) “Innovation in Organizations: Appropriateness <strong>of</strong> Perspectives From Small Group Studies for
Strategy Formulation”, Human Relations, Vol 34, No. 9, pp 763-788.
Chenhall, R.H. (2003) “Management Control System Design Within its Organizational Context: Findings From
Contingency-Based Research and Directions for <strong>the</strong> Future”, Accounting, Organizations and Society, Vol
28, No. 2-3, pp 127-168.
238

Maurizio Massaro et al.
Cohen, W.M. and Levinthal, D. A. (1990) “Absorptive Capacity: A New Perspective on Learning and Innovation”,
Administrative Science Quarterly, Vol 35, No. 1, pp 128-152.
Davila, A., Foster, G. and Li, M. (2009) “Reasons for Management Control Systems Adoption: Insights from
Product Development Systems Choice by Early-Stage Entrepreneurial Companies”, Accounting,
Organizations and Society, Vol 34, No. 3-4, pp 322-347.
Dent, J.F. (1990) “Strategy, Organization and Control: Some Possibilities for Accounting Research”, Accounting,
Organizations and Society, Vol 15, No. 1-2, pp 3-25.
Drew, S. (1999) “Building Knowledge Management into Strategy: Making Sense <strong>of</strong> a New Perspective”, Long
Range Planning, Vol 32, No. 1, pp 130-136.
Emmanuel, C., Otley, K. and Merchant, D. (1990) Accounting for Management Control, Thompson Learning,
London.
Gerdin, J. and Greve, J. (2008) “The Appropriateness <strong>of</strong> Statistical Methods for Testing Contingency Hypo<strong>the</strong>sis
in Management Accounting Research”, Accounting, Organizations and Society, Vol 33, No. 7-8, pp 995-
1009.
Hansen, M.T., Nohria, N. and Tierney, T. (1999) “What’s Your Strategy for Managing Knowledge?”, Harvard
Business Review, Vol 77, No. 2, pp 106-116.
Henri, J.F. (2006) “Management Control Systems and Strategy: A Resource-Based Perspective”, Accounting,
Organizations and Society, Vol 31, No. 6, pp 529-558.
Henri, J.F. (2008) “Taxonomy <strong>of</strong> Performance Measurement Systems”, Advances in Management Accounting,
Vol 17, pp 247-288.
Holsapple, C.W. and Jones, K. (2004) “Exploring Primary Activities <strong>of</strong> <strong>the</strong> Knowledge Chain”, Knowledge and
Process Management, Vol 11, No. 3, pp 155-174.
Hopwood, A.G. (1987) “The Archaeology <strong>of</strong> Accounting Systems”, Accounting, Organizations and Society, Vol
12, No. 3, pp 207-234.
Jordan, J. and Jones, P. (1997) ”Assessing Your Company’s Knowledge Management Style”, Long Range
Planning, Vol 30, No. 3, pp 392-398.
Kaufman, L. and Rousseeuw, P.J. (1990) Finding Groups in Data: An Introduction to Cluster Analysis, John Wiley
& Sons Ltd., New York.
Ketchen, D.J. and Shook, C.L. (1996) “The Application <strong>of</strong> Cluster Analysis in Strategic Management Research:
an Analysis and Critique”, Strategic Management Journal, Vol 17, No. 6, pp 441-458.
Langfield-Smith, K. (1997) “Management Control Systems and Strategy: A Critical Review”, Accounting,
Organizations and Society, Vol 22, No. 2, pp 207-232.
Miller, D. (1996) “A Preliminary Typology <strong>of</strong> Organizational Learning: Syn<strong>the</strong>sizing <strong>the</strong> Literature”, Journal <strong>of</strong>
Management, Vol 22, No. 3, pp 485-505.
Nonaka, I and Konno, N. (1998)“The concept <strong>of</strong> Ba”, California Management Review, 40, 3, pp 40-54.
Otley, D.T. (1980) “The Contingency Theory <strong>of</strong> Management Accounting: Achievement and Prognosis”,
Accounting, Organizations and Society, Vol 5, No. 4, pp 413-428.
Patokorpi, E. (2009) “Situated, Embodied Human Interaction and its Implications for Context Building in
Knowledge Mobilisation Design”, Electronic Journal <strong>of</strong> Knowledge Management, Vol 7, No. 3, pp 368-377.
Shields, M.D. (1997) “Research in Management Accounting by North Americans in <strong>the</strong> 1990s”, Journal <strong>of</strong>
Management Accounting Research, Vol 9, pp 3-61.
Simons, R.L. (1994) Levers <strong>of</strong> Control: How Manager Use Innovative Control Systems to Drive Strategic
Renewal, Harvard Business School Press, Boston.
Teece, D.J. (2000) “Strategies for Managing Knowledge Assets: <strong>the</strong> Role <strong>of</strong> Firm Structure and Industrial
Context”, Long Range Planning, Vol 33, No. 1, pp 35-54.
Teece, D.J. (Ed.) (1987) The Competitive challenge: Strategies for Industrial Innovation and Renewal, Harper &
Row, Ballinger Division, New York.
Van de Ven, A. (2004) “The Context-Specific Nature <strong>of</strong> Competence and Corporate Development”, Asia Pacific
Journal <strong>of</strong> Management, Vol 21, No. 1-2, pp 123-147.
Van de Ven, A.H. and Engleman, R.M. (2004) “Central Problems in Managing Corporate Innovation and
Entrepreneurship”, Corporate Entrepreneurship, Vol.7, pp. 47-72.
Vandenbosch, B. (1999) “An Empirical Analysis <strong>of</strong> <strong>the</strong> Association Between <strong>the</strong> Use <strong>of</strong> Executive Support
Systems and Perceived Organizational Competitiveness”, Accounting, Organizations and Society, Vol 24,
No.1, pp 77-92.
Zack, M.H. (1999) “Developing a Knowledge Strategy”, California Management Review, Vol 41, No. 3, pp 125-
145.
239

Intellectual Capital Management: Case Study Portugal
Versus Romania
Florinda Matos 1 , Albino Lopes 2 , Marta-Christina Suciu 3 and Alex Ghitiu 3
1
ISCTE – University Institute <strong>of</strong> Lisbon, Lisboa, Portugal
2
ISCSP - Technical University <strong>of</strong> Lisbon, Portugal
3
Academy <strong>of</strong> Economic Studies Bucharest, Romania
Florinda.Matos@iscte.pt
alopes@iscsp.utl.pt
suciuchristina@yahoo.com
alexghitiu@yahoo.com
Abstract: The new economy requires new approaches and methods to measure both tangible and intangible
assets. Well-designed indicators, based on a coherent <strong>the</strong>oretical framework, are like words and syntax <strong>of</strong> a
language. This can help managers to develop a new way <strong>of</strong> thinking and to understand better <strong>the</strong> relationship
between people within <strong>the</strong>ir organizations and how <strong>the</strong>y can make pr<strong>of</strong>its in <strong>the</strong>ir company based mostly on <strong>the</strong>
value added by intangible assets and intellectual capital. In most <strong>European</strong> countries, <strong>the</strong> management <strong>of</strong>
intellectual capital is at a very early stage, regarding <strong>the</strong> awareness <strong>of</strong> <strong>the</strong> critical role it has in more competitive
countries. Appeal to intangible assets to create and develop value added is a significant challenge for
pr<strong>of</strong>essionals in countries such as Portugal and Romania. Many organizations, both from <strong>the</strong> national and
international level are concerned with <strong>the</strong> promotion within <strong>the</strong>m <strong>of</strong> new models <strong>of</strong> intellectual capital reporting
and <strong>of</strong> monitoring <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> policies <strong>the</strong>y develop in this direction. We believe that both in Portugal
and Romania, such a scientific approach applied locally, is quiet novelty mostly from <strong>the</strong> practical point <strong>of</strong> view. In
<strong>the</strong> case <strong>of</strong> Portuguese and Romanian companies, with numerous problems <strong>of</strong> competitiveness, <strong>the</strong> acceptance
<strong>of</strong> intellectual capital management implies <strong>the</strong> existence <strong>of</strong> quantifiable returns that justify <strong>the</strong> investment.
However, in <strong>the</strong>se countries, we can find cases <strong>of</strong> successful companies with business activities directed to <strong>the</strong>
permanent innovation, which appears associated with a long-run sustainable investment in <strong>the</strong> strategic
management <strong>of</strong> talent and creativity. The aim <strong>of</strong> this paper is to present an empirical research conducted with
Romanian and Portuguese Small and Medium-sized Enterprises (SMEs), which seem to demonstrate a clear
association between <strong>the</strong> intellectual capital management and organizational performance. Ano<strong>the</strong>r objective is to
apply <strong>the</strong> Intellectual Capital Model - ICM developed by <strong>the</strong> first two authors (Matos and Lopes) in 2008 for
Portugal in different business and cultural contexts (Portuguese and Romanian). The research is based also on
<strong>the</strong> categorization methodology defined by Yin (2003) as a multiple case study. The sample consists <strong>of</strong> some
SMEs chosen both from Portugal and Romania that develop <strong>the</strong>ir economic activity in <strong>the</strong> production <strong>of</strong> tangible
and intangible assets. The paper presents briefly and compares <strong>the</strong> results obtained in research carried out in
both countries. Despite <strong>the</strong> differences between <strong>the</strong> two countries, <strong>the</strong> findings indicate <strong>the</strong> strategic need to
invest in intellectual capital management as a key element <strong>of</strong> improving <strong>the</strong> SMEs organizational performance
and <strong>of</strong> assuring and developing a long-run sustainable competitive advantage for SME. This research aims to
contribute to <strong>the</strong> international recognition <strong>of</strong> intellectual capital management as a new paradigm <strong>of</strong> business
management. Our research is at a starting point but it might be a useful prerequisite for possible future <strong>the</strong>oretical
and empirical investigations. This paper seeks to develop both in Portugal and Romania a framework <strong>of</strong> IC
reporting by starting to learn and to adapt some best practices identified abroad.
Keywords: intellectual capital management, SMEs, talent management, knowledge-based economy, intangible
assets, competitive advantage
1. Introduction
According to <strong>the</strong> new paradigm, intellectual capital is seen to have taken progressively more <strong>of</strong> a
leading role in companies as it is through it that information can be changed into knowledge.
However, considering <strong>the</strong> current context, where <strong>the</strong> markets become more competitive, forcing
companies to be constantly innovating, strategic management <strong>of</strong> intellectual capital seems to be <strong>the</strong>
most valuable asset, as <strong>the</strong> main driver <strong>of</strong> competitive advantage.
Competitiveness requires that companies differentiate through continuous innovation. Therefore,
knowledge has a vital role in all types <strong>of</strong> innovation.
In Europe, SMEs are an important driver <strong>of</strong> economic growth, and <strong>the</strong>ir importance as a source <strong>of</strong>
innovation and technological development has been rediscovered. Fur<strong>the</strong>rmore, SMEs may gain
competitive advantage if <strong>the</strong>y use knowledge effectively, making intellectual capital management
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essential. Only <strong>the</strong> proper management <strong>of</strong> intellectual capital can ensure <strong>the</strong> improvement <strong>of</strong>
company's internal processes and, consequently, <strong>the</strong> successful management <strong>of</strong> its resources.
This research aims to show how <strong>the</strong> same factor - intellectual capital management - in different
business contexts may have a similar importance.
We used <strong>the</strong> case study methodology, according to Yin (2003), to examine intellectual capital
management in Portuguese and Romanian companies.
Case studies tend to be selective, focusing on one or two issues that are fundamental to
understanding <strong>the</strong> system being examined in our case it studies <strong>the</strong> relationship between <strong>the</strong>
company´s management <strong>of</strong> individual and collective talents and its organizational success.
The following sections summarize <strong>the</strong> main aspects <strong>of</strong> <strong>the</strong> research.
We conclude that using <strong>the</strong> same model – Intellectual Capital Model - in different contexts (different
countries, different economies, and different companies), we can identify a set <strong>of</strong> common best
practices in managing intellectual capital.
These best practices, analyzed using <strong>the</strong> parameters <strong>of</strong> <strong>the</strong> ICM, allow us to infer <strong>the</strong> possibility <strong>of</strong>
adapting <strong>the</strong> Model to different business contexts.
2. Literature review: Intellectual capital and models
The growing importance <strong>of</strong> intellectual capital has its foundations in several studies carried out since
<strong>the</strong> 70s, which focused on so-called invisible assets.
Among <strong>the</strong>se studies highlight <strong>the</strong> works <strong>of</strong> Hiroyuki Itarni (1991).
However, intellectual capital has gained prominence only after <strong>the</strong> works <strong>of</strong> Sveiby (1997), in Sweden.
The author gave a new vision <strong>of</strong> intellectual capital in considering <strong>the</strong> intangible assets as <strong>the</strong> main
strategic issue that should be put to <strong>the</strong> organizations.
Since <strong>the</strong>n, several authors proposed models and methodologies for assessing <strong>the</strong> intellectual capital
<strong>of</strong> organizations. The fur<strong>the</strong>r development <strong>of</strong> <strong>the</strong>se models was found with authors such as Edvinson
and Malone (Edvinson and Malone, 1997).
Edvinson and Malone (1997), proposed a model, “Skandia Navigator”, which divides intellectual
capital into two categories: human capital and structural capital. Thus, according to this vision,
intellectual capital is <strong>the</strong> sum <strong>of</strong> structural capital and human capital, this being <strong>the</strong> basic capacity for
<strong>the</strong> creation <strong>of</strong> high quality value.
Sveiby, (1997), developed a measurement methodology, “The Intangible Asset Monitor”, by dividing
<strong>the</strong> intangible assets into three groups: individual competence, internal structure and external
structure. This methodology is based on quantitative and qualitative indicators to assess <strong>the</strong>
intellectual capital. The "Intangible Asset Monitor" is used by several companies around <strong>the</strong> world that
<strong>of</strong>fer an overview <strong>of</strong> intellectual capital. The “Skandia IC Report" is <strong>the</strong> result <strong>of</strong> that assessment.
Sveiby (1997) recommends replacing <strong>the</strong> traditional accounting methodology with a new methodology
that contains a knowledge perspective. For <strong>the</strong> author, this methodology is very important to complete
<strong>the</strong> financial information and evaluates <strong>the</strong> company´s efficiency and stability.
Among <strong>the</strong> most relevant methodologies are also <strong>the</strong> Balanced Scorecard” (Kaplan and Norton, 1992,
1996,1996a) <strong>the</strong> “IC Accounting System” (Mouritsen et al., 2001), <strong>the</strong> “Value Explorer” (Andriessen
and Tissen, 2000), and <strong>the</strong> “Intellectual Capital Benchmarking System” (Viedma, 2001).
These different approaches are based on <strong>the</strong> measurement <strong>of</strong> organizations intangible assets.
Andriessen (2004, 2004a) by applying <strong>the</strong> "<strong>the</strong>ory <strong>of</strong> multidimensional value measurement" to <strong>the</strong>
nations, gives a new vision to strategic intellectual capital management.
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These models and methodologies will not be developed as this is not <strong>the</strong> objective <strong>of</strong> this paper. On
<strong>the</strong> o<strong>the</strong>r hand, it is assumed that <strong>the</strong> readers <strong>of</strong> this paper will be able to access <strong>the</strong> different
approaches in <strong>the</strong>se models, easily.
The model used in this paper is <strong>the</strong> “Intellectual Capital Model” (ICM) (Matos and Lopes, 2009).
The choice <strong>of</strong> this Model is linked to <strong>the</strong> need for being able to identify, in an integrated and consistent
way, <strong>the</strong> complexity <strong>of</strong> <strong>the</strong> factors in <strong>the</strong> framework <strong>of</strong> organizational knowledge. Compared with o<strong>the</strong>r
models, ICM seems to be more adapted to evaluate <strong>the</strong> intellectual capital management.
The ICM - Intellectual Capital Model - consists <strong>of</strong> 4 Quadrants specified by <strong>the</strong>ir parameters (Matos
and Lopes, 2009).
Figure 1: ICM - Intellectual Capital Model (Matos and Lopes, 2009)
The Quadrant Individual Capital, Team Capital and Processes Capital are related to <strong>the</strong> company's
internal environment, <strong>the</strong> Quadrant Clients Capital is related to <strong>the</strong> external environment.
In ICM, is called Individual Capital <strong>the</strong> Tacit Knowledge / Human Capital Quadrant. It is <strong>the</strong> knowledge
inherent to <strong>the</strong> individual himself, and containing <strong>the</strong> real source <strong>of</strong> value, talents and <strong>the</strong> skills to
generate innovation. Here, one has included <strong>the</strong> <strong>the</strong>oretical and practical knowledge <strong>of</strong> <strong>the</strong> individuals
and <strong>the</strong> capacities <strong>of</strong> different types, such as artistic, sporting or technical.
The Team Capital is <strong>the</strong> Human Capital / Explicit Knowledge Quadrant. The team shares <strong>the</strong> explicit
knowledge. In this area, knowledge applies to <strong>the</strong> individual in <strong>the</strong> form <strong>of</strong> facts, concepts or tools.
When <strong>the</strong> Explicit Knowledge is associated to Structural Capital, we are in <strong>the</strong> presence <strong>of</strong> applied
experience, as <strong>the</strong> whole organization is <strong>the</strong> holder <strong>of</strong> formalized knowledge, able to be passed on,
this is <strong>the</strong> Processes Capital. This Quadrant represents <strong>the</strong> ensemble <strong>of</strong> shared knowledge, summed
up by experts (scientific community), recognized as <strong>the</strong> most advanced form <strong>of</strong> knowledge. This type
<strong>of</strong> knowledge covers, among o<strong>the</strong>r dimensions, <strong>the</strong> organizational routines or <strong>the</strong> organizational
memory. Organizational memory represents <strong>the</strong> register <strong>of</strong> an organization, represented by a set <strong>of</strong>
documents and artefacts. Its goal is to expand and amplify knowledge through its acquisition,
organization, dissemination, usage and refinement. Organizational memory can be a way <strong>of</strong>
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registering tacit knowledge, making it explicit, so that through business processes it becomes part <strong>of</strong>
<strong>the</strong> patrimony <strong>of</strong> <strong>the</strong> company, to be shared and recreated.
The Clients Capital is <strong>the</strong> result <strong>of</strong> <strong>the</strong> interaction Structural Capital / Tacit Knowledge. This typology
represents <strong>the</strong> organizational knowledge in its practical form and is already incorporated into <strong>the</strong> tacit
experiences formalized in <strong>the</strong> team. This knowledge, although hidden, becomes accessible through
interaction, and it is <strong>the</strong> principal characteristic <strong>of</strong> <strong>the</strong> performance <strong>of</strong> highly specialized teams.
In <strong>the</strong> Model presented <strong>the</strong> Network and NTIC are essential in <strong>the</strong> relationship between <strong>the</strong> 4
Quadrants.
Thus, <strong>the</strong> companies that put <strong>the</strong> NTIC at <strong>the</strong> service <strong>of</strong> human resources have a great advantage,
because <strong>the</strong>y can reduce <strong>the</strong> administrative difficulties in solving simple problems, increase <strong>the</strong>
quality <strong>of</strong> services and promote continuous improvement and personal growth.
The approach to <strong>the</strong> concept <strong>of</strong> Network is not a new concept. The network, as a social concept, is
<strong>the</strong> genesis <strong>of</strong> <strong>the</strong> social constructs <strong>of</strong> individuals. More recent is <strong>the</strong> approach to <strong>the</strong> concept <strong>of</strong>
network system as a factor in <strong>the</strong> acquisition <strong>of</strong> knowledge and innovative action. In conclusion, <strong>the</strong>
NTIC are crucial to be effective Networks.
In <strong>the</strong> ICM, <strong>the</strong> relational capital is <strong>the</strong> result <strong>of</strong> various interactions that take place within <strong>the</strong>
organization and that allows to transform tacit knowledge into explicit knowledge. This knowledge put
to <strong>the</strong> service <strong>of</strong> customers and all stakeholders, allows organizations to achieve high performances.
ICM parameters are:
Use <strong>of</strong> New Technologies <strong>of</strong> Information and Communication – NTIC
Use <strong>of</strong> Networks
I – Individual Capital Quadrant
Training / Qualification and Talent management
Valuation <strong>of</strong> Know - How and Innovation
Investment in Innovation and Development (ID)
Existence <strong>of</strong> a Policy for Talent Retention
II – Team Capital Quadrant
Training / Qualification
Team Work
Innovation in teams
Leadership in teams
III – Processes Capital Quadrant
Processes Systematization
Registration <strong>of</strong> Organizational Knowledge
Existence <strong>of</strong> Certification, environmental and social policies
Partnerships
Investment in Innovation and Development (ID)
The Brands Creation and Management
Complaints System
The existence <strong>of</strong> Awards
IV – Clients Capital Quadrant
Market Audits
Management <strong>of</strong> <strong>the</strong> Clients' Satisfaction
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It should be noted that <strong>the</strong> ICM is a dynamic model, <strong>the</strong>refore is not a model completely stabilized.
Thus, as your application will be looking into more companies, may be fur<strong>the</strong>r adjustments. Indeed,
this is one <strong>of</strong> <strong>the</strong> advantages <strong>of</strong> model: its interactive dynamism, which has proved very good in
turbulent business contexts.
3. Empirical research
3.1 Methodological framework case study
The Intellectual Capital Model (ICM) was applied in two business cases <strong>of</strong> Portuguese SMEs.
The same study was replicated in two cases <strong>of</strong> Romanian SMEs.
This research aims to verify whe<strong>the</strong>r <strong>the</strong>re is a clear association between intellectual capital
management and good organizational performance (efficiency and innovation).
Equally we intend to confirm MCI and its parameters in different international contexts.
This research follows <strong>the</strong> categorization defined by Yin (2003) as an explanatory case since it is
intended to evaluate <strong>the</strong> behavior <strong>of</strong> ICM in organizations identified as excellent.
Following <strong>the</strong> concepts defined by Yin (2003) and Hamel et al. (1993) we chose a sample <strong>of</strong> two
Portuguese cases: The case <strong>of</strong> YDreams and <strong>the</strong> case <strong>of</strong> Amândio José Lobo (A.JLobo), and two
Romanians cases: The case <strong>of</strong> <strong>the</strong> Unicredit Leasing and <strong>the</strong> case <strong>of</strong> Akcedo Dynamic.
We had a convenience sample, according to Yin (2003, p. 79).
Ano<strong>the</strong>r factor that was considered in selecting <strong>the</strong>se cases was <strong>the</strong> company’s activity sector.
Amândio José Lobo is clearly an industrial company, with an industrial production; YDreams fits into
<strong>the</strong> group <strong>of</strong> creative industries, so an industry focused on intangible assets.
In <strong>the</strong> case <strong>of</strong> Romanian companies, both companies are in <strong>the</strong> area <strong>of</strong> intangible assets: <strong>the</strong> financial
and s<strong>of</strong>tware development area.
Regarding <strong>the</strong> pr<strong>of</strong>ile <strong>of</strong> respondents, we examined <strong>the</strong> leader's vision.
As Yin (2003, p.99) this empirical study will follow <strong>the</strong> triangulation <strong>of</strong> data. This triangulation will be
supported by ga<strong>the</strong>ring information from different data sources in order to verify if <strong>the</strong> same sources
corroborate <strong>the</strong> same phenomenon.
As criteria <strong>of</strong> quality research are considered <strong>the</strong> four tests referred by Yin (2003, p. 34): construct
validity, internal validity, external validity and reliability.
Following <strong>the</strong> methodological procedures set out above, we used content analysis, according to
Bardin (2009) with <strong>the</strong> following steps <strong>of</strong> content analysis: pre-analysis, content analysis, processing
<strong>of</strong> <strong>the</strong> results interpretation.
As one <strong>of</strong> <strong>the</strong> techniques mentioned by several authors, <strong>the</strong> analysis <strong>of</strong> categories, according to
Bardin (2009) is <strong>the</strong> technique used in this research.
3.2 Presentation <strong>of</strong> research subjects
YDreams
YDreams was established in 2000. Its activity lies in <strong>the</strong> creative industries to <strong>the</strong> global market.
Research and development has allowed YDreams pioneering and success in areas such as
ubiquitous computing, interactive media, augmented reality or biometric sensors.
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YDreams currently has 150 employees.
Amândio José Lobo, Lda
Florinda Matos et al.
The Amândio José Lobo, began operations in 1984. The company's goal was <strong>the</strong> production <strong>of</strong>
precision mechanical components.
In <strong>the</strong> last decade, <strong>the</strong> company has specialized in high precision components, normally associated
with raw materials such as noble Aeronautical Aluminum, Stainless Steel, Chromium-Nickel, etc..
These components are used in applications as diverse as commercial and military aircraft, robots,
trains, medical and pharmaceutical industries, among o<strong>the</strong>rs.
The company currently has 150 employees.
Unicredit Leasing
Unicredit Leasing is activating on multinational level in <strong>the</strong> financial field more specific in <strong>the</strong> leasing
field. The company’s ownership is external and on shares, its 8 year’s old being established in 2002 a
total number <strong>of</strong> employees <strong>of</strong> 200.
Akcedo Dynamic
Akcedo Dynamic is activating on Romanian national level in <strong>the</strong> S<strong>of</strong>tware innovation and development
field. The company’s type is small to medium, its 4 years old being established in 2006. The company
has a total number <strong>of</strong> employees <strong>of</strong> 113.
3.3 Methodological procedures content analysis
Continuing <strong>the</strong> methodological procedures <strong>of</strong> content analysis set out above, we proceeded to <strong>the</strong>
content analysis according to Bardin (2009).
So, we started by defining <strong>the</strong> categories guiding <strong>the</strong> questions asked to respondents, followed by <strong>the</strong>
analysis <strong>of</strong> <strong>the</strong> collected material for interpretation <strong>of</strong> <strong>the</strong> dominant <strong>the</strong>mes in each category. We did
what Bardin (2009) considers <strong>the</strong> categorical analysis, according to semantic criteria, which requires
<strong>the</strong> verification <strong>of</strong> <strong>the</strong> presence <strong>of</strong> items with a focus on ICM and its parameters.
Note that <strong>the</strong> Guidelines had been designed, taking into account three levels <strong>of</strong> analysis:
(A) Level 1 - Quadrants
(B) Level 2 - Parameters
(C) Level 3 - Overall organization <strong>of</strong> MCI.
Thus, <strong>the</strong> data were categorized, first according to <strong>the</strong> four quadrants, second according to <strong>the</strong>
subcategories that represent each <strong>of</strong> <strong>the</strong> parameters. The aim is to check <strong>the</strong> connection between <strong>the</strong>
MCI quadrants.
Also, for each parameter were established facts which were supposed to prove.
We use <strong>the</strong> technique <strong>of</strong> semi-structured interview with open Guide (See Case Study Script
Interview).
The data analysis will confirm, or not confirm, <strong>the</strong> pre-defined categories, or possibly add new
categories.
We have a categorical analysis <strong>of</strong> issues in which we observed <strong>the</strong> frequency (absolute and relative)
<strong>of</strong> <strong>the</strong> data collected and we analyzed <strong>the</strong> relationships between <strong>the</strong>se data.
The second phase <strong>of</strong> this process was <strong>the</strong> collection and analysis <strong>of</strong> subcategories to which are
added <strong>the</strong> researcher inferences.
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Finally, <strong>the</strong>re is a systematization <strong>of</strong> results, relating <strong>the</strong>m to <strong>the</strong> original objectives, we apply new
inferences and we seek to obtain a complete understanding <strong>of</strong> <strong>the</strong> research.
To follow <strong>the</strong>se methodological procedures, we proceed to <strong>the</strong> full transcript <strong>of</strong> <strong>the</strong> interviews. After,
<strong>the</strong> data were categorized, according to <strong>the</strong> categories and subcategories defined a priori. At this
stage, we found that <strong>the</strong>re was no need to introduce more categories.
4. Results
The data analysis allows us to verify that new technologies are used in <strong>the</strong> four companies as tools
for organizational development. New technologies are an integral part <strong>of</strong> <strong>the</strong> processes <strong>of</strong> each
company in terms <strong>of</strong> recording and sharing <strong>of</strong> knowledge, as an element <strong>of</strong> interaction with internal
and external stakeholders and as a tool for business management.
The notion <strong>of</strong> "network" is evident in <strong>the</strong> organizations. The networks are essential in interacting with
different stakeholders.
Although with different systems, "Stock Ideas", as a tool for continuous improvement and innovation,
seems to have an important role.
In <strong>the</strong> companies analyzed, to qualify, as talent management, is evidenced by how <strong>the</strong>se companies
encourage <strong>the</strong> acquisition and development <strong>of</strong> knowledge for <strong>the</strong>ir employees. We can say that <strong>the</strong>re
is a continuous improvement program for talent.
The valuation <strong>of</strong> employee’s know-how, as a determinant <strong>of</strong> continuous improvement and innovation,
are reflected in respondents' answers. The awards <strong>of</strong> monetary and non-monetary nature are
commonplace.
The Research and Development are areas - key in <strong>the</strong> companies studied. This research is carried
out by companies’ specific groups but, in general, is encouraged throughout <strong>the</strong> company.
The respondents' answers clearly show a policy <strong>of</strong> retaining talent.
Creativity is a key factor in any business but is not sufficient for good organizational performance. We
found <strong>the</strong> need for employees with an interdisciplinary character.
Teamwork is prevalent, as part <strong>of</strong> <strong>the</strong> culture <strong>of</strong> each company.
In any <strong>of</strong> <strong>the</strong> companies we found that teamwork is permanently stimulated but in performance
assessment is <strong>the</strong> individual component that has a greater importance.
Although <strong>the</strong> team's main goal is <strong>the</strong> external customer, internal customer is not forgotten by <strong>the</strong>
companies interviewed.
The respondents' answers reveal <strong>the</strong> attention given to <strong>the</strong> transmission <strong>of</strong> knowledge within <strong>the</strong>
team, that lets everyone know what is important in <strong>the</strong> business activity.
There is a corporate culture where innovation is present.
It is <strong>the</strong> incremental innovation that has a wider relevance. A disruptive innovation is more complex
and requires greater resources. Thus, for example, in Amândio José Lobo this innovation is bought in
Germany.
Respondents emphasized <strong>the</strong> importance <strong>of</strong> leadership. Representatives <strong>of</strong> YDreams, <strong>of</strong> Amândio
José Lobo, <strong>of</strong> Unicredit Leasing and, and <strong>of</strong> Akcedo Dynamic highlight emergent leadership, which is
rotating and associated with different projects. The leader is one who sets <strong>the</strong> example and leading
<strong>the</strong> rest <strong>of</strong> <strong>the</strong> team. The companies have a systematic process, based on computer systems.
In parallel with a systematization <strong>of</strong> processes, <strong>the</strong>re is <strong>the</strong> record <strong>of</strong> organizational knowledge, which
is available on each company.
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According to <strong>the</strong> responses, we found that companies have certifications, some specific to <strong>the</strong> sector
where <strong>the</strong>y work.
Environmental policies and social interaction with <strong>the</strong>ir external environment, are an important
element <strong>of</strong> companies' activities.
Partnerships, are crucial in creating and developing value for each <strong>of</strong> <strong>the</strong> companies studied.
As we had seen for <strong>the</strong> parameter Technologies, any <strong>of</strong> <strong>the</strong> studied companies made investments in
ID, which allowed <strong>the</strong>m <strong>the</strong> connection between processes and <strong>the</strong>ir fur<strong>the</strong>r simplification.
We can verify that any <strong>of</strong> <strong>the</strong> companies studied has its strategy based on constant innovation which
leads to a wide variety <strong>of</strong> brands and patents that are essential in its differentiation from o<strong>the</strong>r
competitors.
The answers indicate <strong>the</strong> existence <strong>of</strong> a complaints system with one internal and one external
component.
We found that companies were awarded multiple times. These awards are recognition <strong>of</strong> <strong>the</strong>
interaction <strong>of</strong> business processes with customers.
Any <strong>of</strong> <strong>the</strong> companies carries out market studies, which are crucial to innovation and development <strong>of</strong>
<strong>the</strong>ir products.
The data analysis shows that any company has its organizational routines focused on customer
relations, in a perspective <strong>of</strong> Total Quality Management (TQM).
As we have seen in <strong>the</strong> process, <strong>the</strong> complaints system is part <strong>of</strong> <strong>the</strong> culture <strong>of</strong> each company.
Complaints are also exploited as an opportunity for continuous improvement focused on <strong>the</strong> client.
Internationalization is decisive in any <strong>of</strong> <strong>the</strong> companies examined. This internationalization is
accompanied by a permanent innovation whose success is based on partnerships.
5. Summary <strong>of</strong> conclusions
Through content analysis <strong>of</strong> Bardin (2009) in <strong>the</strong> context <strong>of</strong> case study according to Yin (2003) we
verified <strong>the</strong> applicability <strong>of</strong> Intellectual Capital Model (MCI) and its parameters.
The results <strong>of</strong> content analysis allow us to conclude that all <strong>the</strong> parameters <strong>of</strong> ICM were demonstrated
as well as <strong>the</strong>ir articulation within <strong>the</strong> Quadrants.
Case Study Interview Script was designed taking into consideration <strong>the</strong> Quadrants, <strong>the</strong> Parameters
and Overall MCI organization. The script is <strong>the</strong> result <strong>of</strong> several empirical research undertaken with
<strong>the</strong> aim <strong>of</strong> improving an audit intellectual capital management tool. There is thus a direct connection
between <strong>the</strong> various issues that are interrelated. The operationalization <strong>of</strong> relationships (which results
in relational capital) is achieved through <strong>the</strong> Networks that are facilitated by <strong>the</strong> existence <strong>of</strong> New
Technologies <strong>of</strong> Information and Communication.
Quadrants Capital Individual, Team Capital and Processes Capital are quadrants that have directly to
do with company´s environment, but which are essential for good performance in Capital Client
Quadrant. Capital Client Quadrant has to do with <strong>the</strong> way firms interact with <strong>the</strong>ir external
environment.
The transformation <strong>of</strong> tacit knowledge <strong>of</strong> individuals in explicit knowledge <strong>of</strong> <strong>the</strong> teams, is
implemented by sharing knowledge <strong>of</strong> <strong>the</strong> team. When this knowledge is associated with structural
capital, allows <strong>the</strong> formalization and development <strong>of</strong> organizational memory, which can improve <strong>the</strong>
processes for Total Quality.
The continued focus on customer satisfaction is achieved through interaction between <strong>the</strong> structural
capital and tacit knowledge.
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The training / qualification are crucial in <strong>the</strong> transformation <strong>of</strong> tacit knowledge into explicit knowledge.
This parameter acts as a promoter and facilitator <strong>of</strong> a team culture, with total focus on quality client
service.
It was also found that <strong>the</strong> alignment between <strong>the</strong> various leaders <strong>of</strong> <strong>the</strong> company is a key factor in <strong>the</strong>
continuing development <strong>of</strong> teams, including <strong>the</strong> creative teams.
"Networks" Intra and Inter-organizational and <strong>the</strong> "New Technologies" are structural elements that
allow <strong>the</strong> articulation between <strong>the</strong> four quadrants.
Finally, <strong>the</strong> talent management as an integral element <strong>of</strong> intellectual capital management presented
itself as <strong>the</strong> main factor in organizational success <strong>of</strong> <strong>the</strong> companies studied.
6. Final conclusion
This research allowed us to conclude that Intellectual Capital Model (ICM) and its parameters can be
an instrument for auditing intellectual capital management. The investment in talent management
seems to be a determinant key <strong>of</strong> organizational performance.
Despite <strong>the</strong> differences between <strong>the</strong> two countries (Portugal and Romania) and <strong>the</strong> differences
between <strong>the</strong> companies analyzed, particularly with regard to forms <strong>of</strong> management and business
area, <strong>the</strong> findings seem to point to <strong>the</strong> same factors for improving organizational performance. The
intellectual capital management is thus a factor <strong>of</strong> competitive advantage. To consolidate <strong>the</strong> results
will be important to conduct fur<strong>the</strong>r research in a larger universe <strong>of</strong> Romanian companies. Research
should also be extended to o<strong>the</strong>r countries, verifying <strong>the</strong> behavior <strong>of</strong> MCI and its parameters, in <strong>the</strong>se
different contexts.
Acknowledgments
This article is also a result <strong>of</strong> <strong>the</strong> projects: Creative economy & knowledge-based society. Challenges
& opportunities for Romania” (IDEI 1224, project financed by CNCSIS /UEFISCSU, Partnerships
92116 and POSDRU/6/1.5/S/11 „Doctoral Program and PhD Students in <strong>the</strong> education research and
innovation triangle”. The second project is co funded by <strong>the</strong> <strong>European</strong> Social Fund through <strong>the</strong>
Sectorial Operational Programme for Human Resources Development 2007-2013, coordinated by <strong>the</strong>
Bucharest Academy <strong>of</strong> Economic Studies.
7. Appendix: Case study script interview
1. What is <strong>the</strong> role <strong>of</strong> new technologies on company´s organizational development?
2. How new technologies are used by <strong>the</strong> company to interact with <strong>the</strong> various stakeholders?
3. Do you consider that new technologies can help to improve <strong>the</strong> customer service quality?
4. In <strong>the</strong> company, <strong>the</strong>re is a network culture?
5. Is <strong>the</strong>re any type <strong>of</strong> instrument Exchange <strong>of</strong> Ideas?
6. In <strong>the</strong> company <strong>the</strong>re is a network that allows contact with <strong>the</strong> various partners (customers,
suppliers, employees, etc.).
7. How does <strong>the</strong> company encourage <strong>the</strong> acquisition <strong>of</strong> knowledge and developing <strong>the</strong> talents <strong>of</strong>
each employee?
8. Employees who provide <strong>the</strong>ir individual knowledge and expertise are rewarded?
9. The company encourages its employees to be innovative?
10. The Innovation is disruptive or incremental?
11. The company has a policy <strong>of</strong> retaining talent?
12. There are some employees that you considers excessive at this point? How many? (%).
13. In five years, <strong>the</strong> number <strong>of</strong> employees would be <strong>the</strong> same?
14. What is <strong>the</strong> number or percentage <strong>of</strong> employees <strong>of</strong> <strong>the</strong> obsessive type?
15. What is <strong>the</strong> number or percentage <strong>of</strong> employees <strong>of</strong> <strong>the</strong> creative type?
16. What is <strong>the</strong> number or percentage <strong>of</strong> employees who have a sense <strong>of</strong> team?
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17. Are you afraid that some employees may go to <strong>the</strong> competition?
18. The company's work is organized in groups or teams?
19. Has <strong>the</strong> company a policy <strong>of</strong> compensation attached to <strong>the</strong> performance evaluation?
20. If yes, what is more valuable? The individual performance or a team performance?
21. What is <strong>the</strong> turnover rate in <strong>the</strong> company? Is turnover influenced by <strong>the</strong> reward system?
22. Have you ever fired an employee for doing a bad job?
23. Each client is seen by <strong>the</strong> team as a project or individualism exists in <strong>the</strong> relationship with
clients?
24. The work teams are focused on customers? In external customers and also internal
customers?
25. Each time that an employee acquires new knowledge (in process <strong>of</strong> formation or o<strong>the</strong>r) he
shares this knowledge with <strong>the</strong> rest <strong>of</strong> <strong>the</strong> team?
26. The company encourages innovation, in general, or this is just focused on innovative teams?
27. Do you consider that teams are innovative? What kind <strong>of</strong> innovation is more frequent
(sequential improvement, or o<strong>the</strong>r)?
28. Teams / groups have a leader or boss? (This leader was elected, it was rotating or
emerging?)
29. The company uses new technology to record and store information relating to all processes
(company documentation)? How?
30. This information can be accessed at any time by <strong>the</strong> various partners (employees, customers,
suppliers, etc.)?
31. Company employees make any record <strong>of</strong> <strong>the</strong>ir knowledge (CV, ideas, contacts, information,
etc.)? How is it done?
32. Are <strong>the</strong> environmental policies, namely <strong>the</strong> "zero carbon" interfering in <strong>the</strong> internal policies <strong>of</strong>
<strong>the</strong> company?
33. The company provides any type social policies?
34. The company has some kind <strong>of</strong> partnership? How <strong>the</strong>se partnerships help to create value for
<strong>the</strong> company?
35. There have been investments in ID that allowed simplify organizational processes?
36. The company has invested in <strong>the</strong> creation <strong>of</strong> trademarks / patents management? How?
37. Is <strong>the</strong>re any system <strong>of</strong> internal complaints from employees <strong>of</strong> <strong>the</strong> organization?
38. The company has ever been awarded? What kind <strong>of</strong> awards?
39. The company has a specialized staff to oversee <strong>the</strong> competition and to control what is she
doing in terms <strong>of</strong> innovation (e.g. visits to fairs, internet research, etc.)?
40. The company conducts market research? How do <strong>the</strong>se studies affect <strong>the</strong> company's
policies?
41. In <strong>the</strong> relationship with customers, <strong>the</strong> company has a continued focus on total quality? What
importance is given to customer complaints?
42. The company recently entered into new markets? With <strong>the</strong> same products / services or new
products / services?
43. The internationalization <strong>of</strong> <strong>the</strong> company is part <strong>of</strong> current strategies? This internationalization
is done through networking / partnerships or alone?
44. Innovation is <strong>the</strong> result <strong>of</strong> listening to <strong>the</strong> needs <strong>of</strong> customers, employees' ideas, teams’ ideas
or <strong>the</strong> interaction <strong>of</strong> several variables?
45. How are <strong>the</strong>se ideas selected and processed into products and services important to <strong>the</strong>
customer?
46. How are <strong>the</strong>se ideas validated in <strong>the</strong> market?
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47. Opinion - In your opinion, <strong>the</strong>re is some relationship between <strong>the</strong> company´s management <strong>of</strong>
individual and collective talents and its organizational success?
References
Amândio José Lobo ( AJLobo): Available: http://www.ajlobo.com/ [05 December 2010].
Akcedo Dynamic: Available: http://www.akcedo.com/ [05 December 2010].
Andriessen, D. and Tisane R. (2000) Weightless Wealth. Financial Times. Prentice Hall.
Andriessen, D. (2004) Making Sense <strong>of</strong> Intellectual Capital. Designing a Method for <strong>the</strong> Valuation <strong>of</strong> Intangibles.
Elsevier Butterworth-Heineman, Burlington (MA) and Oxford (UK).
Andriessen, D. (2004a) “IC valuation and measurement: classifying <strong>the</strong> state <strong>of</strong> <strong>the</strong> art” Journal <strong>of</strong> Intellectual
Capital, Vol. 5, No. 2, pp 230-242.
Bardin, Laurence (2009) Análise de Conteúdo. Lisboa: Edições 70.
Edvinsson, L. and Malone, M.S. (1997) Intellectual Capital, Harper Collins Publishers Inc., New York.
Hamel, J., Dufour, S., & Fortin, D. (1993). Case study methods. Newbury Park, CA: Sage Publications.
Kaplan RS and Norton DP (1992) ”The Balanced Scorecard” Harvard Business Review, Jan-Feb 71-79.
Kaplan RS and Norton DP (1996) “Using <strong>the</strong> Balanced Scorecard as a Strategic Management System" Harvard
Business Review. Jan-Feb.
Kaplan RS and Norton DP (1996a) The Balanced Scorecard, Harvard Business School Press, Boston
Massachusetts.
Itami Hiroyuki; Roehl Thomas W. (1991) Mobilizing invisible assets. London: Harvard University Press.
Lopes, A; Matos F. (2008) “Intellectual Capital Management - Certification Model” 9th <strong>European</strong> <strong>Conference</strong> on
Knowledge Management, Southampton Solent University, Southampton.
Matos F.; Lopes A. (2009) “Intellectual Capital Management – SMEs Accreditation Methodology” Paper read at
<strong>European</strong> <strong>Conference</strong> on Intellectual Capital 09, INHolland University <strong>of</strong> Applied Sciences, Haarlem, The
Ne<strong>the</strong>rlands, 28-29 April.
Mouritsen, Jan, Larsen, H.T., Bukh, P.N. and Johansen, M.R. (2001) ”Reading an Intellectual Capital Statement
Paper “The 4th.Intangibles conference” en Stern School <strong>of</strong> Business, New York University.
Sveiby, K. E. (1997) The New Organizational Wealth. Managing & Measuring Knowledge-Based Assets, Berrett-
Koehler Publishers, San Francisco.
Unicredit Leasing: Available: http://www.unicreditleasing.ro/ [05 December 2010].
Viedma (2001) “ICBS Intellectual Capital Benchmarking System” Journal <strong>of</strong> Intellectual Capital, Vol 2 No 2, pp
148-164.
Ydreams: Available: http://www.ydreams.com/ [05 December 2010].
Yin,R. (2003). Case study research: Design and methods (3nd ed.)Thousand Oaks, CA: Sage Publications.
250

Intellectual Capital Management and Food Control
Florinda Matos 1 , Susana Rodrigues 1 , Albino Lopes 2 , Rui Coutinho 3 and Nuno
Matos 4
1
School <strong>of</strong> Technology and Management – CIGS, Polytechnic Institute <strong>of</strong> Leiria,
Portugal
2
ISCSP – CAPP - Technical University <strong>of</strong> Lisbon, Portugal
3
ESAS - Polytechnic Institute <strong>of</strong> Santarém, Portugal
4
PMEConsult, Santarém, Portugal
florinda.matos@ipleiria.pt
suzana@ipleiria.pt
alopes@iscsp.utl.pt
rmscoutinho@gmail.com
nuno.matos@pmeconsult.pt
Abstract: Companies increasingly exposed to globalization, are faced with many challenges. Today it is no
longer enough to produce well; we must be proactive, synergistic and very competitive. These assumptions are
based on access and sharing <strong>of</strong> knowledge as a condition for achieving maximized levels <strong>of</strong> productivity and
competitiveness. Developments in food control, as well as improvements in food inspection and surveillance
systems, are mainly due to globalization <strong>of</strong> <strong>the</strong> food chain, <strong>the</strong> increasing importance <strong>of</strong> <strong>the</strong> Codex Alimentarius
Commission, and <strong>the</strong> obligations under <strong>the</strong> World Trade Organization. This development is <strong>the</strong> result <strong>of</strong> great
interest in developing food standards and regulations, as well as streng<strong>the</strong>ning <strong>the</strong> infrastructure <strong>of</strong> food control
in <strong>the</strong> world. In this context, intellectual capital is one <strong>of</strong> <strong>the</strong> organizations' most valuable assets that should be
managed. In <strong>the</strong> case <strong>of</strong> food businesses <strong>the</strong> problem <strong>of</strong> intellectual capital management has become more
complex, since many types <strong>of</strong> food need handling, expertise, and <strong>the</strong> observance <strong>of</strong> all procedures in order to
produce safe quality food. This involves many hours <strong>of</strong> training and an on-going sharing <strong>of</strong> knowledge. The aim
<strong>of</strong> this paper is to discuss <strong>the</strong> importance <strong>of</strong> intellectual capital management in <strong>the</strong> food sector. It is intended to
verify if <strong>the</strong> food quality control is linked to how companies manage <strong>the</strong>ir intellectual capital. The research
methodology used is <strong>the</strong> case study through a qualitative research, carried out in a Portuguese company in <strong>the</strong>
food sector. In terms <strong>of</strong> originality, we intend to study <strong>the</strong> issue <strong>of</strong> intellectual capital management in a different
area from which this asset has usually been studied. The practical implications <strong>of</strong> this research lead us to <strong>the</strong> fact
that in <strong>the</strong> case <strong>of</strong> food control, management <strong>of</strong> intellectual capital is a key factor in ensuring product quality and
<strong>the</strong>refore may influence <strong>the</strong> company’s production capacity.
Keywords: intellectual capital management, knowledge, food control
1. Introduction
The current economic trend shows a growing importance <strong>of</strong> organizations' intangible assets.
In many sectors <strong>of</strong> <strong>the</strong> economy, intangible assets have become less important and knowledge is
considered as a source <strong>of</strong> competitive advantage.
In this sense, knowledge is information that enables decision making in a certain context and
knowledge management is <strong>the</strong> organization's ability to identify and codify knowledge, stimulate its
development and facilitate its implementation.
This knowledge may be used, but becomes <strong>the</strong> organizations' property only, when it is voluntarily
provided, we have been talking about intellectual capital.
For food businesses, <strong>the</strong> problem <strong>of</strong> intellectual capital management has become more complex,
since many types <strong>of</strong> food require too much manipulation and expertise, as well as compliance to all
procedures in order to produce safe food.
Indeed, food safety, is defined by Henson and Traill (1993), as <strong>the</strong> inverse <strong>of</strong> food risk, i.e. <strong>the</strong>
probability that <strong>the</strong>re is no damage by consumption <strong>of</strong> a food, it has become crucial in <strong>the</strong> food chain.
On <strong>the</strong> o<strong>the</strong>r hand, speaking <strong>of</strong> food quality does not mean food security. The quality is only one
element <strong>of</strong> food security.
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In <strong>the</strong> case <strong>of</strong> <strong>the</strong> food industry and quality assurance, particularly manufacturing <strong>of</strong> meat, food
security (safety) depends on various quality checks carried out since <strong>the</strong> production process until it
reaches <strong>the</strong> consumer. Thus, food security can only be guaranteed through a rigorous inspection.
This paper studies food control at <strong>the</strong> level <strong>of</strong> industry and distribution <strong>of</strong> meat. This industry has a
strategic role in <strong>the</strong> supply chain security, because it allows <strong>the</strong> connection between <strong>the</strong> productive
sector and <strong>the</strong> final consumer.
The food control held at this level ensures food safety, with consequent financial benefits to <strong>the</strong> entire
production chain.
Empirical research was developed in <strong>the</strong> context <strong>of</strong> achieving a master's <strong>the</strong>sis in order to prove <strong>the</strong>
relationship between food control and intellectual capital management.
We used <strong>the</strong> methodology <strong>of</strong> single case study according to Yin (2003), which was applied to <strong>the</strong>
Model <strong>of</strong> Intellectual Capital (Matos and Lopes, 2009). For reasons <strong>of</strong> confidentiality required by <strong>the</strong>
company, target search is <strong>the</strong> only available information considered essential to <strong>the</strong> understanding
and interpretation <strong>of</strong> this research.
The following sections summarize <strong>the</strong> main aspects <strong>of</strong> <strong>the</strong> research.
2. Literature review: Intellectual capital models
Several authors have advocated <strong>the</strong> importance <strong>of</strong> measuring intellectual capital from a strategic
perspective (Petty and Guthrie 2000; Zhou and Fink 2003) as a way to assess <strong>the</strong> management and
development <strong>of</strong> intangible assets (Leliaert, Candries et al. 2003).
Although, <strong>the</strong>re have been some attempts to measure intellectual capital using financial methods, it
was found that <strong>the</strong>se methods are not sufficient. Authors, like Edvinsson and Malone (1997) and
Malhotra (2003) have advocated <strong>the</strong> need to complement financial methods to non-financial methods,
to provide <strong>the</strong> true value <strong>of</strong> organizations.
Thus, <strong>the</strong>re have been several models and methodologies that represent different approaches to <strong>the</strong>
measurement <strong>of</strong> intellectual capital.
Williams (2000) proposed a classification <strong>of</strong> intellectual capital models depending on <strong>the</strong> type <strong>of</strong>
expected outcome and <strong>the</strong> identification <strong>of</strong> intellectual capital, according to <strong>the</strong> following categories:
Scorecard Method, Direct Intellectual Capital Methods, Market Capitalization Methods and Return on
Assets. This classification has been adopted by many authors.
To <strong>the</strong> authors, <strong>the</strong>re seem to be no perfect methods, ie none <strong>of</strong> <strong>the</strong> methods are able to meet all
needs. The authors tend to choose <strong>the</strong> method according to <strong>the</strong> context and <strong>the</strong> objectives <strong>the</strong>y seek.
Among <strong>the</strong> methods, most referred, we find <strong>the</strong> "Intangible Assets Monitor” (Sveiby, 1997) and <strong>the</strong>"
Skandia Navigator “Edvinsson and Malone (1997), which are Scorecard methods.
Among <strong>the</strong> methods and methodologies for evaluating intellectual capital, authors highlight <strong>the</strong>
following:
Kaplan (Kaplan and Norton, 1992, 1996a) – “Balanced Scorecard” methodology
Brooking (1996) - Technology Broker
Bontis (1996) - Citation-Weighted Patents
Sveiby (1997) – “Intangible Assets Monitor” model
Stewart (1997) - Economic Value Added
Edvinson (Edvinson and Malone, 1997) – “Skandia Navigator” model
Roos, Dragonetti et al. (1997) - Intellectual Capital Index
Lev (1999) - Knowledge Capital Earnings
Andriessen and Tissen (2000) - “Value Explorer” methodology
Allee (2000) - Intangible Value Framework
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Edvinsson (2000) - IC Rating
Joia (2000) - Intellectual Capital Rating
Florinda Matos et al.
Anderson and McLean (2000) - Total Value Creation
M´Pherson and Pike (2001) - Inclusive Valuation Methodology
Mouritsen et al. (2001) - “IC Accounting System” methodology
Meritum (2001) Meritum Guidelines
Lev (2002) - Value Chain Scoreboard
Stam (2002) - Intellectual Capital Monitor
Mouritzen, Bukh et al. (2003) - Danish Guidelines
Viedma (Viedma, 2001, 2003) - “Intellectual Capital Benchmarking System” methodology
Leliaert, Candries et al. (2003) - The 4-Leaf Model
Boedker, Guthrie et al. (2005) - Intellectual Capital Value Creation
Litschka, Markom et al. (2006) - The Plexus Model
Schiuma, Erro, Carduce (2008) - Regional Intelectual Capital Índex (RICI)
Sanchez (2009) - ICU Report
These models and methodologies will not be developed as this is not <strong>the</strong> objective <strong>of</strong> this paper. On
<strong>the</strong> o<strong>the</strong>r hand, it is assumed that <strong>the</strong> readers <strong>of</strong> this paper will be able to access <strong>the</strong> different
approaches in <strong>the</strong>se models easily.
The model used in this paper is <strong>the</strong> “Intellectual Capital Model” (ICM) (Matos and Lopes, 2009).
The choice <strong>of</strong> this Model is linked to <strong>the</strong> need for being able to identify, in an integrated and consistent
way, <strong>the</strong> complexity <strong>of</strong> <strong>the</strong> factors in <strong>the</strong> framework <strong>of</strong> organizational knowledge. Compared with o<strong>the</strong>r
models, ICM seems to be more adapted to evaluate <strong>the</strong> intellectual capital management. The ICM -
Intellectual Capital Model - consists <strong>of</strong> 4 Quadrants specified by <strong>the</strong>ir parameters (Matos and Lopes,
2009).
Figure 1: ICM - Intellectual capital model (Matos and Lopes, 2009)
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Florinda Matos et al.
The Quadrant Individual Capital, Team Capital and Processes Capital are related to <strong>the</strong> company's
internal environment, <strong>the</strong> Quadrant Clients Capital is related to <strong>the</strong> external environment.
ICM parameters are:
Use <strong>of</strong> New Technologies <strong>of</strong> Information and Communication – NTIC
Use <strong>of</strong> Networks
Individual Capital Quadrant
Training / Qualification and Talent management
Valuation <strong>of</strong> Know - How and Innovation
Investment in Innovation and Development (ID)
Existence <strong>of</strong> a Policy for Talent Retention
Team Capital Quadrant
Training / Qualification
Team Work
Innovation in teams
Leadership in teams
Processes Capital Quadrant
Processes Systematization
Registration <strong>of</strong> Organizational Knowledge
Existence <strong>of</strong> Certification, environmental and social policies
Partnerships
Investment in Innovation and Development (ID)
The Brands Creation and Management
Complaints System
The existence <strong>of</strong> Awards
Clients Capital Quadrant
Market Audits
Management <strong>of</strong> <strong>the</strong> Clients' Satisfaction
Complaints System dos clients
New Markets
It should be noted that <strong>the</strong> ICM is a dynamic model and <strong>the</strong>refore it is not a completely stabilized
model. Moreover, as its application will be implemented in more companies, fur<strong>the</strong>r adjustments may
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be required. Indeed, this is one <strong>of</strong> <strong>the</strong> advantages <strong>of</strong> this model: its interactive dynamism, which has
proven to be very good in turbulent business contexts.
3. Empirical research
This survey was conducted in 2010 in a large Portuguese company, in <strong>the</strong> area/sector <strong>of</strong> <strong>the</strong> meat
industry.
The company studied works in <strong>the</strong> area/sector <strong>of</strong> fresh meat products, cutting <strong>of</strong> casings (pork, lamb
and goat), slicing <strong>of</strong> parts (pork, beef, veal, lamb and goat), and preparation <strong>of</strong> minced, prepared and
marinated meat as well as its packaging.
The company has a total <strong>of</strong> 540 employees, 350 permanent and <strong>the</strong> rest/remaining in temporary
work.
This research aims to discuss <strong>the</strong> importance <strong>of</strong> intellectual capital management in <strong>the</strong> food sector.
We used <strong>the</strong> single case study methodology according Yin (2003) associated with Intellectual Capital
Model (Matos and Lopes, 2009). We have considered this model appropriate to audit intellectual
capital management. According to Yin (2003, p. 39-40) case studies can be single or multiple
drawings.
Single case studies are ideal for cases <strong>of</strong> revelation. The case study is an excellent tool when we
want to understand a reality and for defining future paths <strong>of</strong> research.
Regarding <strong>the</strong> pr<strong>of</strong>ile <strong>of</strong> respondents, we examined <strong>the</strong> leader's vision.
Similarly to Yin (2003, p.99) this empirical study will follow <strong>the</strong> triangulation <strong>of</strong> data. This triangulation
will be supported by ga<strong>the</strong>ring information from different data sources in order to verify if <strong>the</strong> same
sources corroborate <strong>the</strong> same phenomenon.
As criteria <strong>of</strong> quality research, we shall consider <strong>the</strong> four tests referred by Yin (2003, p. 34): construct
validity, internal validity, external validity and reliability.
Following <strong>the</strong> methodological procedures set out above, we used content analysis, according to
Bardin (2009) with <strong>the</strong> following steps <strong>of</strong> content analysis: pre-analysis, content analysis, processing
<strong>of</strong> <strong>the</strong> results interpretation.
As one <strong>of</strong> <strong>the</strong> techniques mentioned by several authors, <strong>the</strong> analysis <strong>of</strong> categories, according to
Bardin (2009) is <strong>the</strong> technique used in this research.
We started by defining <strong>the</strong> categories guiding <strong>the</strong> questions asked to respondents, followed by <strong>the</strong>
analysis <strong>of</strong> <strong>the</strong> collected material for interpretation <strong>of</strong> <strong>the</strong> dominant <strong>the</strong>mes in each category.
The Guidelines had been designed, taking into account three levels <strong>of</strong> analysis:
(A) Level 1 - Quadrants
(B) Level 2 - Parameters
(C) Level 3 - Overall organization <strong>of</strong> ICM.
To follow <strong>the</strong>se methodological procedures, we proceeded to <strong>the</strong> full transcript <strong>of</strong> <strong>the</strong> interviews.
Afterwards, <strong>the</strong> data was categorized according to <strong>the</strong> categories and subcategories defined a priori.
4. Results
The data analysis allowed us to verify that new technologies are very important in <strong>the</strong> company.
New technologies enable <strong>the</strong> improvement <strong>of</strong> processes, <strong>the</strong> identification <strong>of</strong> new work patterns and
new information systems, in order to constantly improve <strong>the</strong> industry performance. Never<strong>the</strong>less, only
approximately 10% <strong>of</strong> <strong>the</strong> employees use <strong>the</strong> new technologies.
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Integrated teamwork is <strong>the</strong> key to good performance. Integrated teamwork means sharing
consistently and cohesively ideas and information at all organizational levels: strategically and
operationally in all organizational functions (planning, product development, acquirement, commercial,
financing, etc.). Teams are heterogeneous. Teams work is process; since <strong>the</strong> reception <strong>of</strong> <strong>the</strong> product
to its delivery to <strong>the</strong> customer. The aim <strong>of</strong> <strong>the</strong> company is to ensure product delivery, with commercial
presentation, on time and according to customer needs. The maturity <strong>of</strong> <strong>the</strong> teams is regarded as a
decisive factor in competitiveness. In this area <strong>of</strong> activity, <strong>the</strong>re is a very strong component <strong>of</strong>
information flow, resulting from business planning. The planning activity is multiple and includes
production planning, cutting planning, cargo planning, and transportation planning, among o<strong>the</strong>rs.
Thus, <strong>the</strong> flow <strong>of</strong> information requires constant networking.
Both Internal networks and external networks gain great importance. These networks ensure that <strong>the</strong>
proceedings take place without fail.
These networks are all supported on computer media. New technologies are determining on
delivering customer service quality. New technologies provide information for decision making; allow
communication and enable processes accomplishment.
The flow <strong>of</strong> ideas among company´s people is a key element for <strong>the</strong> creation <strong>of</strong> a network <strong>of</strong>
knowledge. However, <strong>the</strong> respondent admits that <strong>the</strong> intensity <strong>of</strong> work <strong>of</strong>ten does not allow <strong>the</strong>
knowledge sharing. In order to facilitate and stimulate ideas, and knowledge among all employees,
<strong>the</strong> company has introduced <strong>the</strong> Kaisen philosophy (<strong>the</strong> Japanese model, or philosophy, for quality
management). The implementation <strong>of</strong> Kaisen programs allowed <strong>the</strong> use <strong>of</strong> models already tested
(analysis models, implementation models and models <strong>of</strong> effective control task).
The Kaisen model allows <strong>the</strong> emergence <strong>of</strong> new ideas. Simultaneously and to complement that, it
was introduced a suggestion box. Suggestions are discussed and answered. The suggestion system
also works as an internal complaints system.
The ideas developed maintain <strong>the</strong> identity <strong>of</strong> <strong>the</strong> author. This is a way to reward employees and
encourage creativity. Ideas allow a continuous improvement <strong>of</strong> <strong>the</strong> organization. The improvements
achieved are shared to all.
O<strong>the</strong>r interesting result is that <strong>the</strong> company turnover has been declining, standing now at
approximately 10%. One <strong>of</strong> <strong>the</strong> possible explanations for this figure is <strong>the</strong> employee rotation. The
effects <strong>of</strong> rotation have been minimized by increasing <strong>the</strong> processes' efficiency, which has created
less need for overtime work. The retaining talent policy is based on a set <strong>of</strong> procedures, such as team
management, analysis, evaluation, reward, promotion <strong>of</strong> people, to name a few.
Among workers, <strong>the</strong>re is a diversity <strong>of</strong> behaviors. It is common to find obsessive collaborators as well
as creative collaborators.
Due to <strong>the</strong> high level <strong>of</strong> responsibility <strong>of</strong> each <strong>of</strong> <strong>the</strong> functions, organizational commitment is evident in
<strong>the</strong> majority <strong>of</strong> employees.
The company invests in training continuously. Also, various tools to enhance individual
competitiveness are available. Training needs are identified according to <strong>the</strong> technical level <strong>of</strong> each
function, behavioral and social needs. For example, in <strong>the</strong> social area, <strong>the</strong> training covers domestic
violence or domestic economy. The training models allow team knowledge sharing.
Team work is constantly focused on <strong>the</strong> client. There is a constant attempt to bring <strong>the</strong> customer into
<strong>the</strong> company. The work is developed for <strong>the</strong> customer and but also for <strong>the</strong> supplier. The company's
management tries to create a model where everyone has to really take responsibility for customer and
supplier.The aim is to make <strong>the</strong> employee to achieve a high level <strong>of</strong> responsibility as well as allowing
feeling good.
In <strong>the</strong> company <strong>the</strong>re is an emerging leadership. These leaders are people who are identified as
natural leaders.
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O<strong>the</strong>r remarkable result is that innovation has increased at <strong>the</strong> group level. The company has an
innovative area that is active in some ways. There are several levels <strong>of</strong> innovation: <strong>the</strong> elementary
level (incremental type) or disruptive innovation. Innovation is at <strong>the</strong> product level but also at <strong>the</strong> level
<strong>of</strong> equipment and processes. The company does not register <strong>the</strong> patents or trademarks, so <strong>the</strong>
competition <strong>of</strong>ten copies <strong>the</strong> innovations. In <strong>the</strong> future, <strong>the</strong> company is considering starting to register
trademarks and patents.
The report <strong>of</strong> best practices for each function increases company performance. When it is necessary
to replace an employee, <strong>the</strong> company tries to find ano<strong>the</strong>r employee with similar experience. The goal
is that <strong>the</strong> company will not be affect by <strong>the</strong> leave <strong>of</strong> one employee, as <strong>the</strong>y work as team sharing
multitasks.
In subjects considered as intellectual property (times <strong>of</strong> manufacturing, new products, new processes)
<strong>the</strong>re is a permanent information trace.
The company is quality certified with safety and food hygiene.
The environmental policies, focused on sustainability, are a constant concern <strong>of</strong> <strong>the</strong> company.
The company monitors <strong>the</strong> social area in <strong>the</strong> region where it acts to try to reduce <strong>the</strong> social problems
that can have an effect on <strong>the</strong>ir business.
Currently <strong>the</strong> company's partnerships are restricted to <strong>the</strong>ir economic group and to an educational
institution in <strong>the</strong> region.
Most <strong>of</strong> <strong>the</strong> company's staff studied at <strong>the</strong> higher education institution.
The company has been awarded (for about 4 years), for recognition <strong>of</strong> best practices in integrating
and accepting people in temporary work. The monitoring <strong>of</strong> competition and market studies are made
by o<strong>the</strong>r companies in its group.
The company has a specific area for complaints. All complaints are dealt with individually.
The company has a fixed set <strong>of</strong> products; however, it will launch new products to evaluate customer
behavior.
The company operates only in <strong>the</strong> Portuguese market. There are no international projects, since <strong>the</strong>
domestic market is sufficient. Possible strategies for internationalization are always dependent on <strong>the</strong>
policies defined by <strong>the</strong> economic group in which <strong>the</strong> company operates.
Whenever <strong>the</strong>re is a new idea, it is validated in <strong>the</strong> market in two ways: through <strong>the</strong> number <strong>of</strong> sales
and through customer feedback.
Any product, before being placed on <strong>the</strong> market, is tested for <strong>the</strong> presentation and
behavior/positioning on <strong>the</strong> shelf.
The new products are <strong>the</strong> result <strong>of</strong> listening to <strong>the</strong> needs <strong>of</strong> customers, internal groups/sets <strong>of</strong> ideas
and <strong>the</strong> ideas <strong>of</strong> some internal employees.
5. Summary <strong>of</strong> conclusions
The data analysis shows that <strong>the</strong> company has its organizational routines focused on customer
relations, in a perspective <strong>of</strong> Total Quality Management (TQM).
Through training, <strong>the</strong> company creates a team culture. As <strong>the</strong> interviewee said: "The important thing is
<strong>the</strong> team as a whole and not individual people." It is <strong>the</strong> team culture that is able to fill any gaps that
occur at <strong>the</strong> individual level. This team culture, combined with an emerging leadership and very flat
organizational structure, is a key determinant <strong>of</strong> <strong>the</strong> stability <strong>of</strong> <strong>the</strong> company. This stability is also
promoted through organizational commitment.
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The networks and new technologies are very important, especially in interaction with various
stakeholders.
However, <strong>the</strong> company recognizes that <strong>the</strong> networks facilitate <strong>the</strong> flow and sharing <strong>of</strong> knowledge, but
sometimes do not work.
Innovation though existing (incremental and disruptive) is not translated in <strong>the</strong> registration <strong>of</strong>
trademarks and patents, which means that <strong>the</strong> company has some difficulty in defending itself from
competitors.
The exchange <strong>of</strong> ideas and suggestions, coupled with <strong>the</strong> recognition given to <strong>the</strong>se elements is a
key element <strong>of</strong> <strong>the</strong> firm's innovative capacity.
The appreciation <strong>of</strong> <strong>the</strong> expertise <strong>of</strong> employees enables a greater commitment to organizational
efficiency and effectiveness.
Despite <strong>the</strong> turnover, corresponding to <strong>the</strong> difficulties <strong>of</strong> <strong>the</strong> tasks, it appears that <strong>the</strong>re is a particular
emphasis on <strong>the</strong> retention <strong>of</strong> people, which results from training programs, performance assessment
and career management.
The focus on internal and external clients also seems to contribute to organizational stability.
The company has a lot <strong>of</strong> attention with all that has to do with food safety because <strong>the</strong>ir success or
failure depends on <strong>the</strong> security guarantees given. The certificates represent <strong>the</strong> food stamp
guarantee.
Internationalization is not a current goal <strong>of</strong> <strong>the</strong> company, since <strong>the</strong>y are constrained by global
strategic guidelines <strong>of</strong> its economic group.
6. Final conclusion
This survey, conducted in <strong>the</strong> context <strong>of</strong> <strong>the</strong> case study Yin (2003), using <strong>the</strong> Model <strong>of</strong> Intellectual
Capital has allowed us to verify that it is possible to audit <strong>the</strong> management <strong>of</strong> intellectual capital in <strong>the</strong>
food business. We could also conclude that <strong>the</strong>re is a direct relationship between <strong>the</strong> quality <strong>of</strong> food
control and management <strong>of</strong> intellectual capital.
For <strong>the</strong> company studied we conclude that when <strong>the</strong> tacit knowledge <strong>of</strong> individuals is transformed into
explicit knowledge <strong>of</strong> <strong>the</strong> team, which is formalized in processes and operationalized in customer
satisfaction, <strong>the</strong>re is <strong>the</strong> improvement <strong>of</strong> food control.
When <strong>the</strong> knowledge <strong>of</strong> <strong>the</strong> team becomes explicit, it allows <strong>the</strong> development <strong>of</strong> organizational
memory, which facilitates <strong>the</strong> improvement in view <strong>of</strong> Total Quality.
The continued focus on customer satisfaction is achieved through interaction between <strong>the</strong> structural
capital and tacit knowledge.
Intellectual capital management is thus a factor <strong>of</strong> competitive advantage in <strong>the</strong> food industry.
To consolidate <strong>the</strong> results, it will be important to conduct fur<strong>the</strong>r research in a larger universe <strong>of</strong>
similar companies.
References
Allee, V. (2000) "The Value Evolution", Journal <strong>of</strong> Intellectual Capital, Vol. 1, No 1, 17-30.
Anderson, Mclean. Total Value Creation. Available: www.totalvaluecreation.com [05 December 2010].
Andriessen, D. and Tisane R. (2000) Weightless Wealth. Financial Times. Prentice Hall.
Andriessen, D. (2004) Making Sense <strong>of</strong> Intellectual Capital. Designing a Method for <strong>the</strong> Valuation <strong>of</strong> Intangibles.
Elsevier Butterworth-Heineman, Burlington (MA) and Oxford (UK).
Andriessen, D. (2004a) “IC valuation and measurement: classifying <strong>the</strong> state <strong>of</strong> <strong>the</strong> art” Journal <strong>of</strong> Intellectual
Capital, Vol. 5, No. 2, 230-242.
Bardin, Laurence (2009) Análise de Conteúdo. Lisboa: Edições 70.
Boedker, C., J. Guthrie, et al (2005). "An integrated framework for visualizing intellectual capital", Journal <strong>of</strong>
Intellectual Capital, Vol. 6, No 4, 510-527.
258

Florinda Matos et al.
Bontis, N. (1996). "There´s a price to on your head: managing intellectual capital strategically", Business
Quarterly, Summer.
Brooking, A. (1996) Intellectual Capital: Core Assets for <strong>the</strong> Third Millennium Enterprise, London, United
Kingdom.
Edvinsson, L. and Malone, M.S. (1997) Intellectual Capital, Harper Collins Publishers Inc., New York.
Henson, S.; Traill, B. (1993) The demand for food safety: market imperfections and <strong>the</strong> role <strong>of</strong> government. Food
Policy, Vol. 18 No. 2.
Kaplan RS and Norton DP (1992) ”The Balanced Scorecard” Harvard Business Review, Jan-Feb 71-79.
Kaplan RS and Norton DP (1996) “Using <strong>the</strong> Balanced Scorecard as a Strategic Management System" Harvard
Business Review. Jan-Feb.
Kaplan RS and Norton DP (1996a) The Balanced Scorecard, Harvard Business School Press, Boston
Massachusetts.
Joia, L. (2000) "Measuring Intangible Corporate Assets", Journal <strong>of</strong> Intellectual Capital, Vol. 1, No 1, : 68-84.
Leliaert, Candries, et al. (2003). "Identifying and managing IC: a new classification", Journal <strong>of</strong> Intellectual
Capital, Vol. 4, No 2, 202-214.
Lev, B (2002) Intangibles: Management, Measurement and Reporting, Brookings Institute Press, Washington
DC.
Litschka, M., A. Markom, et al. (2006). "Measuring and analyzing intellectual assets: an integrative approach",
Journal <strong>of</strong> Intellectual Capital, Vol. 7 No 2, 160-173.
Malhotra, Y (2003). Measuring Knowledge Assets <strong>of</strong> a Nation: Knowledge Systems for Development. New York,
Research Paper prepared for <strong>the</strong> Invited Keynote Presentation delivered at <strong>the</strong> United Nations.
Matos F.; Lopes A. (2009) “Intellectual Capital Management – SMEs Accreditation Methodology” Paper read at
<strong>European</strong> <strong>Conference</strong> on Intellectual Capital 09, INHolland University <strong>of</strong> Applied Sciences, Haarlem, The
Ne<strong>the</strong>rlands, 28-29 April.
MERITUM - Guidelines for Managing and Reporting on Intangibles, Available:
http://www.uam.es/proyectosinv/meritum/Link%20Guidelines%20Meritum/ [05 December 2010].
M´Pherson, Pike (2001) "Accounting, empirical measurement and intellectual capital", Journal <strong>of</strong> Intellectual
Capital, Vol. 2, No 3, 246-260.
Mouritsen, Jan, Larsen, H.T., Bukh, P.N. and Johansen, M.R. (2001) ”Reading an Intellectual Capital Statement
Paper “The 4th.Intangibles conference” en Stern School <strong>of</strong> Business, New York University.
Mouritzen, J., P. Bukh, et al. Intellectual Capital Statements - The New Guideline, Available:
http://www.sveiby.com/articles/IntangibleMethods.htm [05 December 2010].
Petty, R. E J., Guthrie (2000). "Intellectual capital literature review", Journal <strong>of</strong> Intellectual Capital, Vol1, No 2,
155-176.
Roos, J., N. DragonettiI, et al (1997). Intellectual Capital: Navigating in <strong>the</strong> New Business Landscape, Macmillan,
New York.
Sanchez P., Elena S., Castrillo R. 2009: Intellectual capital dynamics in universities: a reporting model. Journal <strong>of</strong>
Intellectual Capital. Vol. 10 No. 2.
Schiuma, G., Lerro A., Carlucci D., (2008) The Knoware Tree and <strong>the</strong> Regional Intellectual Capital Index: An
assessment within Italy. Journal <strong>of</strong> Intellectual Capital Vol. 9 No. 2.
Stam (2002) Intellectual Capital Monitor, Available :
http://www.intellectualcapital.nl/publications/Intellectual%20Capital%20Monitor.pdf
StewartT, T (1997). Intellectual Capital - The New Wealth Organization, Doubleday, New York.
Sveiby, K. E. (1997) The New Organizational Wealth. Managing & Measuring Knowledge-Based Assets, Berrett-
Koehler Publishers, San Francisco.
Viedma (2001) “ICBS Intellectual Capital Benchmarking System” Journal <strong>of</strong> Intellectual Capital, Vol 2 No 2, 148-
164.
ViedmaI, J. (2003). "In Search <strong>of</strong> an Intellectual Capital Theory", The Electronic Journal <strong>of</strong> Knowledge
Management, Vol 1, Issue 2, 213-226.
Williams, M. (2000). "Is a company' s intellectual capital performance and intellectual capital disclosure practices
related?" McMasters Intellectual Capital <strong>Conference</strong>, Toronto, Canada.
Yin, R. (2003). Case study research: Design and methods (3nd ed.)Thousand Oaks, CA: Sage Publications.
Zhou, A. E D. Fink (2003). "The Intellectual Capital Web: a systematic linking <strong>of</strong> intellectual capital and
knowledge management", Journal <strong>of</strong> Intellectual Capital, Vol. 4, (2003), 34-48.
259

Knowledge Management for Knowledge Workers
Ludmila Mládková
University <strong>of</strong> Economics Prague, Czech Republic
mladkova@vse.cz
Abstract: Knowledge workers represent more than half <strong>of</strong> all employees in advanced economies. In general
knowledge workers are people who, when working, use <strong>the</strong>ir brain more than <strong>the</strong>ir muscles. While agricultural
and industrial worlds depended on <strong>the</strong> work <strong>of</strong> manual workers and <strong>the</strong> life standard <strong>of</strong> <strong>the</strong>ir inhabitants and <strong>the</strong>
success <strong>of</strong> agricultural and industrial organizations grew due to <strong>the</strong> increase <strong>of</strong> manual worker productivity,
existing knowledge economy depends on <strong>the</strong> work <strong>of</strong> knowledge workers and <strong>the</strong> labour productivity <strong>the</strong>y can
achieve. Major creative force <strong>of</strong> knowledge worker is knowledge. Quality <strong>of</strong> work <strong>of</strong> knowledge workers depend
not only on <strong>the</strong>ir ability to create, distribute and share knowledge but also on how <strong>the</strong> work with knowledge is
organized in <strong>the</strong>ir organizations. Knowledge as a changing system with interactions among experience, skills,
facts, relationships, values, thinking processes and meanings (Veber 2000) consists <strong>of</strong> two dimensions, explicit
and tacit. Explicit dimension <strong>of</strong> knowledge can be expressed in formal and systematic language and can be
shared in <strong>the</strong> form <strong>of</strong> data, scientific formulae, specifications, manuals. Tacit dimension <strong>of</strong> knowledge is highly
personal and hard to discover and formalize. Explicit knowledge and intuition, mental models, experience,
abilities, skills, etc. create it. It is deeply rooted in action, procedures, routines, commitments, ideas, values and
emotions. It is difficult to share and communicate. Knowledge workers work with both dimensions <strong>of</strong> knowledge.
Explicit knowledge is usually present in <strong>the</strong> form <strong>of</strong> data in some information system; tacit knowledge is linked to
its human holder or holders. Organizations do not usually have problem to organize work with explicit knowledge.
ICT and modern information systems <strong>of</strong>fer many solutions how to adjust work with explicit knowledge to needs <strong>of</strong>
knowledge workers <strong>of</strong> individual organizations. Tacit knowledge is more problematic. Organizations tend to
underestimate it and do not create or even inhibit environment that is necessary for its sharing. The empiric
research on knowledge management in Czech organizations has started at <strong>the</strong> University <strong>of</strong> Economics, Prague
in 2004 and goes on to <strong>the</strong>se days. The article discusses chosen results <strong>of</strong> this research.
Keywords: knowledge, tacit knowledge, explicit knowledge, knowledge worker, knowledge sharing
1. Knowledge workers
Generally, <strong>the</strong> most valuable knowledge in an organisation is in <strong>the</strong> heads <strong>of</strong> <strong>the</strong> employees
(Kokavcová, Malá 2009), so called knowledge workers. Literature specifies that knowledge workers
represent more than half <strong>of</strong> all employees in advanced economies. In general knowledge workers are
people who, when working, use <strong>the</strong>ir brain more than <strong>the</strong>ir muscles. Knowledge workers can be
identified in any culture and in any phase <strong>of</strong> humankind development. However, technologic and
social changes in <strong>the</strong> 20 th Century caused a remarkable increase in <strong>the</strong>ir numbers in organizations in
advanced economies.
Knowledge worker is not a <strong>the</strong>oretical idiom but it has close relation to terms like talented employees
(Buckingham, C<strong>of</strong>fman 2005) or best employees. The work and productivity <strong>of</strong> knowledge workers
depend on <strong>the</strong>ir ability to develop and use <strong>the</strong>ir knowledge which is <strong>the</strong> process that cannot be
observed, e.g. it is not possible to control and correct <strong>the</strong> way how <strong>the</strong>y work. As existing knowledge
economy depends on <strong>the</strong> work <strong>of</strong> knowledge workers and <strong>the</strong> labour productivity <strong>the</strong>y can achieve,
this fact has great importance from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> management.
Definitions <strong>of</strong> knowledge workers differ. Different authors understand knowledge workers differently.
Peter Drucker (Drucker 1954) was <strong>the</strong> first to use <strong>the</strong> term knowledge worker. Knowledge worker, by
Drucker is:
A person who has knowledge important for <strong>the</strong> organisation and <strong>of</strong>ten is <strong>the</strong> only person who has
it
A person who can use <strong>the</strong> knowledge in work
The knowledge is partly subconscious; <strong>the</strong> worker may not know about it or may not understand
its importance. O<strong>the</strong>r employees <strong>of</strong> <strong>the</strong> organisation have a limited approach to <strong>the</strong> knowledge,
<strong>the</strong>y cannot learn it (it is demanding on time or finances or is impossible as <strong>the</strong>y do not have <strong>the</strong>
knowledge or skills to develop it) or <strong>the</strong>y cannot or are not allowed to use it (knowledge is linked
to some certificate or diploma)
Knowledge workers <strong>of</strong>ten work intellectually, but this is not a rule.
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Ludmila Mládková
Alvin T<strong>of</strong>fler (T<strong>of</strong>fler 1990) understands typical knowledge worker as a scientists, an engineer or a
person who operates sophisticated technology. By him, knowledge worker must be able to create and
improve his/her technological knowledge or manage technological knowledge <strong>of</strong> co-workers.
Jack Vinson from Northwestern University wrote that knowledge worker is every employee who uses
his brain more than hands. Knowledge workers depend on <strong>the</strong>ir knowledge and ability to learn, even
though <strong>the</strong>y work with hands (Vinson 2009).
Thomas Davenport (Davenport 2005) sees knowledge workers as people with high degrees <strong>of</strong>
expertise, education, or experience. By Davenport, <strong>the</strong> primary purpose <strong>of</strong> knowledge workers’ job
involves <strong>the</strong> creation, distribution, or application <strong>of</strong> knowledge. Knowledge workers think for a living
(Davenport 2005).
Jonathan B. Spira in internet discussion concludes: “We can, in part, describe knowledge workers in
terms <strong>of</strong> what <strong>the</strong>y are not. They are not factory workers, <strong>the</strong>y are not labourers, <strong>the</strong>y are not farm or
field workers (<strong>the</strong> term "out in <strong>the</strong> field" notwithstanding). But that doesn’t tell us very much. Many, but
not all, knowledge workers are <strong>of</strong>fice workers. Some, but not all, are managers or white-collar
workers. Some, but not all, are pr<strong>of</strong>essionals, such as doctors or lawyers.” (Spira 2008).
O<strong>the</strong>r authors even think that <strong>the</strong> term 'knowledge worker' is now a meaningless concept in developed
countries because <strong>the</strong> shift Drucker started to notice in <strong>the</strong> '50s from jobs requiring manual work to
jobs requiring knowledge work is now complete (Allee 2002, Shawn 2007).
This article understands adopts Jack Vinsons’s approach to knowledge workers.
As mentioned above, knowledge workers are difficult to manage. They usually do not work in a linear
way and we cannot follow <strong>the</strong>ir work. Even though <strong>the</strong> final result <strong>of</strong> a knowledge workers’ work may
have a manual character, <strong>the</strong> most important part is done in <strong>the</strong>ir heads where <strong>the</strong>y analyse large
numbers <strong>of</strong> variables in any moment and adjust <strong>the</strong>ir work to <strong>the</strong> development <strong>of</strong> <strong>the</strong>se variables. The
work <strong>of</strong> knowledge workers is hidden; <strong>the</strong> observer does not see and know <strong>the</strong> process. The work <strong>of</strong>
knowledge workers cannot be observed and directly controlled. Knowledge workers <strong>of</strong>ten posses
knowledge that is not widely available and even <strong>the</strong>ir managers do not have it. They are <strong>of</strong>ten well
educated or experienced, create <strong>the</strong>ir own work standards, and make decisions independently. These
decisions include <strong>the</strong> process <strong>of</strong> work and methods <strong>the</strong>y use. Many <strong>of</strong> <strong>the</strong>m make <strong>the</strong> final control <strong>of</strong>
<strong>the</strong>ir product or service <strong>the</strong>mselves.
2. Knowledge workers and knowledge
Knowledge is a major tool and raw material <strong>of</strong> knowledge workers. Knowledge can be defined in
many ways. For example Tobin defines knowledge as information plus intuition and experience (Tobin
1996), Beckman sees knowledge as information plus selection, experience, principles, limitations and
learning (Beckman 1997). Veber understands knowledge as a changing system with interactions
among experience, skills, facts, relations, values, thinking processes and meanings (Veber, 2000).
It is <strong>the</strong> role <strong>of</strong> organizations to prepare environment where knowledge workers can create, share and
use both explicit and tacit knowledge. Knowledge management helps organizations to meet this role.
Knowledge management can be defined as <strong>the</strong> performance <strong>of</strong> knowledge processes (Wiig, Hoog,
Speck 1997), or as a managerial approach <strong>of</strong> organisational leadership, <strong>the</strong> creation <strong>of</strong> an
organisational environment and <strong>the</strong> achievement <strong>of</strong> organisational objectives based on <strong>the</strong> alignment
<strong>of</strong> knowledge and processes through <strong>the</strong> usage <strong>of</strong> knowledge resources and appropriate methods,
techniques, and tools (Bureš 2005). Liebowitz and Megbolugbe understand knowledge management
as utilization <strong>of</strong> knowledge resources and intellectual capital (Liebowitz, Megbolugbe 2003). The style
<strong>of</strong> organizational knowledge management influences <strong>the</strong> work with intellectual assets <strong>of</strong> organization
and should be tailored to needs <strong>of</strong> its knowledge workers.
The article cannot cover all aspects <strong>of</strong> knowledge management that influence work and productivity <strong>of</strong>
knowledge workers. Three important factors were chosen out <strong>of</strong> many: type <strong>of</strong> organizational
structure, functionality <strong>of</strong> knowledge market and trust. When <strong>the</strong>se factors do not fit needs <strong>of</strong>
knowledge workers, <strong>the</strong>y fail access knowledge <strong>the</strong>y need to fulfil <strong>the</strong>ir tasks and to be productive.
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3. Our research
Ludmila Mládková
The research on knowledge management in organizations in <strong>the</strong> Czech Republic started in 2004 and
goes on to <strong>the</strong>se days. The intention <strong>of</strong> <strong>the</strong> research is to monitor development <strong>of</strong> knowledge
management activities in our country, to identify best practices and to evaluate potential <strong>of</strong> our
corporate environment for knowledge workers. Organizations are chosen randomly, <strong>the</strong>y come from
different industries, including <strong>the</strong> public administration and governmental area. A size <strong>of</strong> organizations
also differs; we have interviewed both big multinational organizations and SME’s. The only
prerequisite for organization to be covered by <strong>the</strong> research is location <strong>of</strong> its premises in <strong>the</strong> Czech
Republic. Up till now we have interviewed 131 organizations.
The research is a qualitative research and it is based on a questionnaire. The questionnaire mostly
consists <strong>of</strong> closed questions with option <strong>of</strong> commentary; some opened questions are supplied, too.
Questionnaires are filled in interviews with respondents from chosen organizations. Interviews are
supervised by instructed interviewers. The quality <strong>of</strong> questionnaires is checked.
The questionnaire provides us with detailed information about work with knowledge and knowledge
management in interviewed organizations. It helps to identify best practices and mistakes and
problems and gives us a picture about quality and functionality <strong>of</strong> knowledge market.
As stated above, this article covers only <strong>the</strong> part <strong>of</strong> <strong>the</strong> research dedicated to <strong>the</strong> type <strong>of</strong>
organizational structure, knowledge market and trust.
4. Theoretical background <strong>of</strong> <strong>the</strong> research
Knowledge management literature <strong>of</strong>fers various definitions and concepts <strong>of</strong> knowledge. Knowing well
business reality in our country and having in mind <strong>the</strong> fact that final users <strong>of</strong> our work are our
managers we decided to use simple knowledge concept. The definition <strong>of</strong> knowledge we use is build
on Veber’s approach. For us knowledge is a changing system with interactions among experience,
skills, facts, relations, values, thinking processes and meanings (Veber 2000). Knowledge is always
related to human action and emotion. Knowledge is highly subjective.
As for knowledge itself we work with Polanyi’s concept <strong>of</strong> two dimensions, explicit and tacit (Polanyi
1966).
We explain explicit dimension <strong>of</strong> knowledge as knowledge which can be expressed in formal and
systematic language and can be shared in <strong>the</strong> form <strong>of</strong> data, scientific formulae, specifications,
manuals, etc. It can be processed, transmitted and stored. We support idea that explicit knowledge is
actually information and can be transferred to data. E.g. explicit knowledge can be formalized and
stored and distributed as data (Mládková 2005). Data is usually distributed and stored in some ICT
<strong>the</strong>se days. It means that when working with explicit knowledge we <strong>of</strong>ten work and manage work with
a technology.
Tacit dimension <strong>of</strong> knowledge is perceived as highly personal and hard to discover and formalize.
Explicit knowledge and intuition, mental models, experience, crafts, skills, etc. create it. It is deeply
rooted in action, procedures, routines, commitment, ideas, value and emotions. It is always related to
living being or to <strong>the</strong> group and is difficult to share and communicate (Mládková 2005). We agree on
Polanyi’s statement that tacit knowledge is problematic to externalize because <strong>the</strong> process <strong>of</strong>
externalization damage it (Polanyi 1966). Managing tacit knowledge means managing people.
From our point <strong>of</strong> view <strong>the</strong> concept <strong>of</strong> two dimensions has important practical advantage – it helps us
to explain to managers that tacit knowledge cannot be managed <strong>the</strong> same way as <strong>the</strong> explicit one.
This mistake is quite common in our traditionally hierarchical environment.
5. Organizational structure and its impact on work <strong>of</strong> knowledge workers
Organizational structure is a backbone <strong>of</strong> organization. It predetermines what an organization can and
cannot do. From this point <strong>of</strong> view organizational structure is an important factor <strong>of</strong> knowledge
management and management <strong>of</strong> knowledge workers. It influences knowledge and communication
channels, functionality <strong>of</strong> knowledge market, trust, permeability <strong>of</strong> borders between departments and
many o<strong>the</strong>r factors.
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Ludmila Mládková
As for <strong>the</strong> typology <strong>of</strong> organizational structures, we adopted classification <strong>of</strong> organizational structures
by Nonaka and Takeuchi (Nonaka, Takeuchi 1995) for our research. Nonaka and Takeuchi classify
organizational structures to three groups: top down structures, bottom up structures and combined
structures (Nonaka and Takeuchi call combined structures middle up down model). Being aware <strong>of</strong>
<strong>the</strong> fact that many <strong>of</strong> our organizations are adjusting <strong>the</strong>ir organizational structures to changing
environment and that change <strong>of</strong> <strong>the</strong> organizational structure is a difficult process that cannot be done
in one moment, we added two transitional types <strong>of</strong> organizational structures to our research; transition
from top down to bottom up structure and transition from bottom up to combined structure. We do not
analyze how far organizations get in <strong>the</strong> transformation but it is generally expected that <strong>the</strong>y are at
least in <strong>the</strong> middle <strong>of</strong> <strong>the</strong> process.
Table 1: Organizational structures in organizations in <strong>the</strong> Czech Republic
Organizational structures in organizations in <strong>the</strong> Czech Republic
Type <strong>of</strong> structure Nb. <strong>of</strong>
organizations
Top down 58 44%
Transition from top down to bottom up structures 16 12%
Bottom up 20 15%
Transition from bottom up to combined structure 6 5%
Combined structure 31 24%
Total 131 100%
The result <strong>of</strong> <strong>the</strong> research indicates that 44% <strong>of</strong> our organizations have hierarchical top down
structure. From <strong>the</strong> point <strong>of</strong> view <strong>of</strong> knowledge management and management <strong>of</strong> knowledge workers,
this type <strong>of</strong> structure is <strong>the</strong> least convenient. It is based on strict division <strong>of</strong> labour and limits
cooperation and knowledge sharing. The power and decision making competencies are concentrated
in <strong>the</strong> hands <strong>of</strong> top managers who create basic concepts, ideas and objectives and distribute <strong>the</strong>m as
tasks to subordinate levels <strong>of</strong> <strong>the</strong> organization. The role <strong>of</strong> <strong>the</strong> employee is limited. Knowledge
channels are opened only in <strong>the</strong> top down direction and only simple explicit knowledge can pass
through <strong>the</strong>m. Subordinate levels do not communicate on <strong>the</strong> horizontal level and <strong>the</strong> co-operation <strong>of</strong>
individual hierarchical levels is also limited. A bottom up flow <strong>of</strong> knowledge is problematic.
Hierarchical borders damage <strong>the</strong> knowledge. The knowledge loses its context and different
departments explain it differently. The flow <strong>of</strong> tacit knowledge is restricted even more. Tacit
knowledge exists only in <strong>the</strong> heads <strong>of</strong> individuals, and is owned and shared in specialized parts <strong>of</strong>
departments (Mládková 2005).
Table 2: Interrelation between organizational structure, knowledge sharing and cooperation
Interrelation between organizational structure, knowledge sharing and cooperation
Type <strong>of</strong> structure Number <strong>of</strong>
Organizations
Employees
share
knowledge
Cooperation, Interest in O<strong>the</strong>rs
Yes No
Top down 58 32 55% 28 48% 30 52%
Transition from top down to bottom up
structures
16 9 56% 12 75% 4 25%
Bottom up 20 15 75% 16 80% 4 20%
Transition from bottom up to combined
structure
6 6 100% 6 100% 0 0%
Combined structure 31 27 87% 27 87% 3 10%
Cooperation and interest in o<strong>the</strong>r people are important prerequisites <strong>of</strong> knowledge sharing. People do
not share <strong>the</strong>ir knowledge with people with whom <strong>the</strong>y do not communicate and who <strong>the</strong>y are not
interested in. When examined in relation to <strong>the</strong> type <strong>of</strong> organizational structure, cooperation and
interest in o<strong>the</strong>rs are much higher in bottom up and combined structures. E.g. organizations that
decide for <strong>the</strong>se structures provide better environment for knowledge sharing (table 2) than top down
structures. The same result was reported for knowledge sharing itself; <strong>the</strong> less hierarchical was <strong>the</strong>
structure, <strong>the</strong> better knowledge sharing was reported by <strong>the</strong> organization (table 2).
Bottom up (27% <strong>of</strong> organizations, toge<strong>the</strong>r with transition to bottom up structure) and combined
structures (29% <strong>of</strong> organizations, toge<strong>the</strong>r with transition to combined structure) provide much more
convenient environment for work <strong>of</strong> knowledge workers. Bottom up structures are flexible, flat
263

Ludmila Mládková
organizational structures where decision making is related to <strong>the</strong> knowledge (Mládková 2005).
Knowledge is localized in <strong>the</strong> middle or bottom level <strong>of</strong> <strong>the</strong> organizational structure. They support
creation and work with both dimensions <strong>of</strong> knowledge; <strong>the</strong>y are beneficial especially for work with tacit
knowledge that is naturally shared in teams and communities. Their only disadvantage is barriers
between departments that limit across border sharing.
Combined organizational structure is a structure built on three layers. The vertical layer is responsible
for <strong>the</strong> management <strong>of</strong> <strong>the</strong> company (both day-to-day and strategic) and can be hierarchical. The
horizontal layer is responsible for creation <strong>of</strong> major values <strong>of</strong> <strong>the</strong> organization. It creates, distributes
and uses knowledge (both tacit and explicit). The horizontal layer consists <strong>of</strong> project teams. The third
layer, <strong>the</strong> knowledge layer, is responsible for archiving and recording knowledge, both explicit and
tacit. Combined structure allows creating and using <strong>the</strong> full potential <strong>of</strong> different relationships in <strong>the</strong>
company and fully supports its knowledge management activities (Mládková 2005).
Results <strong>of</strong> <strong>the</strong> research on organizational structure, cooperation and knowledge sharing prove
inconvenience <strong>of</strong> top down structure for knowledge management and work <strong>of</strong> knowledge workers.
Still, 44% <strong>of</strong> our organizations chose this type <strong>of</strong> structure, even though it is not beneficial. We explain
this high number as a cultural factor. Top down structures are traditional structures in our country and
many organizations naturally choose <strong>the</strong>m without taking into account <strong>the</strong>ir advantages and
disadvantages.
6. Knowledge market and its impact on work <strong>of</strong> knowledge workers
Knowledge market is a physical and virtual market where people exchange <strong>the</strong>ir knowledge
(Davenport, Prusac 1998). Or knowledge Markets are formal or informal community contexts,
platforms, or environments (real or virtual) used to promote knowledge commerce, trade and
exchange, demand and supply, between knowledge buyers and sellers (Knowledge Market
Consortium 2010). Prusac and Cohen think that internal organizational knowledge markets have
similar features as o<strong>the</strong>r markets (Prusac, Cohen 1997). In organizations both explicit and tacit
knowledge is exchanged <strong>the</strong>re. Knowledge workers benefit from functional knowledge market. But
knowledge markets in organizations <strong>of</strong>ten suffer various pathologies:
Organization does not know if <strong>the</strong>y have certain knowledge or no
Knowledge is asymmetrically spread in organization; people who need it do not have access to it
Employees search knowledge <strong>the</strong>y need only within people <strong>of</strong> <strong>the</strong>ir close circle and do not trust
knowledge from people <strong>the</strong>y do not know well
Pathologies than lead to typical knowledge market dysfunctions:
Knowledge monopolies
Artificial knowledge shortage
Knowledge barriers (Davenport, Prusac 1998)
The research on functionality <strong>of</strong> knowledge market was done indirectly by questions on knowledge
ownership that mapped knowledge monopolies and questions on knowledge flow and communication
channels that mapped access to knowledge in an organization. In table 3 all percentages are
calculated from 131 organizations.
Table 3: Functionality <strong>of</strong> knowledge market
Functionality <strong>of</strong> knowledge market
Number <strong>of</strong> organizations
Knowledge is perceived as personal ownership 27 21%
Knowledge is perceived as ownership <strong>of</strong> organizational group 23 18%
Knowledge flow is free, open book management 63 48%
Knowledge flow is limited 68 52%
Knowledge flow is limited, we need free knowledge flow 21 16%
Knowledge flow is limited, we do not need free knowledge flow 14 11%
Communication and communication channels are open 76 58%
Communication and communication channels are not open 57 44%
Communication and communication channels are not open, we need it 17 13%
Communication and communication channels are not open, we do not need
it
13 10%
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Ludmila Mládková
When examining free flow <strong>of</strong> knowledge through organizations, we discovered that 63 organizations
(48%) have so called open book management (knowledge flow is free). Sixty eight organizations
(52%) reported limited knowledge flow. Twenty one organizations out <strong>of</strong> <strong>the</strong>se 68 (31%) think that
<strong>the</strong>y need free knowledge flow, 14 organizations out <strong>of</strong> 68 (21%) think that <strong>the</strong>y do not need free
knowledge flow. It is only 11% out <strong>of</strong> 131 interview organizations.
Open communication channels were reported by 76 organizations (58%), blocked communication
channels by 57 organizations (44%). We also asked organizations whe<strong>the</strong>r <strong>the</strong>y need free
communication channels, 17 organizations out <strong>of</strong> 57 (30%) recorded that <strong>the</strong>y need and 13
organizations out <strong>of</strong> 57 (23%) do not need free communication channels.
Knowledge market can be functional only when employees share knowledge, knowledge flow is free
and communication channels opened. All three requirements were met by 47 organizations out <strong>of</strong> 131
(36%).
Results <strong>of</strong> <strong>the</strong> research show that majority <strong>of</strong> interviewed organizations do not manage <strong>the</strong>ir
knowledge markets properly and that <strong>the</strong>ir knowledge markets suffer serious problems. Some
organizations even block <strong>the</strong>ir knowledge flow and communication channels intentionally. To illustrate
<strong>the</strong> situation, none <strong>of</strong> those organizations needed limited knowledge flow and blocked communication
channels due to security reasons. It is sad because ineffective knowledge market inhibits knowledge
sharing and work <strong>of</strong> knowledge workers.
7. Trust and its impact on work <strong>of</strong> knowledge workers
Trust is a factor that influences work with knowledge and knowledge sharing, especially sharing <strong>of</strong>
tacit knowledge. People do not share <strong>the</strong>ir knowledge with people who <strong>the</strong>y do not trust. E.g.
knowledge workers who do not trust each o<strong>the</strong>r tend to keep <strong>the</strong>ir knowledge for <strong>the</strong>mselves and
build knowledge monopolies. As <strong>the</strong> result <strong>the</strong>y inhibit <strong>the</strong>ir performance.
There are many definitions <strong>of</strong> trust. We understand trust as defined by Fukuyama and Robinson.
Fukuyama and Robinson think that trust it <strong>the</strong> expectation <strong>of</strong> regular, honest, and cooperative
behaviour based on commonly shared norms and values (Fukuyama 1995, Robinson et al 1996).
Trust can be classified to certain groups. Deterrence trust is derived through <strong>the</strong> presence <strong>of</strong>
sanctions for opportunistic behaviour (Rousseau et al 1998). Knowledge based trust is based on
knowing o<strong>the</strong>r individual and being able to predict his behaviour (Shapiro et al 1992). Identification
based trust is derived through empathy and sharing <strong>of</strong> common values (Shapiro et al 1992).
Relational trust is derived over time through information <strong>of</strong> trustee within <strong>the</strong> frame <strong>of</strong> <strong>the</strong> relationship
(Rousseau et al 1998). Calculus based trust is calculated on <strong>the</strong> basis <strong>of</strong> deterrents and intentions
and competence (Rousseau et al 1998). Economic factors based trust is derived from a rational
decision based on costs and benefits (Kim, Prabhakar 2000). Institutional trust is a feeling <strong>of</strong>
confidence and security <strong>of</strong> institution (Ford 2003). Personality based trust is trust based on personal
and pr<strong>of</strong>essional character <strong>of</strong> individual (Mládková 2010).
We asked organizations which types <strong>of</strong> trust are applicable for <strong>the</strong>m. In our opinion knowledge,
identification, relational and personality types <strong>of</strong> trust support knowledge sharing and work <strong>of</strong>
knowledge workers. Deterrence trust inhibits especially tacit knowledge sharing because it creates
fear, in case <strong>of</strong> calculus and economic trust, knowledge is a power and is not shared. Institutional
trust does not influence internal knowledge sharing in organizations; it was involved due to our
curiosity.
Table 4. gives us an overview <strong>of</strong> types <strong>of</strong> trust our respondents mentioned as <strong>the</strong> most applicable for
<strong>the</strong>m, e.g. trust in <strong>the</strong>ir organization is mostly based on that type. Fifteen organizations (25%) from
total did not answer this question or <strong>the</strong> answer was unclear. All percentages are calculated from 131
organizations. The table shows types <strong>of</strong> trust in relation to <strong>the</strong> type <strong>of</strong> organizational structure adopted
by <strong>the</strong> organization.
The mostly reported type <strong>of</strong> trust is trust based on knowledge, 34% <strong>of</strong> organizations reported it.
Second mostly reported type is trust based on relationships, 18%. These results show that people
tend to trust people who are known to have certain knowledge and people with whom <strong>the</strong>y have good
relationship. Except <strong>of</strong> one organization with bottom up structure, trust based on deterrence was
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Ludmila Mládková
mentioned only by organizations with top down structure (12%). This result is logic. Top down
organizational structure based on hierarchy and sub ordinance supports this type <strong>of</strong> trust. Being
aware <strong>of</strong> historical and cultural consequences <strong>of</strong> our region it was no surprise that identification based
trust was reported only by 5% <strong>of</strong> organizations even though this type supports corporate wide
knowledge sharing.
Table 4: Trust
Types <strong>of</strong> trust and organizational structure
Type <strong>of</strong>
trust/Type <strong>of</strong>
structure
Top down
structure
Transition
from top
down to
bottom up
structure
Bottom up
structure
Transition
from bottom
up to
combined
structure
Combined
structure
Suma
Deterrence 7 12% 0 0% 1 5% 0 0% 0 0% 8 6%
Knowledge 17 29% 6 38% 6 30% 2 33% 13 42% 44 34%
Identification 1 2% 0 0% 1 5% 2 33% 2 6% 6 5%
Relational 12 21% 3 18% 4 20% 1 17% 3 10% 23 18%
Calculus 0 0% 0 0% 0 0% 0 0% 0 0% 0 0%
Econ. factors 1 2% 0 0% 1 5% 0 0% 1 3% 3 2%
Institutional 0 0% 0 0% 0 0% 0 0% 0 0% 0 0%
Personality 5 9% 1 6% 0 0% 0 0% 5 16% 11 8%
No answer 15 25% 6 38% 7 35% 1 17% 7 23% 36 27%
Nb. <strong>of</strong>
organizations
58 16 20 6 31 131
8. In conclusion
Knowledge workers are people who, when working, use <strong>the</strong>ir brain more than <strong>the</strong>ir muscles.
Knowledge is <strong>the</strong>ir important asset and tool. Knowledge workers can be productive only when <strong>the</strong>ir
organizations create convenient environment for cooperation and knowledge sharing and support
<strong>the</strong>m with knowledge <strong>the</strong>y need. Results <strong>of</strong> our research indicate that organizations in <strong>the</strong> Czech
Republic do not create environment and knowledge management systems supportive for <strong>the</strong>ir
knowledge workers.
44% <strong>of</strong> organizations that participated in our research reported top down organizational structure,
structure that inhibits knowledge sharing and knowledge management activities. Majority <strong>of</strong>
organizations, 64% do not have functional knowledge markets; mostly due to blocked communication
channels (44%) and limited flow <strong>of</strong> knowledge through organization (52%). Knowledge market can be
functional only when employees share knowledge, knowledge flow is free and communication
channels are opened. All three requirements were met by only 36% <strong>of</strong> interviewed organizations. As
for <strong>the</strong> trust, <strong>the</strong> mostly reported type <strong>of</strong> trust is trust based on knowledge, 34% <strong>of</strong> organizations
reported it. Second mostly reported type is trust based on relationships, 18%. Only 5% <strong>of</strong> interviewed
organizations reported identification trust, important prerequisite <strong>of</strong> corporate wide knowledge sharing.
Inconvenient type <strong>of</strong> organizational structure, inhibited knowledge sharing and dysfunctions <strong>of</strong>
knowledge market limit <strong>the</strong> work and productivity <strong>of</strong> knowledge workers. Over 25 year long research
<strong>of</strong> Gallup Organization focused on employees’ performance and loyalty to <strong>the</strong>ir organizations
(Buckingham, C<strong>of</strong>fman 2005) shows that performance <strong>of</strong> employees depends on availability <strong>of</strong>
materials and equipment <strong>the</strong>y need for <strong>the</strong>ir work. In case <strong>of</strong> knowledge workers, it is, out <strong>of</strong> material
equipment, knowledge. Lack <strong>of</strong> necessary information, knowledge and contacts or difficult access to
<strong>the</strong>m is frustrating and humiliating for knowledge workers. Many knowledge workers can work with old
tools and equipment but <strong>the</strong>y cannot do anything without knowledge. Proper environment and
knowledge management provides knowledge workers with all knowledge assets <strong>the</strong>y need;
knowledge hostile environment and improper knowledge management restricts knowledge workers’
access to <strong>the</strong>ir most important asset.
The results <strong>of</strong> our research are fully compatible with <strong>the</strong> fact that <strong>the</strong> Czech Republic has serious
problems with innovativeness. Our research points at one <strong>of</strong> possible reasons – Czech organizations
manage <strong>the</strong>ir knowledge in very poor way which inhibits productivity <strong>of</strong> <strong>the</strong>ir knowledge workers.
266

References
Ludmila Mládková
Allee, V. (2002) Presentation at International <strong>Conference</strong> KM Europe 2002, 13-15 Nov. 2002 London. UK.
Beckman, T. A. Methodology for Knowledge Management. In: Proc. IASTED Al and S<strong>of</strong>tware Computing
<strong>Conference</strong>, ACTA Press, Banff, 1997, pp 29-32.
Buckingham, M, C<strong>of</strong>fman, C. (2005) First, Break All <strong>the</strong> Rules. London: Simon&Schuster UK. ISBN 1-4165-0266-
1
Bureš, V. 2005 Methodology <strong>of</strong> Knowledge Management Implementation, 3. International <strong>Conference</strong> on
Multimedia and Information & Communication Technologies: Recent Research Developments in Learning
Technologies. Cáceres, Spain, Formatex, Vol. 3, 2005, pp 963-668.,
Davenport, T.(2005) Thinking for Living. HVB School Publishing, 2005, ISBN 1-59139-423-6
Davenport T.H., Prusac L. (1998) Working knowledge. Harvard Business School Press. UK 1998. ISBN 0-87584-
655-6
Drucker, P. F. (1954) Landmarks <strong>of</strong> Tomorrow. A Report on <strong>the</strong> New ‘Post-Modern’World. Transaction Publisher
London. ISBN 1-56000-622-6.
Ford, D. P. (2003) Trust and Knowledge Management: The Seeds <strong>of</strong> Success. In Holsapple W. C. Handbook on
Knowledge Management. Springer-Verlag New York, 2003, ISBN 3-540-43527-1.
Fukuyama, F. (1995) Trust: The Social Virtues and <strong>the</strong> Creation <strong>of</strong> Prosperity. New York: Free Press.
Kim, K. & Prabhakar, B. (2000) Initial trust, perceived risk, and <strong>the</strong> adoption <strong>of</strong> Internet banking. ICIS 2000
<strong>Proceedings</strong>, Brisbane, Australia, p. 537-543.
Kokavcová, D., Malá, D. 2009. Knowledge Sharing – <strong>the</strong> Main Prerequisite <strong>of</strong> Innovation. Kaunas: Management
<strong>of</strong> Organizations: Systematic Research. No 51, 2009. ISSN: 1392-1142.
Knowledge Market Consortium, 2010.
Liebowitz, J., Megbolugbe, I. A Set <strong>of</strong> Frameworks to Aid <strong>the</strong> Project Manager in Conceptualizing and
Implementing Knowledge Management Iniciatives. Internationa Journal <strong>of</strong> Project Management 21, No.3,
2003, pp. 189-198
Mládková L. (2005) Moderní přístupy k managementu. Tacitní znalost a jak ji řídit. Modern Approaches to
Management. Tacit Knowledge and how to Manage it. C.H.Beck. Praha. ISBN 80-7179-310-8.
Mládková, L. (2010) Cooperation and its Role in Knowledge Society, Journal <strong>of</strong> International Scientific
Publications, Economy and Business, Volume 4, ISSN 1313-2525, pg. 4-6
Nonaka I., Takeuchi, H. (1995) The Knowledge Creating Company: How Japanese Companies Create <strong>the</strong>
Dynamics <strong>of</strong> Innovation. Oxford University Press. UK. ISBN 0-19-509269.
Polanyi, M. (1966) The Tacit Dimension. London. Routledge & Kegan Paul UK. pg. 6. v Nonaka I.. Toyama, R.,
Byosiere, P.: A Theory <strong>of</strong> Organisational Knowledge Creation: Understanding <strong>the</strong> Dynamic Process <strong>of</strong>
Creating Knowledge. Eudokma. Kodaň. 2001. pg. 494.
Prusac, L., Cohen, D., Knowledge Buyers, Sellers and Brokers: The Political Economy <strong>of</strong> Knowledge. Centre for
Business Innovation, Working Paper, January 1997, pp/ 1-27.
Robinson, S. L. et al (1996) Trust and Breach <strong>of</strong> <strong>the</strong> Psychological Contract. Administrative Science Quarterly,
41, 574-599.
Rouseau, D.M., Sitkin, B.S., Burt R.S., Camerer C. (1998) Not so Different After All: a Crossdiscipline View <strong>of</strong>
Trust. California Institute <strong>of</strong> TechnologyAcadomy <strong>of</strong> Management Review1998, Vol. 23, No. 3, 393-404.
Shawn (2009) http://www.anecdote.com.au/archives/2007/11/our_need_for_th.html. 22.5.2009 13:53.
Shapiro, D., Sheppard, B.H. & Cheraskin, L. (1992) Business on a Handshake. Negotiation Journal, 8(4), 365-
377.
Spira, J. B. (2008) http://www.kmworld.com/Articles/News/News-Analysis/Knowledge-worker-Do-you-relate-
40808.aspx. 22.5.2009 13:50. Posted Feb 5, 2008.
Tobin, D. (1996) Transformational Learning – Renewing Your Company Through Knowledge and Skills.John
Wiley & Sons, NY, 1996
Vinson, J. (2009) www.vinson.com. 5.5.2009, 16:45
Veber, Jaromír a kol. (2000) Management, základy, prosperita, globalizace. Management, Basics, Prosperity,
Globalization, Management Press. Praha. ISBN 80-7261-029-5 pg.
Wiig, K., Hoog, R., Speck, R. Supporting Knowledge Management: A Selection <strong>of</strong> Methods and Techniques.
Expert Systems with Applications 13, 1997, pp. 15-27.
http://www.kikm.org/downloads/LeveragingKnowledgeMarketsStudy.pdf, 27.12.2010, 14:26
267

Applying <strong>the</strong> VAIC Model to Russian Industrial
Enterprises
Maria Molodchik and Anna Bykova
State University Higher School <strong>of</strong> Economics, Perm, Russia
molodchikma@dom.raid.ru
anchen304@mail.ru
Abstract: Increased attention and focus has been laid on <strong>the</strong> strategic importance <strong>of</strong> intellectual capital for
modern management. However, intangible resources appear difficult to measure. Today, <strong>the</strong>re are several
methods, both financial and nonfinancial ones that allow managing <strong>the</strong>m, to provide benchmarking and analyze
its value added function (Sveiby, 2007). The rare investigations <strong>of</strong> intellectual capital in Russian enterprises show
that “Almost in all industries it is still more pr<strong>of</strong>itable to invest in tangible assets ra<strong>the</strong>r than in intangible ones”
(Volkov, Garanina, 2007). Still, some investigations on <strong>the</strong> micro level show that <strong>the</strong>re are enterprises with high
level <strong>of</strong> technological capital and innovative activity. The researchers called <strong>the</strong>m “innovative leaders” and
empirically proved that <strong>the</strong>y have high labour productivity and are awarded by market through extra pr<strong>of</strong>it
(Gonchar et al., 2010). Using <strong>the</strong> research sample and Pulic’s Value Added Intellectual Coefficient (VAIC) <strong>the</strong>
authors investigate empirically <strong>the</strong> dynamics and structure <strong>of</strong> VAIC, and study <strong>the</strong> relation between <strong>the</strong>
intellectual capital and indicators <strong>of</strong> organizational performance, such as labour productivity, sales growth and
pr<strong>of</strong>itability. Additionally, <strong>the</strong> VAIC model allows analysing <strong>the</strong> role <strong>of</strong> human, structural and physical capital.
This paper outlines <strong>the</strong> study based on 350 Russian industrial enterprises’ annual statistical and account reports
from 2005 through 2007. Besides, <strong>the</strong> authors adopt <strong>the</strong> VAIC calculation according to <strong>the</strong> Russian accounting
system’s specifications and limitations. The findings support <strong>the</strong> hypo<strong>the</strong>sis that a company’s intellectual capital
influences favourably <strong>the</strong> organizational performance, and may indicate future competitiveness. A pro<strong>of</strong> showing
that <strong>the</strong> explanatory power <strong>of</strong> models is higher when considering <strong>the</strong> additional variables such as investment in
fixed capital, R&D expenditures and a company’s size is represented. The results extend <strong>the</strong> understanding <strong>of</strong>
<strong>the</strong> intellectual capital role in creation <strong>of</strong> sustainable advantages for companies in developing economies where
different technological advancements may bring different implications for organizational value creation efficiency.
Keywords: VAIC model, organizational performance, Russian industrial enterprises
1. Introduction
New economy imposes new requirements to <strong>the</strong> enterprises. The strategic role <strong>of</strong> intellectual capital
in value creation is widely discussed both on <strong>the</strong>oretical (Bontis, 2001) and empirical (Kremp,
Mairesse, 2004; Chen et al., 2005) levels. However, measuring <strong>the</strong> intangible resources present a
problem today. There are several methods both financial and nonfinancial ones that allow managing
<strong>the</strong>m, to provide benchmarking and analyze its value added function (Sveiby, 2007). A pro<strong>of</strong>
demonstrating that <strong>the</strong> intellectual capital has positive impact on market value, productivity, return on
assets and sales growth is given (Pulic, 2000; S<strong>of</strong>ian et al., 2002; Chen et al., 2005; Firer, Williams,
2003; Kremp, Mairesse, 2004; Diez et al., 2010; Laing et al., 2010). These investigations were carried
out in developed and emerging markets: France, Austria, Spain, Australia, Malaysia, Taiwan and
South Africa.
We have found only few papers that focus on <strong>the</strong> intellectual capital <strong>of</strong> Russian enterprises
(Baiburina, Golovko, 2008; Volkov, Garanina, 2007; Gonchar et. al., 2010). Unfortunately, <strong>the</strong>
economic and institutional regime in Russia impacts <strong>the</strong> efficient use <strong>of</strong> existing and new knowledge
transforming <strong>the</strong>m into competitive advantages. The series <strong>of</strong> studies conducted over 1000 Russian
industrial enterprises show <strong>the</strong> tremendous difference (from 10 to 20 times) in labour productivity
within all branches. And <strong>the</strong> last survey carried out in 2010 demonstrates that “technological leaders
became more powerful and outsiders “fall fur<strong>the</strong>r technological downstairs” (Gonchar et al., 2010,
p.40). These studies empirically proved that “innovative leaders” (<strong>the</strong> enterprises with high level <strong>of</strong>
technological capital and innovation activity) have high productivity and are awarded by market
through extra pr<strong>of</strong>it (Gonchar et al., 2010).
Due to a different accounting system and poor development <strong>of</strong> stock market <strong>the</strong> application <strong>of</strong> modern
methods for measuring intangible assets on <strong>the</strong> organizational level, such as CIV (Calculated
Intangible Value), Market-to-Book-Value, EVA (Economic Value Added), VAIC (Value Added
Intellectual Coefficient) and o<strong>the</strong>rs, is not a simple research task. In this paper <strong>the</strong> authors try to adapt
<strong>the</strong> model <strong>of</strong>fered by Pulic (2000) VAIC to intellectual capital measurement in non-public Russian
companies.
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Maria Molodchik and Anna Bykova
In this paper we aim at identifying <strong>the</strong> relationship between intellectual ability and organizational
performance. For this purpose we employ a unique dataset from Russian companies located within
one geographic area: Perm region. This choice is explained by <strong>the</strong> data collection limitation. The
dataset combines company-specific information related to sales, material costs, R&D expenditures,
company size, pr<strong>of</strong>itability and a number <strong>of</strong> o<strong>the</strong>r indicators. This allows us experimenting with a
variety <strong>of</strong> intellectual capital variables and model specifications, using different linear models.
The second task for us in this study was to find <strong>the</strong> instrument for <strong>the</strong> express intellectual capital
analysis that can be applied to an industrial enterprise. We have found that <strong>the</strong> VAIC model is an
appropriate one.
2. Literature review
Empirical investigation <strong>of</strong> intellectual capital with comparative analyzes differs from research
approach with <strong>the</strong> aim <strong>of</strong> intellectual capital management within a company. The developed
measurements methods (Bontis, 2001; Sveiby, 2007) aim at determining <strong>the</strong> uniqueness <strong>of</strong>
intellectual capital for each company (that means <strong>the</strong> inimitable competitive advantage) and allow
mainly monitoring <strong>the</strong> intellectual capital management but not <strong>the</strong> comparison and benchmarking one
among <strong>the</strong> o<strong>the</strong>rs. In order to compare <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> intellectual capital <strong>of</strong> different
companies we need a method based on <strong>the</strong> available financial and/or non-financial information. If we
take <strong>the</strong> Sveiby’s classification (Sveiby, 2007) <strong>the</strong> most appropriate approach would be <strong>the</strong> group <strong>of</strong>
MCM – Market Capitalization methods and ROA – Return on Assets methods. Among <strong>the</strong>m are CIV
(Calculated Intangible Value), EVA (Economic Value Added), VAIC (Value Added Intellectual
Coefficient), Market-to-book Value, Tobin’s Q and o<strong>the</strong>rs.
The problem for <strong>the</strong> researchers also lies in availability <strong>of</strong> <strong>the</strong> data related to <strong>the</strong> intellectual capital.
For example, Bontis (2003), using <strong>the</strong> data <strong>of</strong> 10000 Canadian corporations, showed that “intellectual
capital disclosure is still very much an academic discussion” – only 68 from 10000 corporations
disclosed intellectual capital terms. Only Scandinavian companies have ventured forward by
publishing intellectual capital statements (Bontis, 2003).
The role <strong>of</strong> <strong>the</strong> intellectual capital in emerging economies is not as visible as in a developed one. The
empirical results are different. We analyzed <strong>the</strong> studies conducted based on data from Taiwan, South
Africa, Malaysia, and Russia. Today, <strong>the</strong> researchers cannot determine strong positive correlation
between <strong>the</strong> intellectual capital and <strong>the</strong> corporate performance in developing countries. Taiwan is <strong>the</strong>
only exception, where almost all investigations show significant positive impact <strong>of</strong> <strong>the</strong> intellectual
capital on <strong>the</strong> market value, pr<strong>of</strong>itability and o<strong>the</strong>r indicators <strong>of</strong> corporate performance.
Taiwan is a good case study <strong>of</strong> an emerging knowledge economy. There are several empirical studies
dedicated to <strong>the</strong> relationship between corporate performance and intellectual capital. Most <strong>of</strong> <strong>the</strong>
authors used VAIC as an intellectual capital indicator.
Chen et al. (2005) analyze <strong>the</strong> relationship between VAIC and Market-to-Book Value as well as
corporate performance (ROA, Growth in revenues and Employee Productivity) for all companies listed
on <strong>the</strong> Taiwan Stock Exchange (TSE) during 1992-2002. The final sample included 4254 firm years.
They argue that Pulic’s Structural Capital neglects Innovative Capital. They proposed to add R&D
expenditure as a part <strong>of</strong> Structural Capital in <strong>the</strong> regression model. As a result, <strong>the</strong> explanatory power
<strong>of</strong> model has been improved. Ano<strong>the</strong>r interesting result <strong>of</strong> this study consisted in <strong>the</strong> conclusion that
investors set different value to three components <strong>of</strong> VAIC. The explanatory power <strong>of</strong> models with
separate account <strong>of</strong> intellectual capital components (human and structural capital) was substantially
higher compared to VAIC, in general. The most significant result in this study with adjusted R-square
equaling 0.848 was reached in <strong>the</strong> panel econometric model, where dependent variable was ROA,
and <strong>the</strong> independent variables included three VAIC components, R&D and Advertising expenditures.
Ano<strong>the</strong>r study <strong>of</strong> Tseng and Goo (2005) proved that <strong>the</strong> effect <strong>of</strong> intellectual capital on enhancing <strong>the</strong>
corporate value in high-tech companies was higher than in non-high-tech companies. Innovation and
relationship capital impact directly and positively <strong>the</strong> corporate value (measured by Market-to-Book
Value, Tobin’Q, VAIC). On <strong>the</strong> contrary, human and organizational capital have indirect positive
impact on <strong>the</strong> corporate value.
The latest investigation <strong>of</strong> 80 Taiwan technological companies (Shiu, 2006) showed that VAIC had a
significant positive correlation with pr<strong>of</strong>itability (ROA) and market value, and negative correlation with
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Maria Molodchik and Anna Bykova
productivity. The certain time lag relationship between VAIC and <strong>the</strong> corporate performance has also
been found in this study.
Using data from 75 publicity traded companies in South Africa, Firer and Williams (2003) examined
<strong>the</strong> relationship between <strong>the</strong> intellectual capital and traditional measures <strong>of</strong> <strong>the</strong> corporate
performance. They have not found any strong positive effects <strong>of</strong> VAIC on pr<strong>of</strong>itability, productivity and
market value. The overall physical capital appeared as <strong>the</strong> most significant resource <strong>of</strong> <strong>the</strong> corporate
performance.
The empirical evidence from Malaysia shows that <strong>the</strong> companies with higher intellectual capital tend
to achieve higher performance levels (S<strong>of</strong>ian et al., 2002). The study conducted over more than 100
large Malaysian companies found positive association for different components <strong>of</strong> intellectual capital
with industry leadership, future outlook, pr<strong>of</strong>it growth, successful new products and o<strong>the</strong>r factors.
We have found only two econometric-based empirical investigations <strong>of</strong> <strong>the</strong> intellectual capital
developed on <strong>the</strong> Russian companies. The researchers from St. Petersburg Volkov and Garanina
(2007) have chosen <strong>the</strong> Calculated Intangible Value method <strong>of</strong>fered by T. Stewart in order to
investigate <strong>the</strong> impact <strong>of</strong> fundamental value <strong>of</strong> tangible and intangible assets on <strong>the</strong> market value <strong>of</strong>
<strong>the</strong> Russian companies. They developed econometric models based on <strong>the</strong> data <strong>of</strong> Russian stock
market from 2001 through 2005 for 43 companies. It was concluded that <strong>the</strong> market value <strong>of</strong> assets in
<strong>the</strong> Russian economy depends on <strong>the</strong> fundamental value <strong>of</strong> both tangible and intangible assets. But
<strong>the</strong> role <strong>of</strong> tangible assets is higher than that <strong>of</strong> <strong>the</strong> intangible ones. This study also provides <strong>the</strong>
industry analysis. Evidence is represented showing that <strong>the</strong> relationship between <strong>the</strong> market value <strong>of</strong>
assets and <strong>the</strong> fundamental value <strong>of</strong> intangible assets was better explained in such industries as
engineering and communication services.
Using <strong>the</strong> data from 19 open Russian companies from 2002 through 2006, Baiburina and Golovko
(2008), investigated <strong>the</strong> drivers <strong>of</strong> intellectual enterprise value. The authors determined intellectual
enterprise value as <strong>the</strong> difference between market value <strong>of</strong> ordinary shares and balance value <strong>of</strong>
equity. They showed that <strong>the</strong> intellectual enterprise value was influenced by expenditures on training
<strong>of</strong> employees, controlling shareholder, total assets/number <strong>of</strong> employees, delta dividend payout, and
delta investment.
In this paper we take into account previously obtained empirical results and try to extend <strong>the</strong>
understanding <strong>of</strong> <strong>the</strong> intellectual capital role in <strong>the</strong> emerging economy conducting <strong>the</strong> empirical study
over 350 non-public Russian industrial enterprises located in Perm region.
3. Research design
In our research study we have chosen Value Added Intellectual Coefficient as an indicator <strong>of</strong>
organizational intellectual ability.
The Value Added Intellectual Coefficient, VAIC indicates “corporate value creation efficiency, or
corporate intellectual ability. VAIC measures how much new value has been created per invested
monetary unit in resources” (Pulic, 2000). The higher <strong>the</strong> VAIC coefficient is, <strong>the</strong> better management
utilizes a company’s value creation potential. To <strong>the</strong> first time VAIC was tested by Pulic (2000) on 30
randomly selected companies from <strong>the</strong> FTSE (UK) 250 from 1992 through 1998 (Pulic, 2000). He has
found out that <strong>the</strong> average values <strong>of</strong> VAIC and a company’s market value exhibited a high degree <strong>of</strong>
correspondence.
The potential <strong>of</strong> VAIC is motivated by growing evidence in <strong>the</strong> literature. This method has <strong>the</strong>
following advantages (Pulic, 2000):
Standardized measures approach that allows international comparative analysis;
Use <strong>of</strong> audited information, <strong>the</strong>refore calculations can be considered objective and verifiable;
Easy calculation, which promises future universal acceptance as measurement <strong>of</strong> corporation
performance (such as ROA, MV/BV, and o<strong>the</strong>rs).
VAIC consists <strong>of</strong> <strong>the</strong> total sum <strong>of</strong> <strong>the</strong> value creation efficiency <strong>of</strong> <strong>the</strong> intellectual capital that contains
two components: human and structural capital and physical capital. The procedures calculating <strong>the</strong>
Value Added intellectual Coefficient are, as follows (Pulic, 2000).
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Maria Molodchik and Anna Bykova
VAIC = ICE +CEE
ICE – Intellectual capital efficiency is obtained by adding up <strong>the</strong> partial efficiencies <strong>of</strong> human and
structural capital: ICE=HCE+SCE
HCE – Human capital efficiency: indicator <strong>of</strong> <strong>the</strong> Value Added efficiency <strong>of</strong> human capital;
SCE – Structural capital efficiency: indicator <strong>of</strong> <strong>the</strong> Value Added efficiency <strong>of</strong> structural capital.
CEE – Capital employed efficiency: indicator <strong>of</strong> <strong>the</strong> Value Added efficiency <strong>of</strong> capital employed.
Intellectual capital as mentioned above has two components: human and structural capital. All <strong>the</strong>
expenditures for employees are embraced in <strong>the</strong> human capital. According to Pulic (2000), <strong>the</strong> VAIC
concept is <strong>the</strong> first one, where salaries and wages are no more part <strong>of</strong> “input” expenses.
The human capital is defined by Edvinson and Malone (1997) as “combined knowledge, skill,
innovativeness and ability <strong>of</strong> <strong>the</strong> company’s individual employees to meet <strong>the</strong> task at hand. It also
includes <strong>the</strong> company’s values, culture and philosophy”. Pulic (2000) suggested calculating <strong>the</strong>
human capital (HC) using companies’ total salaries and wages, and <strong>the</strong> human capital efficiency as a
ratio <strong>of</strong> <strong>the</strong> Value Added to <strong>the</strong> Human Capital.
HCE = VA/HC
VA – Value Added is calculated as <strong>the</strong> difference between total sales (OUT) and material costs
(INPUT).
The second component <strong>of</strong> intellectual capital is a structural capital. Edvinson and Malone (1997)
suggested that it is “everything left at <strong>the</strong> <strong>of</strong>fice when <strong>the</strong> employees go home”. The structural capital
includes hardware, s<strong>of</strong>tware, databases, organizational structure, patents, trademarks and everything
else <strong>of</strong> <strong>the</strong> organizational capability that supports <strong>the</strong> employees’ productivity. This form <strong>of</strong> capital is
not an independent size compared to <strong>the</strong> human capital. It is dependent on <strong>the</strong> created value added
and in reverse proportion to <strong>the</strong> Human Capital, and is calculated as follows:
SC= VA – HC
This means that <strong>the</strong> higher <strong>the</strong> share <strong>of</strong> human capital in <strong>the</strong> created Value Added is, <strong>the</strong> smaller is
<strong>the</strong> share <strong>of</strong> <strong>the</strong> Structural Capital. That is why <strong>the</strong> efficiency <strong>of</strong> <strong>the</strong> Human Capital and <strong>the</strong> Structural
Capital is calculated in a different manner. Pulic suggested that <strong>the</strong> Structural Capital efficiency can
be obtained as a ratio <strong>of</strong> <strong>the</strong> Structural Capital and <strong>the</strong> Value Added.
SCE = SC/VA
The Value Added Intellectual Coefficient contains not only <strong>the</strong> efficiency <strong>of</strong> <strong>the</strong> Intellectual Capital but
also <strong>the</strong> efficiency <strong>of</strong> employed capital that can be calculated by dividing <strong>the</strong> Value Added by <strong>the</strong>
Capital Employed (CE - book value <strong>of</strong> <strong>the</strong> net assets).
CEE = VA/CE
VAIC is an output-oriented process method that can be applied across different business forms and at
various levels <strong>of</strong> operations.
Any link between VAIC and its components, drivers and organizational performance is unlikely to be
simple. We <strong>the</strong>refore consider <strong>the</strong> possibility that <strong>the</strong> link between VAIC, its components, performance
indicators and drivers may be non-linear and conditional on o<strong>the</strong>r factors. We focus on two prominent
hypo<strong>the</strong>ses. Following this fact, two models have been constructed during <strong>the</strong> research:
1. The Model is directed on <strong>the</strong> performance and VAIC relationship search. It assumes that <strong>the</strong>
positive link between VAIC and organizational performance indicators exists for <strong>the</strong> Russian
industrial companies [Hypo<strong>the</strong>sis 1].
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2. The Model is directed on <strong>the</strong> performance and VAIC components relationship search. It
assumes that <strong>the</strong> positive link between <strong>the</strong> intellectual capital and capital employed efficiency and
company performance indicators exists for <strong>the</strong> Russian industrial companies [Hypo<strong>the</strong>sis 2].
We allowed for companies’ size and industries’ diversification. We also checked for our results
robustness to <strong>the</strong> omission <strong>of</strong> all control variables. With regard to <strong>the</strong>se assumptions and literature
background we used <strong>the</strong> following research framework:
Figure 1: The research scheme (source: modified from Laing, Dunn, Hughes-Lucas (2010))
The review <strong>of</strong> <strong>the</strong> empirical literature (Pulic, 2004; Firer, Williams, 2003; Chen et al., 2005) reveals <strong>the</strong>
use <strong>of</strong> VAIC as both a dependent and an independent variable. It will be included in this study as a
dependent variable, in order to test <strong>the</strong> extent to which it may be related to a company performance.
Table 1 provides a brief description <strong>of</strong> variables used in our study that were selected based on earlier
studies and <strong>the</strong>oretical models. In order to capture possible effects, we also consider natural
logarithms <strong>of</strong> <strong>the</strong> measures.
Table 1: Variable list
Variable Variable description
Dependent variables
TLP_vad Total labour productivity (is measured by value added ) per 1 employee
Sales_growth Total net sales figures (t) – total net sales figures (t-1)/total net sales figures (t-1);
measures changes in <strong>the</strong> total sales <strong>of</strong> <strong>the</strong> firm.
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Variable Variable description
ROE Return on Equity
Pr<strong>of</strong>itability Net pr<strong>of</strong>it figures / total net sales figures
Intellectual capital variables
VAIC Value added intellectual coefficient
ICE Intellectual capital efficiency
CEE Capital employed efficiency
CAPEX Capital investments
R&D Research and development expenditures (dummy variable)
Before <strong>the</strong> empirical study results in <strong>the</strong> next section we will present <strong>the</strong> employed data and <strong>the</strong>
research scheme.
4. Data and methodology
The data for <strong>the</strong> survey was provided by Russian Federal Agency <strong>of</strong> Government Statistics (Rosstat)
and its regional department (Permstat) as well as by SPARK-INTERFAX and FIRA Pro Russian
databases based on <strong>the</strong> companies’ annual statistical and financial reports. The data includes
information on 401 small, medium and large companies from different industries, classified according
to <strong>the</strong> 3-digit OKVED codes (classification system <strong>of</strong> economic activity) over 2005-2007 years. The
dataset compiled by <strong>the</strong> authors reports <strong>the</strong> gross value-added (GVA) <strong>of</strong> 23 sectors across <strong>the</strong> Perm
region and includes <strong>the</strong> following information:
Common indicators – form and structure <strong>of</strong> ownership, company age, industry and enterprise
code.
Economic indicators – total revenue, costs, export, company pr<strong>of</strong>itability and unit labour costs.
Specific indicators – total labour productivity, R&D expenditures.
The representativeness study shows <strong>the</strong> sample equivalence to Perm region economic structure at
<strong>the</strong> sector level (with probability <strong>of</strong> 0,683). This fact alone provides motivation for studying <strong>the</strong>
intellectual capital for manufacturing industries only. It should be mentioned that a preliminary
segregation <strong>of</strong> <strong>the</strong> sample was made in this analysis to filter out those companies that did not fall into
manufacturing sectors, leaving a total <strong>of</strong> 101 companies, using which <strong>the</strong> study was carried out.
Table 2 helped us to characterize <strong>the</strong> type <strong>of</strong> a company that agreed to collaborate in our study. It
presents several descriptive objectives <strong>of</strong> <strong>the</strong> sample, where <strong>the</strong> median and <strong>the</strong> standard deviation <strong>of</strong>
<strong>the</strong> variables are detailed.
Table 2: The sample descriptive adjectives (contains data <strong>of</strong> 2007)
Indicator
Objects observation
numbers
Median St. deviation
Total labour productivity (calculated with value added), thous.
$
279 9,3 45,3
ROE, % 293 21,5 459,7
Pr<strong>of</strong>itability, % 289 3,9 42,8
Capex, thous. $ 300 12,7 19668,3
Sales growth, % 289 0,15 3,06
Employees, numbers 297 190 1705
SCE 248 1,0 2,2
HCE 248 1,9 2,6
CEE 248 0,5 0,4
ICE 248 2,3 2,8
VAIC 245 4,0 3,5
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Maria Molodchik and Anna Bykova
Let us now turn to VAIC and its components for our sample. According to <strong>the</strong> established approach to
<strong>the</strong> competitiveness <strong>the</strong>ory and intellectual capital concept, <strong>the</strong> higher intellectual capital efficiency
degree is, <strong>the</strong> more competitive and successful is a company, as measured by total labour
productivity, ROE, pr<strong>of</strong>itability and o<strong>the</strong>r measures.
5. Results <strong>of</strong> <strong>the</strong> models’ estimation
As mentioned earlier, <strong>the</strong> interest in <strong>the</strong> study <strong>of</strong> intellectual capital emerged due to <strong>the</strong>ir assumed
ability to stimulate <strong>the</strong> value creation. Never<strong>the</strong>less, empirical research <strong>of</strong>fers contradictory results
that, on occasions, calls into question <strong>the</strong> statements made in <strong>the</strong> papers that study this link. It should
be made clear that we also used <strong>the</strong> following variables among <strong>the</strong> measures for value creation: sales
growth, pr<strong>of</strong>itability and return on equity (ROE), none <strong>of</strong> which showed any significant results for our
sample <strong>of</strong> companies. Only <strong>the</strong> total labour productivity (measured by value added) can be regarded
as a dependent variable (or traditional indicator) in our sample. There is no statistically significant
correlation existing between <strong>the</strong> independent variables. To test Hypo<strong>the</strong>sis 1 we have constructed <strong>the</strong>
following equation impact on <strong>the</strong> company’s productivity in <strong>the</strong> region:
Y = α + α1VAIC+ α2Capex+ α3R&D+ α4Size+ α5Industry + ξ (1) ,
where dependent variable represents <strong>the</strong> company’s competitiveness and is measured by total labour
productivity. OLS method is used for regression equation coefficient estimation. In case <strong>of</strong> Hypo<strong>the</strong>sis
1 confirmation, <strong>the</strong> variables reflecting intellectual capital efficiency, need to be statistically significant
and have <strong>the</strong> positive sign.
The results <strong>of</strong> <strong>the</strong> regression analyses are shown in Table 3.
Table 3: Regression results for model 1
Independent variables
Depend variable: Total labour productivity
α Statistical significance
VAIC 32,890 ,085*
Capex 0,002 ,000***
R&D 232,714 0,087**
Size ,282 , 485
Industry membership -71,657 ,721
Constant 211,869 ,131
F 56,778
Prob>F 0,000***
Adj. R-square 0,562
Observation numbers 226
Notes: * Significant at p

Maria Molodchik and Anna Bykova
The regression results are shown in Table 4 below:
Table 4: Regression results for model 2
Independent variables
Depend variable: Total labour productivity
α Statistical significance
ICE 41,511 ,082*
CEE 18,251 ,553
Capex ,002 ,000***
R&D 235,224 ,085*
Size -126,372 ,746
Industry membership -65,171 ,487
Constant 207,053 ,141
F 47,241
Prob>F 0,000**
Adj. R-square 0,563
Observation numbers 226
Notes: * Significant at p

Maria Molodchik and Anna Bykova
The figures show <strong>the</strong> good position <strong>of</strong> company A in comparison with average meanings, but also <strong>the</strong>
growth potential in terms <strong>of</strong> human and employed capital efficiency and traditional performance
indicators.
6. Conclusion
For <strong>the</strong> Perm companies our results suggest that VAIC and its components with o<strong>the</strong>r establishments
are significantly associated with a company’s performance measured by total labour productivity. As
such, our findings are ra<strong>the</strong>r similar to those from o<strong>the</strong>r recent research (Firer, Williams, 2003; Diez et
al., 2010). We found that <strong>the</strong> VAIC TM model is appropriate to express company’s intellectual ability
analysis.
At <strong>the</strong> same time, our results need to be interpreted with a certain dose <strong>of</strong> caution. Although we took
much care in trying to ascertain <strong>the</strong> robustness <strong>of</strong> <strong>the</strong> reported results, <strong>the</strong>re are no limits to <strong>the</strong>
number <strong>of</strong> additional sensitivity tests that could be applied in terms <strong>of</strong> data, variable definitions, model
specification and econometric techniques. Fur<strong>the</strong>rmore, we did not investigate a question <strong>of</strong>
occurrence <strong>of</strong> processes’ causality <strong>of</strong> intellectual capital efficiency and labour productivity, pr<strong>of</strong>itability,
sales growth and o<strong>the</strong>rs. Considering <strong>the</strong> organizational intellectual ability phenomenon specificity, it
is necessary to carry out a qualitative research. Fur<strong>the</strong>r investigation may concern analysis <strong>of</strong> <strong>the</strong>
companies’ organizational intellectual ability best-practices.
This paper has discussed <strong>the</strong> organizational intellectual ability analysis. Today, <strong>the</strong>re exists <strong>the</strong> broad
umbrella for a wide variety <strong>of</strong> similar, but never<strong>the</strong>less different concepts. A deeper understanding <strong>of</strong>
how companies benefit from intellectual capital is necessary to avoid confusion, formulate a
meaningful organizational intellectual ability concept, and select <strong>the</strong> appropriate methodology. The
knowledge-based environment in Russia and majority <strong>of</strong> o<strong>the</strong>r currently developing countries requires
a new model with intangible assets disclosure. In this case, <strong>the</strong> intellectual capital is receiving an
increased attention.
Acknowledgements
This study comprises research findings from <strong>the</strong> ‘Intellectual Capital Evaluation” Project carried out
within The Higher School <strong>of</strong> Economics’ 2011 Academic Fund Program.
References
Baiburina, E.R., Golovko, T.V., (2008), “Empirical investigation <strong>of</strong> intellectual enterprise value and its factors for
big Russian companies”, Corporate Finance, №2 (6), pp.5-23
Bontis, N. (2001), “Assessing knowledge assets: a review <strong>of</strong> <strong>the</strong> models used to measure intellectual capital”,
International Journal <strong>of</strong> Management Reviews, Vol.3, No1: pp. 41-60
Bontis, N. (2003), “Intellectual capital disclosure in Canadian corporations”, Journal <strong>of</strong> Human Resource Costing
and Accounting, Vol. 7 N1/2, pp. 9-20.
Chen, M-C., Cheng, S-J., Hwang, Y. (2005), “An empirical investigation <strong>of</strong> <strong>the</strong> relationship between intellectual
capital and firms’ market value and financial performance”, Journal <strong>of</strong> Intellectual Capital, Vol.6, No.2, pp.
159-176
Diez, J.M., Ochoa, M.L., Prieto, M. B., Santidrian, A. (2010), “Intellectual capital and value creation in Spanish
firms”, Journal <strong>of</strong> Intellectual Capital, Vol.11 No.3, pp.348-367
Edvinsson, L. and Malone, M. S., (1997), Intellectual Capital: Realizing your Company’s True Value by Finding its
Hidden Brainpower. New York, NY: Harper Business.
Firer, S. and Williams, M. (2003), “Intellectual capital and traditional measures <strong>of</strong> corporate performance”, Journal
<strong>of</strong> Intellectual Capital, Vol.4 No.3, pp.348-360
Gonchar, K., Kuznecov, B., Dolgopyatova, T., Golikova, V., Yakovlev, A. (2010), “Firms and markets in 2005-
2009: evidence from two rounds <strong>of</strong> manufacturing industry research”, [online]
https://www.hse.ru/data/2010/04/07/1218113331/report.pdf
Kremp, E., Mairesse J., (2004), Knowledge management, innovation and productivity: a firm level exploration
based on manufacturing CIS3 DATA, National Bureau <strong>of</strong> Economic Research
Laing G., Dunn J., Hughes-Lucas S. Applying <strong>the</strong> VAIC model to Australian hotels, Journal <strong>of</strong> Intellectual Capital,
Vol. 11, No.3, 2010, pp. 269-283
Pulic, A. (2000), “MVA and VAIC analysis <strong>of</strong> randomly selected companies from FTSE 250”, [online] www.vaicon.net
Pulic, A. (2000), “Basic information on VAIC TM” , [online], www.vaic-on.net
Shiu, H.-J. (2006), The Application <strong>of</strong> <strong>the</strong> Value Added Intellectual Coefficient to Measure Corporate
Performance: Evidence from Technological Firms, International Journal <strong>of</strong> Management, Vol.23 No.2, pp.
356-365
276

Maria Molodchik and Anna Bykova
S<strong>of</strong>ian, S., Tayles, M., Pike R., (2002), The implications <strong>of</strong> intellectual capital on performance measurement and
corporate performance, [online], www.fppsm.utm.my/.../57-<strong>the</strong>-implications-<strong>of</strong>-intellectual-capital-onperformance-measurement-and-corporate-performance.html
Sveiby, K.-E., (2007), Methods for Measuring Intangible Assets, [online]
http://www.sveiby.com/articles/IntanbibleMethods.htm
Tseng, C.-Y., Goo, Y.-J. J., (2005), Intellectual capital and corporate value in an emerging economy: empirical
study <strong>of</strong> Taiwanese manufacturers, R&D Management, 35, 2, pp. 187-201
Volkov, D., Garanina T., (2007), Intangible Assets: Importance in <strong>the</strong> Knowledge-Based Economy and <strong>the</strong> Role in
Value Creation <strong>of</strong> a Company. The Electronic Journal <strong>of</strong> Knowledge Management, Volume 5 Issue 4,
pp.539-550, [online] www.ejkm.com
277

Perspectives on <strong>the</strong> Possibilities Companies Have to
Recognise and Measure Intellectual Capital
Maria Cristina Morariu
The Academy <strong>of</strong> Economic Studies, Bucharest, Romania
cristina.m.morariu@gmail.com
Abstract: Intellectual capital (IC) is a concept that in our view can be assimilated to <strong>the</strong> unidentified flying objects
in <strong>the</strong> way that researcher and academics have been asking questions such as: does it really exist? If it does,
what is it? Can we control it? Can we measure it? All <strong>the</strong>se questions corroborated with <strong>the</strong> fact that <strong>the</strong>re is no
unique world-wide accepted response to <strong>the</strong> recognition and valuation <strong>of</strong> IC, challenged us to <strong>the</strong> present
research paper. By trying to answer <strong>the</strong> questions mentioned above, our paper represents a mix between
literature review and conceptual analysis in <strong>the</strong> way that: (1) having as starting point <strong>the</strong> IC’s definitions
formulated so far, we are trying to draw one <strong>of</strong> our own; (2) we discuss different options that companies have to
recognise IC in <strong>the</strong> financial statements; (3) in our efforts to make a case for recognising IC as an asset, we are
analysing IC against several key words such as control, substance over form, risks, future benefits; (4) after
reviewing <strong>the</strong> models developed so far for measuring IC, we develop and launch a new model <strong>of</strong> our own; (5)
consequently we propose for debate an accounting treatment to recognise and subsequently measure IC; (6)
having in mind <strong>the</strong> disclosure requirements applicable to every financial statements item, this paper discusses
<strong>the</strong> ability <strong>of</strong> companies to disclose information about IC, and presents different views regarding <strong>the</strong> importance
and usefulness <strong>of</strong> IC reporting. As any study, our paper has limitations that are summarized and presented within
<strong>the</strong> conclusions section. The value and <strong>the</strong> originality <strong>of</strong> this research paper can be supported by <strong>the</strong> genuine
approach used to position IC as a component <strong>of</strong> <strong>the</strong> financial statements, <strong>the</strong> reasoning used to recognise,
measure and account for IC and last but not least by <strong>of</strong>fering a framework and a model that could be tested by
researchers in <strong>the</strong>ir future empirical studies.
Keywords: intellectual capital, definition, control, asset, measurement, disclosure, reporting
1. Introduction
The purposes <strong>of</strong> <strong>the</strong> study are: (1) to formulate a definition for IC, (2) to test whe<strong>the</strong>r IC meets asset
definition, (3) to provide an alternative tool for measuring and accounting for IC, (4) to convince that
IC reporting is possible and desirable.
Methodology used is a mix between literature review and conceptual analysis. We use literature
review as a foundation and as support for our new insights in <strong>the</strong> way that we discuss published
literature, we give a new interpretation <strong>of</strong> old articles and combine new with old interpretations;
never<strong>the</strong>less we trace <strong>the</strong> progression <strong>of</strong> <strong>the</strong> concepts analysed, we summarize and syn<strong>the</strong>size <strong>the</strong>
arguments and ideas <strong>of</strong> o<strong>the</strong>rs and we conclude <strong>the</strong> sections with our own ideas. Conceptual analysis
was also used when analyzing IC into its constituent parts and when testing if IC meets asset
definition criteria as we break down for analysis <strong>the</strong> key concepts <strong>of</strong> asset definition like control, future
economic inflows and measurement.
The objectives <strong>of</strong> <strong>the</strong> study are addressed in three different sections that give <strong>the</strong> structure <strong>of</strong> <strong>the</strong>
paper: <strong>the</strong> first purpose is addressed in <strong>the</strong> next section “Defining IC” after a summary <strong>of</strong> different
definitions given to IC; <strong>the</strong> second purpose and <strong>the</strong> third one are addressed toge<strong>the</strong>r in a single
independent section “IC faces asset definition” after we present different arguments for and against
recognising IC as an asset and after we summarise different tools developed so far to measure IC;
<strong>the</strong> fourth purpose is addressed in an independent section “IC disclosures” that presents different
views regarding <strong>the</strong> importance and usefulness <strong>of</strong> IC reports so to convince entities to report IC. The
paper ends with a final section “Conclusions” that draws <strong>the</strong> conclusions, presents <strong>the</strong> limitations <strong>of</strong>
<strong>the</strong> study and considers its future implications.
2. Defining IC
In time, economists such as Walras and Fisher considered human beings or <strong>the</strong>ir acquired abilities
and skills (English Classical school), as a component <strong>of</strong> capital (Kiker, 1966; Kendrick, 1961). Their
reasons for inclusion were: (1) <strong>the</strong> cost <strong>of</strong> rearing and educating human beings is a real cost; (2) <strong>the</strong>
product <strong>of</strong> <strong>the</strong>ir labour adds to <strong>the</strong> national wealth; (3) an expenditure on a human being that
increases this product will, ceteris paribus, increase national wealth (Kiker, 1966:485). In our days,
perspective has changed in <strong>the</strong> way that researchers and practitioners concentrate <strong>the</strong>ir attention on
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<strong>the</strong> abilities and skills embedded in <strong>the</strong> human beings. By doing so, in time a new concept was born,
developed and continues to challenge practitioners and researchers: intellectual capital.
The concept <strong>of</strong> “intellectual capital” was advanced by Adam Mueller, Friedrich List (Kendrick, 1961:
105) and referred to technical knowledge, know-how, forms <strong>of</strong> organization and tangible capital
goods. It is <strong>the</strong> result <strong>of</strong> investment in <strong>the</strong> discovery and spread <strong>of</strong> productive knowledge. Stewart
(1997) defines it as “packaged useful knowledge” that includes organization’s processes,
technologies, patents, employees’ skills and information about customers, suppliers and stakeholders
(Luthy, 1998: 4). In 1996, Brooking defines IC as combined intangible assets which enable <strong>the</strong>
company to function and comprises market assets, intellectual property assets, human – centred
assets, infrastructure assets (Luthy, 1998: 4-5). In Edvinsson and Malone’s view, IC is formed <strong>of</strong>
human capital and structural capital (customer, organizational, innovation and process capital) and
considers it as debt issue (Lonnqvist, 2002). OECD defines IC as human capital and structural capital,
where <strong>the</strong> former refers to s<strong>of</strong>tware, distribution and supply chains, and <strong>the</strong> latter refers to employee’s
resources, customer and suppliers (Lonnqvist, 2002). Lonnqvist (2002: 14) by considering it as a
synonym <strong>of</strong> intangible asset defines IC as immaterial sources <strong>of</strong> value related to employees’
capabilities, organizations’ resources and <strong>the</strong> way <strong>of</strong> operating and <strong>the</strong> relationship with its
stakeholders. Some authors (Roslender, R. & Fincham, 2001: 387) are saying that IC is <strong>the</strong> “new”
goodwill, something that <strong>the</strong> business builds up over time, and which provides <strong>the</strong> major foundation
for its continued competitive advantage. According to Ulrich (Feleaga & Malciu, 2004: 216), IC =
competence x commitment. IC depends on <strong>the</strong> way each employee thinks, is doing <strong>the</strong> job and on <strong>the</strong>
way <strong>the</strong> company applies policies and systems for <strong>the</strong> duties to be done. IC is a valuable asset in <strong>the</strong>
way it is more likely to produce a competitive advantage just because it is unique and difficult to
imitate (Hitt et al., 2001). A similar view is shared by Nahapiet & Ghoshal (1998) that consider IC as
acquired knowledge, skills, and capabilities that enable persons to act in new ways, as a valuable
resource and a capability for action based in knowledge and knowing.
As <strong>the</strong> above literature review shows, <strong>the</strong>re are many and antagonist ways <strong>of</strong> defining <strong>the</strong> concept <strong>of</strong>
IC. Consequently, we consider it is now <strong>the</strong> moment to open for discussion our view that is almost
similar to some views already mentioned above. As a starting point in trying to define IC we consider
that:
A1: IC is an underlying characteristic <strong>of</strong> <strong>the</strong> employees, from which future benefits are expected to
flow to <strong>the</strong> entity, which encompasses <strong>the</strong> followings: skills, capabilities, experience, knowledge and
last but not least morality.
Fur<strong>the</strong>rmore, we agree with Nelson and Winter (Nahapiet & Ghoshal, 1998) that consider
knowledge is not reducible to what any single individual knows; knowledge is an attribute <strong>of</strong>
<strong>the</strong> firm as a whole. Similarly, we extrapolate this view to skills, capabilities, experience and
morality in <strong>the</strong> way that:
A2: we refer in our study not to <strong>the</strong> IC embedded in a particular employee, but to that one embedded
in all <strong>the</strong> employees working for certain departments existing within <strong>the</strong> company. Each department’s
IC is a component <strong>of</strong> <strong>the</strong> company’s overall IC.
For <strong>the</strong> extrapolation we have made above and for <strong>the</strong> fact that we have considered all employees we
applied a rational based on common sense: assuming that one employee is leaving <strong>the</strong> entity, <strong>the</strong>
normal action company is taking is to find someone else (with similar knowledge, skills, experience
etc) to perform <strong>the</strong> task. In addition, an entity can not change its goals, visions; nor can it stop
production <strong>of</strong> goods/ provision <strong>of</strong> services if an employee leaves <strong>the</strong> company. What if a key
employee leaves <strong>the</strong> entity? We agree that <strong>the</strong> availability <strong>of</strong> people with explicit knowledge and tacit
skills is clearly an important part <strong>of</strong> an organization’s IC, particularly in <strong>the</strong> context where <strong>the</strong>
performance <strong>of</strong> individual employees is crucial (Cook & Yanow cited by Nahapiet & Ghoshal, 1998),
but we consider that even if a key employee is leaving, <strong>the</strong> company’s normal reaction, in <strong>the</strong> context
<strong>of</strong> maximizing its fortune, would be to keep IC at a constant level. In <strong>the</strong> worst scenario, we may
consider it an impairment indicator, but not write <strong>of</strong>f.
An extra paragraph is still needed here to explain why we have allocated IC per departments and not
per entity as a whole. As in <strong>the</strong> case <strong>of</strong> assets (recognised in <strong>the</strong> financial statements) that are
classified in classes <strong>of</strong> assets, we consider proper to treat IC per classes too, that is per departments
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as we consider that not all <strong>the</strong> departments <strong>of</strong> an entity have <strong>the</strong> same pattern to generate inflow to
<strong>the</strong> entity.
3. IC faces asset definition
3.1 General considerations
Human investment is used by Schultz (1961) as an explanation for <strong>the</strong> puzzle <strong>of</strong> dynamic and growth
<strong>of</strong> <strong>the</strong> economy. He admits that human resources have both quantitative and qualitative dimensions.
Moreover, he is also trying to distinguish between expenditure and investment and considers that
much <strong>of</strong> direct expenditure on education is clear example <strong>of</strong> investment in human capital. In order to
distinguish between expenditure and investment, he suggests <strong>the</strong> following classification <strong>of</strong>
expenditure: expenditure that satisfies consumer preferences and in no way enhances <strong>the</strong> capabilities
– <strong>the</strong>y represent pure consumption and expenditure that enhances capabilities and do not satisfy any
preferences underlying consumption – <strong>the</strong>y represent pure investment. The consumption component
<strong>of</strong> education is ei<strong>the</strong>r for current consumption or for future consumption.
Human capital <strong>the</strong>orists suggest that companies invest in employees skills when this investment can
be justified in terms <strong>of</strong> future productivity (Lepak & Snell, 1999). According to Gu & Lev, expenditure
providing investment character could be capitalized as assets <strong>the</strong> sooner sustainability <strong>of</strong> <strong>the</strong> created
potential is secure and depreciation can start when <strong>the</strong> revenues are generated from <strong>the</strong>se
investments. O<strong>the</strong>r arguments that Meer-Kooistra & Zijlstra (2001) bring to sustain <strong>the</strong>ir view (<strong>of</strong> not
including IC in <strong>the</strong> balance sheet) regard <strong>the</strong> fact that components <strong>of</strong> IC can not be expressed in
financial terms, and that financial accounting limits to internal elements whereas IC includes both
internal and external ones.
After considering <strong>the</strong> views above, we position ourselves stating that:
A3: companies should capitalise that part <strong>of</strong> IC that is specific and unique to <strong>the</strong> company. Only that
part is <strong>the</strong> asset <strong>of</strong> <strong>the</strong> company as it represents something that o<strong>the</strong>r companies do not have. IC is a
non current asset with indefinite useful life into which o<strong>the</strong>r resources can be invested, with <strong>the</strong>
expectation <strong>of</strong> a future flow <strong>of</strong> benefits to <strong>the</strong> entity (view sustained by Nahapiet & Ghoshal, 1998;
Burt, 1997) that becomes obsolete if not used, and entails maintenance (training, brainstorming, team
building) o<strong>the</strong>rwise it may lose efficiency and <strong>the</strong>re<strong>of</strong> become impaired.
Later on we test whe<strong>the</strong>r IC meets asset definition criteria and we open for discussion our solution for
splitting <strong>the</strong> IC between asset and expense.
3.2 Control understanding
First condition raised by <strong>the</strong> definition <strong>of</strong> <strong>the</strong> asset (IASB, 2006) is that <strong>the</strong> company must control <strong>the</strong>
asset. So, it invites companies to consider <strong>the</strong> substance over form. But, how can a company control
its employees? Before answering this question we must clarify what control means to us:
A4: Control means that <strong>the</strong> company assumes both <strong>the</strong> benefits and <strong>the</strong> risks (by findings way to
mitigate it) resulted from using IC.
With regards to <strong>the</strong> “form”, a company can achieve control over its employees by having a labour
contract listing <strong>the</strong> rights and <strong>the</strong> duties <strong>of</strong> each party and <strong>the</strong> consequences resulted from breaking
<strong>the</strong>m followed by a good and clear job description (in this way <strong>the</strong> legal commitment from both sides
is assured: company and employees).
When it comes to <strong>the</strong> “substance”, we consider a company can achieve <strong>the</strong> control over its
employees through a good management that inspires good corporate practices to all employees. The
management’s aim must be to get <strong>the</strong> employees on <strong>the</strong> company’s side, to make <strong>the</strong>m loyal, faithful
and dedicated. Like o<strong>the</strong>r authors (Lepak and Snell, 1999; Birkinshaw et al., 2002) we embrace <strong>the</strong>
contingency <strong>the</strong>ory (Value Based Management) as we belief <strong>the</strong>re is no single system <strong>of</strong> human
resources management suitable for all organisations. Information about <strong>the</strong> goals, <strong>the</strong> activities and
<strong>the</strong> processes and <strong>the</strong>ir results is crucial in managing and controlling IC (Meer-Kooistra & Zijlstra,
2001: 3).
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A5: In our view meeting just <strong>the</strong> “form” is not about controlling IC, it is about controlling <strong>the</strong> employee
only, but if “substance” is achieved <strong>the</strong>n we can consider we control IC.
How can companies prove that substance is achieved, that <strong>the</strong> employees are motivated as to
conclude that <strong>the</strong> company controls IC? In this respect we use <strong>the</strong> rational embedded in <strong>the</strong> balance
scorecard designed by Kaplan & Norton in 1992 (Wikipedia, 2010): <strong>the</strong> company sets goals for each
dimension (as applicable) and for each goal indicators (financial or non-financial) are set as a
measure and employees’ departments are assigned on <strong>the</strong> job and make accountable for it.
Companies can assess whe<strong>the</strong>r goals have been achieved through calculating actual indicators and
comparing <strong>the</strong>m with <strong>the</strong> targeted ones. But what if one indicator is above <strong>the</strong> average and ano<strong>the</strong>r
one is below? Considering that IC is assessed per departments our solution for <strong>the</strong>se situations can
be summarised as it follows:
A6: control over IC has been achieved for those departments having <strong>the</strong> majority <strong>of</strong> indicators equal
or above <strong>the</strong> targeted ones.
Returning to A4, <strong>the</strong>re is one part <strong>of</strong> <strong>the</strong> statement left to discuss: control means also to assume risk
generated from using IC, in <strong>the</strong> way <strong>of</strong> finding methods to mitigate it. But, what are <strong>the</strong> risks
associated with IC? Potential answers would be: a bad management, <strong>the</strong> employees don’t have ideas
anymore. O<strong>the</strong>rs may say that because employees leave <strong>the</strong> company every day, IC is being
considered a very risky, vulnerable item and <strong>the</strong>re<strong>of</strong> impossible to control. We do not agree with this
view as although human resources may be mobile to some degree, capabilities may not be valuable
for all firms or even for <strong>the</strong>ir competitors. Some capabilities are based on firm-specific knowledge, and
o<strong>the</strong>rs are valuable when integrated with additional individual capabilities and specific firm resources
that may not be mobile (Hitt et al., 2001).
From our point <strong>of</strong> view, one way to mitigate <strong>the</strong> risk associated with <strong>the</strong> employees leaving and using
<strong>the</strong> skills for o<strong>the</strong>r companies (to control) is by developing specific, customized company’s skills. By
investing in human capital through on <strong>the</strong> job experiences, <strong>the</strong> companies are likely to increase
human capital uniqueness; it may be impossible for competitors to ei<strong>the</strong>r imitate or bid away <strong>the</strong>se
talents (Lepak & Snell, 1999; Tsai, 2002; Birkinshaw et al., 2002). In addition, if some employees can
be seen as core assets for a certain company, <strong>the</strong>y may not be seen likewise for ano<strong>the</strong>r one.
3.3 IC and future benefits
The benefits expected to flow can be summarized as it follows (Adler & Kwon, 2002): product
innovation, team effectiveness, reducing turnover rates, encourage entrepreneurship, formation <strong>of</strong>
start-up companies, streng<strong>the</strong>n supplier relations, inter-firm learning. According to Hitt et al. (2001)
<strong>the</strong>re is a curvilinear relationship between human capital and firm performance in <strong>the</strong> way that early
costs may exceed marginal productivity, but as human capital accumulates synergy and productivity
increase (employee gains tacit knowledge and learns to apply both articulate and tacit knowledge by
practice), average costs decrease. They also demonstrated that <strong>the</strong>re is a positive relationship
between leveraging human capital and firm performance. As it can be proved IC generates future
inflow to <strong>the</strong> company and that <strong>the</strong>re are underlying risks in it, and if <strong>the</strong> substance over form principle
is met <strong>the</strong>n we can conclude that <strong>the</strong> company controls IC. Having said this, <strong>the</strong> next step would be to
question whe<strong>the</strong>r IC can be reliably measured.
3.4 Measuring IC
In order to recognize IC in <strong>the</strong> financial statements we need an objective and reliable measure. In
o<strong>the</strong>r words, we need a market where <strong>the</strong> value is created. But we do not have a market for IC just
because it is unique. Many methods have been developed and empirically tested for measuring IC.
Some <strong>of</strong> <strong>the</strong>m are summarized below:
Company’s capital market value minus company’s book value (Gu & Lev, 2001; Hall, 1993; Luthy,
1998). This method is criticised as it assumes <strong>the</strong>re is no mispricing in capital markets and
because <strong>the</strong> historical balance sheet values <strong>of</strong> assets reflect <strong>the</strong>ir current values (Bond &
Cummings, 2000; Brennan, 2001);
Skandia Navigator developed by Edvinsson and published in 1993 as a supplement to <strong>the</strong> annual
report; Critics brought relate to it being tedious; assign no dollar values to it; it uses proxy
measures to track trends (Shamsuddin, 2010);
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Tobin’s q developed by James Tobin (1969). The method is similar to market to book method
except for using replacement cost instead <strong>of</strong> book value (Wikipedia, 2010);
Intangible Asset Monitor developed by Sveiby (1997) Classifies IC into <strong>the</strong> three categories:
internal, external and individual competence. Provides strategic information <strong>of</strong> <strong>the</strong> firm. Difficult to
assign monetary financial values to <strong>the</strong> final measure (Bontis, 2001).
Our solution for identifying a market value for skills and capabilities and thus measuring IC relates to
outsourcing activities. Of course <strong>the</strong>re are skills and capabilities that can not be outsourced and for
which a market does not exist (Stanciu 2008), but we consider that for those services that can be
outsourced <strong>the</strong>re is market and <strong>the</strong>refore for those an objective and reliable value can be obtained.
How is outsourcing used and why do we need it to measure IC?
A7: In our view, by applying opportunity cost in combination with make or buy decisions, companies
should be able to identify, acknowledge and value IC.
Like with o<strong>the</strong>r assets, a company can decide whe<strong>the</strong>r for some functions it needs full time employees
and for o<strong>the</strong>rs outsourcing seams <strong>the</strong> best choice (Lepak & Snell, 1999). We consider that <strong>the</strong> cost <strong>of</strong>
externalisation can be used as a tool to measure <strong>the</strong> IC. For full time employees, <strong>the</strong> company can
ask itself how much would cost if o<strong>the</strong>r company would do <strong>the</strong> job. This cost should be compared with
<strong>the</strong> total cost company is paying for its employees. For those situations where <strong>the</strong> existing cost is
above <strong>the</strong> potential cost <strong>the</strong> company would have paid if outsourced, <strong>the</strong> company should ask itself if
outsourcing would be a better solution. If <strong>the</strong> answer to this question is negative, meaning <strong>the</strong>
company concludes that even if <strong>the</strong> cost it is paying is higher, <strong>the</strong> company still decides to keep its
employees, <strong>the</strong>n it means we speak about IC and <strong>the</strong> difference between those two costs should be
considered an asset in <strong>the</strong> balance sheet.
A8: we do not capitalize fully for IC, we recognize as an asset only that part that o<strong>the</strong>r companies do
not have. The part that can be outsourced is available to lots <strong>of</strong> companies and is not <strong>the</strong> company’s
individual asset.
3.5 Accounting treatment
If companies choose to recognize IC as an asset in <strong>the</strong> balance sheet (Dr <strong>the</strong> asset), it means we
shall need a credit item also, that can be a reserve that is unrealised and that is to be realised by <strong>the</strong>
moment <strong>the</strong> business is sold, or when is sold. How can a company ascertain whe<strong>the</strong>r IC has been
realised? How can a company calculate <strong>the</strong> amount to be transferred from unrealised to realised
reserves? These questions can be reformulated as it follows: how can a company ascertain whe<strong>the</strong>r
<strong>the</strong> benefits estimated to be generated when it recognised <strong>the</strong> asset, have been generated? How can
a company calculate <strong>the</strong> amount to be reversed? The answer to <strong>the</strong>se questions gravitates around
<strong>the</strong> level to which <strong>the</strong> company achieved <strong>the</strong> objectives set (balance scorecard), and we provide
below <strong>the</strong> steps we consider necessary to be taken:
1. After evaluating <strong>the</strong> resources <strong>the</strong>y have, companies set both financial and non-financial
targets on both short and long run for each <strong>of</strong> <strong>the</strong> four directions defined by Kaplan & Norton.
2. For each objective set, indicators are to be established in order to measure whe<strong>the</strong>r <strong>the</strong>
objectives are achieved.
3. For each objective <strong>the</strong>re is a department <strong>of</strong> employees that can significantly influence <strong>the</strong>
accomplishment.
4. Calculate IC to be recognised on <strong>the</strong> debit (outsourcing model presented above). The same
amount shall be assigned on <strong>the</strong> credit to unrealised reserves.
5. Annually, <strong>the</strong> company shall acknowledge where it stands comparing to <strong>the</strong> long term objective
and reverse unrealized reserves to reserves proportional with targets met.
4. IC disclosures
Reporting IC has been a challenging task for both reporters and for users <strong>of</strong> information. There were
several studies investigating <strong>the</strong> quantity and <strong>the</strong> quality <strong>of</strong> information that companies provide in
respect <strong>of</strong> IC and several studies carried out aiming to provide guidance with regards to <strong>the</strong>
information to be made available. Few examples <strong>of</strong> such studies are summarised in table below.
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Table 1: (Morariu, 2010)
No Author
Maria Cristina Morariu
Year <strong>of</strong>
publication
IC classification:
Internal,
External, Human
Number <strong>of</strong>
sample
companies
Country
1 Guthrie, J. and Petty, R. 2000 1 19 Australia
2 Brennan, N. 2001 1 11 Ireland
3 Bontis, N. 2003 1 10,000 Canada
4 Goh, P.C. and Lim, K.P. 2004 1 20 Malaysia
5 Wong, M., Gardner, C. 2005 1 60 New Zealand
6 Abdolmohammadi, M.J. 2005 1 58
USA
7 Bukh, P.N. et al 2005 68 Denmark
8 Bozzolan, S., O'Regan, P. and Ricceri, F. 2006 1 30x2 Italy, UK
9 Boesso, G. and Kumar, K. 2007 72 Italy & USA
10 White, G., Lee, A. and Tower G. 2007 102 Australia
11 Vergauwen, Bollen and Oirbans 2007 2007 1 60 Sweden, Denmark, UK
12 Striukova, L., Unerman, J. and Guthrie, J. 2008 1 15
UK
13 Ax, C. and Marton, J. 2008 27 Sweden
14 Bruggen, A., Vergauwen, P. and Dao, M 2009 125 Australia
15 Sharabati, A. A., Jawad, S. N. and Bontis, N. 2010 1 15 Jordan
The studies above prove that companies in <strong>the</strong> past tried to report IC and thus <strong>the</strong>y may be used
toge<strong>the</strong>r with <strong>the</strong> existing guidelines issued in this respect (MERITUM 2002, DMTI 2003) as a
benchmark and a framework for nowadays entities. Additional arguments encouraging entities to
report IC are represented by <strong>the</strong> benefits companies have if reporting IC. Some <strong>of</strong> <strong>the</strong>m are
summarized below against <strong>the</strong> downside aspect <strong>of</strong> reporting IC.
According to Bukh (2003) IC reports by reducing <strong>the</strong> uncertainty shall reflect in lower risk premium
and <strong>the</strong>reby a more accurate valuation <strong>of</strong> <strong>the</strong> companies. Botosan (Mouritsen, Nikolaj and Marr 2004)
argues that disclosing information on factors such as relationships, internally generated assets and
knowledge is likely to lower <strong>the</strong> cost <strong>of</strong> equity by decreasing uncertainty about future prospects <strong>of</strong> a
company and facilitates a more precise valuation <strong>of</strong> <strong>the</strong> company. Fur<strong>the</strong>rmore, some may say that
voluntary intellectual capital disclosure (ICD) is an appropriate approach for companies to meet
stakeholders’ IC information needs and to reduce <strong>the</strong> information asymmetry (Vergauwen, Bollen and
Oirbans 2007, Bozzolan, O'Regan and Ricceri 2006). Surprisingly, <strong>the</strong> results obtained by Bruggen,
Vergauwen and Dao (2009) contradict this affirmation. The <strong>European</strong> Union’s Green Book (2001)
considers a wider set <strong>of</strong> benefits such as improved company image, employees’ commitment and
productivity and use <strong>of</strong> natural resources.
Never<strong>the</strong>less, <strong>the</strong>se benefits must be compared with <strong>the</strong> cost <strong>of</strong> providing ICDs because if <strong>the</strong>y are
not <strong>of</strong>fset by benefits, companies would not be stimulated to undertake <strong>the</strong> process (Polo and
Vazquez 2008). Meer-Kooistra & Zijlstra (2001) findings show that in practice for <strong>the</strong> time being
nei<strong>the</strong>r providers nor users <strong>of</strong> IC information are keen to report it externally. Moreover, some authors
found that practitioners are reluctant to publish such information because in <strong>the</strong>ir view it will mean
giving insight into <strong>the</strong>ir competitive advantage, and that financial analysts and <strong>the</strong> capital market do
not pay so much attention to IC disclosures, as <strong>the</strong>y are sceptical, <strong>the</strong>y don’t understand it, <strong>the</strong>y find
difficult to compare as <strong>the</strong>y are unique, <strong>the</strong>y consider it irrelevant as <strong>the</strong> information provided show
indicators <strong>of</strong> general interest without specifying <strong>the</strong> management’ value creation model (Meer-
Kooistra & Zijlstra, 2001; Bukh, 2003; Mouritsen, 2003).
5. Conclusions
Review <strong>of</strong> <strong>the</strong> literature proves that IC is a controversial concept due to some authors considering it
as a capital component, or as an intangible asset, and last but not list as a liability. This never ending
debate was <strong>the</strong> intrigue <strong>of</strong> our paper that in addition contains our opinions too. According to our
purposes, we have managed to (1) define and explain ourselves IC; (2) prove that IC meets asset
definition; (3) provide a new tool for measuring IC; (4) bring convincing arguments that IC reporting is
possible and desirable. As any study, our paper has limitations as follows: When defining IC we
disregarded <strong>the</strong> o<strong>the</strong>r components <strong>of</strong> IC as defined by o<strong>the</strong>r researchers. When exposing our way to
determine control we took into account that achieving an objective depends significantly on one
department. In reality one department may influence <strong>the</strong> achievement <strong>of</strong> several goals, and one goal
may be achieved by <strong>the</strong> cumulative efforts <strong>of</strong> more than one department. The tool we have proposed
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Maria Cristina Morariu
for determining <strong>the</strong> part <strong>of</strong> IC to be capitalised can not be applied to those companies that are
providers for such services that may be outsourced. We are aware that capitalising or issuing IC
reports is a taught task, it is a challenge, but in our view, without those, companies can not <strong>of</strong>fer <strong>the</strong>
“true and fair” performance and can mislead stakeholders.
Acknowledgements
This work was supported by CNCSIS –UEFISCSU, project number PNII – IDEI code 1859/2008,
contract no. 837/2009
References
Adler, P.S. & Kwon S. (2002) “Social Capital: Prospects for a New Concept”, The Academy <strong>of</strong> Management
Review, vol. 27, no. 1: 17-40
Birkinshaw, J., Nobel, R., Ridderstrale, J. (2002) “Knowledge as a Contingency Variable: Do <strong>the</strong> Characteristics
<strong>of</strong> Knowledge Predict Organization Structure?”, Organization Science, vol. 13, no 3: 274-289
Bond, S. R., Cummins, J. G., Eberly, J., Shiller, R. J. (2000) “The Stock Market and Investment in <strong>the</strong> New
Economy: Some Tangible Facts and Intangible Fictions”, Brookings Papers on Economic Activity, vol. 2000,
no. 1: 61-124
Bontis, N., (2001). “Assessing Knowledge Assets: A review <strong>of</strong> <strong>the</strong> Models Used to Measure Intellectual Capital”,
International Journal <strong>of</strong> Management Reviews, Vol. 3, No. 1, pp. 41-60
Bozzolan, S., O'Regan, P. and Ricceri, F. (2006) “Intellectual Capital Disclosure (ICD), a Comparison <strong>of</strong> Italy and
<strong>the</strong> UK”, Journal <strong>of</strong> Human Resource Costing & Accounting, vol. 10, no. 2, pp. 92-113
Brennan, N. (2001) “Reporting Intellectual Capital in Annual Reports: Evidence from Ireland”, Accounting,
Auditing & Accountability Journal, vol. 14, no.4: 423-436
Bruggen, A., Vergauwen, P. and Dao, M. (2009) “Determinants <strong>of</strong> Intellectual Capital Disclosure: Evidence from
Australia”, Management Decision, vol. 47, No. 2, pp. 233-245
Bukh, P. N. (2003) “The Relevance <strong>of</strong> Intellectual Capital Disclosure: A Paradox”, Commentary, Accounting,
Auditing & Accountability Journal, vol. 16, no.1: 49-56
Burt, R.S. (1997) “The Contingent Value <strong>of</strong> Social Capital”, Administrative Science Quarterly, vol. 42, no. 2: 339-
365
Danish Ministry <strong>of</strong> Science, Technology and Innovation (DMTI) (2003) “Intellectual Capital Statements - The New
Guideline”, available online at http://en.vtu.dk/publications/2003/intellectual-capital-statements-<strong>the</strong>-newguideline/intellectual-capital-statements-<strong>the</strong>-new-guideline.pdf
<strong>European</strong> Union (2001) Green Book. Promoting a <strong>European</strong> framework for corporate social responsibility,
available on-line at
http://www.jussemper.org/Resources/Corporate%20Activity/Resources/greenpaper_en.pdf
Feleaga, N. & Malciu, L. (2004) Provocarile Contabilitatii Internationale, la Cumpana dintre Milenii: Modele de
Evaluare si Investitii Imateriale, Bucuresti: Editura Economica
Gu, F. & Lev, B. (2001) “Intangible Assets Measurement, Drivers, Usefulness”, available on-line at
http://pages.stern.nyu.edu/~blev/intangible-assets.doc
Hall, R. (1993) “A Framework Linking Intangible Resources and Capabiliites to Sustainable Competitive
Advantage”, Strategic Management Journal, vol. 14, no. 8: 607-618
Hitt, A.M., Bierman, L, Shimizu, K., Kochhar, R. (2001) “Direct and Moderating Effects <strong>of</strong> Human Capital on
Strategy and Performance in Pr<strong>of</strong>essional Service Firms: A Resource-Based Perspective”, The Academy <strong>of</strong>
Management Journal, vol. 44, no. 1:13-28
International Accounting Standards Board (2006) “International Financial Reporting Standards”, IASC Publication
Department, London, UK
Kendrick, J.W. (1961) “Some Theoretical Aspects <strong>of</strong> Capital Measurement”, The American Economic Review,
vol. 51, no. 2: 102-111
Kiker, B.F. (1966) “The Historical Roots <strong>of</strong> <strong>the</strong> Concept <strong>of</strong> Human Capital”, The Journal <strong>of</strong> Political Economy, vol.
74, no. 5:481-499
Lepak, D.P. & Snell, S.A. (1999) “The Human Resource Architecture: Toward a Theory <strong>of</strong> Human Capital
Allocation and Development”, The Academy <strong>of</strong> Management Review, vol. 24, no. 1: 31-48
Lonnqvist, A. (2002) “Measurement <strong>of</strong> Intangible Assets–An Analysis <strong>of</strong> Key Concepts”, available on-line at
http://www.ebrc.fi/kuvat/275-294.pdf
Luthy, D. H. (1998) “Intellectual Capital and Its Measurement”, available on-line at http://www3.bus.osakacu.ac.jp/apira98/archives/pdfs/25.pdf
Meer-Kooistra, J. & Zijlstra, S. M. (2001) „Reporting on Intellectual Capital”, Accounting, Auditing & Accountability
Journal, vol. 14, no. 4: 456-476
MERITUM (2002) “Guidelines for Managing and Reporting on Intangibles”, Meritum’s Project, TSER Programme
Morariu, M. C. (2010) “Reporting <strong>of</strong> Intellectual Capital from <strong>the</strong> Romanian Companies’ Perspective”,
<strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 7th International <strong>Conference</strong> on Intellectual Capital and Knowledge Management, Hong
Kong, China
Mouritsen, J. (2003) “Overview Intellectual Capital and <strong>the</strong> Capital Market: The Circulability <strong>of</strong> Intellectual
Capital”, Accounting, Auditing & Accountability Journal, vol. 16, no. 1: 18-30
284

Maria Cristina Morariu
Mouritsen, J., Nikolaj, P. and Marr, B. (2004) “Reporting on Intellectual Capital: why, what and how?”, Measuring
Business Excellence, vol. 8, no. 1, pp. 46-54
Nahapiet, J. & Ghoshal, S. (1998) “Social Capital, Intellectual Capital, and <strong>the</strong> Organizational Advantage”,
Academy <strong>of</strong> Management Review, vol. 23, no. 2: 242-266
Polo, F. C. and Vazquez, D. G. (2008) “Social Information within <strong>the</strong> Intellectual Capital Report”, Journal <strong>of</strong>
International Management, vol.14, pp. 353-363
Roslender, R. & Fincham, R. (2001) “Thinking Critically about Intellectual Capital Accounting”, Accounting,
Auditing & Accountability Journal, vol. 14. no.4: 383-398
Shamsuddin, A. et al (2010) “The Development <strong>of</strong> an Intellectual Capital Index for Malaysian
Companies”, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 7th International <strong>Conference</strong> on Intellectual Capital and Knowledge
Management, Hong Kong, China
Schultz, T.W. (1961) “Investment in Human Capital”, The American Economic Review, vol. 51, no. 1: 1-17
Schultz, T.W. (1961) “Investment in Human Capital: Reply”, The American Economic Review, vol. 51, no. 5:
1035-1039
Stanciu, M. C. (2008) “Intellectual Capital, A Challenge to Get <strong>the</strong> “True and Fair View”, Accounting and
Management Information Systems, no. 24, pp. 72-87
Sveiby, K.E. (2007). “Methods for Measuring Intangible Assets”, available at
www.sveiby.com/articles/IntangibleMethods.htm
Tsai, W. (2002) “Social Structure <strong>of</strong> “Coopetition” within a Multiunit Organization: Coordination, Competition, and
Intraorganizational Knowledge Sharing”, Organization Science, vol. 13, no. 2: 179-190
Value Based Management (2008), Contingency Theory – Fiedler, available on-line at
http://www.valuebasedmanagement.net/methods_contingency_<strong>the</strong>ory.html
Vergauwen, P., Bollen, L. and Oirbans, E. (2007) “Intellectual Capital Disclosure and Intangible Value Drivers: an
Empirical Study”, Management Decision, vol. 45, no. 7, pp. 1163-1180
Wikipedia, (2010) “The Free Encyclopaedia”, available on line at http://en.wikipedia.org/
285

The Structural Model <strong>of</strong> Intellectual Capital in Higher
Education Institutions
Fattah Nazem
Islamic Azad University- Roudehen Branch, Tehran, Iran
nazem@riau.ac.ir
Abstract: Higher education system is one <strong>of</strong> <strong>the</strong> most important and complicated products <strong>of</strong> human
achievements. In addition, universities are social systems which have been known as <strong>the</strong> center <strong>of</strong> knowledge
and information as well as thinking bases for leading societies. In today’s complex, competitive world, intellectual
capital is considered as a competitive advantage for organizations and an indication <strong>of</strong> a part <strong>of</strong> <strong>the</strong>
organization’s economic function. The purpose <strong>of</strong> <strong>the</strong> present study was to provide a structural model <strong>of</strong>
intellectual capital in higher education institutions based on managers’ creative problem-solving and
organizational culture. The population <strong>of</strong> <strong>the</strong> research included all employees <strong>of</strong> Islamic Azad University (IAU).
332 managers and three employees under <strong>the</strong>ir supervision (totally 996 employees) were selected using
stratified and cluster random sampling method. The research instruments were three questionnaires which were
administered in 86 IAU branches and education centers: Bontis’s (1997) Intellectual Capital Questionnaire which
consisted <strong>of</strong> 52 items with three underlying constructs <strong>of</strong> human capital, customer capital, and structural capital
and Cronbach Alpha <strong>of</strong> 0.95; Managers’ Creative Problem-Solving Questionnaire (Whetten & Cameron, 2006)
which was comprised <strong>of</strong> 22 items with dimensions <strong>of</strong> logical problem solving, creative problem solving,
developing innovation and Cronbach Alpha 0.82; and a researcher-made questionnaire for organizational culture
which was constructed based on <strong>the</strong> Robbin’s (1996) <strong>the</strong>ory with 28 items and underlying factors <strong>of</strong> individual
initiative, risk tolerance, direction, integration, conflict tolerance, management contact, control, and reward
system (α = 0.92). The results <strong>of</strong> path analysis using LISREL s<strong>of</strong>tware indicated that dimensions <strong>of</strong> creative
problem-solving and organizational culture had a direct effect on intellectual capital with <strong>the</strong> indices <strong>of</strong> 0.03 for <strong>the</strong>
former variable and 0.80 for <strong>the</strong> latter one. The model also showed that <strong>the</strong> factor <strong>of</strong> integrity in organizational
culture had <strong>the</strong> highest direct effect on <strong>the</strong> intellectual capital.
Keywords: Intellectual capital, creative problem-solving, organizational culture, higher education, structural
model
1. Introduction and purpose <strong>of</strong> <strong>the</strong> study
Higher education system is one <strong>of</strong> <strong>the</strong> most important and complicated products <strong>of</strong> human
achievements. Green (1997) explains that higher education provides <strong>the</strong> technical knowledge and
skill that industry requires it in future and <strong>the</strong> fact that governments depend on this knowledge to have
an effective and strategic programming. In <strong>the</strong> past decade, academics have paid attention to <strong>the</strong> role
<strong>of</strong> knowledge for global competitiveness in <strong>the</strong> third millennium. Obviously, knowledge is recognized
as sustainable strategies to acquire and maintain companies’ competitive advantage (Barney, 1991;
Drucker, 1988). Therefore, in <strong>the</strong> knowledge-based world, organization capabilities are based on
knowledge and managers should have to understand which capabilities <strong>the</strong>y need in order to maintain
<strong>the</strong>ir competitive advantages (Barney, 1991).
Intellectual capital provides <strong>the</strong> concept <strong>of</strong> knowledge management that helps managers to identify
and to classify <strong>the</strong> knowledge components <strong>of</strong> an organization. Intellectual capital concepts have been
an explosion <strong>of</strong> interesting studies since FORTUNE magazine published in 1991 (Stewart, 1991).
Intellectual Capital — such as knowledge, skill, relationships — is, more than ever, <strong>the</strong> vital strategic
and competitive resources. Academics believe that <strong>the</strong> benefits, which all economic participants –
employees, managers, investors, governments - gain by accepting Intellectual capital as a resource
and by measuring its efficiency (Pulic, 2004). In knowledge-based economy, companies do not
produce just products or services but create added value to survive in <strong>the</strong> new economic reality.
Academics believe that intellectual capital is <strong>the</strong> lever for maintaining competitive advantages and
sustainable performance. Accordingly, identifying, valuing, managing Intellectual capital is becoming
increasingly important for companies (Bontis, 1996). In Fortune, Steward (1991) defines intellectual
capital as “knowledge that transfers raw materials and makes <strong>the</strong>m more valuable”. The concepts <strong>of</strong>
intellectual capital seem to have classified as a consensus <strong>of</strong> dividing an intellectual capital into three
different groups (Edvinsson and Sullivan, 1996). Human capital simply comprises <strong>the</strong> competence,
skills, experience, and intellectual agilities <strong>of</strong> <strong>the</strong> individual employees (Bounfour, 2003), structural
capital includes processes, systems, structures, brands, intellectual property, and o<strong>the</strong>r intangibles
that are owned by <strong>the</strong> firm but do not appear on its balance sheet (Brooking, 1996). The remaining
type <strong>of</strong> intellectual capital is customer (social) capital resides ei<strong>the</strong>r at <strong>the</strong> individual or <strong>the</strong>
organizational level. Customer (social) capital is an intermediary form <strong>of</strong> intellectual capital consisting
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<strong>of</strong> knowledge in groups and networks <strong>of</strong> knowledge resources embedded within and derived from a
network <strong>of</strong> relationships (Edvinsson and Malone, 1997).
Peter Drucker (1988) believes that managers are <strong>the</strong> most rare and most valuable resources <strong>of</strong>
organizations. One <strong>of</strong> <strong>the</strong> features necessary for any manager is creative problem-solving skill. The
last several decades have been marked by societal turbulence and rapid social change (T<strong>of</strong>fler,
1980). This societal turbulence has been reflected in several organizational trends. Changing
demographics, social changes, and technological changes are major factors affecting organizations
(Cross, 1981).
According to studies carried out by many organizations, <strong>the</strong>re are three common changes that must
be made in schools in order to produce workers who can cope with <strong>the</strong> new workplace. The first two
are creative problem-solving and <strong>the</strong> ability to work as a member <strong>of</strong> a team. The third critical
competency relates to learning. Some reports call it lifelong learning while o<strong>the</strong>rs call it learning how
to learn. Managers in all types <strong>of</strong> organizations must <strong>the</strong>mselves have <strong>the</strong>se competencies and must
be able to develop and nurture <strong>the</strong>m in those who work with <strong>the</strong>m and for <strong>the</strong>m (Knowles, 1990) Thus,
creative problem-solving, working as a team, and learning in permanent white water are three
competencies that managers need in order to ensure lifelong employability. In order to cope with
societal and organizational trends, it is important to have effective and efficient ways to solve
problems. “A problem can be defined as any situation in which a gap is perceived to exist between
what is and what should be” (Vangundy, 1988, p. 3). An alternative view is that a problem occurs
when “<strong>the</strong>re are obstacles to a smooth transition from one state to <strong>the</strong> o<strong>the</strong>r” (Mayer, 1994, p. 4722).
It is also important to differentiate between routine and non-routine problems. Routine problems are
ones that can be resolved by replicating thinking that has occurred before. Thus, routine problems are
not truly problems since <strong>the</strong>re is not an obstacle blocking <strong>the</strong> transition between what is and what
should be. Non-routine problems, on <strong>the</strong> o<strong>the</strong>r hand, are different from those solved previously, so
creative thinking is required. Creative problem-solving goes beyond “simply retrieving something
previously done in this situation” (Weisberg, 1988, p. 152). Since problem-solving skill is an
indispensable part <strong>of</strong> organizational life, it is undeniably necessary to have competent higher
education managers who are able to initiatively settle down <strong>the</strong> problems, especially in <strong>the</strong> modern
competitive world. Whetten & Cameron (2006) enumerated <strong>the</strong> following aspects <strong>of</strong> initiative problem
solving skill:
Logical problem-solving: A skill with four stages <strong>of</strong> defining <strong>the</strong> problem, creating alternative
solutions, evaluating and selecting <strong>the</strong> alternative solutions, and performing and tracing <strong>the</strong>
solutions.
Creative problem-solving: A skill which removes <strong>the</strong> limitations <strong>of</strong> <strong>the</strong> logical problem-solving
model using initiation and cognitive constraints. It has <strong>the</strong> four stages <strong>of</strong> preparation,
establishment, illumination, and confirmation.
Developing innovation: Free <strong>the</strong> potential in people.
In a study by Whetten and Cameron (2006) on 402 effective managers, it was found out that skills like
individual decision making and problem-solving are among <strong>the</strong> ones owned by effective managers.
Cameron and Tschirhart (1988) also investigated 500 managers in 150 companies and concluded
that problem-solving skill is among <strong>the</strong> five most important skills <strong>of</strong> effective managers. Prentice
(1984) also found out that <strong>the</strong> vital skills <strong>of</strong> effective managers are leadership and problem-solving. In
a research on 721 high ranking managers in American companies, Margerison and Kakabadse
(1984) pointed out <strong>the</strong> most important skills for high ranking managers include <strong>the</strong> ability to analyze,
leadership and management, and decision-making. A study conducted on 50 counsellors, pr<strong>of</strong>essors,
managers, and experts in management development by Whetten and Cameron (1984), revealed that
decision-making and problem-solving are two leading skills in successful managers. Hunsieker (1978)
carried out a study on 1854 navy <strong>of</strong>ficers and ended up with <strong>the</strong> result that two skills with significant
impact on <strong>the</strong> managers’ success are leadership and management skills. Luthans et al. (1985) also
reported <strong>the</strong> same results when <strong>the</strong>y studied 52 managers in 3 organizations.
The result <strong>of</strong> <strong>the</strong> study by Connelly (1996) indicated that <strong>the</strong> creative problem-solving skills accounted
for significant, positive variance, career achievement and solution quality for upper level leaders.
Johnson (1986) also concluded that <strong>the</strong> use <strong>of</strong> creative problem-solving can lead to better outcomes
from <strong>the</strong> customer’s perspective as a result <strong>of</strong> creative solutions. Ano<strong>the</strong>r study carried out by
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Fattah Nazem
Ackerley (2006) revealed that <strong>the</strong>re is a relationship between creativity and leadership among
university students in Business. DiLiello (2006) also found out that individuals who have high
innovation and creativity potential are more likely to perceive opportunities to practice innovation and
creativity when <strong>the</strong>y perceive strong support from <strong>the</strong> workplace. The workplace was measured at <strong>the</strong>
Work Group level, <strong>the</strong> supervisor level, and <strong>the</strong> organizational level. These findings support <strong>the</strong>
<strong>the</strong>oretical propositions that self-leadership and innovation/creativity are related. Baghdarnia (2006)
revealed that <strong>the</strong>re is a significant relationship between managers’ problem-solving skill and
organizational climate with <strong>the</strong> staff’s performance. The managers with problem-solving skill are more
successful. He found that a decent organizational climate and managers with high problem-solving
skill could lead to quality management and high performance among <strong>the</strong> staff in ministry <strong>of</strong> education.
The result <strong>of</strong> a study by Hasanvandi (2009) indicated that <strong>the</strong>re is a relationship between managers’
creative problem-solving skill and organizational climate with <strong>the</strong>ir productivity. This is to say that <strong>the</strong>
productivity can be improved among staff in <strong>the</strong> ministry <strong>of</strong> education provided that <strong>the</strong> two factors <strong>of</strong>
managers’ creative problem-solving skill and organizational climate are present.
In <strong>the</strong> intellectual capital model proposed by Ross and Ross (1997), human capital is considered as
one <strong>of</strong> <strong>the</strong> components <strong>of</strong> intellectual capital which includes such features as senior managers’
leadership and innovation. In Brooking’s (1997) model, human capital encompasses staff’s knowledge
in an organization, problem-solving capabilities, leadership and management skills, and innovation.
Sveiby (1997) also underlines <strong>the</strong> role <strong>of</strong> management skills in human capital. Lim and Dallimore
(2004) delineated that <strong>the</strong> efficiency <strong>of</strong> <strong>the</strong> organization is strategic in management approach one
adopts. Management methods are also considered as one <strong>of</strong> <strong>the</strong> components <strong>of</strong> structural capital by
Sullivan and Sullivan (2006). In his Model, Standfield (1990) pinpointed that efficient and pr<strong>of</strong>itable
operationalizing <strong>of</strong> business. It refers to <strong>the</strong> role <strong>of</strong> managers’ decision-making skill. If <strong>the</strong> organization
is passive, it will lose its competitive nature in <strong>the</strong> international scene. Several intellectual capital
models considered different distinctive features in <strong>the</strong>ir models: in Ramboll Group’s Model (2007)
values and management are among <strong>the</strong> distinctive features <strong>of</strong> intellectual capital, in Edvinsson and
Malone (1997) <strong>the</strong> human capital including leadership and conceptual problem-solving, in Edvinsson
(2002) management skill, in Marr and Giovanni (2001) human capital which includes knowledge asset
that is represented in <strong>the</strong>ir problem-solving skill, initiation, and <strong>the</strong>ir tendency for entrepreneurship, in
Burgman and Goran (2005) management skills are inevitable for more financial benefit. One <strong>of</strong> <strong>the</strong>
challenges <strong>of</strong> intellectual capital which is reported by <strong>the</strong> Danish Ministry <strong>of</strong> Science, Technology, and
Innovation is <strong>the</strong> management challenges which lead to upgrading <strong>the</strong> knowledge resources. The
next challenge is related to <strong>the</strong> innovations which necessary to overcome <strong>the</strong> challenges in
management.
Culture is so important to an organization. Lynn (1999) also concluded that organizational culture is
effective in successful use <strong>of</strong> intellectual capital. Schein (1999) suggested that an organization’s
culture helps it cope with its environment. The culture <strong>of</strong> an organization and its vision and purpose
must be in alignment for it to change (Wallach, 1983). Culture influences <strong>the</strong> communication skills and
decision-making processes <strong>of</strong> <strong>the</strong> organization’s members and affects its credibility (Kowalczyk &
Pawlish, 2002). Organizational culture also shapes <strong>the</strong> organization’s level <strong>of</strong> socialization and
learning (Cooke & Rousseau, 1988). Kowalczyk & Pawlish (2002) correlated <strong>the</strong> importance <strong>of</strong> culture
to an organization’s competitive advantage, adaptability, and level <strong>of</strong> innovation. The culture <strong>of</strong> an
organization may affect organizational system operations, productivity, leadership actions (Taylor,
2003), performance (Cameron & Quinn, 1999), and organizational effectiveness (Valentino, 2004).
Research has shown that culture has influenced employees’ commitment (Webster, 2004) and
behaviors (Atchison, 2002).
Robbins (1996) has mentioned <strong>the</strong> key characteristics <strong>of</strong> organizational culture as follows:
1. Individual initiative: The degree <strong>of</strong> responsibility, freedom, and independence that individuals
have.
2. Risk tolerance: The degree to which employees are encouraged to be aggressive, innovative
and risk-seeking
3. Direction: The degree to which <strong>the</strong> organization creates clear objectives and performance
expectations
4. Integration: The degree to which units within <strong>the</strong> organization are encouraged to operate in a
coordinated manner
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5. Management contact: The degree to which managers provide clear communication,
assistance, and support to <strong>the</strong>ir subordinates
6. Control: The number <strong>of</strong> rules and regulations, and <strong>the</strong> amount <strong>of</strong> direct supervision that are
used to oversee and control employee behavior
8. Reward system: The degree to which reward allocations (salary increases, promotions) are
based on employee performance criteria in contrast to seniority, favoritism, and so on.
9. Conflict tolerance: The degree to which employees are encouraged to air conflicts and
criticisms openly.
In Kaplan & Norton’s (2004) model <strong>of</strong> intellectual capital, <strong>the</strong>re is a special attention paid to <strong>the</strong> culture
and <strong>the</strong> environment <strong>of</strong> learning. In <strong>the</strong> model, culture is <strong>the</strong> core which interrelate <strong>the</strong> components <strong>of</strong>
intellectual capital. In ano<strong>the</strong>r model called Skandia Navigator presented by Edvinnson (1997), culture
connects <strong>the</strong> o<strong>the</strong>r aspects <strong>of</strong> intellectual capital. Organizational culture combines human, structural,
and customer capitals to construct intellectual capital. In ano<strong>the</strong>r model called Technology Broker,
Brooking (1997) believes that culture <strong>of</strong> an organization is rooted in various factors ranging from <strong>the</strong>
values staff make to <strong>the</strong> relation between <strong>the</strong> organization and <strong>the</strong> staff and customers. Here, culture
is considered as an infrastructure asset which is called cooperative culture. In <strong>the</strong> model <strong>of</strong> <strong>the</strong>
Canadian Imperial Bank presented by Saint-Onge (1996), empirical knowledge is defined through
intellectual capital as <strong>the</strong> first dynamic value in a company. In this model, organizational culture has a
big role and is place as part <strong>of</strong> structural asset. In ano<strong>the</strong>r model by Sveiby (1997) called Intangible
Assets Monitor, organizational culture is considered as having a major role. He believed that value
comments are part <strong>of</strong> <strong>the</strong> competition and it is advisable to pay respectable attention to <strong>the</strong> work
environment, customers, and <strong>the</strong> super-ordinates which is a kind <strong>of</strong> common cooperative culture.
Following <strong>the</strong> studies which underlined <strong>the</strong> role <strong>of</strong> intellectual capitals in universities in Western
Ontario, Bontis (1998) presented <strong>the</strong> Model from <strong>the</strong> University <strong>of</strong> Western Ontario in which
organizational culture is a fundamental element in forming structural asset. He believed that
organizations should have <strong>the</strong> culture which is strong enough for <strong>the</strong> individuals to be able to gain
new experience, failure, and learn again something new; <strong>the</strong> culture that punish <strong>the</strong> staff for <strong>the</strong>ir
malfunctions will have <strong>the</strong> least success. Flamholtz (2002) considered culture as <strong>the</strong> major factor in
<strong>the</strong> development <strong>of</strong> an organization and <strong>the</strong> cornerstone <strong>of</strong> <strong>the</strong> long-run goals <strong>of</strong> a successful
company. Copeland (2001) also thought <strong>of</strong> organizational culture as a giant step forward in <strong>the</strong>
development <strong>of</strong> <strong>the</strong> intellectual capital. The necessity to manage intellectual capital in universities is
investigated by some scholars (e.g., Ramier, 2010). Moreover, as asserted by Lonnquist, et al.
(2009), intellectual capital models can be beneficial means to management <strong>of</strong> change.
2. Research questions
1. What is <strong>the</strong> structural model <strong>of</strong> <strong>the</strong> intellectual capital based on managers’ creative problemsolving
and organizational culture in higher education Institutions?
2. Which variables have <strong>the</strong> highest and <strong>the</strong> lowest effectiveness on managing intellectual
capital?
3. How predictive is any one <strong>of</strong> <strong>the</strong> variables on managing intellectual capital?
4. How much is <strong>the</strong> goodness <strong>of</strong> fit in this study?
3. Method <strong>of</strong> <strong>the</strong> study
The research methods which were used in this study are: library research to access <strong>the</strong> <strong>the</strong>oretical
framework and <strong>the</strong> related literature; Survey method to collect, classify, describe, and analyze <strong>the</strong>
data. The population under investigation in this study consists <strong>of</strong> <strong>of</strong>ficial staffs who work in 420
branches and educational centers in 14 zones <strong>of</strong> Islamic Azad University. In order to estimate <strong>the</strong>
2 2
z σ
least volume <strong>of</strong> sample, n = 2 formula was used. Regarding <strong>the</strong> minimum sample
d
required for <strong>the</strong> managers’ group which was estimated as 332 and staff group as 996 (three staff for
each manager), creative problem solving questionnaire was administered to <strong>the</strong> managers and
intellectual capital and organizational culture questionnaires were administered to <strong>the</strong> staffs in 86
branches and educational centers. In order to select <strong>the</strong> research sample, two methods <strong>of</strong> stratified
and cluster random sampling were used.
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The research instruments were as follows: Bontis’s (1997) Intellectual Capital Questionnaire which
consisted <strong>of</strong> 52 items with three underlying constructs <strong>of</strong> human capital, customer capital, and
structural capital and Cronbach Alpha <strong>of</strong> 0.95; Managers’ Creative Problem-Solving Questionnaire
(Whetten & Cameron, 2006) which was comprised <strong>of</strong> 22 items with dimensions <strong>of</strong> logical problemsolving,
creative problem-solving, developing innovation and Cronbach Alpha 0.82; and a researchermade
questionnaire for organizational culture which was constructed based on <strong>the</strong> Robbin’s (1996)
<strong>the</strong>ory with 28 items and underlying factors <strong>of</strong> individual initiative, risk tolerance, direction, integration,
conflict tolerance, management contact, control, and reward system (α = 0.92). The results <strong>of</strong> <strong>the</strong>
study were calculated through path analysis using LISREL s<strong>of</strong>tware.
4. Findings <strong>of</strong> <strong>the</strong> study
In <strong>the</strong> present research, in staffs group 569 subjects were male and 381 subjects were female.
Regarding <strong>the</strong>ir work experience, 253 people had less than 5 years, 334 had between 6 to 10 years,
and 364 had more than 11 years <strong>of</strong> work experience. Regarding <strong>the</strong> academic degree, 201 subjects
had held Diploma or Associate Diploma, 569 subjects held Bachelor’s degree, and 178 subjects held
MA or Ph. D. degrees. Regarding <strong>the</strong> marital status <strong>of</strong> <strong>the</strong> subjects, 195 out <strong>of</strong> <strong>the</strong>m were single and
736 were married. In managers group 263 subjects were male, and 67 subjects were female.
Regarding <strong>the</strong>ir work experience, 49people had less than 5 years, 101 had between 6 to 10 years,
and 181 had more than 11 years <strong>of</strong> work experience. Regarding <strong>the</strong> academic degree, 24 subjects
had held Diploma or Associate Diploma, 133 subjects held Bachelor’s degree, and 172 subjects held
MA or Ph. D. degrees. Regarding <strong>the</strong> marital status <strong>of</strong> <strong>the</strong> subjects, 37 out <strong>of</strong> <strong>the</strong>m were single and
286 were married.
The data collected from <strong>the</strong> administration <strong>of</strong> <strong>the</strong> instruments were analyzed. These data included <strong>the</strong>
different indexes <strong>of</strong> central tendency, variability and <strong>the</strong> distribution <strong>of</strong> both groups, <strong>the</strong> managers’
scores obtained from <strong>the</strong> questionnaire <strong>of</strong> creative problem-solving and its 3 components and <strong>the</strong>
staffs’ scores obtained from intellectual capital and organizational culture questionnaires and <strong>the</strong>ir
related components. The distribution <strong>of</strong> <strong>the</strong> managers’ and <strong>the</strong> staffs’ scores in <strong>the</strong> given variables
had tendency toward normality.
As shown in Figure 1, Chi-square index is 364.47 which is significant at 0.000.The Lambda rate <strong>of</strong>
external latent variable <strong>of</strong> creative problem-solving components was 1.46 for x1 (logical problemsolving),
4.82 for x2 (creative problem-solving), 1.83 for x3 (developing innovation) whose
accumulation form <strong>the</strong> creative problem-solving variable with <strong>the</strong> effectiveness rate <strong>of</strong> 0.03.
Chi-Square=364.47, df =74, P-value=0.000, RMSEA=0.019
Figure 1: Path analysis model for components <strong>of</strong> managers’ creative problem-solving and
organizational culture with intellectual capital management
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It means that 0.03% <strong>of</strong> <strong>the</strong> variation in <strong>the</strong> dependant variable <strong>of</strong> intellectual capital management is
explained by a collection <strong>of</strong> <strong>the</strong>se indices. The variable <strong>of</strong> creative problem-solving indicates <strong>the</strong>
highest amount <strong>of</strong> internal consistency in <strong>the</strong> external latent variable. The Lambda rate <strong>of</strong> external
latent variable <strong>of</strong> organizational culture components was 3.37 for x4 (individual initiative), 2.5 for x5
(risk tolerance), 3.01 for x6 (direction), 2.28 for x7 (integration), 1.22 for x8 (conflict tolerance), 2.36
for x 9 (management contact), 2.07 for x10 (control), and 2.31 for x11 (reward system) whose
accumulation form <strong>the</strong> organizational culture variable with <strong>the</strong> effectiveness rate <strong>of</strong> 0.80. It means that
80% <strong>of</strong> <strong>the</strong> variation in <strong>the</strong> dependant variable <strong>of</strong> intellectual capital management is explained by a
collection <strong>of</strong> <strong>the</strong>se indices. The variable <strong>of</strong> individual initiative indicates <strong>the</strong> highest amount <strong>of</strong> internal
consistency in <strong>the</strong> external latent variable.
The Lambda rate <strong>of</strong> internal latent variable <strong>of</strong> intellectual capital management components was 8.77
for y1 (human capital), 8.82 for y2 (structural capital), 9.25 for y3 (customer capital) whose
accumulation form <strong>the</strong> intellectual capital variable. The variable <strong>of</strong> customer capital indicates <strong>the</strong>
highest amount <strong>of</strong> internal consistency in <strong>the</strong> internal latent variable. Since <strong>the</strong> model’s goodness <strong>of</strong> fit
index is 0.93, it can be stated that it has an acceptable fit. The calculated index indicates <strong>the</strong> direct
effect <strong>of</strong> problem solving components and organizational culture on intellectual capital management.
The index is very low for variable <strong>of</strong> creative problem-solving (0.03) but it is very high for <strong>the</strong> variable
<strong>of</strong> organizational culture (0.80). Moreover, <strong>the</strong> model shows that <strong>the</strong> highest direct effect is related to
“integration”, <strong>the</strong> component <strong>of</strong> organizational culture, on intellectual capital management.
The following table presents <strong>the</strong> indices related to <strong>the</strong> model’s fit:
Table 1: Model’s fit indices
Index
Chi-Square
Lewis-Tucker (Non-normed fit index)
Bentler-Bonett’s (Normed fit index)
Hoelter
Root Mean Square Error (RMSE)
GFI
Rate
364.47
0.92
0.91
0.84
0.019
0.93
Interpretation
Full fit (α=0.001)
High fit (more than 0.90)
High fit (more than 0.90)
High fit (more than 0.70)
High fit (equal to or less than 0.05)
High fit (more than 0.90)
The six goodness <strong>of</strong> fit indices indicate presented model’s fit and empirical data. Therefore,
desirability adaptation is provided for <strong>the</strong> designed model and empirical data and can approve it as an
appropriate model for <strong>the</strong> intellectual capital management. On this account, an appropriate model for
intellectual capital management is designed based on <strong>the</strong> structural equations and <strong>the</strong> desirability
adaptation is an indicative <strong>of</strong> structural equation based on creative problem-solving and organizational
culture with intellectual capital. On <strong>the</strong> whole, it can be proposed that this proposed model has full fit
since Chi-square was higher than 300 (X=364.47) and was significant at 0.001.Also, Lewis-Tucker’s
non-normed fit index (0.92) and Bentler-Bonett’s normed fit index (0.91) were both higher than 0.90.
Besides, Hoelter’s index (0.84) was higher than 0.70 and shows high fit. The root mean square error
(RMSE) (0.019) was lower than 0.05 and indicates <strong>the</strong> new model’s fit.
5. Discussion and conclusions
The results <strong>of</strong> path analysis indicated that since model’s goodness <strong>of</strong> fit index is 0.93, it can be stated
that it has an acceptable fit. The calculated index shows <strong>the</strong> direct effect <strong>of</strong> creative problem-solving
components (0.03) and organizational culture (0.80) on intellectual capital management. Moreover,
<strong>the</strong> model shows that <strong>the</strong> highest direct effect is related <strong>the</strong> variable <strong>of</strong> organizational culture in
intellectual capital model.The results <strong>of</strong> this study is in line with <strong>the</strong> research by Edvinsson & Malone
(1997) in that both emphasize <strong>the</strong> important role <strong>of</strong> organizational culture in intellectual capital model
and consider culture and values as <strong>the</strong> core <strong>of</strong> intellectual capital. Also, Sanchez et al. (2007) believe
that organizational culture is a new instrument to evaluate intellectual capital.
In <strong>the</strong>ir view toward organizational culture, Sandra et al. (2007) consider it as a new tool to evaluate
intellectual capital. In <strong>the</strong>ir model, culture is <strong>the</strong> focal point between different assets. In Kaplan &
Norton’s (2004) model <strong>of</strong> intellectual capital, <strong>the</strong>re is a special attention paid to <strong>the</strong> culture and <strong>the</strong>
environment <strong>of</strong> learning. In <strong>the</strong> model, culture is <strong>the</strong> core which interrelate <strong>the</strong> components <strong>of</strong>
intellectual capital. In Brooking‘s (1997) model, culture is considered as an infrastructure asset which
encompasses values, ceremonies, and heroes known by <strong>the</strong> organization’s work force. In <strong>the</strong>
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intellectual capital model presented by Saint-Onge (1996), culture is viewed as <strong>the</strong> filter to understand
<strong>the</strong> environment according to which certain strategies are adopted. There would be no or little
success in long-term plans if <strong>the</strong> organization’s culture were not in line with <strong>the</strong>se plans. Here,
organizational culture acts as part <strong>of</strong> structural asset through which tacit knowledge is formed. It also
determines <strong>the</strong> increase in <strong>the</strong> benefits from competition. In <strong>the</strong> model presented by Sveiby (1997)
believes that value comments are part <strong>of</strong> <strong>the</strong> competition and it is advisable to pay respectable
attention to <strong>the</strong> work environment, customers, and <strong>the</strong> super-ordinates which is a kind <strong>of</strong> common
cooperative culture. Following <strong>the</strong> studies which underlined <strong>the</strong> role <strong>of</strong> intellectual capitals in
universities in Western Ontario, Bontis (1998) presented <strong>the</strong> Model from <strong>the</strong> University <strong>of</strong> Western
Ontario in which organizational culture is a fundamental element in forming structural asset. He
believed that organizations should have <strong>the</strong> culture which is strong enough for <strong>the</strong> individuals to be
able to gain new experience, failure, and learn again something new; <strong>the</strong> culture that punish <strong>the</strong> staff
for <strong>the</strong>ir malfunctions will have <strong>the</strong> least success. Flamholtz (2002) considered culture as <strong>the</strong> major
factor in <strong>the</strong> development <strong>of</strong> an organization and <strong>the</strong> cornerstone <strong>of</strong> <strong>the</strong> long-run goals <strong>of</strong> a successful
company. Copeland (2001) also thought <strong>of</strong> organizational culture as a giant step forward in <strong>the</strong>
development <strong>of</strong> <strong>the</strong> intellectual capital. Edvinsson (1997) emphasizes <strong>the</strong> important role <strong>of</strong>
organizational culture in intellectual capital model and consider culture and values as <strong>the</strong> core <strong>of</strong>
intellectual capital. Organizational culture is more than just <strong>the</strong> asset <strong>of</strong> an organization. Therefore,
organizational culture is <strong>the</strong> surviving factor and <strong>the</strong> core <strong>of</strong> <strong>the</strong> organization and is, according to
Tierney (1988), an internal interactive communication network which can easily evaluate <strong>the</strong> validity <strong>of</strong>
<strong>the</strong> organization.
According to <strong>the</strong> results <strong>of</strong> this study, <strong>the</strong>re is ano<strong>the</strong>r variable which affects intellectual capital
management is managers’ creative problem-solving. In <strong>the</strong>ir study, Whetten and Cameron (2006)
found out that skills like individual decision-making and problem-solving are among <strong>the</strong> ones owned
by effective managers. Cameron and Tschirhart (1988) also concluded that problem-solving skill is
among <strong>the</strong> five most important skills <strong>of</strong> effective managers. Prentice (1984) also found out that <strong>the</strong>
vital skills <strong>of</strong> effective managers are leadership and problem-solving. In <strong>the</strong>ir research, Margerison
and Kakabadse (1984) pointed out <strong>the</strong> most important skills for high ranking managers include <strong>the</strong>
ability to analyze, leadership and management, and decision-making. A study conducted by Whetten
and Cameron (1984) revealed that decision-making and problem-solving are two leading skills in
successful managers. Hunsieker (1987) also ended up with <strong>the</strong> result that two skills with significant
impact on <strong>the</strong> managers’ success are leadership and management skills. Luthans et al. (1985) also
reported that decision-making skill to solve problems as <strong>the</strong> most influential skills among managers.
According to Baghdarnia (2006), <strong>the</strong> more <strong>the</strong> conceptual abilities and skills <strong>of</strong> <strong>the</strong> managers, <strong>the</strong>
more efficient <strong>the</strong>y will be. Also, managers with creative problem-solving skill are more successful.
Hassanvandi (2009) found out that managers with creative problem-solving skill lead <strong>the</strong>ir
organizations to success. O<strong>the</strong>r studies also underline <strong>the</strong> relationship between managers’ creativity
and creative problem-solving and leadership and <strong>the</strong>ir better function. (Ackerley, 2006; Johnson,
1986).
In Ross and Ross (1997), human capital is considered as one <strong>of</strong> <strong>the</strong> components <strong>of</strong> intellectual capital
which includes such features as senior managers’ leadership and innovation. In Brooking’s (1997)
model, human capital encompasses staff’s knowledge in an organization, problem-solving
capabilities, leadership and management skills, and innovation. Sveiby (1997) also underlines <strong>the</strong> role
<strong>of</strong> management skills in human capital. Stanfield (1990) pinpointed that efficiency <strong>of</strong> <strong>the</strong> managers in
gaining pr<strong>of</strong>it. In Ramboll Group’s Model (2007) values and management are among <strong>the</strong> distinctive
features <strong>of</strong> intellectual capital. In Edvinsson and Malone (1997) <strong>the</strong> human capital including
leadership and conceptual problem-solving are underlined. In Marr and Giovanni’s (2001) model
human capital includes knowledge asset that is represented in <strong>the</strong>ir problem-solving skill, initiation,
and <strong>the</strong>ir tendency for entrepreneurship.
The results <strong>of</strong> <strong>the</strong> studies conducted in <strong>the</strong> field reiterate that success in performing intellectual capital
models requires managers who are creative so that, in <strong>the</strong> complicated and competitive world, <strong>the</strong>y
can solve <strong>the</strong> organization’s problems creatively.The need for management and leadership is vital
and sensible in all fields <strong>of</strong> social activities. Without effective leadership and guidance, material and
human resources are doomed to decrease and destruction, while <strong>the</strong> managers <strong>of</strong> higher education
as people who are in charge <strong>of</strong> organizations and university branches are considered as <strong>the</strong> main and
determining factor in preparing and supplying <strong>the</strong> human resources required by o<strong>the</strong>r organizations
which provide services or products in <strong>the</strong> society.The appointment <strong>of</strong> managers with creative
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Fattah Nazem
problem-solving skill and providing an appropriate organizational culture in universities can help
manage <strong>the</strong> intellectual capital more efficiently. It is also suggested that <strong>the</strong> research projects as this
are to be endorsed in all branches <strong>of</strong> Islamic Azad University (IAU) to upgrade <strong>the</strong> management <strong>of</strong>
intellectual capital. Having <strong>the</strong> effective role <strong>of</strong> higher education in <strong>the</strong> economic, social, political, and
cultural development, it is suggested that this study can also be carried out in o<strong>the</strong>r universities all
around <strong>the</strong> world so as to practically take giant steps in <strong>the</strong> management <strong>of</strong> intellectual capital.
Acknowledgements
This paper is extracted from a research project sponsored by <strong>the</strong> research department <strong>of</strong> <strong>the</strong> Islamic
Azad University, Roudehen Branch to whom I owe a debt <strong>of</strong> gratitude.
References
Ackerley. E.E. (2006) An Investigation <strong>of</strong> The Relationship <strong>of</strong> Creativity and Leadership in University Business
Students, [Ph.D. Dissertation],Nor<strong>the</strong>rn Arizona University.
Atchison, T.A. (2002) "What is Corporate Culture", Trustee, 55(4), 8.
Baghdarnia, M.(2006) The Relationship between Managers' Problem Solving , Organizational Climate and
Performance among <strong>the</strong> Staffs Employed in Education Ministry <strong>of</strong> Tehran Province, [Ed.D.Dissertation],
Tehran, Islamic Azad University – Roudehen Branch.
Barney, J.B. (1991) "Firm Resources and Sustained Competitive Advantage", Journal <strong>of</strong> Management, 17(1), 99-
120.
Bontis, N. (1996) "There is a Price on Your Head: Managing Intellectual Capital Strategically", Business
Quarterly.
Bontis, N. (1997) Intellectual Capital Questionnaire. Hamilton, Canada: Institute for Intellectual Capital Research
Inc.
Bontis, N. (1998) "Intellectual Capital: An Exploratory Study That Develops Measures and Models", Management
Decision, 36(2), 63-76.
Bounfour, A. (2003) "The IC-Dval Approach", Journal <strong>of</strong> Intellectual Capital, 4(3), 396-412.
Brooking, A. (1996) Intellectual Capital: Core Assets for <strong>the</strong> Third Millennium Enterprise, Thompson
Business Press, London.
Brooking, A. (1997) "The Management <strong>of</strong> Intellectual Capital", Long Range Planning, 30(3), 364-365.
Brooking, A. (1997) El Capital Intelectual: El Principal Activo De Las Empresas Del Tercer Milenio, Paidós
Empresa, Barcelona.
Burgman, R. and Goran, R. (2005) The new economy – a new paradigm for managing for shareholder value,
Center for Business Performance, Cranfield School <strong>of</strong> Management.
Cameron, K.S. and Quinn, R.E. (1999). Diagnosing and Changing Organizational Culture.Retrieved July 20,
2004, from Http://Webuser.Bus.Umich.Edu/Cameron/Culture%20book-Chapter%201.Pdf, Pp. 5-11.
Cameron, K., Tschihart, M. (1988) Managerial competencies and organizational effectiveness, Working Paper,
School <strong>of</strong> Business Administration, University <strong>of</strong> Michigan.
Connelly, M.S. (1996) Exploring <strong>the</strong> Relationships <strong>of</strong> Creative Problem-Solving Skills and Wisdom to Leadership
[Ph.D. Dissertation], United States:Virginia George Mason University.
Cooke, R.A., and Rousseau, D.M. (1988) "Behavior Norms and Expectations: A Quantitative Approach to <strong>the</strong>
Assessment <strong>of</strong> Organizational Culture", Group and Organization Studies, 13(3), 245-273.
Copeland, J.E. (2001) "Interview", The Chief Executive, July 1.
Cross, K. P. (1981) Adults as Learners, San Francisco: Jossey-Bass Publishers.
Diliello, T.C. (2006) Maximizing Organizational Leadership Capacity for <strong>the</strong> Future: The Impact <strong>of</strong> Self-
Leadership on Innovation and Creativity, [Ph.D. Dissertation].College <strong>of</strong> Business and Public Management
Department <strong>of</strong> Public Administration: University <strong>of</strong> La Verne.
DMSTI (2003) Intellectual capital statements, <strong>the</strong> new guideline, Copenhagen: Danish Ministry <strong>of</strong> Science,
Technology and Innovation.
Drucker, P.F. (1988) "The Coming <strong>of</strong> <strong>the</strong> New Organization", Harvard Business Review.
Edvinsson, L. and Sullivan, P. (1996) "Developing A Model for Managing Intellectual Capital", <strong>European</strong>
Management Journal, 14(4).
Edvinsson, L. and Malone, M.S. (1997) Intellectual Capital. Realizing Your Company's True Value by Finding its
Hidden Brainpower, Harper Collins, New York, NY.
Edvinsson, L. (2002) Corporate longitude- navigating <strong>the</strong> knowledge economy. Stockholm: Book House
Publishing.
Flamholtz, E. (2002) "La Cultura Empresarial Y La Cuenta De Resultados", Harvard Deusto Business Review,
August, Pp. 62-9.
Green, A. (1997) Education and State Formation in Europe and Asia, In K. Kennedy (Ed), Citizenship
Educational and <strong>the</strong> Modern State, London: The Falmer Press.
Hasanvandi, Z. (2009) The Relationship between Managers' Creative Problem Solving, Organizational Culture
and Productivity among <strong>the</strong> Managers employed in Education Ministry <strong>of</strong> Lorestan Province,
[Ed.D.Dissertation], Tehran, Islamic Azad University – Roudehen Branch.
Hunsicker, F. R. (1978) “What successful managers say about <strong>the</strong>ir skills”, Personnel Journal, November, 618-
621.
293

Fattah Nazem
Johnson, M.J. (1986) The Use <strong>of</strong> Creative Problem Solving Leads to Better Outcomes from <strong>the</strong> Customer's
Perspective as A Result <strong>of</strong> Creative Solutions, [Ph.D. Dissertation], The Fielding Institute.
Kaplan, R.S. and Norton, D.P. (2004) "La Disponibilidad Estratégica De Los Activos Intangibles", Harvard Deusto
Business Review, March, Pp. 38-51.
Knowles, M.S. (1990) The Adult Learner : An Neglected Species (4 th Ed.), Houston : Gulf Publishing Company.
Kowalezyk, S.J., and Pawlish, M.J. (2002) Corporate Branding Through External Perception <strong>of</strong> Organizational
Culture, Corporate Reputation Review, 5(2/3), 159- 174.
Lim, I, K. and Dallimore, P. (2004) “Intellectual capital management attitudes in service industries”, Journal <strong>of</strong>
Intellectual Capital, 5 ( 1),181-194.
LÖnnquist, A., Kianto, A., and Sillan Pää, V., (2009) "Using Intellectual Capital Management for Facilitating
Organizational Change", Journal <strong>of</strong> Intellectual Capital, 10(4), 559-572.
Luthans, F., Rosenkrantz, S. and Hennessey, H. W. (1985) “What do successful managers really do? An
observation study <strong>of</strong> managerial activities” , Journal <strong>of</strong> Applied Behavioral Science, 21, 255- 270.
Lynn, B.E. (1999) "Culture and Intellectual Capital Management: A Key Factor in Successful ICM
Implementation". International Journal <strong>of</strong> Technology Management, Geneva. 18(5,6,7,8), 590-603.
Margerison, C. and Kakabadse, A. (1984) How American chief executives succeed, New Yourk: AMA
publications.
Marr, B. and Giovanni, S. (2001) Measuring and managing intellectual capital and knowledge assets in new
economy organizations. In M. Bourne (ed.), Handbook <strong>of</strong> Performance Measurement, London: Gee
Publishing Ltd.
Mayer, R. E. (1994) "Development <strong>of</strong> Learning Skills in Problem-Solving and Thinking. In T. Husén & T. N.
Postlethwaite" (Eds.) The International Encyclopedia <strong>of</strong> Education (2nd Ed., Vol. 8, Pp. 4722-4728), Oxford,
England: Elsevier Science, Ltd.
Prentice, M. G. (1984) “An empirical search for a relevant management curriculum”, Collegiate News and Views,
Winter, 25- 29.
Pulic, A (2004) "Intellectual Capital- Does it Create or Destroy Value?", Measuring Business Excellence, 8(1), 62-
68.
Ramboll, Group. (2007) “Annual Report 2007”. Copenhagen. (Retrieved March 5, 2007, from: www.ramboll.dk).
Ramirez, Y., (2010) "Intellectual Capital Models in Spanish Public Sector", Journal <strong>of</strong> Intellectual Capital, 11(2),
248-264.
Robbins, S.P. (1996) Organizational Behavior, N.J : Englewood Cliffs, P. 226-228.
Ross, G And Ross, 1. (1997) "Measuring Your Company's Intellectual Performance", Long Range Planning,
30(3), 325.
Schein, E. H. (1999) The Corporate Culture Survival Guide: Sense and Nonsense about Culture, San Francisco:
Jossey-Bass.
Saint-Onge, H. (1996) "Tacit Knowledge: The Key to The Strategic Alignment <strong>of</strong> Intellectual Capital", Strategy
and Leadership, 24(2), 10-14.
Sanchez-Canizares, S.M., Ayuso Munoz, M.A.,And Lopez-Guzman, T. (2007) "Organizational Culture and
Intellectual Capital: A New Model", Journal <strong>of</strong> Intellectual Capital. Bradford. Vol. 8, P. 409-430.
Senge, P.M. (1990) The Fifth Discipline: The Art and Practice <strong>of</strong> <strong>the</strong> Learning Organization, Doubleday/Currency,
New York, NY.
Sullivan J. P. H. and Sullivan S. P. H. (2000) “Valuing intangible companies: An intellectual capital approach”,
Journal <strong>of</strong> Intellectual Capital, 1 ( 4) , 328-340.
Standfield,K.(1999) “Knowcorp”, (Retrieved January5, 2000, from: www.knowcorp.com).
Sveiby, K.E. (1997) The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets,
Berrett-Koehler, New York, NY.
Taylor, M. (2003) "A Question <strong>of</strong> Integrity", Modern Healthcare, 33(2), 6-8.
Tierney, W. (1988) “Organizational culture in higher education”, Journal <strong>of</strong> Higher Education, 59 (1), 2-21.
T<strong>of</strong>fler, A. (1980) The Third Wave, NY: Morrow.
Valentino, C.L., And Brunelle, F.W.H. (2004) "The Role <strong>of</strong> Middle Managers in <strong>the</strong> Transmission and Integration
<strong>of</strong> Organizational Culture", Journal <strong>of</strong> Healthcare Management, 49(6), 393-404.
Vangundy, A. B. (1988) Techniques <strong>of</strong> Structured Problem Solving (2nd Ed.), New York: Van Nostrand Reinhold.
Wallach, E. (1983) "Individuals and Organization: The Cultural Match" [Abstract], Trainingand Development
Journal, 12(2), 28-35.
Webster, C. (2004) "Exploring <strong>the</strong> Relationships among Organizational Culture, Customer Satisfaction, and
Performance". Retrieved July 22, 2004, from
Http://Marketing.Byu.Edu/Htmlpages/Eers/<strong>Proceedings</strong>99/Webster.Htm, Para 1-7, 11-15.
Weisberg, R. W. (1988) Problem Solving and Creativity, In R. J. Sternberg (Ed.), The Nature <strong>of</strong>
Creativity:Contemporary Psychological Perspectives (Pp. 148-176),Cambridge, MA: Cambridge University
Press.
Whetten, D. and Cameron, K. S. (1984) “Management skill training: A needed addition to <strong>the</strong> management
curriculum”, Organizational Behavior Teaching Journal, 8, 10-15.
Whetten, D.A. and Cameron, K.S. (2006) Developing Management Skills: Solving Problems Creatively, Prentice
Hall.
294

Knowledge Dynamics in a Chaotic Environment
Andrei Stefan Nestian
Alexandru Ioan Cuza University, Romania
nestian@uaic.ro
Abstract: The aim <strong>of</strong> this explorative and conceptual paper is to contribute to a better understanding <strong>of</strong> <strong>the</strong> SECI
knowledge dynamics model by analyzing it when confronted with a chaotic environment. Useful prescriptions for
<strong>the</strong> practical use <strong>of</strong> <strong>the</strong> model in organizations confronted with such environments are proposed. The paper is
based on a <strong>the</strong>oretical research in which analysis and comparison <strong>of</strong> relevant literature sources was used. The
way <strong>the</strong> knowledge dynamics model is presented by Ikujiro Nonaka and his co-workers suggests that <strong>the</strong>
evolving spiral is possible mainly because <strong>of</strong> <strong>the</strong> inputs <strong>of</strong> knowledge generation from within. Still, <strong>the</strong> necessary
existence <strong>of</strong> a Ba in order to generate <strong>the</strong> spiral demonstrates that <strong>the</strong> spiral is influenced by inputs form <strong>the</strong> Ba.
This implies <strong>the</strong> acceptance <strong>of</strong> a relationship between <strong>the</strong> environment and <strong>the</strong> knowledge conversion process, in
which <strong>the</strong> environment influences <strong>the</strong> knowledge creation. The article is based on <strong>the</strong> hypo<strong>the</strong>sis that a chaotic
environment, characterized by unpredictability, non-linearity and crisis will lead to specific ways <strong>of</strong> functioning <strong>of</strong>
<strong>the</strong> knowledge conversion process. Chaos is <strong>the</strong> science <strong>of</strong> complex, dynamical, non-linear, far from equilibrium
systems. It is a fitting model to use in today’s unpredictable business environment. Dynamic chaotic systems are
built around “strange attractors” which define <strong>the</strong>ir boundaries and guide <strong>the</strong>ir evolution and growth. Similarities <strong>of</strong>
<strong>the</strong>se systems with <strong>the</strong> knowledge dynamics system comprising <strong>the</strong> SECI cycle and <strong>the</strong> platform for knowledge
creation (Ba) are analyzed. A crisis is seen as a low-probability, high-impact event that threatens <strong>the</strong> viability <strong>of</strong>
<strong>the</strong> organization and is characterized by ambiguity <strong>of</strong> cause, effect, and means <strong>of</strong> resolution, as well as by a
belief that decisions must be made swiftly. Starting from <strong>the</strong> general concept <strong>of</strong> resilience as <strong>the</strong> property <strong>of</strong> a
material to absorb energy when it is deformed elastically, <strong>the</strong> concept <strong>of</strong> resilience <strong>of</strong> <strong>the</strong> knowledge dynamics
system is proposed and explained. The reactions <strong>of</strong> <strong>the</strong> knowledge dynamics system at <strong>the</strong> unpredictable and
non-linear evolutions are investigated starting from <strong>the</strong> possibilities <strong>of</strong> using and producing tacit and explicit
knowledge in <strong>the</strong>se contexts. The <strong>the</strong>oretical and practical implications are analyzed and discussed.
Keywords: knowledge dynamics, chaos, environment, resilience
1. The influence <strong>of</strong> <strong>the</strong> environment upon <strong>the</strong> knowledge creation
The way <strong>the</strong> knowledge dynamics model is presented by Ikujiro Nonaka and his co-workers suggests
that <strong>the</strong> evolving spiral is possible mainly because <strong>of</strong> <strong>the</strong> inputs <strong>of</strong> knowledge generation from within.
Still, <strong>the</strong> necessary existence <strong>of</strong> a Ba in order to generate <strong>the</strong> spiral demonstrates that <strong>the</strong> spiral is
influenced by inputs form <strong>the</strong> Ba. This implies <strong>the</strong> acceptance <strong>of</strong> a relationship between <strong>the</strong>
environment and <strong>the</strong> knowledge conversion process, in which <strong>the</strong> environment influences <strong>the</strong>
knowledge creation.
In order to justify this idea, we start from <strong>the</strong> definition given by Nonaka: Ba is a shared space for
emergent relations. It can be physical (desks, workspaces), virtual (e-mail, teleconferences), mental
(ideas, ideals, shared experiences), or a combination <strong>of</strong> all <strong>the</strong>se. This definition certifies that Ba has
a physical component, <strong>of</strong> space in which <strong>the</strong> knowledge conversion process takes place, as well as a
mental component, which supports <strong>the</strong> transfer <strong>of</strong> ideas, ideals and shared experiences, within <strong>the</strong>
limits <strong>of</strong> <strong>the</strong> physical component <strong>of</strong> Ba.
Nonaka & Konno describe very clearly <strong>the</strong> physical aspect <strong>of</strong> <strong>the</strong> relation between Ba and <strong>the</strong> entities
participating to <strong>the</strong> process <strong>of</strong> knowledge conversion. Therefore, <strong>the</strong>y consider that Ba is <strong>the</strong> world in
which <strong>the</strong> individual is self-conscious as part <strong>of</strong> an environment on which his life depends. The
individual is surrounded by <strong>the</strong> social group that he belongs to, being a part <strong>of</strong> <strong>the</strong> Ba <strong>of</strong> this group. In
<strong>the</strong> way in which <strong>the</strong> Ba <strong>of</strong> <strong>the</strong> individual is <strong>the</strong> group, <strong>the</strong> organization is <strong>the</strong> Ba <strong>of</strong> <strong>the</strong> group. Finally,
<strong>the</strong> market is <strong>the</strong> Ba <strong>of</strong> <strong>the</strong> organization. It is on her that <strong>the</strong> <strong>the</strong> organization’s life depends.(Nonaka
and Konno, 1998: 40-41)
The favorite perspective from which <strong>the</strong> Ba is regarded more <strong>of</strong>ten in <strong>the</strong> articles and research studies
is that <strong>of</strong> organization as Ba <strong>of</strong> groups. The undeclared logic <strong>of</strong> this perspective is <strong>the</strong> “consultancy”
view <strong>of</strong> focusing <strong>the</strong> discourse on <strong>the</strong> practical aspects <strong>of</strong> managerial intervention at <strong>the</strong> level <strong>of</strong>
organization.(Chen, 2002: 59-279) The main perspective used in <strong>the</strong> argumentation in <strong>the</strong> present
article is somewhat different: <strong>the</strong> market is <strong>the</strong> Ba <strong>of</strong> organization.
Starting from <strong>the</strong> idea that <strong>the</strong> market is <strong>the</strong> Ba <strong>of</strong> organizations, <strong>the</strong> interactions which need to be
analyzed will be based on o<strong>the</strong>r rules than in <strong>the</strong> case <strong>of</strong> <strong>the</strong> relation between groups and <strong>the</strong> main
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organization. This time we speak about o<strong>the</strong>r elements that suffer interactions, and in <strong>the</strong> Ba <strong>the</strong>re will
be included <strong>the</strong> external components as well as <strong>the</strong> internal components <strong>of</strong> <strong>the</strong> organization.
Focusing more precise on <strong>the</strong> point <strong>of</strong> interest in <strong>the</strong> present article, <strong>the</strong> problem <strong>of</strong> this analysis is <strong>the</strong>
connection between <strong>the</strong> environment and <strong>the</strong> organization, from <strong>the</strong> perspective <strong>of</strong> <strong>the</strong>ir positioning as
elements <strong>of</strong> dynamic conversion <strong>of</strong> knowledge. In order to reveal <strong>the</strong>se connections, at <strong>the</strong> level <strong>of</strong>
knowledge conversion, we will analyze <strong>the</strong> case <strong>of</strong> relations between a chaotic environment and <strong>the</strong>
organization.
Thus, this article is based on <strong>the</strong> hypo<strong>the</strong>sis that a chaotic environment, characterized by
unpredictability, non-linearity and crisis will lead to specific ways <strong>of</strong> functioning <strong>of</strong> <strong>the</strong> knowledge
conversion process.
2. The chaotic environment
The chaos <strong>the</strong>ory is a field <strong>of</strong> study in various fields <strong>of</strong> activity – maths, physics, philosophy, economy,
studying <strong>the</strong> behavior <strong>of</strong> <strong>the</strong> dynamic systems, highly sensitive to initial conditions. The chaos <strong>the</strong>ory
was built around ma<strong>the</strong>matical equation describing complex, dynamical, non-linear systems. Chaos is
<strong>the</strong> science <strong>of</strong> complex, dynamical, non-linear, co-creative, far from equilibrium system.(Fitzgerald
and Eijnatten, 2002: 412 – 423)
In order to classify it <strong>the</strong>matically speaking, <strong>the</strong> ideas <strong>of</strong> <strong>the</strong> chaos <strong>the</strong>ory start from <strong>the</strong> general <strong>the</strong>ory
<strong>of</strong> systems. A system is a set <strong>of</strong> parts that interact with each o<strong>the</strong>r as a whole. A chaotic environment
is defined as an environment characterized from a determinist perspective by non-linearity,
bifurcations and strange attractors.
In <strong>the</strong> chaotic dynamic systems <strong>the</strong> dynamic balance is kept through <strong>the</strong> simultaneous existence <strong>of</strong>
<strong>the</strong> evolution and identity <strong>of</strong> <strong>the</strong> system. The history, identity and sense <strong>of</strong> existence for <strong>the</strong> system
define its limits and guide its evolution and growth while <strong>the</strong> natural processes <strong>of</strong> growth guide it to
chaos.
The chaos <strong>the</strong>ory treats dynamic systems as auto-organized systems from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> <strong>the</strong>
manner in which <strong>the</strong>y organize and structure, as well as from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> <strong>the</strong> way in which
<strong>the</strong>y grow and change. This view not only does involve <strong>the</strong> internal emergent order, but also <strong>the</strong>
coevolution with <strong>the</strong> environment. The chaos <strong>the</strong>ory states that <strong>the</strong> system creates its own order
whilst its evolution, by integrating <strong>the</strong> changes induced by <strong>the</strong> interactions with <strong>the</strong> environment in <strong>the</strong>
system’s identity. Because a chaos system operates in an unstable combination <strong>of</strong> randomness and
order, it continuously changes and evolves. As answer to <strong>the</strong> changes and turbulences in <strong>the</strong>
environment <strong>the</strong> system transforms <strong>the</strong> rules which it follows in order to cope better with <strong>the</strong> changing
environment. Because <strong>the</strong> chaotic environment is non-linear, small changes in <strong>the</strong> initial statuses can
take place, growing exponentially, creating major shocks on <strong>the</strong> growing and evolution <strong>of</strong> <strong>the</strong> systems.
Bifurcation points can cause sudden changes in direction, character, or structure and permanently
redefine a system in new and unexpected ways. The feedback modulates <strong>the</strong> system, ei<strong>the</strong>r for
mentaining its stability (negative feedback), or for amplifying <strong>the</strong> deviations and abnormalities,
destabilizing <strong>the</strong> actual state, and introducing new types in <strong>the</strong> system (positive feedback). Starting
from <strong>the</strong> essence <strong>of</strong> <strong>the</strong> feedback, <strong>the</strong> resulting fact is that a new system is bettered, creates its own
future and adapts continuously to <strong>the</strong> environment on <strong>the</strong> basis <strong>of</strong> <strong>the</strong> intelligence and information
which it contains.(Bechtold, 1997: 193-201)
3. Chaos and knowledge dynamics
The spiral <strong>of</strong> knowledge creation is not autonomous and self - maintained. The evolving spiral is
possible with inputs from <strong>the</strong> Ba platforms for knowledge creation and not with knowledge generation
from within. The evolving spiral <strong>of</strong> knowledge creation passes sequentially through individual
processes and organizational processes in a deterministic way, although knowledge dynamics is not a
physical process.(Bratianu, 2010: 193 -200)
Nonaka & Konno affirm that Ba is just a organic ground for creating knowledge. The concentration <strong>of</strong>
knowledge in Ba doesn’t involve consuming <strong>the</strong>se resources, but a cyclic ecologic process <strong>of</strong>
cultivation-valuing <strong>the</strong> resources.(Nonaka and Konno, 1998: 53) In <strong>the</strong> <strong>the</strong>ory <strong>of</strong> complexity, <strong>the</strong>
feedback <strong>of</strong> <strong>the</strong> system is <strong>the</strong> generator <strong>of</strong> economic results for <strong>the</strong> company. This is possible due to
<strong>the</strong> organizations knowledge, educated on <strong>the</strong> market, which allow <strong>the</strong> obtaining <strong>of</strong> a sense from <strong>the</strong>
signals in <strong>the</strong> environment. For example, <strong>the</strong> process <strong>of</strong> acquiring knowledge from <strong>the</strong> environment is
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strongly supported by <strong>the</strong> direct interactions with clients and suppliers. To be more specific,
socializing involves knowledge capturing by physical proximity, <strong>the</strong> necessary thing being <strong>the</strong>
development <strong>of</strong> shared activities, in <strong>the</strong> same environment.
3.1 Holons
The concept <strong>of</strong> Ba as it is defined by Nonaka & Konno includes a series <strong>of</strong> characteristics for <strong>the</strong>
systems which are considered in <strong>the</strong> chaos <strong>the</strong>ory. First <strong>of</strong> all, <strong>the</strong> perspective <strong>of</strong> <strong>the</strong> Ba’s included
one into ano<strong>the</strong>r, respects <strong>the</strong> holons <strong>the</strong>ory. Holons are entities that are wholes and parts <strong>of</strong> wholes
in <strong>the</strong> same time (Koestler, in van Eijnatten, 2004: 438). They are structures simultaneously
autonomous and dependent, being characterized as having <strong>the</strong>ir own identity, having <strong>the</strong>ir own status
in a community characterized by self-transcendence, which allows <strong>the</strong> individual development, and
self dissolution, which allows <strong>the</strong>m to split into sub holons.(Wilber, in van Eijnatten, 2004: 438)
Self-transcendence allows a holon to better understand <strong>the</strong> reality it faces, while evolving on <strong>the</strong> scale
<strong>of</strong> knowledge. Thus <strong>the</strong> holonic capacity is <strong>the</strong> ability <strong>of</strong> holons to operate more rationally, with a
superior conscience and with “control and response-ability”. The control-ability is <strong>the</strong> degree in which
a holon is capable <strong>of</strong> influencing <strong>the</strong> future events, and <strong>the</strong> response-ability is <strong>the</strong> capacity <strong>of</strong> coping
with <strong>the</strong> conditions “Far From Equilibrium ”.(van Eijnatten, 2004: 438-439) All <strong>the</strong>se elements referring
to <strong>the</strong> holons are true for <strong>the</strong> Ba too.
The growth <strong>of</strong> <strong>the</strong> holonic capacity <strong>of</strong> <strong>the</strong> organization is <strong>the</strong> function fulfilled by <strong>the</strong> knowledge
dynamics system. In order to discover how this process can be done successfully it is necessary to
place ourselves in <strong>the</strong> enlarged Ba <strong>of</strong> <strong>the</strong> organization. Whilst positioning ourselves, we exit <strong>the</strong> logic
<strong>of</strong> <strong>the</strong> central discourse <strong>of</strong> Nonaka and we give birth to a dilemma connected to <strong>the</strong> knowledge
creation system. Can we use as model <strong>the</strong> SECI spiral, after a holonic logic, in which to place teams
instead <strong>of</strong> individuals, and organization’s Ba instead <strong>of</strong> team’s Ba?
Analyzing this situation from every state <strong>of</strong> this cycle, we obtain <strong>the</strong> following arguments:
1. Individual socialization could be replaced by <strong>the</strong> tacit knowledge transfer between groups.
Shared activity <strong>of</strong> various groups is not a valid solution because <strong>the</strong> tacit knowledge is included in
<strong>the</strong> individual, but <strong>the</strong>re are at least 3 possible solutions: moving <strong>the</strong> individuals through various
groups, including <strong>the</strong> individual into various teams, and organizing temporary interdepartmental
teams such as project management teams.
2. For externalization it is necessary to commit <strong>the</strong> individual to <strong>the</strong> group. This commitment
allows <strong>the</strong> knowledge to transcend <strong>the</strong> individual barriers, thus becoming transferable between
individuals. The perspective <strong>of</strong> surpassing <strong>the</strong> barriers <strong>of</strong> <strong>the</strong> group imposes <strong>the</strong> commitment and
trust between groups, possible to accomplish by stimulating <strong>the</strong> collaboration between groups and
between departments.
3. In combination, <strong>the</strong> key aspects are <strong>the</strong> diffusion and systematization <strong>of</strong> knowledge. This
involves capturing knowledge from <strong>the</strong> inside and outside <strong>of</strong> <strong>the</strong> organization. Secondly, this
knowledge must be dissipated in <strong>the</strong> organization by meetings and discussions. Thirdly,
knowledge can be transferred as documents. The manners in which we can do <strong>the</strong> combinations
don’t differ according to <strong>the</strong> positioning at <strong>the</strong> level <strong>of</strong> individual or team.
4. During <strong>the</strong> internalization, <strong>the</strong> key point is <strong>the</strong> individual’s identification <strong>of</strong> explicit knowledge
present in <strong>the</strong> organization, useful for his activity, which he will start applying, thus modifying
some <strong>of</strong> his routines based on <strong>the</strong> tacit knowledge obtained previously. This process leads to new
tacit knowledge, which becomes <strong>the</strong> basis <strong>of</strong> a new SECI cycle, by means <strong>of</strong> <strong>the</strong> transfer provided
by <strong>the</strong> socialization process. Replacing <strong>the</strong> individual with <strong>the</strong> group doesn’t lead to sense
change, so we can state that internalization isn’t affected by <strong>the</strong> proposed view.
3.2 Chaordic system
Secondly, <strong>the</strong> characteristics <strong>of</strong> <strong>the</strong> knowledge dynamics system respect <strong>the</strong> chaordic systems’
definition. Chaordic comes from <strong>the</strong> amalgamation <strong>of</strong> chaos and order, and means:
1. Something simultaneously organized and chaotic
2. Structured in a manner which isn’t dominated by chaos or by order
3. Something existing at <strong>the</strong> boundary between chaos and order.
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Chaordic systems are complex, capable <strong>of</strong> surviving in turbulent conditions, known as “Far From
Equilibrium (FFE)”. A chaordic system is a dynamic and complex arrangement <strong>of</strong> connections
between elements, which form a whole, whose behavior is unpredictable and structured. (Fitzgerald in
van Eijnatten, 2004: 431)
A chaordic system is under <strong>the</strong> influence <strong>of</strong> different attractors. An attractor is a force or a condition
which leads a system to repeating a certain behaviour, in a different manner every time, but within <strong>the</strong>
limits <strong>of</strong> clear boundaries.(Marchall and Zohar, 1997: 580). Although <strong>the</strong>y don’t act as external force,
<strong>the</strong> attractors serve as a magnet, creating an influence area.
Polley defines <strong>the</strong> basin <strong>of</strong> an attractor as <strong>the</strong> region in which an attractor is capable <strong>of</strong> accomplishing
successfully its function as magnet. The bifurcation points show up when a holon placed at <strong>the</strong> edge
<strong>of</strong> an attractor’s field goes under <strong>the</strong> influence <strong>of</strong> ano<strong>the</strong>r attractor (Polley, 1997: 446-447). According
to <strong>the</strong> evolutional direction generated by an attractor, <strong>the</strong>y were classified as seen in <strong>the</strong> table 1. (van
Eijnatten, 2004: 434)
Table 1: Attractor’s classification, based on <strong>the</strong> evolutional direction generated by <strong>the</strong> attractor
Atractor Abbreviation
Equilibrium attractor E
Near to equilibrium attractor NTE
Far from equilibrium attractor FFE
Fatal chaos attractor FC
Bearing in mind <strong>the</strong> concept <strong>of</strong> attractor, <strong>the</strong> chaotic evolution is defined as “A dynamical process
passing from one attractor basin to <strong>the</strong> next in an incessant journey toward <strong>the</strong> ‘edge’ <strong>of</strong> chaos”.(van
Eijnatten, 2004: 434)
There is a question that arises from applying <strong>the</strong> concepts above on <strong>the</strong> example <strong>of</strong> knowledge
dynamics system, question connected to <strong>the</strong> idea <strong>of</strong> attractor: can we state that Ba is a gravitational
field with decreasing force towards its edges? The idea is coherent with <strong>the</strong> need <strong>of</strong> having a center <strong>of</strong>
attraction, which <strong>of</strong>fers identity and integrity to <strong>the</strong> system. If we accept this view, as consequence we
can say that an organization will be <strong>the</strong> less vulnerable to ”strange attractors” which appeared in <strong>the</strong>
environment, <strong>the</strong> more <strong>the</strong> organization can maintain a greater intensity <strong>of</strong> <strong>the</strong> attraction <strong>of</strong> <strong>the</strong> Ba
produced by it, on a broader distance surrounding it. This could be stated in more concrete terms as
<strong>the</strong> tendency <strong>of</strong> involving customers and suppliers in <strong>the</strong> dynamic process <strong>of</strong> knowledge creation, at a
participation level similar to that <strong>of</strong> <strong>the</strong> employees. Only in this way <strong>the</strong> intensity <strong>of</strong> <strong>the</strong> Ba outside <strong>the</strong>
organization can have closer levels to <strong>the</strong> one inside <strong>the</strong> organization.
O<strong>the</strong>r problems that must be cleared up when applying concepts from <strong>the</strong> <strong>the</strong>ory <strong>of</strong> chaos on <strong>the</strong>
dynamic system <strong>of</strong> knowledge creation are non-linearity and <strong>the</strong> relation between this and <strong>the</strong>
attractors’ existence. There are two questions arising from here. The knowledge conversion
processes in <strong>the</strong> SECI cycle, are <strong>the</strong>y linear or non-linear? Can <strong>the</strong> ideas <strong>of</strong> attractors and bifurcation
be included in SECI functioning?
Bearing in mind that <strong>the</strong> real value for <strong>the</strong> organization <strong>of</strong> knowledge created in this dynamic process
isn’t revealed but contextually, <strong>the</strong> only conclusion is that <strong>the</strong> conversion processes are non-linear.
The knowledge is generated in <strong>the</strong> system, and only afterwards tested in order to determine <strong>the</strong>ir
value. The result is a different value for each knowledge, independent from its production manner.
In chaotic systems <strong>the</strong>re are bifurcation points which can cause sudden changes <strong>of</strong> direction,
character or structure, which permanently define <strong>the</strong> system in new and unexpected ways.(van
Eijnatten, 2004: 433) This statement is valid for <strong>the</strong> knowledge dynamics system. Learning processes
lead to new behaviors <strong>of</strong> <strong>the</strong> system, which is defined each time it contacts a new reality which has
impact on <strong>the</strong> system. We can say that <strong>the</strong> system receives impulses for learning each time it
contacts a new attractor. Therefore, <strong>the</strong> appearance <strong>of</strong> sudden changes in <strong>the</strong> system’s state is
possible under <strong>the</strong> impact <strong>of</strong> a new attractor: newly discovered knowledge, whose valuing involves
system changes.
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4. The resilience <strong>of</strong> <strong>the</strong> knowledge dynamics system
Based on <strong>the</strong> study <strong>of</strong> ma<strong>the</strong>matical properties <strong>of</strong> nonlinear evolutionary models it is found that <strong>the</strong>
essential characteristic <strong>of</strong> nonlinear evolutionary models is getting away from continuity.(OuYang and
Lin,1998: 699). However, this is not <strong>the</strong> case <strong>of</strong> self-organized dynamic systems, as <strong>the</strong>y can keep
<strong>the</strong>ir existential continuity by means <strong>of</strong> <strong>the</strong> built-in response mechanisms to <strong>the</strong> non-linear evolutions
<strong>of</strong> <strong>the</strong> environment.
Because <strong>the</strong> chaotic environment is non-linear, small changes in <strong>the</strong> initial statuses can take place,
growing exponentially, creating major shocks on <strong>the</strong> growing and evolution <strong>of</strong> <strong>the</strong> systems. The key
process that characterizes <strong>the</strong> chaotic environments is that <strong>of</strong> <strong>the</strong> appearance and dissapearance <strong>of</strong>
attractors with unpredictable magnitude. In order to survive in this kind <strong>of</strong> environment, <strong>the</strong> evolving
dynamic systems must possess <strong>the</strong> capacity <strong>of</strong> realizing <strong>the</strong> turbulent passing through different
influence areas <strong>of</strong> <strong>the</strong> attractors. The systems must have <strong>the</strong> capacity <strong>of</strong> adsorbing <strong>the</strong> impact <strong>of</strong> <strong>the</strong>
influence areas in <strong>the</strong> environment. They have to be resilient. Resilience is <strong>the</strong> property <strong>of</strong> a material
to absorb energy when it is deformed elastically and <strong>the</strong>n, upon unloading to have this energy
recovered. In o<strong>the</strong>r words, it is <strong>the</strong> maximum energy per unit volume that can be elastically stored.
(Avallone, Baumeister and Sadegh, 2007)
Singularizing this concept at <strong>the</strong> context <strong>of</strong> dynamic creation <strong>of</strong> knowledge, we obtain <strong>the</strong> following:
The resilience <strong>of</strong> <strong>the</strong> knowledge dynamics system is its capacity <strong>of</strong> absorbing adaptive tensions
generated by <strong>the</strong> appearance <strong>of</strong> new attractors in <strong>the</strong> environment, preserving its integrity and
identity, in order to generate new knowledge and behaviors after getting in contact with <strong>the</strong>se
attractors.
The most powerful attractor from <strong>the</strong> system <strong>of</strong> dynamic creation <strong>of</strong> knowledge is <strong>the</strong> Ba <strong>of</strong> groups,
which defines <strong>the</strong> internal space <strong>of</strong> <strong>the</strong> organization. This is <strong>the</strong> gravitational center <strong>of</strong> <strong>the</strong> entire
system, <strong>of</strong>fering to it integrity and identity. In <strong>the</strong> case <strong>of</strong> positioning <strong>the</strong> analysis at <strong>the</strong> level <strong>of</strong> <strong>the</strong> Ba
<strong>of</strong> organizations, <strong>the</strong>re must be taken into account <strong>the</strong> external attractors, created by <strong>the</strong> market. The
appearance <strong>of</strong> a new attractor in a company’s environment will lead to <strong>the</strong> appearance <strong>of</strong> a bifurcation
which can be fatal or can have effects which are exponentially positive. The system is drawn to <strong>the</strong>
edge <strong>of</strong> chaos by major impact <strong>of</strong> <strong>the</strong> attractor in <strong>the</strong> environment, followed by a change in its form or
recovering <strong>of</strong> <strong>the</strong> initial form. If <strong>the</strong> system survives <strong>the</strong> impact with <strong>the</strong> environment, it will change its
behaviour under <strong>the</strong> influence <strong>of</strong> <strong>the</strong> attractor. It will thus learn something new, but this new element
will be limited by <strong>the</strong> tendency <strong>of</strong> maintaining integrity and identity <strong>of</strong> <strong>the</strong> system. The resilience <strong>of</strong> <strong>the</strong>
knowledge dynamics system is connected to <strong>the</strong> tendency <strong>of</strong> maintaining integrity and identity <strong>of</strong> Ba.
The tendency <strong>of</strong> returning to using anterior knowledge is given by <strong>the</strong> force as attractor <strong>of</strong> its “validity”.
The new attractor appeared in <strong>the</strong> environment must have enough force to produce a change in
behaviour. Because <strong>the</strong> observers <strong>of</strong> chaotic systems can most <strong>of</strong> <strong>the</strong> times see <strong>the</strong> change <strong>of</strong>
direction <strong>of</strong> movement without determining <strong>the</strong> cause, <strong>the</strong> term which is mostly used is “strange
attractor”. Knowledge that becomes attractor by causing <strong>the</strong> appearance <strong>of</strong> fields <strong>of</strong> attraction in <strong>the</strong>
environment can be known or unknown in <strong>the</strong> organization.
According to <strong>the</strong> sense and magnitude <strong>of</strong> <strong>the</strong>se attractors, <strong>the</strong> organization will feel some adaptive
pressures. In case <strong>of</strong> E-type attractors or NTE-type, <strong>the</strong> organization will feel a minimum adaptive
pressure. In case <strong>of</strong> FFE-type attractors or FC attractors, <strong>the</strong> organization will focus on <strong>the</strong> margins <strong>of</strong>
<strong>the</strong> chaos, and its resilience will be challenged. More precise, <strong>the</strong>se new attractors are in fact new
knowledge held by an individual on <strong>the</strong> market. They can be ei<strong>the</strong>r knowledge <strong>of</strong> competitors <strong>of</strong>
suppliers, or new behaviors <strong>of</strong> customers, provoked by <strong>the</strong>ir newly accumulated knowledge.
Incremental improvements given by competitors to <strong>the</strong>ir products will represent most certainly E-type
<strong>of</strong> NTE-type attractors, while <strong>the</strong> appearance on <strong>the</strong> market <strong>of</strong> a substitution product based on new
technology will most probably represent a FFE-type attractor or FC-type attractor.
The game <strong>of</strong> double influence generated by <strong>the</strong> main attractor (Ba <strong>of</strong> teams) and an external attractor
<strong>of</strong> <strong>the</strong> organization will have adaptive consequences in <strong>the</strong> knowledge creation system, proportional to
<strong>the</strong> divergence <strong>of</strong> forces and magnitude <strong>of</strong> influence <strong>of</strong> both <strong>the</strong>se. The bigger <strong>the</strong> tension between
<strong>the</strong> two, <strong>the</strong> more difficult <strong>the</strong> adaptive processes will be.
In order to better cope with <strong>the</strong> pressures, <strong>the</strong> organization has to develop its holonic capacity.
Reduction <strong>of</strong> <strong>the</strong>se pressures must be made by extending Ba as much as possible in <strong>the</strong>
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environment, in order to make <strong>the</strong> Ba <strong>of</strong> <strong>the</strong> organization an important attractor in <strong>the</strong> environment <strong>of</strong>
<strong>the</strong> organization. This is <strong>the</strong> strategy that <strong>the</strong> innovative companies adopt to impose to <strong>the</strong> followers
rhythm <strong>of</strong> evolution on <strong>the</strong> market. Hamel and Prahalad state that <strong>the</strong> focus <strong>of</strong> <strong>the</strong> strategic process
must be that <strong>of</strong> transforming <strong>the</strong> industry, and not that <strong>of</strong> transforming <strong>the</strong> organization.(Hamel and
Prahalad, in Bechtold, 1997: 196) The organization must <strong>the</strong>refore improve its ”control-ability”, in
order to be able to ra<strong>the</strong>r control <strong>the</strong> environment than <strong>the</strong> o<strong>the</strong>r way round. Ano<strong>the</strong>r solution,
connected to <strong>the</strong> improvement <strong>of</strong> “response-ability” is <strong>the</strong> opening <strong>of</strong> organization in order to let <strong>the</strong>
influences <strong>of</strong> <strong>the</strong> attractors in <strong>the</strong> environment manifest inside, allowing <strong>the</strong> development <strong>of</strong> <strong>the</strong> early
warning systems. Early Warning systems are similar to boxes <strong>of</strong> acoustic resonance, created to
maximize <strong>the</strong> impact <strong>of</strong> <strong>the</strong> external attractors. They are based on <strong>the</strong> maximisation <strong>of</strong> <strong>the</strong> information
and environmental knowledge circulation speed, so <strong>the</strong>y lead to <strong>the</strong> solution <strong>of</strong> beeing instantly
informed by acting simultaneously with <strong>the</strong> environment.
Both solutions mean an orientation towards accepting in <strong>the</strong> SECI cycle <strong>of</strong> as much as possible
contributors. Brigid L. Bechtold affirms that <strong>the</strong> chaos <strong>the</strong>ory imposes a process <strong>of</strong> continuous
strategic development, which involves all members <strong>of</strong> <strong>the</strong> organization and customers and suppliers.
In her opinion, <strong>the</strong> strategic planning should become a continuous process because <strong>the</strong> changes in
<strong>the</strong> environment will need strategic repositioning most frequently. Involving all members <strong>of</strong> <strong>the</strong>
organization will lead to growth in <strong>the</strong> knowledge <strong>of</strong> organizations, and to its better matching to <strong>the</strong>
environment.(Bechtold, 1997: 196)
5. Crises
Passing from an area <strong>of</strong> E-type or NTE-type factors in a FFE-type or FC-type factors area, will be <strong>the</strong>
element that produces <strong>the</strong> maximum possible pressure. This passing is characteristic for <strong>the</strong>
appearance <strong>of</strong> crises. An organizational crisis is a low-probability, high-impact event that threatens <strong>the</strong>
viability <strong>of</strong> <strong>the</strong> organization and is characterized by ambiguity <strong>of</strong> cause, effect, and means <strong>of</strong>
resolution, as well as by a belief that decisions must be made swiftly (Pearson and Clair, 1998, p. 60)
The description <strong>of</strong> <strong>the</strong> organization’s crisis involves <strong>the</strong> need for resilience <strong>of</strong> <strong>the</strong> organization, and in
particular <strong>the</strong> resilience <strong>of</strong> <strong>the</strong> knowledge creation system, in chaotic contexts. Pearson and Clair
claim that ”Effective crisis planning aims at identifying <strong>the</strong> early warning signals for <strong>the</strong> crisis. The
chronic crisis stage is sometimes called <strong>the</strong> “clean-up” stage <strong>of</strong> a crisis situation, when <strong>the</strong>
organization tries to recover from <strong>the</strong> crisis, identify its vulnerabilities and learn from <strong>the</strong> failures and
successes <strong>of</strong> its response. The crisis resolution stage is when <strong>the</strong> organization comes back to
normality and resumes full functionality”. Identifying early signals is essential when <strong>the</strong>ir evolution is
non-linear, learning from crisis is essential for <strong>the</strong> implementing future changes and <strong>the</strong> final point is
returning to a new functional state.
6. Using knowledge
Using tacit knowledge under <strong>the</strong> conditions <strong>of</strong> change in <strong>the</strong> evolutional direction <strong>of</strong> <strong>the</strong> system
caused by <strong>the</strong> influence <strong>of</strong> a new attractor will have to start from testing new contexts and states
through which a system will need to pass, in order to determine <strong>the</strong> new tacit knowledge, relevant for
new contexts. Mobilizing <strong>the</strong> tacit knowledge will have to be done starting from <strong>the</strong> zones <strong>of</strong> tacit
knowledge explored and validated, but unused in previous contexts, because <strong>of</strong> <strong>the</strong>ir inadequation to
those contexts. A significant strength <strong>of</strong> tacit knowledge is in its efficiency and efficacy as internal
patterns are combined with incoming information to develop situation-focused responses that are
context sensitive. (Bennet and Bennet, 2008: 88)
The idea <strong>of</strong> accumulating knowledge through socializing experiences is <strong>the</strong> best way to produce <strong>the</strong>
activation <strong>of</strong> new tacit knowledge accumulated in <strong>the</strong> past. The characteristic <strong>of</strong> chaotic systems to
repeat a certain behavior each time in a different form leads to <strong>the</strong> idea <strong>of</strong> developing tacit knowledge
and not explicit knowledge. This latter statement is supported by <strong>the</strong> necessity <strong>of</strong> relating to a context
which makes sense, when defining knowledge. Explicit knowledge is transferable between individuals,
but hardly transferable in o<strong>the</strong>r contexts, while <strong>the</strong> tacit knowledge is difficult to transfer between
individuals, but easily transferable in o<strong>the</strong>r contexts.
The role <strong>of</strong> potentially useful knowledge becomes very important in <strong>the</strong> context <strong>of</strong> chaotic
environment. Be it tacit or explicit, knowledge already accumulated when <strong>the</strong> new attractor manifests
will allow tension reduction and thus risk reduction towards <strong>the</strong> integrity and identity <strong>of</strong> <strong>the</strong> system, or
else rapid adaptation <strong>of</strong> its behavior. We recommend previous exploration <strong>of</strong> marginal evolutions <strong>of</strong>
<strong>the</strong> environment which could in fact be early signals <strong>of</strong> future development <strong>of</strong> a new attractor in <strong>the</strong>
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Andrei Stefan Nestian
environment. The direct contact with <strong>the</strong>se realities, which have a strange character in <strong>the</strong>
environment, is highly recommended in order to differ between accidental evolutions and early signals
<strong>of</strong> <strong>the</strong> appearance <strong>of</strong> a strange attractor.
7. Conclusions
In chaotic environments, organizations act as holons, <strong>the</strong>ir evolution being influenced by <strong>the</strong>
appearance <strong>of</strong> attractors in <strong>the</strong> environment. The knowledge dynamics system in its turn is a holon.
The key process which characterizes <strong>the</strong> chaotic environments is that <strong>of</strong> <strong>the</strong> appearance and
disappearance <strong>of</strong> attractors with a magnitude which cannot be predicted. In order to survive in this
medium, <strong>the</strong>se evolutional dynamic systems must possess <strong>the</strong> ability to successfully accomplish <strong>the</strong>
passing through different areas <strong>of</strong> influence <strong>of</strong> <strong>the</strong> attractors. The easy passing through can be
defined as maintaining <strong>the</strong> integrity and identity <strong>of</strong> <strong>the</strong> system, on <strong>the</strong> basis <strong>of</strong> its adaptation to <strong>the</strong>
attractors’ influence.
The function that <strong>the</strong> knowledge dynamics system has is <strong>the</strong> development <strong>of</strong> <strong>the</strong> holonic capacity <strong>of</strong>
<strong>the</strong> organization. An organization will be <strong>the</strong> less vulnerable to ”strange attractors” which appeared in
<strong>the</strong> environment, <strong>the</strong> more it can maintain on a broader distance surrounding it a higher intensity <strong>of</strong>
<strong>the</strong> attraction <strong>of</strong> <strong>the</strong> Ba produced <strong>of</strong> <strong>the</strong> organization itself. More precisely, this is viewed as two
tendencies: to influence <strong>the</strong> market, and not to be influenced by it, respectively involving <strong>the</strong>
customers and suppliers in <strong>the</strong> dynamic process <strong>of</strong> knowledge creation at a level similar to that <strong>of</strong> <strong>the</strong>
employees.
The resilience <strong>of</strong> <strong>the</strong> knowledge dynamics system is its capacity <strong>of</strong> absorbing adaptive tensions
generated by <strong>the</strong> appearance <strong>of</strong> new attractors in <strong>the</strong> environment, preserving its integrity and
identity, in order to generate new knowledge and behaviors after getting in contact with <strong>the</strong>se
attractors.
Because <strong>the</strong> change in <strong>the</strong> way <strong>of</strong> thinking and behaving <strong>of</strong> <strong>the</strong> system takes place due to <strong>the</strong> passing
<strong>of</strong> <strong>the</strong> system through <strong>the</strong> areas <strong>of</strong> new attractors, we can state that new knowledge production is
related to <strong>the</strong> contact with new attractors. They represent development factors, so <strong>the</strong> rhythm <strong>of</strong>
knowledge production will be influenced by <strong>the</strong> appearance <strong>of</strong> new attractors.
In chaotic environments <strong>the</strong> main role in survival and adaptation is held by tacit knowledge because
<strong>the</strong>y are more easily transferable in new contexts.
References
Avallone, E., Baumeister, Th., Sadegh, A. (2007) Marks' Standard Handbook for Mechanical Engineers 11 th
Edition, Mc-Graw Hill, New York.
Bechtold, B. (1997) ‘Chaos <strong>the</strong>ory as a model for strategy development’, Empowerment in Organizations, vol. 5,
no. 4, pp. 193-201.
Bennet, D., Bennet, A. (2008) ‘Engaging tacit knowledge in support <strong>of</strong> organizational learning’, VINE, vol. 38, no.
1, pp.72 – 94.
Bratianu, C. (2010) ‘A Critical Analysis <strong>of</strong> Nonaka‟s Model <strong>of</strong> Knowledge Dynamics’, Electronic Journal <strong>of</strong>
Knowledge Management, vol. 8, no. 2, pp. 193 – 200.
Chen, C. (2008) ‘Linking <strong>the</strong> knowledge creation process to organizational <strong>the</strong>ories. A macro view <strong>of</strong>
organization-environment change’, Journal <strong>of</strong> Organizational Change Management, vol. 21, no. 3, pp. 259-
279.
van Eijnatten, F.(2004) ‘Chaordic systems thinking. Some suggestions for a complexity framework to inform a
learning organization’, The Learning Organization, vol. 11, no. 6, pp. 430-449.
Fitzgerald, L., (2002) ‘Chaos: <strong>the</strong> lens that transcends’, Journal <strong>of</strong> Organizational Change Management, vol. 15,
no. 4, pp.339 – 358.
Fitzgerald, L., van Eijnatten, F. (2002) ‘Chaos speak: a glossary <strong>of</strong> chaordic terms and phrases’, Journal <strong>of</strong>
Organizational Change Management, vol. 15, no. 4, pp.412 – 423.
Nonaka, I., Konno, N. (1998) ‘The concept <strong>of</strong> „Ba‟: building a foundation for knowledge creation’, California
Management Review, vol.40, no.3, Spring, pp.40-54.
Marchall, I., Zohar, D. (1997), Who’s Afraid <strong>of</strong> Schrodinger’s Cat? The New Science Revealed:
Quantum Theory, Relativity, Chaos and <strong>the</strong> New Cosmology, Bloomsbury, London.
OuYang, S., Lin, Y. (1998) ‘Some problems on “classical chaos’, Kybernetes, vol. 27, no. 6/7, pp. 691 – 700.
Pearson, C.M., Clair, J.A. (1998), ‘Reframing crisis management’, Academy <strong>of</strong> Management Review, vol. 23, no.
1, pp. 59-76.
Polley, D. (1997), ‘Turbulence in organizations: new metaphors for organizational research’, Organization
Science, vol. 8, no. 5, pp. 445-57.
301

Increasing Knowledge Management Maturity in
Organisations: A Capabilities - Driven Model
Theodora Ngosi 1 , Markus Helfert 2 and Ashley Braganza 3
1
National University <strong>of</strong> Ireland, Maynooth, County Kildare, Ireland
2
Dublin City University, Ireland
3
Brunel University, Uxbridge, UK
Theodora.Ngosi@nuim.ie
markus.helfert@computing.dcu.ie
ashley.braganza@brunel.ac.uk
Abstract: Recent surveys conducted by academic researchers and industry practitioners suggest that
organisations still struggle to adopt knowledge management (KM). Success <strong>of</strong> KM initiatives is hampered by
several factors, for example: limited understanding <strong>of</strong> KM concepts. In this paper we argue that inadequate KM
maturity models undermine KM success. Maturity encourages clarity <strong>of</strong> epistemological assumptions and
judgements to plan and control <strong>the</strong> KM activities. This paper discusses how organisations investing in KM
initiatives can increase KM maturity to develop knowledge assets and to maximise <strong>the</strong> use <strong>of</strong> knowledge that
adds value in various functions. The features and limitations <strong>of</strong> use <strong>of</strong> selected extant maturity models applied in
KM are examined. The paper makes two key contributions to <strong>the</strong> KM field. One, it introduces <strong>the</strong> Information
Technology-Capability Maturity Framework (IT-CMF) as a means <strong>of</strong> mapping KM maturity. Two, <strong>the</strong> paper
develops a capability-driven KM maturity model, based on <strong>the</strong> IT-CMF. Drawing upon <strong>the</strong> dominating qualities <strong>of</strong>
this model, one implication for practice is to develop different viewpoints <strong>of</strong> capabilities for KM initiatives. The
paper concludes by providing explanations <strong>of</strong> increasing KM maturity, based on an interpretive lens.
Keywords: knowledge management, maturity models, knowledge management capabilities, information
technology-capability maturity framework
1. Introduction
The rise <strong>of</strong> <strong>the</strong> knowledge economy over <strong>the</strong> past two decades has propelled organisations to drive
for ready access to knowledge for increased growth performance and improving efficiency,
effectiveness, innovation, and production (Al-Ali, 2003; OECD, 2005). Approximately 80% <strong>of</strong> large
companies have a formal knowledge management (KM) program (Skyrme, 2002; Mertins et al.,
2010). A KM spending report also indicates that, in <strong>the</strong> United States companies were expected to
spend at least $US85 billion on KM in 2008, an increase <strong>of</strong> nearly 16% from 2007 (AMR Research,
2007).
Knowledge is considered <strong>the</strong> key strategic factor <strong>of</strong> competitive advantage (Darroch & McNaughton,
2002; Ferrari & Toledo, 2004), and <strong>the</strong> main source for value creation (Earl, 2001). Moreover, many
organisations are beginning to grasp <strong>the</strong> overlaps <strong>of</strong> this knowledge market-based paradigm with
intellectual capital (Marr & Ross, 2005). Various scholarly works (such as Al-Ali, 2003; Cheng et al.,
2005; Maditinos et al., 2011; Sullivan, 2000) have some agreement that intellectual capital is <strong>the</strong>
knowledge, applied experience, enterprise processes and technology customer relationships,
products and pr<strong>of</strong>essional skills which are valuable assets to an organisation. The big differences
between knowledge assets and intellectual capital <strong>of</strong>ten exist between a company's market value and
its book value. In this paper, we make a case for increasing KM maturity. We content that, primarily
an organisation needs to mature its knowledge capabilities and measure knowledge assets in order to
determine intellectual capital, and how it can focus on <strong>the</strong> exploitation <strong>of</strong> its market value.
Here, we outline <strong>the</strong> concepts underpinning KM and insights. The ‘<strong>European</strong> Guide for Good Practice
in Knowledge Management’ defines KM as a planned and ongoing management <strong>of</strong> activities and
processes for leveraging knowledge to enhance competitiveness through better use and creation <strong>of</strong>
individual and collective knowledge resources (CEN, 2004: 11). Key principles that facilitate
knowledge activities include creating, organising and capturing potentially useful knowledge to
achieve maximum usage in performance (King, 2007; Wiig, 1997).
As <strong>the</strong> focus on <strong>the</strong> use <strong>of</strong> knowledge in organisations becomes increasingly strategic, insights from
empirical surveys indicate that many organisations are still struggling with <strong>the</strong>ir KM efforts (Braganza
& Möllenkramer, 2002). Amongst <strong>the</strong>se we include <strong>the</strong> KPMG survey conducted on <strong>the</strong> top 500
organisations in <strong>the</strong> <strong>European</strong> Union (KPMG, 2003). The results <strong>of</strong> this survey suggest that KM is
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Theodora Ngosi et al.
applied in virtually every business unit and function: such as, distribution channels, human resources,
marketing, service delivery, procurement, and research and development. However, 78% <strong>of</strong> <strong>the</strong>
respondents <strong>of</strong> this survey believe that <strong>the</strong>y are currently missing out on business opportunities by
failing to successfully implement KM, and to exploit available knowledge (KPMG, 2003). In ano<strong>the</strong>r
set <strong>of</strong> surveys and case studies conducted by Bain & Company (2001) and Mertins et al. (2010), <strong>the</strong>
results show that many organisations underestimate <strong>the</strong> complexity <strong>of</strong> <strong>the</strong>ir KM programs. Many socalled
KM programs are discarded as failed attempts because <strong>of</strong> <strong>the</strong> cost; size, complexity, <strong>the</strong>
entwined organisational issues, and <strong>the</strong>ir relationship to performance (cf. Storey & Barnett, 2000).
On <strong>the</strong> basis <strong>of</strong> <strong>the</strong>se insights this paper argues that, <strong>the</strong> lack <strong>of</strong> KM maturity models undermines <strong>the</strong>
success <strong>of</strong> KM programs. The paper proposes <strong>the</strong> opportunity for increasing KM maturity in
organisations by proposing a capability-driven model. We apply <strong>the</strong> Information Technology-
Capability Maturity Framework (IT-CMF) to map KM maturity levels, and to define KM capabilities
transformation activities to increase KM maturity. In contrast to prominent KM maturity models we
describe in this paper, <strong>the</strong> IT-CMF represents an emerging ‘blueprint’ for business IT management
covering IT activities, capability processes and improvement <strong>of</strong> business value. This framework can
be applied as an assessment tool as well as a management system to help improvement <strong>of</strong> an
organisation’s IT capability through incremental maturity levels, over time (cf. Curley, 2004).
This paper has five sections, and begins in Section 2 by describing <strong>the</strong> concept <strong>of</strong> maturity. Five KM
maturity models selected from <strong>the</strong> literatures are reviewed in order to highlight dominating qualities <strong>of</strong>
<strong>the</strong> models, and <strong>the</strong>ir limiting effect on KM programs. Section 3 introduces <strong>the</strong> IT-CMF that might help
us to understand <strong>the</strong> concept <strong>of</strong> increasing KM maturity and capability. Section 4 describes a
conceptual model that we put forward as our proposal for a capability-driven KM maturity model.
Section 5 provides a discussion that also draws upon <strong>the</strong> implications for practice <strong>of</strong> this model. The
paper concludes with a summary <strong>of</strong> work aimed to extend this conceptual model. The proposed
conceptual KM maturity model is a key contribution for developing both a business capability-oriented
focus in KM. We bridge <strong>the</strong> gap in knowledge by using this model to explain how organisations can
increase KM maturity and capability in an integrated way.
2. Literature review
2.1 The concept <strong>of</strong> maturity
Maturity is a concept that has been covered in different subject areas such as electronic data
processing (Nolan, 1979), lean enterprise transformation (Nightingale & Mize 2002), organisations
(Greiner, 1972), project management (Cooke-Davies, 2005), and s<strong>of</strong>tware process improvement
(Humphrey, 1989). Maturity is considered an evaluative and comparative instrument. Organisations
judge <strong>the</strong>ir maturity position that gives <strong>the</strong> current reality <strong>of</strong> its performance. This maturity position is
<strong>the</strong> most appropriate starting point from which to develop systematic actions toward improvement, in
a consistent and insightful way.
Moreover, <strong>the</strong> assessment <strong>of</strong> each level is based on comprehensive set <strong>of</strong> criteria comprising
concept, function, behaviour aspects for observation, requirements to be met, and measurement
(Humphrey, 1989). In turn, each level is treated more or less as a rigid ‘entity’, because measurement
is carried out at a single point in time, from which classifications <strong>of</strong> collected data are collected for
analysis, reflection and syn<strong>the</strong>sis. Measurement <strong>of</strong> both quantitative and qualitative factors includes: a
defined process for building <strong>the</strong> outcomes from each level to monitor progress, and to take corrective
actions at each level when necessary. The measures <strong>the</strong>mselves, <strong>the</strong> boundaries within which data is
collected from each maturity level are analysed to define corrective actions.
Maturity evolves <strong>the</strong>n, through a progression <strong>of</strong> levels or stages with transformations over time.
Maturity will correlate to an organisation’s measure <strong>of</strong> <strong>the</strong> degree <strong>of</strong> progress accomplished across
applicable contexts <strong>of</strong> a maturity level, at a particular time and adjudged to performance (cf. Cooke-
Davies, 2005). With regards to KM, increasing maturity means an organisation creates an
environment in which predictability <strong>of</strong> KM activities is high and risk is low (cf. Humphrey, 1989). An
organisation with full maturity has in place <strong>the</strong> KM practices, <strong>the</strong> discipline that allows knowledge
capabilities to be developed and to move on to <strong>the</strong> exploitation <strong>of</strong> measured knowledge assets that
are <strong>of</strong> value.
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Theodora Ngosi et al.
2.2 Dominating qualities <strong>of</strong> selected KM maturity models
A review <strong>of</strong> <strong>the</strong> literature identified approximately fifteen KM maturity models commonly known as
KMMM (Gottschalk & Khandelwal, 2004). The majority <strong>of</strong> <strong>the</strong>se models apply well-established
concepts from <strong>the</strong> S<strong>of</strong>tware Engineering Institute Capability Maturity Model (CMM). The CMM
describes maturity through five levels, namely initial, repeated, defined, managed, and optimising
(Humphrey, 1989).
In this review, we summarise five selected KM maturity models depicted in Table 1. There are two
main categorises. The first category is <strong>the</strong> practice-based models which as are: Infosys Technologies
(Kochikar, 2000; 2008), Siemens (Ehms & Langen, 2002) and Skyrme Associates (2002). The second
category is <strong>the</strong> empirical: KM Maturity Pyramid Model (Hung & Chou, 2005) and Step Maturity
Roadmap (Robinson et al., 2006). These two models were developed through empirical case study
approaches. The applicability <strong>of</strong> <strong>the</strong> Pyramid Model has been evaluated through a case study
approach to KM practices. Next, we apply scope and content to frame <strong>the</strong> broader issues that <strong>the</strong>se
models address.
Table1: Summary <strong>of</strong> KM maturity models
Low maturity High maturity
Infosys
Siemens
Level 1 Level 2 Level 3 Level 4 Level 5
DEFAULT REACTION AWARE CONVINCED SHARING
Undefined Basic
repeatability
INITIAL REPEATABL
E
Processes
not planned
or controlled
KM pilot
projects
Restricted
data-driven
decision
making
Quantitative
decision
making
Strong return on
investment
DEFINED MANAGED OPTIMISING
Stable &
practiced KM
activities
Common
strategy &
standardised
approaches to
KM
KM adaptable to
new conditions
Level 6
Skyrme
Associates
AD HOC
KM practised
FORMAL
KM formal
EXPANDING
KM grows in
COHESIVE
Coordination
INTEGRATED
Formal
EMBEDDED
KM blends
to some level projects practice <strong>of</strong> KM activity standards & seamlessly
across <strong>the</strong> & knowledge approaches in daily
organisation sharing
activities
KMMM
Pyramid
Model
Steps
Maturity
Roadmap
INITIAL REPEATABL
E
Processes
not
consciously
controlled
Importance
<strong>of</strong> KM is
recognised
DEFINED MANAGED OPTIMISING
Stable &
practiced KM
activities
Indicators to
<strong>the</strong> efficiency <strong>of</strong>
robust KM
activities
Regular
measures
Strategic control
<strong>of</strong> KM through
measurement
START-UP TAKE-OFF EXPANSION PROGRESSIVE SUSTAINABILITY
Increasing
awareness <strong>of</strong>
benefits for
business
improvement
Developmen
t <strong>of</strong> KM
strategy
Visibility <strong>of</strong>
leadership
Change
management
304
Measurement
improves
performance <strong>of</strong>
KM activities
Sustaining <strong>the</strong>
performance <strong>of</strong>
KM activities

Theodora Ngosi et al.
The scope <strong>of</strong> <strong>the</strong> five models is based on a holistic view underpinning a maturity approach. This view
considers multi-dimensional elements that complement each o<strong>the</strong>r in explaining KM activities,
evolving contexts, and relationships between <strong>the</strong>m (cf. Mentzas et al., 2001). For instance, a KM
program can include a knowledge life cycle and its associated activities for creating, capturing and
maintaining <strong>the</strong> organisation’s knowledge assets. Strategy, people and skills, processes, methods,
technology and its application in KM activities blend seamlessly in this holistic view (Skyrme, 1999).
The content <strong>of</strong> <strong>the</strong> five models comprises <strong>the</strong> following dimensions:
The general objective is to present maturity based on a more or less comprehensive set <strong>of</strong>
criteria.
Level 1, based on some assessment method indicates <strong>the</strong> current status <strong>of</strong> KM in <strong>the</strong>
organisation, and this shows <strong>the</strong> most appropriate starting point before a KM project begins
(Ehms & Langen, 2002).
Depending on <strong>the</strong> results <strong>of</strong> <strong>the</strong> assessment, maturity progresses through five to six levels, with
different organisational contexts, from <strong>the</strong> lower to higher levels.
As shown in Table 1, <strong>the</strong> maturity features <strong>of</strong> each model are populated at relevant levels.
2.3 Limitations <strong>of</strong> selected KM maturity models
Drawing from reviewed literatures we have identified <strong>the</strong> main limitations <strong>of</strong> <strong>the</strong> five models as
assessment, measurement, capabilities, and best practices.
The five models make an assumption that Level 1 is <strong>the</strong> staring point. Whereas an initial assessment
is a requisite to capture a maturity posture: where <strong>the</strong> organisation is at a given point in time (cf.
Curley, 2004; Braganza, Hackney et al., 2009). The Pyramid Model (Hung & Chou, 2005) is <strong>the</strong>
exception. It provides a detailed six-phase procedural assessment. However, it is difficult to verify that
this assessment can be aligned with <strong>the</strong> maturity levels in <strong>the</strong> deployment <strong>of</strong> KM activities.
All five models have <strong>the</strong> same conclusion that progression through <strong>the</strong> maturity levels implies
‘something’ is being measured’; <strong>the</strong> measurement is not emphasised to capture relevant knowledge,
take problem-solving actions or to verify success at each maturity level. Maturity levels correspond to
capability which has significant consequences on <strong>the</strong> organisation to manage different elements (such
as processes, people, and technology), and to achieve <strong>the</strong> desired performance improvements.
However, <strong>the</strong>se models are limited in providing guidelines on capabilities in KM and how to improve
maturity levels. In this regard <strong>the</strong> models also neglect best practices (Kerzner, 2006) as a core
concept for KM maturity.
3. Overview <strong>of</strong> IT-CMF
In this section we describe <strong>the</strong> IT-CMF. This framework is designed as a systematic framework that
enables senior chief executives to interrogate, understand and improve an organisation’s maturity,
ensuring realisation <strong>of</strong> IT capabilities and optimal delivery <strong>of</strong> business value from IT investments (cf.
Curley 2004, 2007). The choice for using IT-CMF is based on its ability to apply a holistic approach
that brings toge<strong>the</strong>r a fascinating complement <strong>of</strong> business and IT activities. The structure <strong>of</strong> <strong>the</strong> IT-
CMF depicted in Figure 1 comprises three integrative layers: strategy, macro and micro.
[1] The strategy layer underpins <strong>the</strong> primary elements <strong>of</strong> IT-CMF. These are business context;
business strategy; IT capability; business operations; and, business value (Curley, 2007). The
connection between <strong>the</strong>m is that: in <strong>the</strong> business context, an organisation’s IT posture centres
attention on <strong>the</strong> meaning in <strong>the</strong> relationships between <strong>the</strong> business vision matched to <strong>the</strong>
business strategy; business operations, to include IT capabilities <strong>the</strong> might bring opportunities for
business success. The IT strategy follows from business strategy, for <strong>the</strong> delivery <strong>of</strong> business
value on its strategy.
[2] The macro layer characterises both <strong>the</strong> content and context <strong>of</strong> application <strong>of</strong> IT-CMF. The
content embraces four macro-processes (MPs) that underpin value-oriented IT management,
namely: Managing IT like a business, Manage <strong>the</strong> IT budget, Managing <strong>the</strong> IT capability and
Manage IT for business value.
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Figure 1: Delineation <strong>of</strong> IT-CMF Meta-elements (source: adapted from <strong>the</strong> Innovation Value Institute)
[3] The micro-layer comprises 32 critical processes (CPs) assigned to <strong>the</strong> four <strong>the</strong> MPs. Each CP
adjuncts capability building blocks (CBBs) to capture <strong>the</strong> content <strong>of</strong> <strong>the</strong> CPs and <strong>the</strong> assumptions
underpinning five incremental maturity levels. These are initial, basic, intermediate, advanced and
optimised (Curley 2004, 2007). Measurement is orchestrated at each maturity level.
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4. Conceptual KM maturity model
Theodora Ngosi et al.
4.1 Meta-elements <strong>of</strong> <strong>the</strong> KM maturity model
In this section we propose a conceptual model aimed at increasing KM maturity and capability in
organisations. This model applies <strong>the</strong> meta-elements <strong>of</strong> <strong>the</strong> IT-CMF, namely: <strong>the</strong> MP for ‘Managing
<strong>the</strong> IT Capability’, <strong>the</strong> maturity levels and CBBs described earlier. This MP ensures that we retain our
focus on <strong>the</strong> association between business strategy, IT and KM in a much broader sense that
addresses KM capabilities. In brief, IT capability is defined as <strong>the</strong> ability to mobilise and deploy ITbased
resources (such as hardware, s<strong>of</strong>tware and services) in combination with o<strong>the</strong>r resources
(such as people, skills, IT infrastructure) and capabilities all embedded in processes and business
routines (Bharadwaj, 2000). Organisation capabilities address, among o<strong>the</strong>r factors, business
leadership, operational efficiency, and performance improvements to successfully create effective
strategies for business or value (cf. Overby et al 2006; Ulrich & Smallwood, 2004).
4.2 Structure and qualities <strong>of</strong> <strong>the</strong> conceptual KM maturity model
The proposed model depicted in Figure 2 pr<strong>of</strong>iles two views: The static view representing <strong>the</strong>
structure <strong>of</strong> KM maturity in five maturity levels <strong>of</strong> <strong>the</strong> IT-CMF. The dynamic view addressing <strong>the</strong> CBBs
that articulate <strong>the</strong> scope <strong>of</strong> each maturity level including its dominant qualities <strong>of</strong> maturity and
example capabilities, from one level to <strong>the</strong> next (see Table 2).
Level 1-Initial
In this level, we focus on <strong>the</strong> CBBs formal plans driven by a definition <strong>of</strong> <strong>the</strong> organisation’s maturity
posture. The organisation can use <strong>the</strong> IT-CMF comprehensive self-assessment questionnaire tailored
to capture a maturity posture against any <strong>of</strong> <strong>the</strong> four MPs described earlier. In our view, this
assessment is a prerequisite for <strong>the</strong> planning process for <strong>the</strong> KM effort. A detailed assessment may
take four to six weeks (Agerback & Deutscher, 2010) requiring <strong>the</strong> organisation not only to assesses
its practices, but also that it understands <strong>the</strong> implications <strong>of</strong> its maturity posture against defined KM
issues it aims to develop. The results <strong>of</strong> this assessment help <strong>the</strong> organisation to define formal plans
for <strong>the</strong> KM effort that can include: (a) capabilities needed at appropriate levels <strong>of</strong> maturity; (b) a
strategy and goals that provide a baseline for measuring contributions <strong>of</strong> <strong>the</strong> KM programs (Heisig &
Iske, 2003); and, (c) KM roadmap that can serve as an implementation guideline for individual
programs.
Level 2-Basic
At level-2 we apply <strong>the</strong> CBBs, organisation knowledge culture and implementation <strong>of</strong> KM. The
organisation knowledge culture operates at a deeper level where employees can perform KM
activities (Cooper, 1998). It enables empowerment, trust and respect before employees really start to
engage in creating, sharing and exploiting knowledge and learning (cf. Oliver& Kandadi, 2006). Key
decisions around culture will include assigning skilled roles such as KM directors that can drive <strong>the</strong>
KM effort, manage both <strong>the</strong> KM programs and knowledge assets, and empower employees to adopt a
knowledge culture.
Implementation engages pilot KM programs guided by a life cycle for focusing KM activities. These
programs can help <strong>the</strong> organisation to test <strong>the</strong> viability <strong>of</strong> <strong>the</strong> KM effort, and search for undisclosed
needs. If successful, a long term strategy is defined. The first steps <strong>of</strong> a change management process
are introduced in order to shape <strong>the</strong> organisation’s capabilities that encourage desired behaviours for
KM.
Level 3-Intermediate
At level 3, <strong>the</strong> organisation becomes business-focused to capitalise on its KM efforts. The CBBs that
propel this business focus are integration and measurement. Constructive integration is achieved by
designing a comprehensive KM infrastructure. This becomes <strong>the</strong> central feature in which <strong>the</strong>
organisation can nurture <strong>the</strong> identity <strong>of</strong> its KM activities that can reflect ‘what we stand for’ and ‘how
we work’. At <strong>the</strong> same time, it enhances <strong>the</strong> culture that enables continuous learning and works at
sustaining an organisational memory (CEN, 2004; Drucker, 1999). The infrastructure will include
knowledge processes, communities and governance mechanisms to leverage and exploit knowledge.
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Theodora Ngosi et al.
IT systems, address connectivity for sharing <strong>of</strong> knowledge. It implements phased measurement and
standardised metrics to quantify knowledge, and to that capture benefits that will convince senior
executives, regarding <strong>the</strong> value <strong>of</strong> KM initiatives (see Bose, 2004; CEN, 2004; Fairchild, 2002).
Figure 2: Conceptual KM model for increasing maturity and capabilities
Level 4-Advanced
At this advanced level, KM activities are robust. The CBB management capabilities is appropriate
because it brings toge<strong>the</strong>r <strong>the</strong> holistic complement <strong>of</strong> <strong>the</strong>se factors to also build on <strong>the</strong> KM experience
in order to define <strong>the</strong>ir meaning in subsequent judgements <strong>of</strong> improvement actions. Moreover,
management capability has far-reaching implications on <strong>the</strong> performance <strong>of</strong> <strong>the</strong> organisation. It is <strong>the</strong>
continuous capacity senior executives to develop incisive actions (and new ideas) necessitating <strong>the</strong>
achievement <strong>of</strong> declared goals and implementing innovative changes to house <strong>the</strong> needed
capabilities (Ulrich & Smallwood, 2004). We exemplify three management capabilities and <strong>the</strong>ir
attributes: repository, management <strong>of</strong> KM infrastructure and leadership.
First, is a comprehensive a repository that protects and secures <strong>the</strong> knowledge assets <strong>the</strong>
organisation owns. This repository is a library; it is <strong>the</strong> means to remove uncertainty (Galbraith, 1977;
Daft & Lengel, 1986) related to knowledge processing, needs and consistency. A well-managed
knowledge library can be linked to all employees, and to make <strong>the</strong> knowledge so readily accessible
that it can't be avoided (Davenport & Glaser, 2002).
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Theodora Ngosi et al.
Second, <strong>the</strong> management <strong>of</strong> <strong>the</strong> KM infrastructure aims to address operational excellence.
Importantly, it encourages specialisation <strong>of</strong> KM efforts, creating unique applications <strong>of</strong> knowledge
assets and implementing performance management systems for enhancing employee skills (Kulkarni
& Freeze, 2004).
Third, leadership styles are adapted in specified target areas (NASA, 2004). A capabilities audit can
be conducted, which will show positive KM experience and lessons upon which build tangible
recommendations. Executives can <strong>the</strong>n, develop capability roadmaps anchoring high-level decisions
about strengths and opportunities that can be developed to improve leadership styles.
Level 5-Optimising
In this final level <strong>the</strong> organisation drives long-term continuous improvement as strategic decisions.
The organisation can focus attention on CBBs <strong>of</strong> governance and continuous improvement.
Governance <strong>of</strong> KM is still regarded phenomenon (Zyngier et al., 2004). We adopt <strong>the</strong> IT governance
perspective (Weill & Ross, 2004) that: when <strong>the</strong> organisation has an established KM infrastructure,
governance implies that senior executives understand how <strong>the</strong>y can fulfil <strong>the</strong>ir obligations for
responsible leadership in strategic decisions regarding KM; managing all dimensions <strong>of</strong> KM in relation
to organisation functions, structures and process. Important dimensions that can ground <strong>the</strong> essence
<strong>of</strong> governance and continuous improvement are alignment and best practices.
Continuous improvement is part <strong>of</strong> <strong>the</strong> integrated KAM infrastructure that is supported by a knowledge
policy and knowledge strategy, both <strong>of</strong> which are aligned with <strong>the</strong> overall business strategy. This
alignment ensures compatibility between governance mechanisms, exploitation <strong>of</strong> valued knowledge
assets, and <strong>the</strong> use <strong>of</strong> IT. In line with Chan et al. (2006), alignment leads to more focused and
strategic use <strong>of</strong> key elements such as IT and processes, which in turn, lead to constructive continuous
improvements. Governance mechanisms can be less structured to overcome problems such as
coordination <strong>of</strong> knowledge in different organisation locations. Best practices blend seamlessly in <strong>the</strong>
KM infrastructure to enhance a universal knowledge life cycle. Internal and external benchmarking <strong>of</strong>
best practices assists <strong>the</strong> organisation with <strong>the</strong> development <strong>of</strong> breakthrough performance.
4.3 Increasing maturity
Based on <strong>the</strong> key capabilities identified above and discussions with domain experts we have
developed a guideline and activities for transforming organisations towards a higher KM maturity
level. Key activities to transform an organisation from one maturity level to <strong>the</strong> next are summarised in
Table 2, and can be broadly described with four phases: initiate, expand, incorporate and sustain.
Table 2: Levels for transforming organisations KM maturity
Level Maturity transformations activities
1 to 2
Define key aims <strong>of</strong> KM and a high level KM roadmap.
Identify and priorities a small number <strong>of</strong> subsequent programs.
Initiate
Ensure communication <strong>of</strong> KM aims, challenges and roadmap to all employees.
Develop a detailed KM roadmap and identify major programs.
Assign roles that facilitate <strong>the</strong> effective implementation <strong>of</strong> <strong>the</strong> KM roadmap and
2 to 3
programs.
Develop a knowledge culture through change programs.
Expand
Embed a knowledge life cycle in KM programs, incorporating suitable performance
measures, procedures and standardised evaluation <strong>of</strong> project results.
Develop, implement and manage knowledge repository/library.
Conduct employee surveys, and feedback discussions.
3 to 4
Incorporate
4 to 5
Sustain
Measure and communicate <strong>the</strong> impact <strong>of</strong> KM activities and <strong>the</strong> impact <strong>of</strong> knowledge
assets on business performance.
Define an integrated KM infrastructure.
Maintain, continuously assess and improve KM infrastructure supported with
knowledge policy and knowledge strategy both <strong>of</strong> which are aligned with <strong>the</strong> overall
business strategy.
Ensure regular communication <strong>of</strong> KM activities and benefits.
Embed measures that mature knowledge capabilities; measure knowledge assets. and
determine how to focus on <strong>the</strong> exploitation <strong>of</strong> knowledge and intellectual capital for market
value.
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5. Discussion and summary
Theodora Ngosi et al.
This paper has reviewed five selected KM maturity models. We made <strong>the</strong> judgement that <strong>the</strong>se
models lack <strong>the</strong> specificity to deal with holistic factors that influence maturity. In response, we have
proposed a conceptual model that aims to increase KM maturity in organisations and address
capabilities. The IT-CMF has helped to support <strong>the</strong> attention to <strong>the</strong> dynamic interplay <strong>of</strong> <strong>the</strong>se factors
that influence KM efforts, in particular, given that <strong>the</strong>se factors are not easy to address
methodologically. By using <strong>the</strong> IT-CMF, we have documented our conceptual KM maturity model in
considerable detail that serves to capture <strong>the</strong> meaning <strong>of</strong> <strong>the</strong> achievement <strong>of</strong> maturity.
5.1 Implications for practice
This conceptual KM maturity model has an overarching implication for practice that, it engages <strong>the</strong>
true nature <strong>of</strong> maturity and a holistic perspective that is based on an integrative basis from which
make incisive decisions about KM efforts. It captures some sense <strong>of</strong> <strong>the</strong>se dynamics for increasing
KM maturity, whilst shaping <strong>the</strong> meaning <strong>of</strong> key capabilities for practice.
5.2 Contributions
This paper makes two contributions: One, <strong>the</strong> proposed conceptual KM maturity model is a key
contribution for developing a business capability-driven focus in KM. Two, we bridge <strong>the</strong> gap in
knowledge by using this model to explain how organisations can increase KM maturity and capability
in an integrated way, including suggested recommendations described in Table 2.
5.3 Concluding remarks and future research agenda
Academically, <strong>the</strong>re are still challenges to overcome to develop KM maturity models that embrace <strong>the</strong>
combined perspectives <strong>of</strong> <strong>the</strong> organisation which are deeply embedded in KM efforts. In our future
research work this conceptual KM maturity model should be verified in various companies. The
upcoming stages <strong>of</strong> our research includes a longitudinal pilot studies for companies that have agreed
to operationalise this model to make it possible to clarify its elements.
References
Agerback, A. & Deutscher, S. (2010) Managing IT for Business Value-The Gold Standard, The Boston Consulting
Group, pp. 7-12
Al-Ali, N. (2003) Comprehensive Intellectual capital Management: Step-by-step, Hoboken, NJ: John Wiley &
Sons Inc.
AMR Research (2007) <strong>the</strong> knowledge management spending report 2007-2008.
(http://www.amrresearch.com/Content/View.asp?pmillid=20744)
Bain &Company (2001) Management tools, Boston, MA.
Bharadwaj, A.S (2000) A Resource-Based Perspective on Information Technology Capability and Firm
Performance: An Empirical Investigation, MIS Quarterly, 24(1): 169-196.
Bose, R. (2004) Knowledge management metrics, Industrial Management & Data Systems, 104(6):457-468
Braganza, A., Hackney, R. & Tanudjojo, S. (2009) Organizational knowledge transfer through creation,
mobilization and diffusion: a case analysis <strong>of</strong> InTouch within Schlumberger, Information Systems Journal,
19, 499–522.
Braganza, A. & Möllenkramer, G (2002) Anatomy <strong>of</strong> a failed knowledge management initiative: Lessons from
Pharma Corp's experiences. Knowledge and Process Management 9, 23-33.
Braganza, A. (2004) Rethinking <strong>the</strong> data-information-knowledge hierarchy: towards a case model, International
Journal <strong>of</strong> Information Management, 24(4), 347-356.
CEN Workshop Agreement (2004) <strong>European</strong> Guide to good Practice in Knowledge Management-CWA 14924-
Part 1: Knowledge Management Framework.
Chan, Y.E., Sabherwal, R. and Thatcher, J.B. (2006) Antecedents and Outcomes <strong>of</strong> Strategic IS Alignment: An
empirical investigation, IEEE Transactions on Engineering Management, 51(3): 27–47.
Chen, M.C., Cheng, S.J. and Hwang, Y. (2005) An empirical investigation <strong>of</strong> <strong>the</strong> relationship between intellectual
capital and firms’ market value and financial performance, Journal <strong>of</strong> Intellectual Capital, 6(2): 159-76,
Emerald Group Publishing Ltd.
Cooper, J. R. (1998) A multidimensional approach to <strong>the</strong> adoption <strong>of</strong> innovation, Management Decision, 36(8),
493-502.
Cooke-Davies, T. J. (2001) Towards improved project management practice: Uncovering <strong>the</strong> evidence for
effective practices through empirical research, USA: Dissertation.com.
Curley, M. (2004) The Transformation at Intel, MIS Quarterly Executive, 5(4):109-122.
Curley, M. (2007) Introducing and IT Capability Maturity Framework, International <strong>Conference</strong> on Enterprise
Information Systems.
310

Theodora Ngosi et al.
Daft, R. L. & Lengel, R. H. (1986) Organizational information requirements, media richness and structural design,
Management Science, 32, 554-571.
Darroch, J. & McNaughton, R. (2002) Examining <strong>the</strong> link between knowledge management practices and types <strong>of</strong>
innovation, Journal <strong>of</strong> Intellectual Capital, 3(3), 210-222.
Davenport, T. & Glaser, J. (2002) Just-in-Time Delivery Comes to Knowledge Management, Harvard Business
Review, (pp. 107-11).
Drucker, P. (1999) Beyond <strong>the</strong> Information Revolution, The Atlantic Monthly (October 1999, pp. 47-57).
Earl, M.J. (2001) Knowledge management strategies: towards a taxonomy, Journal <strong>of</strong> Management Information
Systems, 18(1):215-233.
Ehms, K. & Langen, M. (2002) Holistic Development <strong>of</strong> Knowledge Management with KMMM, Siemens
AG/Corporate Technology, Munich (available at:
http://www.knowledgeboard.com/doclibrary/knowledgeboard/kmmm_article_siemens_2002.pdf).
Fairchild, A. M. (2002) Knowledge Management Metrics via a Balanced Scorecard Methodology. In: <strong>Proceedings</strong>
<strong>of</strong> <strong>the</strong> 35th Hawaii International <strong>Conference</strong> on System Sciences, IEEE Computer Society.
Firestone, J. M. & McElroy, M. W. (2005) Doing Knowledge Management, The Learning Organization Journal,
12(2), Emerald Group Publishing, Ltd. (available at
http://www.emeraldinsight.com/10.1108/09696470510583557).
Ferrari, F.M. & de Toledo, J.C. (2004) Analyzing <strong>the</strong> knowledge management through <strong>the</strong> product development
process, Journal <strong>of</strong> Knowledge Management, 8 (1), 117-129.
Galbraith, J. R. (1977) Organization Design. Reading, MA: Addison Wesley.
Gottschalk, P. & Candela, V.K. (2004) Stages <strong>of</strong> growth for knowledge management technology in law firms,
Journal <strong>of</strong> Computer Information Systems, 44(4): 111-124.
Grant, R. M. (1995) Contemporary Strategy Analysis, Oxford, UK: Blackwell Publishers Inc.
Greiner, L. (1972) Evolution and revolution as organizations grow, Harvard Business Review 50(4) In: Hatch M.J.
1997. Organisational Theory: Modern, Symbolic and Postmodern Perspectives (pp. 37-46). Oxford: Oxford
University Press.
Heisig, P. & Iske, P. (2003) <strong>European</strong> knowledge management framework. In: <strong>European</strong> Guide to Good Practice
in Knowledge Management (Work in progress, Draft Version 3.0), Berlin, Ger: CEN/ISSS.
Hung,Y-H. & Chou, S-H, T. (2005) On Constructing a Knowledge Management Pyramid Model, IEEE Computer
Society.
Humphrey, W. S. (1989) Managing <strong>the</strong> S<strong>of</strong>tware Process, Reading, MA: Addison-Wesley.
Kerzner, H. (2006) Project management best practice: achieving global excellence. New Jersey, NJ: John Wiley
& Sons Inc.
King, W. R (2007) Keynote Paper: Knowledge management: a systems perspective, International Journal <strong>of</strong>
Business Systems and Research, (1)1.
KPMG. (2003) KPMG's Knowledge Management Survey 2002/2003.
Kochikar, V. P. (2000) The Knowledge Management Maturity Model- A Staged Framework for Leveraging
Knowledge, The KM World 2000 <strong>Conference</strong> (available at:
http://whitepapers.zdnet.co.uk/0,39025945,60008205p,00.htm).
Kulkarni, U & Freeze R. (2004) Development and Validation <strong>of</strong> a Knowledge Management Capability Assessment
Model. In: <strong>Proceedings</strong> <strong>of</strong> Twenty-Fifth International <strong>Conference</strong> on Information Systems (pp. 657-699).
Maditinos, D., Chatzoudes, D., Tsairidis, C. and Theriou, G. (2011) The impact <strong>of</strong> intellectual capital on firms’
market value and financial performance, Journal <strong>of</strong> Intellectual Capital, 12(1): 132-151, Emerald Group
Publishing Ltd.
Marr, B and Roos, G (2005) A Strategy Perspective on Intellectual Capital, in B. Marr (ed, Perspectives on
Intellectual Capital, Multidisciplinary Insights into management, Measurement, Reporting, Amsterdam:
Elsevier
Mertis, K., Heisig, P and Vorbeck, J. (eds.) (2010) Knowledge Management: Concepts and Best Practices, Berlin,
Ger: Springer-Verlag.
NASA Knowledge Management Team (2004) Strategic Plan for Knowledge Management, National Aeronautics
and Space Administration NASA Publication.
Nolan, R (1979) Managing <strong>the</strong> Crisis in data Processing, Harvard Business Review, 57(2):115-126.
Nightingale, D. J. & Mize, J. H (2002) Development <strong>of</strong> a lean enterprise transformation maturity model,
Information Knowledge Systems Management, 3, 15–30.
Oliver, S. & Kandadi, K.R. (2006) How to develop knowledge culture in organizations? A multiple case study <strong>of</strong>
large distributed organizations, Journal <strong>of</strong> Knowledge Management, 10(4):6–24.
Overby, E., BharadwaJ, A. & Sambamurthy, V. (2006) Enterprise agility and <strong>the</strong> enabling role <strong>of</strong> information
technology, <strong>European</strong> Journal <strong>of</strong> Information Systems 15, 120–131.
Robinson, H.S., Anumba, C. J., Carrillo, P.M. & Al-Ghassani, A.M (2006) STEPS: A Knowledge Management
Maturity Roadmap for Corporate Sustainability, Business Process Management Journal, 12(6): 793-808
Skyrme, D. (1999) Knowledge Management: Building <strong>the</strong> Collaborative Enterprise London, UK: Ovum.
Storey, J. & Barnett E. (2000) Knowledge management initiatives: learning from failure. Journal <strong>of</strong> Knowledge
Management, 4(2): 145–156.
Sullivan, P. H. (2000) Value-driven Intellectual Capital: How to Convert Intangible Corporate Assets into Market
Value, New York, NY: John Wiley & Sons.
Ulrich, D. & Smallwood, N. (2004) Capitalizing on Capabilities, Harvard Business Review (HBR Spotlight, pp. 1-
10).
311

Theodora Ngosi et al.
Weill, P., and Ross, W. J. (2004) IT Governance, how top performers manage IT decisions for superior results,
Harvard Business School Press.
Zyngier, S., Burstein, F., & McKay, J. (2004) Knowledge management governance: A multifaceted approach to
organisational decision and innovation support (available
at:http://vishnu.sims.monash.edu.au:16080/dss2004/proceedings/pdf/87_Zyngier_Burstein_McKay.pdf)
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Strategic Innovation and Knowledge Management: The
Logic <strong>of</strong> Creativity and Development Institutionalization,
Framing and Diffusion
Bongani Ngwenya
Solusi University, Zimbabwe
ngwenyab@solusi.ac.zw
nbongani@gmail.com
Abstract: The purpose <strong>of</strong> this paper is to generate a discussion and suggest a development <strong>of</strong> a framework for
institutionalization <strong>of</strong> strategic innovation and knowledge management by analyzing various research literatures
and data collection through interpretivist research conventions. Strategic innovation involves making knowledge
creation and innovative action a way <strong>of</strong> life, seeking to create and expand markets ra<strong>the</strong>r than just reacting to
customer demand, and redirecting resources from pr<strong>of</strong>itable but dwindling lines <strong>of</strong> business to support emerging
lines that are potentially more pr<strong>of</strong>itable. The researcher explores conceptual links between knowledge
development and management <strong>of</strong> strategic innovation and argues that strategic innovation is <strong>the</strong> purposeful
orchestration <strong>of</strong> knowledge development and creativity. It is found that, while strategic innovation and knowledge
management enhances organizational creativity and development, through resource-based strategy, that is, firmspecific
assets and knowledge, variously referred to as competencies and distinctive capabilities, and is not a
new phenomenon in developed technologies and economies, that have early adopted <strong>the</strong> management practice,
<strong>the</strong> social, political and economic context <strong>of</strong> emerging technologies and economies may not readily
accommodate current strategic innovation and knowledge management frameworks. Drawing on organizational
decision-making research, this research argue that, both early and late adopters respond to framing and
interpreting adoption decision situations as opportunities versus threats. Thus a need to rethink <strong>the</strong> classic
institutional, framing and diffusion paradigm, to suggest models that emerging technologies and economies could
adopt to suit <strong>the</strong>ir social, political and economic context.
Keywords: innovation, knowledge management, creativity ,organizational development, institutionalization,
diffusion
1. Introduction
This paper is based on <strong>the</strong> premise that, strategic innovation and knowledge management are
purposeful orchestration <strong>of</strong> organizational creativity and development within firms, be <strong>the</strong>y in
emerging technologies and economies, or developed ones; a knowledge-based view <strong>of</strong> <strong>the</strong> firm. A
central argument <strong>of</strong> <strong>the</strong> knowledge-based view <strong>of</strong> <strong>the</strong> firm, an extension <strong>of</strong> <strong>the</strong> resources-based view,
is that differences in <strong>the</strong> knowledge bases and innovative capabilities <strong>of</strong> different firms are <strong>the</strong> main
determinants <strong>of</strong> differences in <strong>the</strong>ir performance (Grant, 1996; Kogut and Zander, 1992). Thus <strong>the</strong>
extension <strong>of</strong> <strong>the</strong> resource-based view to include <strong>the</strong> knowledge management-based view, as
suggested in this paper, develops a resource-based strategy paradigm, which emphasizes <strong>the</strong>
importance <strong>of</strong> firm-specific assets and knowledge, variously referred to as core competences,
intellectual property and distinctive capabilities, which can be patented, protected by copyrights laws
and also expressed as trademarks. This perspective on sources <strong>of</strong> competitive advantage is
complemented by knowledge management and learning perspectives on strategic innovation (Pitt and
Clarke, 1999). This paper explores conceptual links between strategic innovation and knowledge
management as a leverage for firm’s potential for creativity and development. Abraham and Knight
(2001), suggest that, top-performing strategic leaders use creativity and innovative action to access
and leverage underlying firm potential. Here, wealth creation depends more and more on leveraging
intangible resources and less and less on <strong>the</strong> tangible resources <strong>of</strong> land, labour, and capital. In this
new environment, performance improvement through deliberate, systematic, and results-oriented
knowledge creation and management, and innovative action provides a ‘meta-strategy,’ which
leverages organizational talent and capabilities and hedges against risks in order to grow and create
new wealth.
The purpose <strong>of</strong> this paper is, however not to define <strong>the</strong> emerging concept <strong>of</strong> strategic innovation and
knowledge management, but to generate a discussion and interest about <strong>the</strong> strategic innovation and
knowledge management models and modalities that may be feasible in <strong>the</strong> emerging technologies
and economies that is, <strong>the</strong> models that will take into account <strong>the</strong> social, political and economic context
<strong>of</strong> <strong>the</strong> emerging economies like Zimbabwe. This paper also extends <strong>the</strong> institutional <strong>the</strong>ory’s account
<strong>of</strong> diffusion by examining <strong>the</strong> interplay between economic and social considerations in adoption
decisions. Drawing on organizational decision-making research, this paper argues that both early and
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late adopters respond to framing and interpreting adoption decision situations as opportunities versus
threats. Thus <strong>the</strong> rationale and motivation for undertaking this research and contributing to <strong>the</strong> body <strong>of</strong>
knowledge <strong>the</strong> rethinking <strong>of</strong> <strong>the</strong> classic institutional, framing and diffusion model, to suggest strategic
innovation and knowledge management model or framework that emerging technologies and
economies like Zimbabwe could adopt to suit <strong>the</strong>ir social, political and economic context.
In <strong>the</strong> order <strong>of</strong> consideration, <strong>the</strong> author first examines some insights from <strong>the</strong> literature and
conceptual framework. Following <strong>the</strong> discussion <strong>of</strong> <strong>the</strong> conceptual framework, a discussion <strong>of</strong> this
empirical investigation <strong>of</strong> framing and interpreting adoption decision situations based on <strong>the</strong>
interpretivist research conventions used in this paper is done. The research methodology is outlined,
followed by <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> data, and discussion. Finally, <strong>the</strong> conclusions are drawn. As a result <strong>of</strong>
this investigation, a strategic innovation and knowledge management framework or model that can be
feasible in <strong>the</strong> emerging technologies and economies, and takes into account <strong>the</strong> social, political and
economic context <strong>of</strong> <strong>the</strong>se emerging technologies and economies could be developed following
fur<strong>the</strong>r research in <strong>the</strong> future.
2. Insights from <strong>the</strong> literature and conceptual framework
Innovation stands out as one excellent objective <strong>of</strong> management activity in general, and knowledge
management specifically (Ruggles and Little, 1997). The two experts in <strong>the</strong>ir research fur<strong>the</strong>r suggest
that, or examine innovation as one end to which knowledge management can be applied. Pimentel
and Campos (2008) suggest that creativity and innovation is <strong>the</strong> key to survival and pr<strong>of</strong>itability in a
rapidly evolving, complex and competitive global business environment. Technology is integral to
virtually every facet <strong>of</strong> business. It plays pivotal role in <strong>the</strong> development, manufacture and delivery <strong>of</strong>
innovative products and services to <strong>the</strong> market. Effective management <strong>of</strong> innovation, product design
and development is important for technology leadership. Thus, <strong>the</strong> alignment <strong>of</strong> intellectual property
strategy with innovation and business strategy is challenging and yet critical for bottom line growth.
Knowledge management comprises a range <strong>of</strong> strategies and practices used in an organization to
identify, create, represent, distribute, and enable adoption <strong>of</strong> insights and experiences. Such insights
and experiences comprise knowledge, ei<strong>the</strong>r embodied in individuals or embedded in organizational
processes or practices (Nonaka, 1991). Many large companies and non-pr<strong>of</strong>it organizations have
resources dedicated to internal knowledge management efforts, <strong>of</strong>ten as part <strong>of</strong> <strong>the</strong>ir business
strategy, information technology, or human resources management departments (Addicott, McGivern
and Ferlie, 2006). Knowledge management efforts typically focus on organizational objectives such as
improved performance, competitive advantage, innovation, creativity, development, <strong>the</strong> sharing <strong>of</strong>
lessons learned, integration and continuous improvement <strong>of</strong> <strong>the</strong> organization. Knowledge
management efforts can help individuals and groups to share valuable organizational insights, to
reduce redundant work, to avoid reinventing <strong>the</strong> wheel per se, to reduce training time for new
employees, and retain intellectual capital (McAdam and McCreedy, 2000; Thompson and
Walsham,2004). The efficient operation <strong>of</strong> a firm requires congruence between <strong>the</strong> firm’s product and
knowledge domains (Grant, 1996), a strong innovative knowledge base can increase a firm’s rent
generation potential by streng<strong>the</strong>ning its ability to take advantage <strong>of</strong> opportunities in product markets
(Gopalkrishnan, 2000). Also, innovation in <strong>the</strong> form <strong>of</strong> a unique and superior combination <strong>of</strong> firm
resources may introduce ‘creative destruction’ to <strong>the</strong> competitive landscape and bring considerable
benefits to <strong>the</strong> innovative firm (Schumpeter, 1934). Innovation can thus be a fundamental force that
drives a firm’s exploitation in <strong>the</strong> marketplace, resulting in positive economic performance for <strong>the</strong> firm
(Griliches, 1990; Hall, 2000).
Usually, intensive investment in Research and Development can help a firm maintain an ample stock
<strong>of</strong> innovative knowledge assets, which are <strong>of</strong>ten traceable, at least in part, through <strong>the</strong> firm’s patenting
history (Hoetker and Agarwal, 2007). Although rival firms may imitate certain codifiable but
nonpatented innovative outputs, <strong>of</strong>ten much <strong>of</strong> a firm’s innovative knowledge can be ‘isolating
mechanism’ deterring rivals from appropriating economic returns through imitation (Mahoney and
Pandian, 1992; Rumelt, 1984). Also, a continuous focus on accumulating innovative knowledge
assets increases a firm’s absorptive capacity, putting it in a better position to transform strategic
inputs into valuable products or services (Cohen and Levinthal, 1990; Kor and Mahoney, 2005). The
outcome <strong>of</strong> innovative knowledge can also prove difficult for o<strong>the</strong>r firms to imitate. Apart from
protective mechanisms such as copyrights and patents, <strong>the</strong> idiosyncratic features <strong>of</strong> a firm make
replication difficulty if o<strong>the</strong>r firms do not have access to <strong>the</strong> asset configuration to which <strong>the</strong> innovative
knowledge was applied (Helfat, 1994; Alchian and Demsetz, 1972; McGrath et al., 1996). In line with
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<strong>the</strong>se arguments, previous empirical studies (DeCarolis and Deeds, 1999; D` Este, 2005; Geroski,
Machin, and Van Reenen, 1993; Roberts and Amit, 2003) have generally demonstrated that
variations among firms in <strong>the</strong>ir rates <strong>of</strong> accumulating new knowledge, and in <strong>the</strong>ir stocks <strong>of</strong> innovative
knowledge assets, contribute to differences in <strong>the</strong> financial performance <strong>of</strong> <strong>the</strong>se firms in <strong>the</strong>ir
different industries. For example, using a sample <strong>of</strong> United States <strong>of</strong> America biotechnology firms,
DeCarolis and Deeds (1999) found that both stocks and flows <strong>of</strong> organizational knowledge had a
positive impact on firm performance. Research has shown similar positive effects <strong>of</strong> innovative inputs
and outputs on performance in various o<strong>the</strong>r geographical and industrial settings, such as Australian
retail banking (Roberts and Amit, 2003), Spanish pharmaceuticals (D` Este, 2005), and United
Kingdom manufacturing (Geroski et al., 1993).This paper argues that, like Total Quality Management
(TQM) practices, Openness in eGovernment, and o<strong>the</strong>r organizational practices, strategic innovation
and knowledge management is an organizational practice that can also be explained and viewed from
<strong>the</strong> institutional <strong>the</strong>ory’s account <strong>of</strong> diffusion, adoption and implementation. Diffusion occurs when
new products and services begin flowing deeper within <strong>the</strong>ir initial markets, or to areas different from
<strong>the</strong> one in which <strong>the</strong>y were originally introduced (Ruggles and Little, 1997).The conventional diffusion
model mostly neglects practice implementation, yet several studies have called for viewing diffusion
practices as dynamic (Rogers, 1978; Strang and Soule, 1998) and thus for studying <strong>the</strong> details <strong>of</strong>
implementation (Edelman, 1992; Fiss and Zajac, 2006; Westphal and Zajac, 2001; Zbaracki, 1998).
The questions <strong>of</strong> why and how organizations adopt new practices have remained a central topic in <strong>the</strong>
management and organization <strong>the</strong>ory literatures (Abrahamson, 1991; Davis & Greve, 1997; Palmer,
Jennings, & Zhou, 1993; Westphal, Gulati, & Shortell, 1997). Prior research has <strong>of</strong>fered a number <strong>of</strong>
important insights into diffusion processes among populations <strong>of</strong> organizations, ranging from <strong>the</strong> role
<strong>of</strong> organization size and market power (Geroski, 2000; Hannan & McDowell, 1984) to <strong>the</strong> importance
<strong>of</strong> imitation processes (DiMaggio & Powell, 1983) and trendsetters (Abrahamson, 1996). Two distinct
approaches to explaining adoption motivation have characterized much <strong>of</strong> this literature on <strong>the</strong>
diffusion <strong>of</strong> practices and administrative technologies (Strang & Macy, 2001). The first approach is
rooted in <strong>the</strong> economic literature, building on <strong>the</strong> rational actor model, in which organizational
adoption is motivated by a desire for technical or efficiency gains and related boosts to economic
performance (Katz & Shapiro, 1987; Teece, 1980). The second approach represents a more
sociological perspective, emphasizing <strong>the</strong> social embeddedness <strong>of</strong> organizations and motivations that
stem primarily from a desire to appear legitimate to powerful constituents, peer organizations, or
outside stakeholders (Abrahamson, 1991; DiMaggio & Powell, 1983).
Perhaps <strong>the</strong> most important integration <strong>of</strong> insights from both sets <strong>of</strong> explanations is Tolbert &
Zucker`s (1983) two-stage model, according to which early adopters seek technical gains from
adoption, but later adopters are primarily interested in <strong>the</strong> social benefits <strong>of</strong> appearing legitimate.
Tolbert & Zucker consequently argued that <strong>the</strong>se later adopters implemented reforms primarily out <strong>of</strong>
a desire to appear legitimate. Similarly, in <strong>the</strong>ir study <strong>of</strong> United States hospitals, Westphal, Gulati, &
Shortell (1997) suggest that early adopters <strong>of</strong> Total Quality Management (TQM) practices were
motivated by efficiency concerns. However as TQM practices became institutionalized and thus
became expected elements <strong>of</strong> organization, <strong>the</strong> logic <strong>of</strong> evaluation shifted, and later adopters were
motivated primarily by legitimacy concerns ra<strong>the</strong>r than efficiency gains.
In this paper, developed technologies and economies, like US, UK, China and Japan that are strong
in innovation and knowledge management are considered as early adopters <strong>of</strong> strategic innovation
and knowledge management practices, while emerging technologies and economies like Zimbabwe
are viewed as later adopters <strong>of</strong> <strong>the</strong> practices. According to <strong>the</strong> institutional <strong>the</strong>ory’s account <strong>of</strong>
diffusion early adopters <strong>of</strong> <strong>the</strong>se practices are motivated by, and seeking technical gains from
adoption, but later adopters are primarily interested in <strong>the</strong> social benefits <strong>of</strong> appearing legitimate, to
realize organizational creativity and organizational development.
Although this two-stage model <strong>of</strong> diffusion has been a touchstone for many studies that apply
institutional <strong>the</strong>ory to practice diffusion (Baron, Dobbin, & Jennings, 1986; Meyer, Stephenson, &
Webster, 1985; Pangarkar & Klein, 1998; Scott, 1995; Westphal & Zajac, 1994), it has recently drawn
critical attention. For example, Lounsbury (2007) argued that segregating economic and social logics
is problematic, since <strong>the</strong> distinction between technical and social benefits is itself embedded in
institutions (Lounsbury, 2002; Thornton, 2004). By implication, technical and social motivations are
less disjointed than previously <strong>the</strong>orized (Schneiberg & Soule, 2005; Scott, Ruef, Mendel, & Caronna,
2000).
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This paper extends <strong>the</strong> interplay between economic benefits <strong>of</strong> strategic innovation and knowledge
management, and social considerations in adoption <strong>of</strong> this framework or model decision. Why would
later adopters be any less interested in <strong>the</strong>se technical gains? In addition, early adoption frequently
leads to greater prestige and more positive customer attitudes (Kamins & Alpert, 2004; Rogers,
1983), which begs a fur<strong>the</strong>r question: Are early adopters really disinterested in <strong>the</strong> social gains that
come with being perceived as market leaders? Fur<strong>the</strong>rmore, several researches have pointed out that
empirical tests <strong>of</strong> <strong>the</strong> model have largely relied on inference about motivations ra<strong>the</strong>r than more direct
assessments (Donaldson,1995; Scott,1995; Tolbert and Zucker,1983) or from later implementation
patterns <strong>of</strong> innovations (Westphal et al., 1997). However drawing on organizational decision-making
research and o<strong>the</strong>r prior researches, this paper argues that, both early and late adopters respond to
framing and interpreting adoption decisions situations as opportunities and threats (Dutton & Jackson,
1987; George, Chattopadhyay, Sitkin, & Barden, 2006; Staw, Sandelands, & Dutton,
1981).Specifically, <strong>the</strong> author argues that early adoption is associated with opportunity framing and
motivations to achieve gains, both economic and social, while later adoption is associated with threat
framing and motivations to avoid losses, again in both economic and social terms.
3. Research methodology
Following interpretivist research conventions, <strong>the</strong> sampling plan was purposeful (Lincoln & Guba,
1985; Spiggle,1994). Zimbabwe`s mainly manufacturing and industrial technology companies
operating in Bulawayo with patent data, registered trademarks and copyrights data were selected for
<strong>the</strong> purposes <strong>of</strong> this paper. The research sampling selection began with <strong>the</strong> group <strong>of</strong> firms in
manufacturing industry, which had evidence <strong>of</strong> patent data granted by government authority
responsible. These also had <strong>the</strong>ir trademarks and copyrights registered. Of <strong>the</strong> 37 manufacturing
firms that met <strong>the</strong> purposeful criterion, 27 were selected for <strong>the</strong> purposes <strong>of</strong> this paper. All <strong>the</strong> 9
technology based operating firms were selected and <strong>the</strong> 3 cellular network companies. The
researcher included a total <strong>of</strong> 39 Chief Executive Officers or Managing Directors selected purposefully
by virtue <strong>of</strong> being <strong>the</strong> highest level managers in <strong>the</strong>se 39 companies. The research method chosen
for this aim is that <strong>of</strong> conceptual/philosophical research. All <strong>of</strong> <strong>the</strong>se respondents had never met <strong>the</strong>
interviewer before. Therefore, <strong>the</strong> researcher conducted 39 individual in depth interviews.
Data collection followed <strong>the</strong> conventions <strong>of</strong> phenomenological interviewing (Thompson et al., 1989).
There is very strong rationale and justification <strong>of</strong> <strong>the</strong> choice <strong>of</strong> methods used for data collection and
analysis in this study. By analyzing <strong>the</strong> concept <strong>of</strong> interpretive research and discussing <strong>the</strong>
components and methods typically linked with it, <strong>the</strong> paper develops <strong>the</strong> argument that it is part <strong>of</strong> <strong>the</strong>
very definition and thus <strong>of</strong> <strong>the</strong> social construction <strong>of</strong> interpretive research. All <strong>of</strong> <strong>the</strong> interviews were
recorded. The interviews began with <strong>the</strong> “grand tour” questions: “ Can you tell me about innovation
and knowledge management?”, “What is your opinion on strategic innovation and knowledge
management, and how far innovative is your firm?, What challenges is Zimbabwe as an emerging
technology and economy facing with regard to adopting and implementing strategic innovation and
knowledge management practices?’’ As <strong>the</strong> interviews progressed <strong>the</strong> interviewer probed and
questioned <strong>the</strong> participants (Thompson et al., 1989). All <strong>the</strong> respondents enjoyed talking freely about
<strong>the</strong>ir opinion on strategic innovation and knowledge management. Interviews lasted from 1 hour to
two and a half hours. The researcher was able to help create an environment in which interruptions
and distractions were reduced (e.g., turning <strong>of</strong>f <strong>the</strong> cell phones). After <strong>the</strong> interviewer and respondent
parted company, <strong>the</strong> interviewer wrote field notes. Next, <strong>the</strong> interviews were transcribed.
Respondents were encouraged to comment on <strong>the</strong>ir transcripts ei<strong>the</strong>r by mail or telephone. The
written transcripts, field notes, and comments yielded 345 single spaced pages.
4. Analysis <strong>of</strong> data
To capture a firm’s level <strong>of</strong> innovative knowledge assets a simple patent count, based on patents
granted that is, patent history <strong>of</strong> <strong>the</strong> firm, was used. Although previous studies have shown that patent
citations are a better measure <strong>of</strong> <strong>the</strong> level <strong>of</strong> a firm’s innovative knowledge assets than a simple
patent count (Hall, 2000). However, <strong>the</strong> social and economic context <strong>of</strong> developing countries,
Zimbabwe included, is not developed yet, to accommodate models <strong>of</strong> patent citations that are
prevalent in developed countries like America and o<strong>the</strong>rs. On <strong>the</strong> o<strong>the</strong>r hand, patented knowledge
may represent only a subset <strong>of</strong> a firm’s innovative knowledge assets (Tabak and Barr, 1998). To
mitigate this limitation, research and development (R&D) intensity was employed as an alternative
proxy for innovative knowledge assets. Previous studies (Griliches, 1990; Jaffe et al., 1993) have
treated investment in R&D as an important determinant <strong>of</strong> <strong>the</strong> intangible component <strong>of</strong> market value
(DeCarolis and Deeds, 1999). To capture a firm’s level <strong>of</strong> knowledge management measure, each
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firm’s yearly expenditure on specific adaptations <strong>of</strong> technologies such as knowledge bases, expert
systems, knowledge repositories, group decision support systems, intranets, and computer supported
cooperative work was scaled by <strong>the</strong> firm’s total assets. Specifically, for knowledge to be made explicit,
it must be translated into information (i.e., symbols outside <strong>of</strong> our heads) (Serenko and Bontis, 2004).
Sensky (2002) suggested and proposed a framework for categorizing <strong>the</strong> dimensions <strong>of</strong> knowledge
which distinguish between embedded knowledge <strong>of</strong> a system outside <strong>of</strong> a human individual (e.g., an
information system may have knowledge embedded into its design) and embodied knowledge
representing a learned capability <strong>of</strong> a human body’s nervous and endocrine systems. In addition, <strong>the</strong>
resources-based view <strong>of</strong> <strong>the</strong> firm also emphasizes that firm-specific knowledge is particularly
important for helping a firm sustain its competitive advantage (Helfat, 1994; Henderson and
Cockburn, 1994). This is because firm-specific knowledge, which by definition is not perfectly
deployable in o<strong>the</strong>r firms, effectively prevents rivals from appropriating innovative rents through
imitation (Mahoney and Pandian, 1992; Rumelt, 1984).
The analysis was undertaken in a systematic format that is similar to previous interpretive research
(Brockman et al., 2008). An extensive systematic and interpretive analysis employing categorization,
abstraction, comparison, dimensionalization, integration, iteration, and refutation was conducted
(Spiggle,1994). As interviews were conducted and transcribed notations were made regarding
perception <strong>of</strong> strategic innovation and knowledge management legitimacy (e.g. realization <strong>of</strong>
transparency and accountability concerns). Then, an interpretive analysis was developed, refined,
and reviewed by <strong>the</strong> researcher. In this way, <strong>the</strong> interpretations sought do describe common patterns
<strong>of</strong> experience (Thompson et al., 1989). Still fur<strong>the</strong>r, <strong>the</strong> researcher formulated a classification analysis
<strong>of</strong> <strong>the</strong> data to identify concepts, guided by <strong>the</strong> literature. Next, <strong>the</strong> researcher elaborated on this
analysis by integrating concepts and bringing into <strong>the</strong> picture a process analysis that <strong>the</strong> perceptions
<strong>of</strong> strategic innovation and knowledge management legitimacy, through institutionalization, framing,
diffusion and implementation decisions are subject to change over time.
4.1 Identification <strong>of</strong> two legitimacy perceptions <strong>of</strong> strategic innovation and
knowledge management
Upon closer inspection <strong>of</strong> <strong>the</strong> framing and adoption decision situations literature and <strong>the</strong> transcriptions
<strong>of</strong> <strong>the</strong> 39 interviews, this interpretivist research analysis revealed two underlying perceptions <strong>of</strong>
strategic innovation and knowledge management legitimacy: (1) Realization <strong>of</strong> Creativity Concern,
and (2) Development Concern. The two rulebooks are consistent with <strong>the</strong> literature that is, drawing
from organizational decision-making research; <strong>the</strong> argument is that both early and late adopters
respond to framing and interpreting adoption decision situations as opportunities versus threats.
When organizational decision makers see situations as opportunities, <strong>the</strong>y are more likely to feel and
respond to motivations for achieving gains relative to <strong>the</strong>ir current position, but in situations viewed as
threats, <strong>the</strong>y are more likely to feel and respond to motivations to avoid losses. For example, early
practice adoption is likely when motivations for gain meet with seeing a new practice as an
opportunity to <strong>the</strong> competition, but later adoption is likely when motivations to avoid losses combine
with viewing a new practice as a threat (Kennedy & Fiss, 2009). As practices diffuse,
institutionalization changes how <strong>the</strong>y are perceived. Early on, practices that promise performance
improvement <strong>of</strong>fer organizational opportunities for advantage, but adoption entail <strong>the</strong> risks-or threatsassociated
with organizational change. With diffusion, however, non adoption presents a competing
risk, for two reasons. First, when early adopters realize performance improvements, <strong>the</strong>ir success
intensify competitive pressure on non adopters to follow. Second, diffusion creates social pressures to
avoid looking illegitimate. At <strong>the</strong> same time, learning among organizations can reduce <strong>the</strong> changerelated
risks <strong>of</strong> adoption (Singh, House, & Tucker, 1986).
Finally, using <strong>the</strong> opportunity and threat concepts is intuitively appealing when considering
organizational decisions about whe<strong>the</strong>r and when to adopt complex administrative innovations such
as creativity and organizational development. As <strong>the</strong> careers <strong>of</strong> senior executives, both in <strong>the</strong> public
and private sectors are increasingly tied to <strong>the</strong> performance <strong>of</strong> <strong>the</strong>ir organizations, <strong>the</strong> fates <strong>of</strong> both
depend on such decisions. Since <strong>the</strong> psychological mechanisms relating to threats and opportunities
have been shown to operate at various levels, including that <strong>of</strong> <strong>the</strong> organization (Chattopadhyay et al.,
2001; Staw et al., 1981), <strong>the</strong>y are attractive for <strong>the</strong> purposes <strong>of</strong> understanding organizational adoption
decisions. Thus, <strong>the</strong> researcher argues that organizational decision makers consider both <strong>the</strong>
efficiency and legitimacy dimensions <strong>of</strong> new practices, and that <strong>the</strong>y can approach adoption decisions
with a focus on ei<strong>the</strong>r preventing losses or promoting gains in ei<strong>the</strong>r dimension. To illustrate this
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argument, <strong>the</strong> researchers mapped decision dimensions (economic versus social) to issue
interpretation (opportunities versus threats) to produce a two-by-two matrix useful for understanding
adoption motivations. Figure 1, below combines <strong>the</strong>se elements to present potential adoption
motivations in a simple diagram. Early adopters` motivations appear in <strong>the</strong> left column; this side <strong>of</strong> <strong>the</strong>
matrix corresponds to an opportunity view associated with achieving gains. Later adopters`
motivations appear in <strong>the</strong> right column; this side corresponds to a threat view associated with
preventing losses.
Motivations predicted
By two-stage model
(Tolbert & Zucker, 1983)
Issue Interpretation
Opportunity Threat
Figure 1: Motivations for adopting innovation
The conventional diffusion model suggests that early adopters are motivated by efficiency gains
(Palmer & Biggart, 2002; Tolbert & Zucker, 1983). This logic for adoption is captured in <strong>the</strong> top-left cell
<strong>of</strong> <strong>the</strong> motivation-issue interpretation matrix in Figure 1 above: adopting organizations are motivated
by achieving economic gains (creativity) and social gains (development). At this point <strong>of</strong> diffusion
process, adopting <strong>the</strong> new practice presents an opportunity ra<strong>the</strong>r than a threat, because it allows an
organization to achieve a performance advantage relative to competitors, since only few organizations
have as yet adopted <strong>the</strong> practice. However, connecting this part <strong>of</strong> <strong>the</strong> conventional diffusion model
with <strong>the</strong>ories <strong>of</strong> issue interpretation requires suggested hypo<strong>the</strong>ses, which is not <strong>the</strong> focus <strong>of</strong> this
paper at this stage.
5. Discussion
Decision
Logic
Technical
Efficacy
Social
Legitimacy
Economic Gains
(Creativity)
Social Gains
(Development)
Early
adopters
Economic Losses
Social Losses
Late
adopters
This paper <strong>of</strong>fers a look at combining rational and social accounts <strong>of</strong> practice diffusion by asking
whe<strong>the</strong>r a concern with avoiding social losses necessarily precludes a concern with avoiding
economic losses, and wanting to look good does not preclude also wanting to do better. This paper
suggests that both early adopters and late adopters respond to framing and interpreting adoption
decision situations as opportunities versus threats. For instance, if <strong>the</strong> <strong>the</strong>orization <strong>of</strong> strategic
innovation and knowledge management as <strong>of</strong>fering performance benefits <strong>of</strong> greater creativity
(economic gain) and development (social gain) appears compelling to adopting organizations
throughout a diffusion process, <strong>the</strong>n one would not expect to see differences between early and later
adopters in terms <strong>of</strong> economic gains as a motive for adoption. This interpretivist study also found that
motivations for strategic innovation and knowledge management to appear legitimate coexist with
motivations to realize organizational creativity and development. These findings prompt rethinking <strong>of</strong>
<strong>the</strong> classic institutional, framing and diffusion model, to suggest strategic innovation and knowledge
318

Bongani Ngwenya
management model or framework that firms in emerging technologies and economies could adopt to
suit <strong>the</strong>ir social political and economic context. Specifically, this paper has shown that both early and
late adopters report having both social and economic motivations for adopting strategic innovation
and knowledge management practices, albeit for pursuing social (development) gains and economic
(creativity) gains versus avoiding social and economic losses. Overall, <strong>the</strong> findings support rethinking
<strong>the</strong> institutional diffusion model’s dichotomization <strong>of</strong> social and technical motivations for adopting
innovations. Finally, this paper deepens understanding <strong>of</strong> why <strong>the</strong> implementation <strong>of</strong> new practices is
frequently shallow or even nonexistent (Meyer & Rowan, 1977; Westphal & Zajac, 1994)-an area that
has drawn increasing research attention. Emerging technologies and economies, are equally
motivated by both social and economic gains for adopting innovation, however from <strong>the</strong> information
ga<strong>the</strong>red from <strong>the</strong> interviews conducted for <strong>the</strong> purposes <strong>of</strong> this paper, it became clear that emerging
technologies and economies have concern about <strong>the</strong>ir social, political and economic contexts that
may not be ready to adopt <strong>the</strong> current strategic innovation and knowledge management models that
are practiced elsewhere.
6. Conclusion
In this paper <strong>the</strong> researcher aimed to rethink <strong>the</strong> role <strong>of</strong> motivations in <strong>the</strong> diffusion <strong>of</strong> practices
among organization by extending <strong>the</strong> diffusion <strong>of</strong> practices to strategic innovation and knowledge
management framework or model. Both legitimacy and efficiency factor into <strong>the</strong> moves <strong>of</strong> both early
and later adopters, that is, wanting to look good does not preclude wanting to do well, based on
literature and data collected from <strong>the</strong> interviews representing <strong>the</strong> views <strong>of</strong> <strong>the</strong> later adopters,
notwithstanding <strong>the</strong> limitations <strong>of</strong> <strong>the</strong> interpretivist research approach. Early on, institutional <strong>the</strong>ory
was criticized for casting managers and leaders as unreflective followers <strong>of</strong> whatever appeared to be
legitimate (Perrow, 1986), but this study has taken considerable steps toward recognizing greater
managerial or leadership rationality and agency (Dacin, Goodstein, and Scott, 2002). For instance in
this research, it was found that motivations for <strong>the</strong> strategic innovation and knowledge management
to appear legitimate coexist with motivations to realize organizational creativity and organizational
development, and that emerging technologies and economies may not be ready to accommodate
current models <strong>of</strong> strategic innovation and knowledge management, taking account <strong>of</strong> <strong>the</strong>ir social,
political and economic context. These findings prompt rethinking <strong>of</strong> <strong>the</strong> classic institutional, framing
and diffusion model, to suggest a grounded <strong>the</strong>ory investigation in future, that would come up with
strategic innovation and knowledge management model or framework that could suit <strong>the</strong> social,
political and economic context <strong>of</strong> emerging technologies and economies.
References
Abraham, J.L., and Knight, D.J 2001, “Strategic innovation”, Strategy& Leadership Journal, vol. 29, no. 1, pp. 21-
27.
Abrahamson, E 1991, “Managerial fads and fashions: The diffusion and rejection <strong>of</strong> innovations”, Academy <strong>of</strong>
Management Review, vol. 16, pp. 586-612.
Abrahamson, E 1996, “Management fashion”, Academy <strong>of</strong> Management Review, vol. 21, pp. 254-285.
Alchian, A. A, and Demsetz, H 1972, “Production, information costs, and economic organization”, American
Economic Review, vol. 62, pp. 777-795.
Barney, J.B 1991, “Firm resources and sustained competitive advantage”, Journal <strong>of</strong> Management, vol. 17, pp.
99-120.
Baron, J., Dobbin, F. R., and Jennings, P.D 1986, “War and peace: The evolution <strong>of</strong> modern personnel
administration in US industry”, American Journal <strong>of</strong> Sociology, vol. 92, pp. 350-383.
Brockman, B., Taylor, V.,and Brockman, C. The price <strong>of</strong> unconditional love: consumer decision making for highdollar
veterinary care, J Bus Res 2008; 61(5): 397-405.
Chattopadhyay, P., Glick, W. H., and Huber, G. P 2001, “Organizational actions in response to threats and
opportunities”, Academy <strong>of</strong> Management Journal, vol. 44, pp. 937-955.
Cohen, W. M,and Levinthal, D. A 1990, “Absorptive capacity: A new perspective on learning and innovation”,
Administrative Science Quarterly, vol. 35, pp. 128-152.
D`Este, P 2005, “How do firms` knowledge bases affect intra-industry heterogeneity? An analysis <strong>of</strong> <strong>the</strong> Spanish
pharmaceutical industry”, Research Policy, vol. 34, pp. 33-45.
Dacin, M. T., Goodstein, J., and Scott, W. R 2002, “Institutional <strong>the</strong>ory and institutional change: Introduction to
<strong>the</strong> research forum”, Academy <strong>of</strong> Management Journal, vol. 45, pp. 45-56.
Davis, G. F., and Greve, H. R 1997, “Corporate elite networks and governance changes in <strong>the</strong> 1980s”, American
Journal <strong>of</strong> Sociology, vol. 103, pp. 1-37.
DeCarolis, D.M, and Deeds, D.L 1999, “The impact <strong>of</strong> stocks and flows <strong>of</strong> organizational knowledge on firm
performance: An empirical investigation <strong>of</strong> <strong>the</strong> biotechnology industry”, Strategic Management Journal, vol.
20, pp. 953-968.
Deephouse, D. L 1996, “Does isomorphism legitimate ?”, Academy <strong>of</strong> Management Journal, vol.39, pp. 1024-
1039.
319

Bongani Ngwenya
DiMaggio, P. J., and Powell, W. W 1983, “The iron cage revisited: Institutional isomorphism and collective
rationality in organizational fields”, American Social Logical Review, vol. 48, pp. 147-160.
Donaldson, L 1995. American anti-management <strong>the</strong>ories <strong>of</strong> organization, New York: Cambridge University Press.
George, E., Chattopadhyay, P., Sitkin, S. B., and Barden, J 2006, “Cognitive underpinnings <strong>of</strong> institutional
persistence and change: A framing perspective”, Academy <strong>of</strong> Management Review, vol. 31, pp. 347-365.
Geroski, P, Machin, S, and Van Reenen, J 1993, “The pr<strong>of</strong>itability <strong>of</strong> innovating firms”, RAND Journal <strong>of</strong>
Economics, vol. 24, pp. 198-211.
Geroski, P. A 2000, “Models <strong>of</strong> technology diffusion”, Research policy, vol. 29, pp. 603-625.
Goodstein, J. D 1994, “Institutional Pressures and strategic responsiveness: Employer involvement in work family
issues”, Academy <strong>of</strong> Management Journal, vol.37, pp.350-385.
Gopalkrishnan, S 2000, “Unraveling <strong>the</strong> links between dimensions <strong>of</strong> innovation and organizational performance”,
Journal <strong>of</strong> High Technology Management Research, vol. 11, pp. 137-152.
Grant, R.M 1996, “Toward a knowledge-based <strong>the</strong>ory <strong>of</strong> <strong>the</strong> firm”, Strategic Management Journal, vol. 17, winter
special issue, pp. 109-122.
Hannan, T. H., and McDowell, J. M 1984, “The determinants <strong>of</strong> technology adoption: The case <strong>of</strong> <strong>the</strong> banking
firm”, RAND Journal <strong>of</strong> Economics, vol. 15, pp. 328-335.
Helfat, C. E 1994, “Firm-specificity in corporate applied R&D”, Organization Science, vol. 5, pp. 173-184.
Hertz, R. Separate but simultaneous interviewing <strong>of</strong> husbands and wives: making sense <strong>of</strong> <strong>the</strong>ir stories. Qual Inq
1995; 1 (4): 429-51.
Hoetker, G, and Agarwal, R 2007, “Death hurts, but it isn’t fatal: The post exit diffusion <strong>of</strong> knowledge created by
innovative companies”, Academy <strong>of</strong> Management Journal, vol. 50, pp. 446-467.
Jackson, S., and Dutton, J. E 1988, “Discerning threats and opportunities”, Administrative Science Quarterly,
vol.33, pp. 370-387.
Kamins, M. A., and Alpert, F. H 2004, “Corporate claims as innovator or market leader: Impact on overall attitude
and quality perceptions and transfer to company brands”, Corporate Reputation Review, vol. 7, pp. 147-
159.
Katz, M. S., and Shapiro, C 1987, “R&D rivalry with licensing or imitation”, American Economic Review, vol. 77,
pp. 402-420.
Kennedy, S., and Fiss, P 2009, “The symbolic management <strong>of</strong> corporate strategy: Framing, decoupling, and
strategic change”, Academy <strong>of</strong> Management Journal, vol. 49, pp. 1173-1193.
Kogut, B,and Zander, U 1992, “Knowledge <strong>of</strong> <strong>the</strong> firm, combinative capabilities, and <strong>the</strong> replications <strong>of</strong>
technology”, Organization Science, vol. 3, pp. 383-397.
Kor, Y. Y, and Mahoney, J. T 2005, “How dynamics, management, and governance <strong>of</strong> resource deployments
influence firm-level performance”, Strategic Management Journal, vol. 26, pp. 489-496.
Lincoln, Y. S., and Guba, E. G. Naturalistic inquiry. Beverly Hills, CA: Sage; 1985.
Lounsbury, M 2002, “Institutional transformation and status mobility: The pr<strong>of</strong>essionalization <strong>of</strong> <strong>the</strong> field <strong>of</strong>
finance”, Academy <strong>of</strong> Management Journal, vol. 45, pp. 255-266.
Lounsbury, M 2007, “A tale <strong>of</strong> two cities: Competing logics and practice variation in <strong>the</strong> pr<strong>of</strong>essionalizing <strong>of</strong>
mutual funds”, Academy <strong>of</strong> Management Journal, vol. 50, pp. 289-307.
MacGrath, R. G, Tsai, M.H, Venkataraman, S,and MacMillan, I.C 1996, “Innovation, competitive advantage and
rent: A model and test”, Management Science, vol. 42, pp. 389-403.
Mahoney, J. T,and Pandian, J.R 1992, “The resource-based view within <strong>the</strong> conversation <strong>of</strong> strategic
management”, Strategic Management Journal, vol. 13, pp. 363-380.
McAdam, W. R. Scott, and M. Zald (Eds), Social movements and organization <strong>the</strong>ory: 122-160. Cambridge, U.K.
Cambridge University Press.
Meyer, J. W., and Rowan, B 1977, “Institutionalized organization: Formal structure as myth and ceremony”,
American Sociological Review, vol. 83, pp. 340-363.
Meyer, M. W., Stephenson, W., and Webster, S 1985. Limits to bureaucratic growth; Berlin: Walter de Gruyter.
Palmer, D. P., Jennings, D., and Zhou, Z 1993, “Politics and institutional change: Late adoption <strong>of</strong> <strong>the</strong>
multidivisional form by large U.S. corporations”, Administrative Science Quarterly, vol. 38, pp. 100-131.
Palmer, D., and Biggart, D. W (Ed) 2002, Organizational institutions, The Blackwell companion to organizations,
Blackwell, 259-280, Oxford, U.K.
Pangarkar, N., and Klein, S 1998, “Bandwagon pressures and interfirm alliances in <strong>the</strong> global pharmaceutical
industry”, Journal <strong>of</strong> International Marketing, vol. 6 (2), pp. 54-73.
Perrow, C (3 rd ) 1986, Complex organizations: A critical essay, New York.
Pitt, M, and Clarke, K 1999, “Competing on Competence: A Knowledge Perspective on <strong>the</strong> Management <strong>of</strong>
Strategic Innovation”, Technology Analysis & Strategic Management Journal, vol. 11, no. 3, pp 301-316.
Roberts, P. W, and Amit, R 2003, “The dynamics <strong>of</strong> innovative capacity and competitive advantage: The case <strong>of</strong>
Australian retail banking,” 1981-1995, Organization Science, vol. 14, pp. 107-122.
Rogers, E (3 rd ed) 1983, Diffusion <strong>of</strong> innovations. New York: Free Press.
Rumelt, R. P 1984, Towards a strategic <strong>the</strong>ory <strong>of</strong> <strong>the</strong> firm. In R.B. Lamb (Ed), Competitive strategic management,
pp 556-570, Prentice Hall, Upper Saddle River.
Schneiberg, M., and Soule, S.A 2005, Institutionalization as a contested, multilevel process: The case <strong>of</strong> rate
regulation in American fire insurance. In G. Davis, D,.
Schumpeter, J.A 1934, The <strong>the</strong>ory <strong>of</strong> economic development: An inquiry into pr<strong>of</strong>its, capital, credit, interest, and
<strong>the</strong> business cycle, Harvard University Press, Cambridge, MA.
Scott, W. R 1995, Institutions and organizations, Thousand Oaks, CA: Sage.
320

Bongani Ngwenya
Scott, W. R., Ruef, M., Mendel, P., and Caronna, C 2000, Institutional change and healthcare organizations:
From pr<strong>of</strong>essional dominance to managed care; Chicago: University <strong>of</strong> Chicago Press.
Singh, J. V., House, R. J., and Tucker, D. J 1986, “Organizational Change and Organizational Mortality”,
Administrative Science Quarterly, vol. 31, pp. 587-611.
Staw, B. M., Sandelands, L., and Dutton, J. E 1981, “Threat rigidity cycles in organizational behavior: A multi
level analysis”, Administrative Science Quarterly, vol. 26, pp. 501-524.
Teece, D 1980, “The diffusion <strong>of</strong> an administrative innovation”, Management Science, vol. 26, pp. 464-470.
Thompson, C., and Locander, W., Pollio, Putting consumer experience back into consumer research: <strong>the</strong>
philosophy and method <strong>of</strong> existential-phenomenology, Consum Res 1989, 16: 133-46 (September).
Thornton, P. H. 2004, Markets from culture: Institutional logics and organizational decisions in higher education
publishing; Stanford, CA: Stanford University Press.
Tolbert, P. S., and Zucker, L. G 1983, “Institutional sources <strong>of</strong> change in <strong>the</strong> formal structure <strong>of</strong> organizations:
The diffusion <strong>of</strong> civil service reform, 1880-1935”, Administrative Science Quarterly, vol. 28, pp. 22-39.
Westphal, J. D., and Zajac, E. J 1994, “Substance and symbolism in CEOs” long-term incentive plans,
Administrative Science Quarterly, vol. 39, pp. 367-390.
Westphal, J. D., and Zajac, E. J 1998, “The symbolic management <strong>of</strong> stockholders: Corporate governance reform
and shareholder reactions”, Administrative Science Quarterly, vol. 43, pp. 127-153.
Westphal, J. W., and Zajac, E. J 1994, “The costs and benefits <strong>of</strong> managerial incentives and monitoring in large
U.S. corporations: When is more not better?” Strategic Management Journal, vol. 15, pp. 121-142.
Westphal, J., Gulati, R., and Shortell, S 1997, “Customization or conformity? An institutional and network
perspective on <strong>the</strong> content and consequences <strong>of</strong> TQM adoption”, Administrative Science Quarterly, vol. 42,
pp. 366-392.
321

The Quality <strong>of</strong> Knowledge Flows and its Impact on <strong>the</strong>
Intellectual Capital Development <strong>of</strong> a University
Corina Pelau 1 , Irina Bena 1 , Anca Daniela Vladoi 1 , Dan Cristian Dabija 2 and Monica
Fufezan 3
1
Academy <strong>of</strong> Economic Studies Bucharest, Romania
2
Babes Bolyai University, Cluj-Napoca, Romania
3
Moda SA, Arad, Romania
corinapelau@yahoo.com
irina.bena@gmail.com
anca.vladoi@gmail.com
cristi_dabija@yahoo.com
monicafufezan@yahoo.com
Abstract: In a world characterized by an overload <strong>of</strong> information, it is important for a university pr<strong>of</strong>essor not only to
transmit to <strong>the</strong>ir students <strong>the</strong> right information, but also to transmit it in <strong>the</strong> right way. Besides <strong>the</strong> transmitted content,
it is also important to have <strong>the</strong> adequate materials, visual aids and o<strong>the</strong>r. The best way to evaluate <strong>the</strong> quality <strong>of</strong> <strong>the</strong>
knowledge flows from pr<strong>of</strong>essors to students is to evaluate <strong>the</strong> way in which <strong>the</strong> students perceive this information
and <strong>the</strong> way this information is used for <strong>the</strong>ir future jobs. The evaluation <strong>of</strong> <strong>the</strong> quality <strong>of</strong> <strong>the</strong> knowledge flows is
important for <strong>the</strong> development <strong>of</strong> <strong>the</strong> performance <strong>of</strong> <strong>the</strong> students. In an indirect way, this leads also to <strong>the</strong>
development <strong>of</strong> <strong>the</strong> university, by <strong>the</strong> creation <strong>of</strong> a good image <strong>of</strong> <strong>the</strong> university. If <strong>the</strong> graduates have good
pr<strong>of</strong>essional results and achieve good positions in <strong>the</strong>ir jobs, this will also have an impact on <strong>the</strong> university. This
article presents <strong>the</strong> results <strong>of</strong> a satisfaction study, done among <strong>the</strong> students from a university from Romania and
focuses on <strong>the</strong> elements regarding <strong>the</strong> quality <strong>of</strong> <strong>the</strong> courses and seminars. Only by qualitative courses can <strong>the</strong>
students <strong>of</strong> <strong>the</strong> university develop. There are analyzed aspects like <strong>the</strong> achieved knowledge within courses, <strong>the</strong>
relevance <strong>of</strong> <strong>the</strong> provided information, <strong>the</strong> recency <strong>of</strong> <strong>the</strong> information, visual support, application and interactivity at
seminars, examples given or utility <strong>of</strong> projects. All <strong>the</strong>se elements are correlated both with <strong>the</strong> performance <strong>of</strong> <strong>the</strong>
students and <strong>the</strong>ir willingness to recommend or continue <strong>the</strong>ir studies at <strong>the</strong> same university. There are analyzed
both elements regarding <strong>the</strong> content <strong>of</strong> <strong>the</strong> courses and <strong>the</strong> quality <strong>of</strong> <strong>the</strong> provided knowledge and also elements
regarding <strong>the</strong> good transmission <strong>of</strong> <strong>the</strong> information, because it is not enough just to transmit good information, but
also <strong>the</strong> way it is transmitted and if <strong>the</strong> transmitted information is perceived by <strong>the</strong> receiver. Especially in a university,
<strong>the</strong>se aspects are important for educational purposes.
Keywords: intellectual capital, satisfaction, knowledge transfer, knowledge flows
1. Introduction
The Romanian higher education services market is characterized mainly by an increased competition,
both from inland and outland universities, and sinking demographics (Bena 2010). Fur<strong>the</strong>rmore, factors
encountered on markets <strong>of</strong> o<strong>the</strong>r countries are present: companies that are beginning to <strong>of</strong>fer own MBAdegrees,
online study programs, higher tuition charges in public institutions due to <strong>the</strong> bad economic
climate (DeShields et al. 2005). The actual marketplace presents challenges that many universities did
not face up until now. Therefore <strong>the</strong>ir attention will have to focus on creating a competitive advantage.
The present paper presents a study on students’ satisfaction with <strong>the</strong> knowledge flows and its impact on
<strong>the</strong> overall students’ satisfaction <strong>of</strong> <strong>the</strong> students and <strong>the</strong>ir recommendation potential. We analyze <strong>the</strong>
following items: <strong>the</strong> scientific level <strong>of</strong> <strong>the</strong> courses, <strong>the</strong> knowledge transfer, <strong>the</strong> relevance and <strong>the</strong> actuality
<strong>of</strong> <strong>the</strong> transferred information, <strong>the</strong> visual aids used during <strong>the</strong> courses and seminars, <strong>the</strong> applications and
<strong>the</strong> examples given, <strong>the</strong> interactivity and <strong>the</strong> utility <strong>of</strong> <strong>the</strong> subjects and <strong>of</strong> <strong>the</strong> projects. By doing this we
determine an external dimension indicator <strong>of</strong> <strong>the</strong> intellectual capital model. Fur<strong>the</strong>rmore <strong>the</strong> management
<strong>of</strong> <strong>the</strong> university is also given an overview <strong>of</strong> <strong>the</strong> process capital perception by its students and
customers.
2. Literature review
Due to changing market conditions higher education service providers – universities – are becoming
increasingly aware <strong>of</strong> <strong>the</strong> importance <strong>of</strong> <strong>the</strong> satisfaction on <strong>the</strong>ir overall outcome. As in <strong>the</strong> case <strong>of</strong>
business companies, authors also apply <strong>the</strong> expression “it costs more to attract a new customer than it
does to retain an existing customer” (DeShields et al. 2005) on <strong>the</strong>se institutions. Satisfied students <strong>of</strong>fer,
as any customers, <strong>the</strong> prospect <strong>of</strong> a prolonged relationship by continuing <strong>the</strong>ir studies at <strong>the</strong> same
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Corina Pelau et al.
institution and fur<strong>the</strong>r <strong>the</strong> benefits <strong>of</strong> a positive word <strong>of</strong> mouth to potential candidates (Grönroos 2004,
Priluck 2003).
The objective <strong>of</strong> education services is to <strong>of</strong>fer learning services for its students, on one hand, and future
employees for companies, on <strong>the</strong> o<strong>the</strong>r hand. Seymour (Seymour 1993) argues that students are
customers for universities. But <strong>the</strong> term customer may broadly include also <strong>the</strong> parents <strong>of</strong> students, <strong>the</strong>
alumni and <strong>the</strong> employers. This paper focuses on <strong>the</strong> student as customer concept and derives <strong>the</strong>
survey on student’s satisfaction from this perspective.
The literature on <strong>the</strong> subject <strong>of</strong> customer satisfaction, agrees that <strong>the</strong> satisfaction construct is based on
<strong>the</strong> confirmation/disconfirmation paradigm (Eggert and Ulaga 2002, Chen and Tsai 2009, Appleton-
Knapp and Krentler 2006). Confirmation appears when <strong>the</strong> customer’s expectations are met by <strong>the</strong>
company. In <strong>the</strong> case <strong>of</strong> disconfirmation <strong>the</strong>re are two possible outcomes: (a) <strong>the</strong> customer’s
expectations are above <strong>the</strong> experienced performance, a case <strong>of</strong> negative disconfirmation; (b) <strong>the</strong>
perceived performance outranks <strong>the</strong> customer’s expectations, in which case a positive disconfirmation
appears.
Stewart (Steward 1997) defines intellectual capital as “<strong>the</strong> intellectual material – knowledge, information,
intellectual property, experience – that can be put to use to create wealth.” The intellectual capital model,
although defined differently in <strong>the</strong> literature, is based on three dimensions. Some <strong>of</strong> <strong>the</strong> most popular
classification schemes proposed by researches are summarized by Akhilesh (Akhilesh 2008): Sveiby
speaks about internal structure, external structure and personnel competence; Stewart focuses on
human capital, structural capital and customer capital.
The Intellectual Capital Navigator developed by Skandia, presents one <strong>of</strong> <strong>the</strong> first evaluation tools. “The
total Market Value <strong>of</strong> a firm is equal to its Financial Capital plus its Intellectual Capital. The components
<strong>of</strong> IC are Human Capital, Structural Capital. Structural Capital can be deconstructed into Organizational
Capital and Customer Capital. Organizational Capital can in turn be deconstructed into Innovation Capital
and Process Capital.” (Van den Berg 2002). In our study <strong>the</strong> students’ satisfaction is an indicator for <strong>the</strong>
customer capital. The satisfaction level for different elements <strong>of</strong> <strong>the</strong> knowledge flow also gives on
overview <strong>of</strong> <strong>the</strong> way <strong>the</strong> process capital is perceived by <strong>the</strong> university’s customers. The research does
not strive to evaluate <strong>the</strong> intellectual capital as a whole as <strong>the</strong> construct is fairly complex and would
require additional effort. We focus on <strong>the</strong> satisfaction aspect as this <strong>of</strong>fers <strong>the</strong> basis for a future long term
relationship with students.
3. Research regarding <strong>the</strong> satisfaction <strong>of</strong> students with <strong>the</strong> knowledge flows at a
university
This article is based on a study which had as main objective <strong>the</strong> determination <strong>of</strong> <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong>
students at <strong>the</strong> Academy <strong>of</strong> Economic Studies (ASE), Bucharest Romania and its impact on <strong>the</strong> attitude
<strong>of</strong> <strong>the</strong> students towards future attendance <strong>of</strong> study programs or recommendations. Therefore a study was
conducted on a sample <strong>of</strong> 1200 students from all faculties <strong>of</strong> ASE, from both <strong>the</strong> Bachelor and <strong>the</strong> Master
programs. There were asked questions about <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> courses and <strong>the</strong>
seminars, <strong>the</strong> competences and <strong>the</strong> attitude <strong>of</strong> <strong>the</strong> teachers and all o<strong>the</strong>r facilities <strong>of</strong> <strong>the</strong> university such
as canteen, dorms, library, scholarships and so on. The research was done in <strong>the</strong> period April-May 2010
at <strong>the</strong> university. The survey contains both Likert-scale, multiple choice and open questions. The
questions regarding <strong>the</strong> satisfaction with several items in ASE were scaled from 1 to 7, where 7 was very
satisfied and 1 totally dissatisfied. Besides <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students, <strong>the</strong>re were also asked
questions about demographic data, such as age, faculty.
There is analyzed <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> knowledge flows and <strong>the</strong> impact <strong>of</strong> this
satisfaction on <strong>the</strong> overall satisfaction <strong>of</strong> <strong>the</strong> students and <strong>the</strong>ir recommendation potential. For this we
analyze <strong>the</strong> following items: <strong>the</strong> scientific level <strong>of</strong> <strong>the</strong> courses, <strong>the</strong> knowledge transfer, <strong>the</strong> relevance and
<strong>the</strong> actuality <strong>of</strong> <strong>the</strong> transferred information, <strong>the</strong> visual aids used during <strong>the</strong> courses and seminars, <strong>the</strong>
applications and <strong>the</strong> examples given, <strong>the</strong> interactivity and <strong>the</strong> utility <strong>of</strong> <strong>the</strong> subjects and <strong>of</strong> <strong>the</strong> projects. All
<strong>the</strong>se aspects have been related to satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> university and <strong>the</strong> willingness to
continue <strong>the</strong> studies at <strong>the</strong> same university. In fig. 1 we can observe <strong>the</strong> absolute satisfaction <strong>of</strong> <strong>the</strong>se
items, on a scale from 1 to 7, where 7 means very satisfied and 1 means totally dissatisfied.
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5.2
5
4.8
4.6
4.4
4.2
4
3.8
Competences
5.06
Teaching Style
4.4
Pedagogical Skills
Corina Pelau et al.
4.67
Implication
4.38
Satisfaction
Attitude
4.42
Communication
4.24
Availability
4.32
Figure 1: Satisfaction with <strong>the</strong> knowledge flows at a university (on a scale <strong>of</strong> 1 to 7, where 7=very
satisfied and 1=totally dissatisfied)
As fig. 1 shows <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> elements <strong>of</strong> knowledge transfer have values
between 4 (average satisfaction) and 5 (ra<strong>the</strong>r satisfied), with <strong>the</strong> exception <strong>of</strong> <strong>the</strong> level <strong>of</strong> courses.
Although <strong>the</strong>re is no high variation between <strong>the</strong> items, we can observe that <strong>the</strong> students are most
satisfied with <strong>the</strong> actuality <strong>of</strong> information (4.76), <strong>the</strong> visual aids (4.73) and <strong>the</strong> applications (4.73). The
next aspects with which <strong>the</strong> students are satisfied are <strong>the</strong> knowledge transfer (4.67), <strong>the</strong> relevance <strong>of</strong>
information (4.63) and <strong>the</strong> interactivity (4.60). The utility <strong>of</strong> <strong>the</strong> subjects and <strong>the</strong> utility <strong>of</strong> <strong>the</strong> projects are
valued with 4.5. The students have <strong>the</strong> least satisfaction with <strong>the</strong> level <strong>of</strong> <strong>the</strong> courses. This can be
explained by <strong>the</strong> fact that <strong>the</strong>y might have very high expectations regarding <strong>the</strong>se or because <strong>the</strong>y are so
well taught that <strong>the</strong> students understand <strong>the</strong>m very well and for this reason <strong>the</strong>y don’t perceive <strong>the</strong>m as
being difficult. The overall satisfaction asked at <strong>the</strong> end <strong>of</strong> <strong>the</strong> questionnaire has a value <strong>of</strong> 4.83, which is
higher than all <strong>the</strong> values <strong>of</strong> <strong>the</strong> considered factors. In <strong>the</strong> following we will analyze if <strong>the</strong> satisfaction <strong>of</strong>
<strong>the</strong> considered factors influences in any way <strong>the</strong> satisfaction with <strong>the</strong> fact that <strong>the</strong> students have chosen
<strong>the</strong> university.
The influence <strong>of</strong> all <strong>the</strong>se factors on <strong>the</strong> satisfaction with <strong>the</strong> university can be measured with <strong>the</strong>
regression analysis with <strong>the</strong> help <strong>of</strong> <strong>the</strong> SPSS. In this analysis we had as dependent variable <strong>the</strong> item
“satisfied that you chose this university” and <strong>the</strong> independent variables <strong>the</strong> items presented in fig. 1. The
results <strong>of</strong> <strong>the</strong> regression analysis are presented in fig. 2.
The R-Square obtained in <strong>the</strong> regression analysis shows that 27.5% <strong>of</strong> <strong>the</strong> dependent variable can be
explained by <strong>the</strong> analyzed factors. Taking in consideration <strong>the</strong> fact that in <strong>the</strong> analysis, <strong>the</strong>re have been
taken in consideration 80 satisfaction items, this value is significant. This value is confirmed by <strong>the</strong> R-
Square change and <strong>the</strong> F-Test in <strong>the</strong> ANOVA Table shows a significance <strong>of</strong> <strong>the</strong> regression <strong>of</strong> 99%.
According to <strong>the</strong> results <strong>of</strong> <strong>the</strong> Regression analysis and assuming that all o<strong>the</strong>r factors are constant we
have <strong>the</strong> following regression function:
Satisfaction = 1.42 – 0.57*level_courses + 0.24*knowledge_transfer + 0.12*relevance_information –
0.05*actuality_information + 0.13*visual_aids + 0.09*applications + 0*examples seminar
+0.04*interactivity + 0.14*utility_subjects + 0.03*utility_projects
The regression function shows that <strong>the</strong>oretically <strong>the</strong> highest influence on <strong>the</strong> satisfaction has <strong>the</strong> level <strong>of</strong>
<strong>the</strong> courses. But if we analyze <strong>the</strong> significance <strong>of</strong> this influence, it is not very high. The next highest
importance has <strong>the</strong> knowledge transfer, an influence which is also confirmed by <strong>the</strong> significance test. The
significance <strong>of</strong> this relation is equal to zero, so that we can reject <strong>the</strong> Zero-Hypo<strong>the</strong>sis. With <strong>the</strong> exception
<strong>of</strong> <strong>the</strong> interactivity and <strong>the</strong> actuality <strong>of</strong> information, all o<strong>the</strong>r factors have a significant influence on <strong>the</strong>
dependent factor. So <strong>the</strong> next highest importance, have <strong>the</strong> factors utility <strong>of</strong> subjects, <strong>the</strong> visual aids and
<strong>the</strong> relevance <strong>of</strong> <strong>the</strong> transmitted information. The least importance have factors, such as applications and
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Corina Pelau et al.
utility <strong>of</strong> projects, while <strong>the</strong> examples <strong>of</strong> seminar don’t have any importance, having a coefficient equal to
zero. The t-test also confirms this result.
Model Summary b
Model R
R
Square
Adjusted
R
Square
Std. Error <strong>of</strong>
<strong>the</strong> Estimate
Change Statistics
R Square
Change
F
Chang
e df1 df2
Sig. F
Change
Durbin-
Watson
1 .530 a .281 .275 1.16910 .281 45.307 10 1159 .000 1.548
a. Predictors: (Constant), utility_project, level_courses, actuality _information, interactivity, knowledge
_transfer, visual_aids, utility_subjects, aplications_seminars, exemples_seminars,
relevance_information
b. Dependent Variable: satisfied_with_ase
ANOVA b
Model
Sum <strong>of</strong>
Squares df Mean Square F Sig.
Regression 619.259 10 61.926 45.307 .000 a
1
Residual 1584.122 1159 1.367
Total 2203.381 1169
a. Predictors: (Constant), utility_project, level_courses, actuality _information, interactivity, knowledge
_transfer, visual_aids, utility_subjects, aplications_seminars, exemples_seminars,
relevance_information
b. Dependent Variable: satisfied_with_ase
Coefficients a
Unstandardized Coefficients
Standardized
Coefficients
Model B Std. Error Beta t Sig.
1
(Constant) 1.422 .226 6.307 .000
level_courses -.057 .042 -.034 -1.332 .183
knowledge_transfer .243 .037 .207 6.556 .000
relevance_info .121 .039 .110 3.106 .002
actuality_info -.052 .033 -.051 -1.565 .118
visual_aids .130 .029 .135 4.425 .000
aplications_seminar .091 .037 .084 2.481 .013
exemples_sem .000 .035 .000 -.010 .992
interactivity .040 .034 .037 1.173 .241
utility_subjects .149 .034 .143 4.416 .000
utility_proiects .037 .011 .082 3.189 .001
a. Dependent Variable: satisfied_with_ase
Figure 2: Results <strong>of</strong> <strong>the</strong> regression analysis
The BETA-test in <strong>the</strong> SPSS analysis shows also <strong>the</strong> highest influence for <strong>the</strong> item knowledge transfer.
According to <strong>the</strong> BETA-test <strong>the</strong> next highest influence, have <strong>the</strong> items utility <strong>of</strong> subjects, visual aids and
<strong>the</strong> relevance <strong>of</strong> <strong>the</strong> transmitted information. As shown also by <strong>the</strong> coefficients o<strong>the</strong>r factors which have
an influence on <strong>the</strong> dependent variable are <strong>the</strong> utility <strong>of</strong> projects, <strong>the</strong> applications.
The t-test shows also an influence <strong>of</strong> all factors on <strong>the</strong> dependent variable “satisfied that you have
chosen this university”, with <strong>the</strong> exception <strong>of</strong> “level <strong>of</strong> courses”, “actuality <strong>of</strong> information”, “interactivity”
and “examples”. The correlation table between <strong>the</strong> independent variables shows no significant
dependence between <strong>the</strong> analyzed items.
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Corina Pelau et al.
In order to improve its image, it is important that <strong>the</strong> university should be recommended. Fig. 3. shows
that satisfied students ra<strong>the</strong>r recommend <strong>the</strong> university to friends or acquaintances. If students which are
unsatisfied, recommend <strong>the</strong> university to less than 56% to <strong>the</strong> people <strong>the</strong>y know, students with an
average or over average satisfaction recommend <strong>the</strong> university to more than 74% <strong>of</strong> <strong>the</strong> people <strong>the</strong>y
know.
100%
80%
60%
40%
20%
0%
77
23
66
34
44
56
26
74
12 6 9
88 94 91
1 2 3 4 5 6 7
Figure 3: Willingness to recommend <strong>the</strong> university depending on satisfaction
4. Conclusion and outlook
This research shows that <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> university, has an impact on <strong>the</strong>
recommendation potential <strong>of</strong> <strong>the</strong> students and consequently on <strong>the</strong> image <strong>of</strong> <strong>the</strong> university. For this
reason it is important for an university to monitor permanently <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong>ir students and take
measures to improve it. In order to be able to improve <strong>the</strong> satisfaction, a university has to know <strong>the</strong>
relevant elements which influence <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students and <strong>the</strong>ir partial level <strong>of</strong> satisfaction.
This article presents <strong>the</strong> results <strong>of</strong> such a satisfaction study and <strong>the</strong> impact <strong>of</strong> different aspects on <strong>the</strong>
overall satisfaction.
The results <strong>of</strong> <strong>the</strong> research show that <strong>the</strong> knowledge flows and <strong>the</strong> way it is transmitted to <strong>the</strong> students
has an impact on <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students. Especially <strong>the</strong> way in which <strong>the</strong> knowledge transfer
takes place, has an impact on <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students. All <strong>the</strong> o<strong>the</strong>r aspects analyzed in <strong>the</strong>
research influence <strong>the</strong> satisfaction and also contribute in an indirect way to <strong>the</strong> knowledge <strong>the</strong> students
achieved through <strong>the</strong> learning process. A good knowledge transfer process has not only an influence on
<strong>the</strong> satisfaction, but also on <strong>the</strong> development <strong>of</strong> <strong>the</strong> human capital <strong>of</strong> <strong>the</strong> university.
Consequently <strong>the</strong> university should try to keep a good quality <strong>of</strong> <strong>the</strong> knowledge transfer, because it not
only influences <strong>the</strong> development <strong>of</strong> <strong>the</strong> human capital <strong>of</strong> <strong>the</strong> university, but also <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong>
students and <strong>the</strong>refore its relational capital. As it was expected <strong>the</strong> knowledge transfer is sustained by <strong>the</strong>
visual aids and <strong>the</strong> relevance <strong>of</strong> information, which also have a high impact on <strong>the</strong> overall satisfaction.
Therefore, <strong>the</strong> university should try to keep its pr<strong>of</strong>essors up to date with <strong>the</strong> relevant information, by
providing <strong>the</strong> necessary research infrastructure and access to recent journals and publications. Visual
aids have also an important role in <strong>the</strong> communication process and contribute by this to a high quality <strong>of</strong>
<strong>the</strong> knowledge transfer.
Acknowledgements
This work was supported from <strong>the</strong> <strong>European</strong> Social Fund through Sectoral Operational Programme
Human Resources Development 2007-2013, project number POSDRU/ 89/ 1.5/ S/ 59184 “Performance
and excellence in postdoctoral research in Romanian economics science domain”.
References
Aldridge, S; Rowley, J. (1998): Measuring customer satisfaction in higher education, in: Quality Assurance in
Education, Volume 6, Number 4, 1998, pp. 197–204.
Akhilesh, K. (2008) „Modeling Intellectual Capital From a Bottom-Up Perspective”. In: O’Sullivan, K. (Ed.) 5th
International <strong>Conference</strong> on Intellectual Capital, Knowledge Management and Organizational Learning, New
York Institute <strong>of</strong> Technology, New York, pp 17-24.
Al-Ali, N. (2003) Comprehensive Intellectual Capital Management, John Wiley & Sons, Hoboken NJ.
Appleton-Knapp, S.L. and Krentler, K.A. (2006) „Measuring Student Expectations and Their Effects on Satisfaction:
The Importance <strong>of</strong> Managing Student Expectations”, Journal <strong>of</strong> Marketing Education, Vol. 28, No. 3, December,
pp 254-264.
326
No
Yes

Corina Pelau et al.
Athiyaman, A. (1997): Linking student satisfaction and service quality perceptions: <strong>the</strong> case <strong>of</strong> university education,
in: <strong>European</strong> Journal <strong>of</strong> Marketing, Vol. 31 No. 7, 1997, pp. 528-540.
Bena, I. (2010): Evaluation <strong>of</strong> Students’ Expectations within <strong>the</strong> Satisfaction Measurement in Higher Education
Services, in: Brătianu, C.; Lixăndroiu, D. and Pop, N. Al. (Ed.) <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 5th International <strong>Conference</strong>
on Business Excellence, Vol. 1, INFOMARKET, Brașov, pp. 63-66.
Bontis, N. (1998) “Intellectual capital: an exploratory study that develops measures and models”, Management
Decision, Vol. 36, No. 2, pp 63-76.
Bratianu, C. (2009), Dinamica cunostintelor, in Bratianu, C. (coord): Capitalul intelectual organizational, Editura ASE,
Bucuresti, pp. 9-38.
Brătianu, C. (2009) Capitalul intelectual organizational, Editura ASE, Bucuresti.
Chen, C.F. and Tsai, M.-H. (2009) “Perceived value, satisfaction, and loyalty <strong>of</strong> TV travel product shopping:
Involvement as a moderator”, Tourism Management, Vol. 29, pp 1166-1171.
DeShields, O.W. Jr; Kara, A. and Kaynak, E. (2005) “Determinants <strong>of</strong> business student satisfaction and retention in
higher education: applying Herzberg’s two-factor <strong>the</strong>ory”, International Journal <strong>of</strong> Educational Management, Vol.
19, No. 2, pp 128-139.
Douglas, J.; Douglas, A. And Barnes, B. (2006) “Measuring student satisfaction at a UK university”, Quality
Assurance in Education, Vol. 14, No. 3, pp 251-267.
Eggert, A. and Ulaga, W. (2002) “Customer perceived value: a substitute for satisfaction in business markets?”,
Journal <strong>of</strong> Business & Industrial Marketing, Vol. 17, No. 2/3, pp 107-118.
Grönroos, Ch. (2004) “The relationship marketing process: communication, interaction, dialogue, value”, The Journal
<strong>of</strong> Business & Industrial Marketing, Vol. 19, No. 2, pp 99-113.
Libbey, H.P. (2004): Measuring Student Relationships to School: Attachment, Bonding, Connectedness and
Engagement, in: Journal <strong>of</strong> School Health, September 2004, Vol. 74, No. 7, pp. 274-283.
Lovelock, C.H., Wirtz, J. (2004): Services marketing – People, technology, strategy, Pearson Prentice Hall, 5th
Edition.
Nonaka, I. (1991) “The Knowledge-Creating Company”, Harvard Business Review, November-December, pp 96-104.
Oldfield, B. M., Baron, S. (2000): Student perceptions <strong>of</strong> service quality in a UK university business and management
faculty, in: Quality Assurance in Education, Volume 8, Number 2,. pp. 85-95
O’Regan, P. and O’Donnel, D. (2000) “Intangible Asset Management: Recognizing, Valuing and Managing
Intellectual Capital”. In: Standford-Smith, B. and Kidd, P.T. (Eds.) E-business: key issues, applications and
technologies, IOS Press, Amsterdam, pp 353-366.
Pelau, C. (2010): The Relation between <strong>the</strong> Performance and Satisfaction <strong>of</strong> Students in Universities, in Bratianu, C.;
Lixandroiu, D.; Pop, N. Al.: Business Excellence, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 5th International <strong>Conference</strong> on Business
Excellence, Brasov.
Pelau, C; Vladoi, A. D.; Fufezan, M.; Dinca, V.; Ghinea, V. (2010): The Influence <strong>of</strong> Knowledge Dynamics on
Consumer Behavior, in: <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 2nd <strong>European</strong> <strong>Conference</strong> on Intellectual Capital, Lisbon, Portugal,
pg. 465-471.
Pop, N. Al.; Tanţău A.; Pelau, C. (2010): Education and New Collaborative Methods. Case Study: MBA
“Entreprenuership and Innovation Management, in: Rusu, C. (ed.): Quality Management in Higher Education,
<strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 6th International Seminar on <strong>the</strong> Quality Management in Higher Education, Tulcea,
Romania, 2010, pg. 659-662.
Priluck, R. (2003) “Relationship marketing can mitigate product and service failures”, The Journal <strong>of</strong> Services
Marketing, Vol. 17, No. 1, pp 37-52.
Seymour, D.T. (1993) On Q: Causing Quality in Higher Education, Oryx, Phoenix AZ.
Stewart, T.A. (1997) Intellectual Capital: The New Wealth <strong>of</strong> Organizations, Doubleday/Currency, New York.
Van den Berg, H.A. (2002) “Models <strong>of</strong> Intellectual Capital Valuation: A Comparative Evaluation”, Knowledge Summit
Doctoral Consortium 2002, [online],
http://www.wedb.net/download/valoracao/aula_4/capital_intelectual_models<strong>of</strong>icvaluation.pdf
327

Hierarchy and Tacit Knowledge in <strong>the</strong> Swedish Armed
Forces: An Organisational Approach
Ulrica Pettersson 1 and James Nyce 2
1 Lund University, Sweden
2 Ball State University, USA
ulrica.pettersson@fhs.se
jnyce@bsu.edu
Abstract: This paper describes in what ways hierarchical organizations influence <strong>the</strong> utilization and
dissemination <strong>of</strong> knowledge. Particular attention will be paid to <strong>the</strong> role that tacit knowledge has. The reporting
system <strong>of</strong> incidents is one element in a larger institutional process, <strong>of</strong>ten termed ‘lessons learned’ (LL). This
process helps to suggest solutions to identify shortcomings and facilitates in making positive experiences
durable. In organizational learning, <strong>the</strong>re is a need to get hold <strong>of</strong> valuable experience, in order to improve. A
serious weakness in several organizations seems to be that numerous experiences are poorly reported. A
common and well known reporting procedure is ‘after action reviews/reports’ (AAR), used e.g. by <strong>the</strong> US Army
and Marine Corps. It is essential that an effective reporting system presumes trust between informants/staff and
<strong>the</strong> organization <strong>the</strong>y work for. However, institutional belief and practice tends to reduce <strong>the</strong> effectiveness LL
might have. Our paper discusses some difficulties in <strong>the</strong> reporting system and makes some elements <strong>of</strong> <strong>the</strong>
problem more understandable. Some alternatives to standard operating practice will be outlined here that could
help remedy some <strong>of</strong> <strong>the</strong>se problems. The ‘just culture’ literature will be used to point out <strong>the</strong> direction
institutional redesign should take regarding responsibility and accountability. This paper could also help guide
future research in this area, by identifying critical assumptions, defining why certain problems need to be refined
and by looking at why current research techniques are not sufficient.
Keywords: trust, just culture, reporting system, disciplinary action, after-action review
1. Introduction
The objective <strong>of</strong> a learning organisation is to adjust <strong>the</strong> organisation’s ability to fit into and adapt to its
environment (Espejo, Schuhmann, Schwninger and Bilello 1996). To achieve something in
organizational learning, <strong>the</strong>re is a permanent need to get hold <strong>of</strong> valuable experience (success and
failure), in order to analyze, and instill improvements. A serious weakness can <strong>of</strong>ten be observed in
this reporting/collecting process. Several organizations seem to fail and numerous reports are also
poorly written. Within any large hierarchical organization <strong>the</strong>re is <strong>of</strong>ten a sizeable distance between
<strong>the</strong> top and bottom ranks. The result is that when problems are recognized <strong>the</strong>y <strong>of</strong>ten get “trapped”
somewhere along <strong>the</strong> chain <strong>of</strong> command. This tends to occur most frequently somewhere in <strong>the</strong>
middle layer <strong>of</strong> <strong>the</strong> hierarchy and this is one reason why some organizational <strong>the</strong>orists have argued
for reducing or ‘flattening’ command chains within <strong>the</strong> modern military organization. The Swedish
Armed Force (SwAF), like most military organizations is extremely hierarchical. Paradoxically, <strong>the</strong>
more discussion <strong>the</strong>re seems to be <strong>of</strong> ‘flattening hierarchies’ and ‘staff empowerment’, <strong>the</strong> more rigid
and hierarchical some organisations seem to become.
Initial position for this research can be found in difficulties a researcher (first author) had in recruiting
volunteers for an experimental study on mistakes and blunders that have occurred on SwAF
international missions. As <strong>the</strong> study went on, considerable attrition among <strong>the</strong> participants in <strong>the</strong>
experiment was observed (Pettersson 2010). Our paper also extends previous research which
concluded that organizational or pr<strong>of</strong>essional culture can prevent individuals from admitting mistakes
and blunders because <strong>the</strong>y fear <strong>the</strong> consequences <strong>the</strong>se admissions may have (Pettersson 2009).
This suggests <strong>the</strong>re is little interest, value, or reward for SwAF’s soldiers and <strong>of</strong>ficers in discussing
mistakes and blunders that took place in missions abroad.
The aim in our work is to discuss difficulties in <strong>the</strong> reporting system and make some elements <strong>of</strong> <strong>the</strong>
problem more understandable. The ‘just culture’ literature has been used to point out <strong>the</strong> direction
organizational redesign ought to take regarding responsibility and accountability. An organization
should encourage individuals to share knowledge and to reflect upon how and with whom <strong>the</strong>y share
it. If this is not done, knowledge can become commodified even fetishized. The result is that
knowledge is given an exchange value and becomes directly linked to <strong>the</strong> expression <strong>of</strong> power
(Ahrenfelt 1995).
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Ulrica Pettersson and James Nyce
How can we study problems <strong>of</strong>ficers meet given this hierarchy? This is necessary to understand if we
are to find solutions and make <strong>the</strong> kinds <strong>of</strong> changes that can reduce friction within <strong>the</strong> organization
and enable <strong>the</strong> organisation to adjust and change.
2. State <strong>of</strong> <strong>the</strong> art
Organizational learning can be defined as <strong>the</strong> creation, acquisition and transfer <strong>of</strong> innovative, ‘state <strong>of</strong>
<strong>the</strong> art’ practices throughout <strong>the</strong> organization.. This is considered effective when it increases <strong>the</strong>
organization’s ability to fit into and adapt to its environment (Espejo, Schuhmann, Schwninger and
Bilello 1996). However, <strong>the</strong>re is a difference between individual and organizational learning. Individual
learning occurs <strong>of</strong>ten when a mistake is observed and corrected, and when a mistake is defined as an
occasion where <strong>the</strong>re is ‘lack <strong>of</strong> fit’ between consequences and intentions (Argyris 1965, Espejo et al.
1996). Argyris (1965) argues that <strong>the</strong>re is a significant difference between experiential adaption and
learning from experience. There is, for example, no guarantee that an individual can learn something
simply through experience, however unique or significant it might be. To make a prediction we need
<strong>the</strong>ory. Without prediction, experience and examples teach nothing. “To copy an example <strong>of</strong> success
without understanding it with <strong>the</strong> aid <strong>of</strong> <strong>the</strong>ory may lead to disaster” (Deming, 2000 p.103).
Organizational learning on <strong>the</strong> o<strong>the</strong>r hand <strong>of</strong>ten occurs when knowledge is shared between groups in
<strong>the</strong> organization in order to influence its progress (Koutsoukis and Mitra 2003, Eden 2009).
Fur<strong>the</strong>rmore, to institute change, new processes or lessons learned in <strong>the</strong> organization must be
incorporated with discretion. Changes in an organization should also be well designed and motivated.
“The members <strong>of</strong> an organization or society for whom plans are made are not passive instruments,
but are <strong>the</strong>mselves designers who are seeking to use <strong>the</strong> system to fur<strong>the</strong>r <strong>the</strong>ir own goals” (Simon
1996, p.153). In an effort to succeed in making changes in an organization, a determining factor
seems to be organizational culture. This reflects <strong>the</strong> organization’s policies and attitudes towards
human error, trust and openness <strong>of</strong> communication between management and staff (Woods, Prineas,
Thavaravy, Beaumont and Cartmill 2003). According to Stewart (1997, p 1) intellectual capital is “…a
guide to <strong>the</strong> strategic and practical issues <strong>of</strong> identifying, capturing, and using knowledge to improve a
company’s competitive advantage. It explains not only why intellectual capital will be <strong>the</strong> foundation <strong>of</strong>
corporate success in <strong>the</strong> future, but also <strong>of</strong>fers practical guidance to companies about how to make
best use <strong>of</strong> <strong>the</strong>ir intangible assets”.
Reason (2000) describes two different approaches towards human error; a ‘person approach’ and a
‘system approach’. The first one focuses on <strong>the</strong> individual and his/her personal mistakes.
Fur<strong>the</strong>rmore, this approach tends to blame <strong>the</strong> persons involved in <strong>the</strong> problem. To do so seems to
be a serious weakness, as it isolates <strong>the</strong> error from <strong>the</strong> context where it occurred. Conversely <strong>the</strong>
system approach presumes that failure is a natural end result <strong>of</strong> all systems involving humans. In this
case <strong>the</strong> approach has total focus on <strong>the</strong> conditions and circumstances under which <strong>the</strong> problem
occurs. Reason (1997) also states that human reaction to making mistakes is almost never frank
confession. There could be several reasons for this, e.g. it will lead to extra work and scepticism <strong>of</strong>ten
exists regarding management’s willingness to act upon such reports. O<strong>the</strong>r issues involved concern
trust absence and fear <strong>of</strong> consequences. May my report damage my own or my colleague’s career?
Reason (1997) later stresses that <strong>the</strong> most significant element in a successful reporting program is
trust. Every organization with a reporting program must iteratively work to protect and promote this
cornerstone. A single case where an individual is punished for his/her report can undermine this trust.
This by extension can negatively impact not just <strong>the</strong> flow <strong>of</strong> reports but <strong>the</strong> reporting program itself.
“We cannot change <strong>the</strong> human conditions, but we can change <strong>the</strong> conditions under which humans
work” (Reason 2000 p 769).
A ‘just culture’ is an expression where individuals in <strong>the</strong> organisation in reality want and dare to be
open about mistakes and failures. A great number <strong>of</strong> organisations say <strong>the</strong>y want everything in <strong>the</strong>
open but in <strong>the</strong> bitter end <strong>the</strong>y do not tolerate everything. The solutions to create a ‘just culture’ could
be found in <strong>the</strong> balance between accountability and safety. All individuals should feel comfortable
reporting accident and failures. The absolutely most important component in a ‘just culture’
organisation is trust (Dekker 2007, Reason 1997).
In medicine, which is <strong>of</strong>ten practiced in large, very hierarchical organizations, we can find <strong>the</strong> same
problem regarding incidents and reports. Lucian and Leape (1994) state that <strong>the</strong> most important
reason that nurses and physicians have not developed a more effective method <strong>of</strong> error prevention is
to be found in <strong>the</strong> culture <strong>of</strong> medical practice. Bosk’s study (2003) <strong>of</strong> medical error comes to much <strong>the</strong>
same conclusion. To improve hierarchical organizations, staff must accept that errors are an
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inevitable part <strong>of</strong> <strong>the</strong> human condition (Lucian and Leape 1994). This is also confirmed by Dekker
(2009a) when he argues that <strong>the</strong> first step to a just organization is a normalization <strong>of</strong> incidents. Many
investigations <strong>of</strong> failure are focused on finding who was responsible and we <strong>of</strong>ten want to find ‘who’
did not do <strong>the</strong>ir job and in extension ‘put <strong>the</strong> accident on <strong>the</strong>ir account’ (2009b). One fundamental
point in <strong>the</strong> organizational learning process is to understand <strong>the</strong> distinction between evaluation and
analysis. “Analysis is a process used to thoroughly understand areas <strong>of</strong> activity identified to have
potential for improvement.” (Eaton, Redmayne and Thordsen 2007, p. 4). No form <strong>of</strong> attaching a value
should be included in analysis; an analysis is a way <strong>of</strong> looking at something in different ways and
developing understanding about it (Eason et al 2007). Malhotra (2007) states, staff must be motivated
to share accurate and timely information within <strong>the</strong> organization. Fur<strong>the</strong>rmore, he stresses that this
can only occur in a culture and organization in which trust is possible. To achieve this, as Senge
(1995) points out, an organization sometimes has to devalue, if not sacrifice, selfishness and selfinterest.
2.1 Aversion to truth
The ability to report mistakes and difficulties calls for an organizational culture that can admit mistakes
and does not punish <strong>the</strong> messenger (Dekker 2009b). In any organization, human errors seem to be
even more difficult to report than technical incidents (Carlemalm 2009). This is because, according to
Ahrenfelt (1995), individuals can be exposed to negative consequences while delivering reports that
superiors do not like. In addition, falsification or <strong>the</strong> embellishment <strong>of</strong> <strong>the</strong> reality can become a tool
that provides upwards mobility. This in fact can be <strong>the</strong> main obstacle to change in an organisation. “If I
don’t do anything, I don’t make any mistakes, and I will not be punished. If I’m not punished, I’m
almost rewarded.” (Ahrenfelt 1995, p.170). In o<strong>the</strong>r words, objective knowledge is seldom <strong>the</strong> platform
upon which an individual’s career and position in an organization advances or rests (Ölçer 2007,
Malhotra 2007). There is a clear sense that any discussion <strong>of</strong> mistakes can damage an individual’s
career. “Knowledge is not just about success stories. If you can encourage employees to record <strong>the</strong>ir
mistakes with no fear <strong>of</strong> fur<strong>the</strong>r action, you will be able to build a truly useful knowledge repository.
With it your organization will be less likely to repeat previous mistakes and able to make decisions
quicker” (Lucier 2003, p. 3). In general <strong>the</strong>re is an unwillingness to admit mistakes for fear <strong>of</strong>
consequences. This organizational ‘fact’ <strong>of</strong>ten conflicts with one <strong>of</strong> <strong>the</strong> core values <strong>of</strong> <strong>the</strong> <strong>of</strong>ficer corps
– to be honest and truthful to one’s bro<strong>the</strong>rs. It is this conflict that fuels much <strong>of</strong> <strong>the</strong> resistance <strong>the</strong>
military has to organizational redesign. It also is responsible for reducing many change and innovation
initiatives in <strong>the</strong> military to something more like window dressing than anything else
2.2 Swedish Armed Forces, a learning organisation?
The SwAF presents itself, as many modern military forces do, as a learning organization (SwAF HQ b
2009). However, in reality <strong>the</strong> organisation is far from fulfilling this requirement (Carlemalm 2009,
Pettersson 2009, 2010). Carlemalm (2009) demonstrates that <strong>the</strong>re is a deficiency in <strong>the</strong> SwAF’s
reporting system, in that reports that describe behaviour outside <strong>the</strong> norm seem to be
unrepresentative in number and kind. This is particularly <strong>the</strong> case in flying operations reports where
<strong>the</strong> link between individual actions and mistakes or error seems so clear.
Every <strong>of</strong>ficer’s competence is measured and his/her promotion is dependent, to a large part, on an
annual written evaluation. This evaluation consists <strong>of</strong> two parts, a certificate <strong>of</strong> that year’s service and
a promotion recommendation written by one’s immediate superior in <strong>the</strong> chain <strong>of</strong> command (SwAF
HQ 1997). Considering <strong>the</strong> <strong>of</strong>ficer’s dependence upon this annual evaluation, one can assume that
personal mistakes and blunders are self reported to one’s chief very infrequently. The result is that
problems <strong>of</strong>ficers encounter in <strong>the</strong> organization are seldom analysed and (re)solved, and <strong>the</strong>
possibilities to reduce frictions in <strong>the</strong> organization remain limited. Over time this could have a less
than beneficial effect for <strong>the</strong> organization.
As most armed forces, <strong>the</strong> SwAF have a ‘set <strong>of</strong> rules and regulations’, containing e.g. disciplinary
action. A superior’s report can have a number <strong>of</strong> consequences for a subordinate. Consequences,
can be divided into two main groups, authorized and unauthorized. First, <strong>the</strong> SwAF personnel
management can, when warranted, administer disciplinary actions that range from a warning, a
temporary or permanent change in position, discharge from <strong>the</strong> service and legal action (SwAF HQ
1997, LAS 1982). Secondly, <strong>the</strong>re are fewer formal disciplinary actions, for example salary reduction,
poor annual written records, suspension <strong>of</strong> education and shifts in assignment (SwAF HQ a 2009). In
any case, <strong>the</strong> balance between what an <strong>of</strong>ficer has done and <strong>the</strong> disciplinary actions taken and justice
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in <strong>the</strong> present system is muddy at best. According to Dekker (2009a) <strong>the</strong>re must be clarity in ‘who
draws <strong>the</strong> line’, and <strong>the</strong>re has to be a balance between <strong>the</strong> individual and <strong>the</strong> organizational
responsibility. It may be necessary for SwAF to make <strong>the</strong> link between punishment and end or desired
result clearer to all involved. There are two traditional <strong>the</strong>ories as to why reprimands and punishment
are used; absolute and relative. Absolute punishment, e.g. retribution, is given purposely to cause
suffering, while relative punishment intends to prevent unwanted behaviour through intimidation. A
‘just culture’ perspective does not support this criminalization <strong>of</strong> human error. To punish people for
human error will not decrease errors, just <strong>the</strong> number <strong>of</strong> errors reported (Reason 1997, Dekker
2009a).
3. Discussion
Today, <strong>the</strong> SwAF, like most armed forces, faces new and additional responsibilities. The majority <strong>of</strong>
<strong>the</strong>m involve operations in new and sometimes unfamiliar environments and cultures around <strong>the</strong>
globe (Smith 2007). This necessitates that learning organisations become more effective, which
means that <strong>the</strong> forces have to identify and implement improvements more rapidly than before. Such
change cycles require a more efficient, equitable lessons learned process (Eden 2009, NATO SG
2008). For such a process to work, it must be implemented in an organizational culture where learning
is accepted and supported. This is an organization that does not search for scapegoats and one
where incidents are normalized (Dekker 2009a, Dekker 2009b). There is a need in particular for <strong>the</strong>
military, where costs do not just include capital but also human injuries and lives, to develop “…a
culture where errors and deviation are regarded not as humans’ failures, but as opportunities to
improve <strong>the</strong> system….” (Lucian and Leape 1994, p. 1857).
Because hierarchy, responsibility, and status are equated with rank and competence in <strong>the</strong> military
and because this is not going to ‘disappear’, <strong>the</strong> problem is how to get ‘bad news’ heard and acted
upon. One solution would be to have <strong>the</strong> SwAF’s reporting structures redesigned in <strong>the</strong> direction <strong>of</strong> a
‘just culture’ where both <strong>the</strong> notion <strong>of</strong> responsibility and report are reinvented. Perhaps <strong>the</strong> closest
analogy in <strong>the</strong> research literature to SwAF’s traditional practices and belief regarding responsibility is
<strong>the</strong> critical incident technique (Flanegan 1954). Here, as in most military organizations, both
responsibility and after action reporting rest on <strong>the</strong> individual. Even in <strong>the</strong> SwAF operations outside
<strong>the</strong> country this still tends to be <strong>the</strong> case. In <strong>the</strong> present reporting system, SwAF staff that expose
shortcomings only face negative consequences and seldom receive any compensation, reward or
appreciation. This means, toge<strong>the</strong>r with <strong>the</strong> link that presently exists between action and discipline in
<strong>the</strong> present system, <strong>the</strong> organization does not provide <strong>the</strong> kind <strong>of</strong> platform that a learning organization
requires. To improve <strong>the</strong> organization’s reporting system, <strong>the</strong> SwAF ought to import norms, values
and behaviour associated with ‘just culture’. This would mean that <strong>the</strong> disciplinary system would have
to be redesigned and all <strong>the</strong> parties involved in <strong>the</strong> reporting system better protected (Carlemalm
2009).
A ‘just culture’ is not something that can be applied from outside, say by consultants, or normatively
by fiat. In fact, <strong>the</strong> management in <strong>the</strong> SwAF must understand that <strong>the</strong> basis for a transformation into
a ‘just culture’ should begin within <strong>the</strong>ir own organization, by understanding its history, traditions and
beliefs. First <strong>the</strong>n, it is possible to influence and make changes in those important pillars in order to
attain a transformation. The SwAF ought to learn and accept that incident must not be a failure; an
incident should be looked upon as a great opportunity to learn. The organization should avoid all sorts
<strong>of</strong> penalties after an incident; <strong>the</strong>re is no scapegoat to hunt down! On <strong>the</strong> contrary, it should in
advance be crystal clear who will act upon an incident- it must not be a superior, part <strong>of</strong> <strong>the</strong>
organization line. The civilians, soldiers and <strong>of</strong>ficers should know <strong>the</strong>ir rights (and responsibilities). A
debriefing program ought to be implemented in <strong>the</strong> SwAF, to normalize incidents and to support <strong>the</strong>
organization’s members after an incident (Dekker 2009a, 2009b). Implementing an efficient reporting
system in <strong>the</strong> SwAF is not just about realizing a new technical system, it is much more about all
members’ beliefs and ambition to be a part <strong>of</strong> and contribute to <strong>the</strong> organization’s progress and future.
No doubt, lack <strong>of</strong> trust and confidence in <strong>the</strong> own organisation will seal people’s lips. One should bear
in mind, trust is extremely hard to build and tremendously easy to break (Dekker 2007)!
4. Conclusion
If <strong>the</strong> reporting system could be reinvented so as to integrate SwAF’s core values and assumptions
regarding <strong>of</strong>ficers, and with what we now know about ‘just culture’ in complex organizations, this
would help SwAF adapt to today’s fast changing operational environments. It would also enable <strong>the</strong>
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military to respond more appropriately to its new demands and responsibilities. As for <strong>the</strong> organization
itself, <strong>the</strong>se changes would help drive correct institutional redesign because <strong>the</strong>y would encourage
staff participation in <strong>the</strong> organization’s improvement processes.
References
Ahrenfelt, B. (1995) Förändring som tillstånd [Change as a State], Studentlitteratur, Lund.
Argyris, C. (1965) Personality and Organization <strong>the</strong> conflict between system and <strong>the</strong> individual, Harper & Row,
New York.
Bosks, C. L. (2003) Forgive and Remember, Managing Medical Failure, The University <strong>of</strong> Chicago Press,
Chicago.
Carlemalm, P. (2009) Just culture or Just culture? B.A. <strong>the</strong>sis, Swedish National Defence College, Stockholm.
Dekker, S. W. A. (2009a) “Just culture: who gets to draw <strong>the</strong> line?”, Cognition Technology and Work, Vol 11, No.
3, pp 177-185.
Dekker, S. W. A. (2009b) Just culture Balancing Safety and Accountability, Ashgate Publishing Limited, Surrey.
Deming, E. (2000) The New Economics - for Industry, Government, Education, <strong>the</strong> MIT Press, London.
Eden, A. (2009) Joint Analysis Handbook, NATO Joint Analysis Lessons Learned Centre, Lisbon.
Eaton, J., Redmayne, J. and Thordsen M. (2007) Joint Analysis Handbook, NATO Joint Analysis Lessons
Learned Centre, Lisbon.
Espejo, R., Schuhmann, W., Schwninger, M. and Bilello, U. (1996) Organizational Transformation and Learning,
John Wiley & Sons, West Sussex.
Flanegan, J. C. (1954) “The Critical Incident Technique”, Psychological Bulletin, Vol 53, No. 4, pp 327-358.
Koutsoukis, N. S. and Mitra, G. (2003) Decision Modeling and Information Systems: <strong>the</strong> information value chain,
Kluwer Academic Publishers Group, Dordrecht.
LAS (1982) Arbetsmarknadsdepartementet-Lag (1982:80) om anställningsskydd [Swedish Law Job Security
(1982:80)].
Lucier, C. (2003) “When knowledge adds up to nothing – Why knowledge management fails and what you can do
about it”, Developed and Learning in Organizations, Vol 17, No. 1, pp 32-35.
Lucian, L. and Leape, M.D. (1994) “Error in Medicine”, Journal <strong>of</strong> <strong>the</strong> American Medical Association, Vol 272, No.
23, pp 1851-1857.
Malhotra, Y. (2007) Knowledge Management Lessons Learned - What works and What Doesn’t, Information
Today, Inc. New Jersey.
NATO SG (2008) North Atlantic Treaty Organization Secretary General. 0806 (INV), NATO Unclassified.
Ölçer, F. (2007) “Practices <strong>of</strong> Knowledge Management in Companies: A Turkey Survey”, <strong>Proceedings</strong> <strong>of</strong> I-
KNOW´07, Graz.
Pettersson, U. (2010) “Acquisition <strong>of</strong> Experience-based Knowledge from <strong>the</strong> Swedish Armed Forces International
Missions; A Comparison between Groups and Individual Performances”, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 7 th International
<strong>Conference</strong> on Intellectual Capital, Knowledge Management & Organizational Learning, Hong Kong.
Pettersson, U. (2009) “Utilization <strong>of</strong> Knowledge in <strong>the</strong> Swedish Armed Forces”. Journal <strong>of</strong> Universal Computer
Science, Vol 15, No. 8, pp 1735-1743.
Reason, J. (2000) “Human error: models and management”, British Medical Journal, Vol. 320,
pp. 768-770.
Reason, J. (1990) Human Error, Cambridge University Press, New York.
Reason, J. (1997) Managing <strong>the</strong> Risks <strong>of</strong> Organizational Accidents, MPG Books Ltd, Cornwall.
Simon, H. (1996) The Science <strong>of</strong> <strong>the</strong> Artificial, The MIT Press, Massachusetts.
Senge, P. (1996) Den femte diciplinen [The Fifth Dicipline], Nerenius & Santérus Förlag, Falun.
Smith, R. (2007) The Utility <strong>of</strong> Force: <strong>the</strong> art <strong>of</strong> war in <strong>the</strong> modern world, Random House Inc., New York.
Stewart, T. A. (1997) “Intellectual Capital: The New Wealth <strong>of</strong> Organization” Qfinance,
http://www.qfinance.com/human-and-intellectual-capital-finance-library/intellectual-capital-<strong>the</strong>-new-wealth<strong>of</strong>-organizations
Swedish Armed Forces Head Quarter a. (2009) Verksamhetsregler Personalförsörjning [-Personnel
Management].
Swedish Armed Forces Head Quarter b. (2009) No. 23 290: 536 04, LL process.
Swedish Armed Forces Head Quarter (1997) Handbok för personaltjänst 6:7 [- Handbook Staff].
Woods, B., Prineas, S., Thavaravy, R., Beaumont, G. and Cartmill, H. (2003) “Where to start? Achieving a just
culture in health care”, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> Australian Aviation Psychology <strong>Conference</strong> (medical track),
Sydney.
332

An Alternative to <strong>the</strong> Crystal Ball: Participatory
Approaches for Sustainable Management
Katja Pook 1 and Campbell Warden²
1 pook perspectives, Goettingen, Germany
²Instituto de Astr<strong>of</strong>isica de Canarias, La Laguna, Tenerife, Spain
mail@pook-perspectives.net
campbell@iac.es
Abstract: The most reliable way to forecast <strong>the</strong> future is to try to understand <strong>the</strong> present." 1 (John Naisbitt)
Humankind has a great ability to learn by using reflection on past and present incidents, actions and perceived
cause-effect relationships for designing and optimising future behaviour. These capabilities bear an <strong>of</strong>ten
underestimated potential for business, research, (public) investment and policy making. The challenge is to
harness and focus <strong>the</strong>se latent resources by means <strong>of</strong> adequate methods. This paper discusses knowledgebased
methods <strong>of</strong> Technology Foresight (TF) and Intellectual Capital Management (ICM) and extracts
commonalities and differences. It also includes some examples and discusses concrete challenges in <strong>the</strong>
process <strong>of</strong> applying <strong>the</strong>se methods. In general, ICM/ICR and Foresight are participatory methods that endeavour
to use current knowledge for shaping future actions. They bring people toge<strong>the</strong>r in a social process to elaborate
on individual experiences and expertise, to create a common language, structure collective thought and enable
appropriation by decision-makers. They contribute to organisational and regional risk management, knowledge
management, organisational learning and instantiate democratic principles in early phases <strong>of</strong> decision-making
processes. This implies in most cases, in <strong>the</strong> private as in <strong>the</strong> public sector, a change in organisational culture,
<strong>of</strong>ten underestimated or even ignored. Too little consideration <strong>of</strong> <strong>the</strong>se requirements harbours a risk for <strong>the</strong>
success and <strong>the</strong> continuous application <strong>of</strong> this kind <strong>of</strong> methods. This paper extracts basic principles <strong>of</strong> TF and
ICM and elaborates on pre-requisites and practical recommendations for <strong>the</strong> successful use <strong>of</strong> knowledge-based
methods to integrate individual knowledge and multiple perspectives in management decision-making. It also
discusses some <strong>of</strong> <strong>the</strong> challenges and risks when introducing participatory methods in hierarchical, or
individualistic, cultures with established power structures.
Keywords: technology foresight, innovation foresight, intellectual capital management, intellectual capital
reporting, knowledge management, strategic decision making
1. Introduction
“The capabilities <strong>of</strong> civilization to build a better future are rich, but terribly inefficient. Improving
efficiency requires seeing <strong>the</strong> status <strong>of</strong> <strong>the</strong> whole and its parts as objectively as possible.” These
words, introducing <strong>the</strong> 2006 State <strong>of</strong> <strong>the</strong> Future publication <strong>of</strong> UN University (Glenn & Gordon, 2006)
resemble <strong>the</strong> general notion that humankind has a great ability to learn by using reflection on past and
present incidents, actions and reactions, for designing and optimising future behaviour. At <strong>the</strong> same
time, <strong>the</strong>se capabilities are <strong>of</strong>ten insufficiently valued for improving business competitiveness and
sustainability, in research, (public) investment and policy making. However, one <strong>of</strong> <strong>the</strong> biggest
challenges in this enterprise is that <strong>of</strong> balancing consistency over time (past, present, future) on <strong>the</strong>
one hand and creativity, openness and innovativeness on <strong>the</strong> o<strong>the</strong>r.
This paper chooses two methodological approaches for integrating individual knowledge into
corporate, or regional, decision making for future investments and strategic direction. This is not done
in an exhaustive way, but ra<strong>the</strong>r in taking <strong>the</strong>m as a starting point to evaluate <strong>the</strong> potential <strong>of</strong>
integrating a certain element <strong>of</strong> democracy into organisational and regional strategic management.
2. Intangibles in strategy management: A paradigm shift for decision making
The era <strong>of</strong> mechanistic models as analogies for organisations is supposed to be over, giving way to
metaphors taken from biology and evolution (e.g. Lazlo et al, 1992), but in practical life, many
strategic decisions are still based on <strong>the</strong> former paradigm. Systems <strong>the</strong>ory approaches and biological
analogies only slowly make <strong>the</strong>ir way into organisational decision-making. The shift in paradigm is a
shift <strong>of</strong> mental models and resulting action, such as, “The world as we know it bears <strong>the</strong> stamp <strong>of</strong> our
own conceptual activity” (Putnam; cited by Howe & Berv, 2000, S. 24). Changing world views takes
1 http://thinkexist.com/quotes/john_naisbitt/2.html
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Katja Pook and Campbell Warden
time, however it is becoming urgent in order to survive and live in our complex and fast changing
environment 2 .
According to a systems approach, any organisation lives in its environment and depends on it
(compare e.g. Weismann & Feige, 1997). The new paradigm in management requires methods and
instruments to sharpen <strong>the</strong> “senses” <strong>of</strong> an organisation, a region or a nation, to estimate possible
futures, evaluate options for action and effectively adapt to, and shape, its environment in both <strong>the</strong>
medium and long term (<strong>the</strong> ‘market’ for pr<strong>of</strong>it companies; ‘global technological developments’ for a
nation’s labour market, etc.). Technology Foresight (TF) and Intellectual Capital Management (ICM)
provide such methods.
This leads us to <strong>the</strong> notion <strong>of</strong> sustainability.
3. Challenges for sustainable development
According to <strong>the</strong> UN Millennium Project 3 <strong>the</strong> 15 global challenges include (among o<strong>the</strong>rs) <strong>the</strong>
following questions:
4. How can genuine democracy emerge from authoritarian regimes?
5. How can policymaking be made more sensitive to global long-term perspectives?
9. How can <strong>the</strong> capacity to decide be improved as <strong>the</strong> nature <strong>of</strong> work and institutions change?
14. How can scientific and technological breakthroughs be accelerated to improve <strong>the</strong> human
condition?
(Source: http://www.millennium-project.org/millennium/challeng.html)
Although referring to a global worldview, <strong>the</strong>se challenges, when it comes to managing development
sustainably, have to be faced at global, regional, national, organisational and even team levels.
The methods discussed in this paper address questions <strong>of</strong> democratic principles, sensitivity to global
long-term perspectives, decision-making capacity in a complex, continually changing, environment as
well as ways to speed-up and focus developments. These processes rely to a large extent on
intangible factors: knowledge, experience and communication among a variety <strong>of</strong> partners and
perspectives; especially in <strong>the</strong> context <strong>of</strong> Knowledge Based societies and economies. In recent years,
we have – again – experienced what happens when existing resources are not managed and
exploited in an intelligent way and considering more than (singular) individual benefits.
Knowledge acquisition and capability building, both in firms and regions, is as much about <strong>the</strong> abilities
<strong>of</strong> “scanning” and “drawing-in” external technology and managing co-operations, as it is about
programs for R+D and Higher Education. Among <strong>the</strong> key issues is <strong>the</strong> challenge to align possibilities
and capabilities for effective development – and to balance several perspectives and interests in one
coherent process.
4. Approaches to incorporate intangibles in strategy management:
Technology foresight and intellectual capital management
From <strong>the</strong> wide range <strong>of</strong> methods and approaches for managing intangible factors in strategy
management two are discussed here: Technology Foresight and Intellectual Capital Management, as
an extension <strong>of</strong> Intellectual Capital Reporting (ICR) (e.g. Flicker & Pook, 2007).
Foresight has its roots in <strong>the</strong> public policy making sector in an endeavour to identify future key generic
technologies and has since been employed in a wide variety <strong>of</strong> socio-economic scenarios and scales.
ICR 4 approaches appreciate intangible factors as crucial for corporate success, and provide methods
2
When we speak <strong>of</strong> “environments” we refer to <strong>the</strong> term in a general sense, embracing social, political, ecological and
economic factors
3
The UN Millenium Project is an example <strong>of</strong> a transnational, transinstitutional enterprise which goes a lot fur<strong>the</strong>r than <strong>the</strong> scope
<strong>of</strong> this paper. Never<strong>the</strong>less, <strong>the</strong> directions <strong>of</strong> <strong>the</strong> project are useful for relating specific organisational challenges to global ones.
4
The developed approaches are for reporting. In <strong>the</strong> following sections we talk about ICM again, including <strong>the</strong> entire
management cycle.
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Katja Pook and Campbell Warden
to report on <strong>the</strong>m. They have also been used by regions/cities (for examples see e.g. <strong>the</strong> <strong>European</strong>
RICARDA project and its report, 2007). While coming from different directions, <strong>the</strong> approaches show
common features. Foresight and ICM/ICR can contribute to a perspective that goes beyond shortterm
decisions. They widen <strong>the</strong> view by integrating multiple perspectives, focussing on resources and
being oriented towards possible futures and our actions for lasting, sustainable effects.
Basic common features:
Using individual experience and expertise
Collaborative knowledge construction
Multi-perspectiveness
Extrapolation from experience to possible futures
For participants and organisers 5 to manage effectively <strong>the</strong> key social processes that can ‘harness’
individual experience and expertise it is necessary to provide an environment where individuals are
ready and willing to share <strong>the</strong>ir knowledge for <strong>the</strong> benefit <strong>of</strong> a group (an organisation, a region, a
nation). Although knowledge is generically individual (e.g. Loveridge, 2006), achieving organizational
sustainability is both a collective and an inclusive process. Successful application <strong>of</strong> TF and ICM
practices depends basically on integrating individuals and multiple perspectives in a group process <strong>of</strong>
collaborative knowledge construction (see e.g. Cook & Brown, 1999) to achieve a social construction
<strong>of</strong> reality and socially shared cognition (Resnick, Levine & Reasley, 1991).
The fourth basic feature is to relate individual knowledge and experiences <strong>of</strong> <strong>the</strong> past to possible
future developments and create a knowledge base for good and sustainable decisions about future
actions and investments. It is in this sense that participatory approaches for sustainable management
<strong>of</strong>fers an alternative to <strong>the</strong> ‘Crystal Ball’, because this future-orientation will clearly shape <strong>the</strong> mind-set
<strong>of</strong> <strong>the</strong> participants and shed a productive and visionary light on <strong>the</strong> enterprise.
Involving experts implies a responsibility <strong>of</strong> <strong>the</strong> organisers as well as <strong>the</strong> decision makers. It
challenges <strong>the</strong> isolated power <strong>of</strong> decision makers in <strong>the</strong> sense that it brings democratic mechanisms
into play (see point 4 <strong>of</strong> <strong>the</strong> global challenges named by <strong>the</strong> UN Millennium Project): It requires
acceptance <strong>of</strong> a multiplicity <strong>of</strong> perspectives and opinions, and a tolerance <strong>of</strong> ambiguity (e.g. Furnham
and Ribchester, 1995). Statements laid on <strong>the</strong> table can no longer be ignored. Participants require
certain kinds <strong>of</strong> information as well as transparency from management.
In <strong>the</strong> typically large groups <strong>of</strong> participants (especially in TF) it is especially hard to introduce <strong>the</strong> ties
that help people to be productive in a collaborative setting (see <strong>the</strong> RICARDIS report on <strong>European</strong>
ICR methods, 2006): Shared Goals, Shared Culture, Shared Learning, Shared Effort, and Shared
Information. The development <strong>of</strong> a 'shared context’ (Nonaka & Kono 1998) plays an important role in
achieving all <strong>of</strong> this and depends on <strong>the</strong> development <strong>of</strong> trust among <strong>the</strong> participants and between <strong>the</strong>
sponsor, <strong>the</strong> manager and <strong>the</strong> stakeholders.
4.1 Technology foresight
Technology Foresight is merely a cluster <strong>of</strong> methods and options to combine <strong>the</strong>m. It is important to
flexibly select methods and adapt <strong>the</strong> process to <strong>the</strong> specific situation, culture and goals in every
scenario. Examples <strong>of</strong> <strong>the</strong> methods used in TF are shown in Figure 1 (see also <strong>the</strong> UNIDO
Technology Foresight Manual, 2005).
Weber & Havas (2007) <strong>of</strong>fer <strong>the</strong> following description <strong>of</strong> <strong>the</strong> values <strong>of</strong> a foresight exercise, “Foresight
processes bring toge<strong>the</strong>r not only experts, but also decision-makers from research, industry, policymaking
and society, and thus a shared understanding <strong>of</strong> current problems, goals and development
options can be expected to emerge among those actors that have an important role to play in shaping
<strong>the</strong> future. This converging understanding <strong>of</strong> <strong>the</strong> issues at play is likely to contribute to improving
implicitly <strong>the</strong> coherence <strong>of</strong> <strong>the</strong> distributed decisions <strong>of</strong> <strong>the</strong>se actors, in line with <strong>the</strong> shared mental
framework <strong>the</strong>y have developed. In o<strong>the</strong>r words, aligning expectations, (...) is a way to shape <strong>the</strong>
5 Organisers <strong>of</strong> <strong>the</strong> social interaction process with certain goals
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future. These so-called process outputs are <strong>of</strong>ten regarded as more important than <strong>the</strong> actual
substantive (or tangible) outputs, like reports and websites” (paraphrased by <strong>the</strong> authors).
Keenan & Popper (2007) provide an up-to-date description <strong>of</strong> what is involved in TF:
“The term ‘foresight’ refers to an open and collective process <strong>of</strong> purposeful, future
oriented exploration, involving deliberation between heterogeneous actors in science and
technology arenas, with a view to formulating shared visions and strategies that take
better account <strong>of</strong> future opportunities and threats.”
Figure 1: Five mental acts and methods (Saritas, 2007)
For <strong>the</strong> sake <strong>of</strong> clarity, it is worthwhile at <strong>the</strong> outset to point out that Foresight is not: Futurology,
Strategic Planning, Forecasting & Prediction.
To elaborate on <strong>the</strong> positive description <strong>of</strong> TF, Keenan and Popper (2007) set out some essential
principles <strong>of</strong> foresight:
Principle <strong>of</strong> future-orientation: Foresight is a future-oriented activity, though not in a predictive
sense. It assumes that <strong>the</strong> future can evolve in different directions, depending upon <strong>the</strong> actions <strong>of</strong>
various players and <strong>the</strong> decisions taken today. In o<strong>the</strong>r words, <strong>the</strong> future can be actively shaped.
Principle <strong>of</strong> participation: Foresight values <strong>the</strong> multiplicity <strong>of</strong> perspectives, interests, and
knowledge held across a dispersed landscape <strong>of</strong> actors, and seeks to bring <strong>the</strong>se toge<strong>the</strong>r in
processes <strong>of</strong> deliberation, analysis, and syn<strong>the</strong>sis. Thus, foresight involves a wider number <strong>of</strong>
different groups <strong>of</strong> actors concerned with <strong>the</strong> issues at stake. Moreover, <strong>the</strong> results <strong>of</strong> foresight
<strong>of</strong>ten have implications for a wide variety <strong>of</strong> actors, so it is important to involve <strong>the</strong>se as far as
possible throughout <strong>the</strong> process.
Principle <strong>of</strong> evidence: Foresight relies upon informed opinion and interpretation, as well as
creative approaches in formulating conjectures on <strong>the</strong> future. However, <strong>the</strong>se are seldom
sufficient on <strong>the</strong>ir own and are complemented with various sorts <strong>of</strong> data from trend analyses and
forecasting, Bibliometrics, and <strong>of</strong>ficial statistics, among o<strong>the</strong>r sources. Clearly, <strong>the</strong> future cannot
be known with certainty and it is impossible to test conjectures on <strong>the</strong> future exhaustively.
However, <strong>the</strong> plausibility <strong>of</strong> conjectures – as well as <strong>the</strong> original insights that <strong>the</strong>y bring – are
essentially ‘market tested’ by <strong>the</strong> decision-makers who rely upon such information.
Principle <strong>of</strong> multidisciplinarity: Foresight recognises that many <strong>of</strong> <strong>the</strong> problems we face today
cannot be understood from a single perspective. Accordingly, foresight intentionally seeks to
transcend traditional epistemic boundaries, bringing toge<strong>the</strong>r different disciplines in processes <strong>of</strong>
deliberation that result in improved understanding and new working relationships.
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Principle <strong>of</strong> coordination: Foresight enrols multiple actors to participate in decision arenas where
conjectures on <strong>the</strong> future are contested and debated. Supported by various data and opinions, <strong>the</strong>
foresight process aligns participant actors around emergent agendas, resulting in a coordinated
mobilisation <strong>of</strong> people and resources.
Principle <strong>of</strong> action orientation: Foresight is not only about analysing or contemplating future
developments but also supporting actors to actively shape <strong>the</strong> future. Therefore, foresight
activities should only be undertaken when it is possible to act on <strong>the</strong> results.
(Based on <strong>the</strong> “ForeIntegra-RI: Practical Guide for integrating Foresight in Research Infrastructures
Policy Formulation”, 2007).
4.2 Intellectual capital management
“The traditional accounting model is based on <strong>the</strong> principle <strong>of</strong> historic cost (...). In providing a record <strong>of</strong>
what has happened in <strong>the</strong> past, historic cost accounts provide a useful starting point in assessing <strong>the</strong>
performance <strong>of</strong> a business. However, without forward looking information, <strong>the</strong> picture that <strong>the</strong>y
provide is incomplete. IC Statements take a different and complementary stance by considering those
things that are valuable in evaluating <strong>the</strong> future (ra<strong>the</strong>r than only <strong>the</strong> past).” (RICARDIS report, 2006,
p7.) The gap between book value and fair market value led to <strong>the</strong> realisation <strong>of</strong> <strong>the</strong> importance <strong>of</strong>
intangible assets and resulted in models for Intellectual Capital Reporting. Intellectual Capital is
mostly conceptualised as intangible assets, covering human, structural and relational capital (e.g.
MERITUM, 2002; German guidelines for ICR (2004); or <strong>the</strong> RICARDIS report (2006), see Figure 2).
Figure 2: Intellectual capital roots <strong>of</strong> an organisation (RICARDIS report, 2006, p. 17)
In <strong>the</strong> existing methods for IC reporting (ra<strong>the</strong>r than full-cycle managing) <strong>the</strong> degree <strong>of</strong> collaborative
knowledge sharing is quite different (compare e.g. <strong>the</strong> Austrian model according to <strong>the</strong>
Universitaetsgesetz and <strong>the</strong> German model, which is based to a large part on personal interaction in
workshops). In this article we refer to methods with a high degree <strong>of</strong> interaction. ICM is an extension,
including not only <strong>the</strong> reporting, but a full management cycle for continuous development.
As is <strong>the</strong> case in Technology Foresight, in ICM <strong>the</strong> process <strong>of</strong> collaborative knowledge exchange and
creation is <strong>the</strong> most valuable, at least for organisational/regional development, because it involves
ga<strong>the</strong>ring multiple perspectives on strategically relevant issues, drawing <strong>the</strong> “big picture” 6 <strong>of</strong> <strong>the</strong>
present and future <strong>of</strong> <strong>the</strong> organisation/region in its environment.
6 In air traffic control, <strong>the</strong> controllers each day at work have to get “<strong>the</strong> picture” before starting to manage <strong>the</strong> direction <strong>of</strong>
individual aircraft in upper air space. We should use this for management
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Katja Pook and Campbell Warden
Although coming from different directions (public sector and policy making on <strong>the</strong> one hand, small and
medium enterprises on <strong>the</strong> o<strong>the</strong>r) TF and ICM show some major commonalities, which have already
been explained above and shall only be summarised here. These points do not claim to be exhaustive
but capture some <strong>of</strong> <strong>the</strong> basic features that TF and ICM have in common:
Collaborative knowledge construction;
Considering multiple individual perspectives to provide an extensive scope <strong>of</strong> opinions and views;
Importance <strong>of</strong> thorough selection <strong>of</strong> participants;
Moderated process (combination <strong>of</strong> subject experts and facilitators for communication);
Require managing extremely high complexity (includes focussing and prioritising goals);
Goal <strong>of</strong> reducing complexity for future decision making;
Divide collaborative knowledge construction and (later) decision making;
Require a creative and productive environment for open communication.
6. Strategies to build a creative and productive environment
It is not easy for someone who has been designated as an expert to deliver <strong>the</strong>ir one own valuable
knowledge and personal experience to a group. On <strong>the</strong> o<strong>the</strong>r hand, it is a privilege to participate in a
process that will create <strong>the</strong> foundation for strategic decision-making. The prerequisites for a
successful process are highly important.
Building a knowledge sharing culture requires using two essential elements: The first is enabling <strong>the</strong>
participants to act as individual experts – not as representatives <strong>of</strong> vested interests – (e.g. <strong>the</strong> sales
team as opposed <strong>the</strong> R+D team, or <strong>the</strong> accountants). If <strong>the</strong>y can see <strong>the</strong> advantage <strong>of</strong> giving <strong>the</strong>ir first
loyalty to <strong>the</strong> process, as opposed to <strong>the</strong>ir o<strong>the</strong>rwise legitimate vested interests 7 <strong>the</strong>n this will facilitate
freedom <strong>of</strong> speech and promote thinking outside <strong>of</strong> <strong>the</strong> ‘organisational box’. The second is <strong>the</strong> right
balance <strong>of</strong> named and anonymous contributions to discussion processes (e.g. combining face-to-face
workshops, brainstorming, visioning etc with two or more rounds <strong>of</strong> Delphi). The intention is to tap into
as much tacit knowledge as possible in such a way that it is made available to all <strong>of</strong> <strong>the</strong> participants in
<strong>the</strong> process.
Using communications’ technologies to facilitate learning is to ensure that not only <strong>the</strong> ‘input’
information that <strong>the</strong> organisation needs is generated and provided but especially that <strong>the</strong> ‘output’
information is ga<strong>the</strong>red, processed, or even re-processed when necessary and distributed in user
friendly formats.
Open innovation systems are supported by letting Foresight play an enabling role in <strong>the</strong> “fast track
development <strong>of</strong> open innovation systems”. In industrial R+D contexts Coombs and Georghiou (2003)
have noted that, “Partnerships for innovation is seen as <strong>the</strong> core for knowledge based economic
initiatives”, such as industrial networking. This has been noted in <strong>the</strong> rapid growth in collaborative
R&D, alliances, and technology-based joint ventures. An estimated 20 to 25% <strong>of</strong> business revenues
stem from alliances between two or more companies (Larsen, 2000). These may combine capabilities
across sectors.
Creating “learning champions”, or <strong>the</strong> development <strong>of</strong> ‘boundary-spanners’, may be realised by
selecting appropriate key participants. They should have <strong>the</strong> vocation to develop advanced
understanding <strong>of</strong>, and skills in, managing <strong>the</strong> knowledge required to ensure “process sustainability”.
These people should be pro-active in informal 1-to-1 encounters and in distilling from open meetings
<strong>the</strong> insights into how <strong>the</strong> process is being shaped, which obstacles are encountered and how <strong>the</strong>se
are overcome, which pitfalls or errors should be avoided in <strong>the</strong> future and how <strong>the</strong> most effective
7 This may be seen as almost impossible in some contexts considering <strong>the</strong> importance placed on <strong>the</strong>ir serving as
“organisational ambassadors” in <strong>the</strong> classical diplomatic sense <strong>of</strong> <strong>the</strong> role <strong>of</strong> a country’s Ambassador! Such barriers can only
come down in a climate <strong>of</strong> ‘non-threatening’ openness and trust.
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translations can be achieved from outputs to outcomes 8 . Some multinational enterprises , e.g.
General Electric, use a process that entails key people moving backwards and forwards between R+D
and Marketing. They have identified <strong>the</strong> advantages <strong>of</strong> “knowledge transition” inside <strong>the</strong> people who
move between key departments as <strong>the</strong>y bring with <strong>the</strong>m <strong>the</strong> “contextual understanding” that cannot
be readily codified. As a result, in many R+D intensive companies, “Research targets are established
centrally first, and groups with different expertise are formed around <strong>the</strong>m. These multidisciplinary and
cross-business function programs are aimed at technology leaps in strategic areas.” These
developments have been <strong>the</strong> logical result <strong>of</strong> what M. Gibbons et al. (1994) referred to in <strong>the</strong>ir
discussion <strong>of</strong> how, “Best practice has moved from a customer-contractor model toward ‘joint
production <strong>of</strong> knowledge’”. But it is not only <strong>the</strong> production <strong>of</strong> knowledge that makes participatory
approaches valuable, but <strong>the</strong> entire way from vision to action: The value <strong>of</strong> <strong>the</strong> results <strong>of</strong> engaging in
Foresight depend, not only on <strong>the</strong> strength <strong>of</strong> <strong>the</strong> achieved expert opinion and consensus building, but
also on <strong>the</strong> capacity <strong>of</strong> <strong>the</strong> stakeholders to influence future trends and events. IC Reporting can be
used to “influence future trends and events”. This is vital in view <strong>of</strong> <strong>the</strong> fact that investing in <strong>the</strong>
innovation-creativity process is inherently risky (Lev, 2001) so <strong>the</strong>re is a clear need to be able to
communicate <strong>the</strong> value creation potential to possible Venture Capitalists and/or o<strong>the</strong>r sources <strong>of</strong>
financial/intellectual support. The degree <strong>of</strong> success in this greatly influences <strong>the</strong> future <strong>of</strong> “an idea” or
a start-up company. Engaging <strong>the</strong> potential Venture Capitalists and/or o<strong>the</strong>r sources <strong>of</strong>
financial/intellectual support via <strong>the</strong>ir participation in focussed foresight related to <strong>the</strong> proposed
development/exploitation <strong>of</strong> <strong>the</strong> company’s IC, can be a very effective way <strong>of</strong> realizing <strong>the</strong> joint “vision
<strong>of</strong> <strong>the</strong> future”.
The future here is being shaped ra<strong>the</strong>r than predicted. As mentioned in <strong>the</strong> introductory section, <strong>the</strong>
underlying mental models <strong>of</strong> TF and ICR are probabilistic ra<strong>the</strong>r than deterministic ones. As
participants have to accept different opinions and viewpoints <strong>the</strong>y also need to consider that <strong>the</strong>re is
not <strong>the</strong> one and only truth. Facilitators <strong>of</strong> <strong>the</strong> process have to make this clear and keep it present
during <strong>the</strong> entire process. Management receives an information base from TF and ICR processes, but
<strong>the</strong>y still carry <strong>the</strong> unlimited responsibility for decisions. No information will automatize decisionmaking.
Decisions are an integral part <strong>of</strong> <strong>the</strong> "governance culture". The style or manner in which an
organisation (or a country) is run (or governed) has a particular set <strong>of</strong> attributes. These are sometimes
referred to as “<strong>the</strong> way we do things” or as “<strong>the</strong> way we are”. This includes <strong>the</strong> unwritten code <strong>of</strong>
acceptable versus unacceptable behaviour, e.g. towards bribe taking, or bribe <strong>of</strong>fering, to illegally
alter <strong>the</strong> actions ano<strong>the</strong>r person or organisation. The way in which authority is exercised, and <strong>the</strong> level
<strong>of</strong> tolerance by subordinates <strong>of</strong> unreasonable or authoritarian behaviour by superiors as well as <strong>the</strong>
opposite in regard to what is expected is <strong>the</strong> way <strong>of</strong> respect or honour.
7. Why use TF and ICM? Benefits and limitations
Structured knowledge-oriented processes like ICR and TF imply an investment, mostly <strong>of</strong> time <strong>of</strong>
(high level) experts; who will <strong>of</strong>ten feel that <strong>the</strong>y have more urgent things to do. Why should
management, i.e. decision makers, invest in <strong>the</strong>se kinds <strong>of</strong> methods that work with intangibles and
where <strong>the</strong> outcomes are hard to express in clear cause-effect-relationships and financial terms? As a
condensation <strong>of</strong> <strong>the</strong> former passages, we state some core arguments in <strong>the</strong> following:
7.1 What can ICM and foresight <strong>of</strong>fer?
Some <strong>of</strong> <strong>the</strong> key approaches that TF and ICM can <strong>of</strong>fer include <strong>the</strong> development <strong>of</strong> a context where
stakeholders can participate in <strong>the</strong> building <strong>of</strong> action networks or advocacy coalitions (Georghiou,
2007) and <strong>the</strong> delivery <strong>of</strong> "products". These can take <strong>the</strong> form <strong>of</strong> reports, recommendations, strategies
etc. However, what is perhaps more important are <strong>the</strong> process “outcomes”, whereby expectations are
aligned to create self-fulfilling prophecies, shared visions, etc. In turn <strong>the</strong>se can be developed into a
roadmap to a desired future.
A wide variety <strong>of</strong> key stakeholders can be linked-in so that a connection is made between decision
makers and subject experts. By working toge<strong>the</strong>r <strong>the</strong>y can create an expert opinion information base
for decision makers, whereby <strong>the</strong>se are “educated” in a process that could be described as
knowledge creation in decision makers. On <strong>the</strong> o<strong>the</strong>r hand <strong>the</strong> subject experts can be sensitised to
8 In this context, “outcomes” refers to <strong>the</strong> use that is made <strong>of</strong> <strong>the</strong> exercise’s results and recommendations.
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<strong>the</strong> challenges <strong>of</strong> leadership and decision-making. The goal is to achieve ‘buy-in’ to <strong>the</strong> “outputs” and
“outcomes” <strong>of</strong> <strong>the</strong> process by creating a shared sense <strong>of</strong> ownership and parenthood.
7.2 Why is <strong>the</strong>re a greater need for foresight and ICM now?
There is an increasing need to support <strong>the</strong> possibility <strong>of</strong> integrating multiple perspectives to deal with
today’s complexity. A greater appreciation <strong>of</strong> this justifies leaving <strong>the</strong> "comfort zone" <strong>of</strong> traditional
policy analysis and development and experimenting with contextual approaches that are more
relevant; "relevant factors and dynamics can be used to identify fundamental and transformational
driving forces" (Schneider, 2007).
In a world that is dominated by short-term success races, <strong>the</strong>re is a growing need to consider longterm
developments in business environments, markets and society to ensure corporate sustainability
and TF and ICM contribute to communication among different disciplines and perspectives by
supporting <strong>the</strong> process <strong>of</strong> socially shared cognition; always focussing on possible futures. Boles
criticized back in 1999 that socially shared cognition has mostly been used in organisations at team
levels and not for creating reality in larger entities.
Future oriented exercises can also support thorough and realistic impact assessments, e.g. <strong>of</strong> large
infrastructures or new technology plants.
7.3 What are <strong>the</strong> limitations <strong>of</strong> foresight and ICM?
Foresight and ICM cannot substitute for decision-making processes. They can provide valuable
information for decisions about future action and investments, but <strong>the</strong>y should not form part <strong>of</strong> <strong>the</strong>
decision making process itself. The division <strong>of</strong> topic-related knowledge exchange and creation on <strong>the</strong>
one hand, and decision-making on <strong>the</strong> o<strong>the</strong>r, helps to avoid spoiling experts by political decisionmaking.
However it should be borne in mind that <strong>the</strong> described methods cannot, on <strong>the</strong>ir own, change an
organisation’s culture or overhaul its strategy. However <strong>the</strong>y do influence culture, communication,
personal relationships and decision-making.
Care has to be taken when introducing participatory approaches into strong hierarchical power
structures as a forced consensus and avoidance <strong>of</strong> conflict can destroy <strong>the</strong> fruitful consideration <strong>of</strong>
multiple perspectives and possibly incompatible opinions. So although a consensus can be reached,
this does not have to be <strong>the</strong> outcome. Striking <strong>the</strong> right balance between <strong>the</strong> old and new is important
to get <strong>the</strong> process going.
8. Critical success factors
Some <strong>of</strong> <strong>the</strong> critical success factors when adopting participatory approaches for sustainable
management are here formulated as recommendations:
Draw a heterogeneous sample <strong>of</strong> perspectives relevant for <strong>the</strong> topics <strong>of</strong> interest;
Assure that participants are willing and capable <strong>of</strong> open innovative thinking and communication;
Assure that <strong>the</strong> sample used is representative <strong>of</strong> all relevant perspectives;
Minimise biases caused by implicit “orders” or interests, work with experts instead <strong>of</strong> “delegates”
<strong>of</strong> a certain interest group;
Have pr<strong>of</strong>essional mediation and facilitation experts present to guide <strong>the</strong> process;
Determine roles and responsibilities and communicate <strong>the</strong>m clearly;
Balance long-term and short term views;
Make methods understandable for <strong>the</strong> participants;
Connect all knowledge to a strategic direction (at <strong>the</strong> end);
Draw realistic conclusions that are transformable into concrete actions;
Simplify complex information / avoid information overload;
Take time for discussion;
Use media and visualisations to edit and simplify information and outcomes;
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Foster <strong>the</strong> sense <strong>of</strong> ownership <strong>of</strong> results among all participants, decision makers, and relevant
stakeholders.
9. Final remark on <strong>the</strong> future <strong>of</strong> future-oriented methods
If we come back to <strong>the</strong> challenges for sustainable global development, it is obvious that ICM and TF
contribute to finding answers (here over-simplified) to <strong>the</strong> questions <strong>of</strong>:
How to establish democratic features in regimes with concentrated power for decision- making?
=> Engage experts and give <strong>the</strong>m a voice to actively participate.
How to make policymaking more sensitive to global long-term perspectives?
=> Consider multiple perspectives and use <strong>the</strong>m as “senses” and information for decision makers.
How to improve <strong>the</strong> capacity to decide as <strong>the</strong> nature <strong>of</strong> work and institutions change?
=> Apply methods <strong>of</strong> collaborative knowledge construction and condensation <strong>of</strong> possible future
scenarios.
How to accelerate scientific and technological breakthroughs?
=> Use existing expertise to focus on <strong>the</strong> most relevant issues and thus make <strong>the</strong> right decisions,
avoid distraction, and set <strong>the</strong> right priorities to focus resource allocation.
Going a step fur<strong>the</strong>r and stepping over organisational borders, Daheim and Uerz (2006) detect a new
trend <strong>of</strong> “open foresight” in <strong>the</strong> corporate sector, strongly linked to <strong>the</strong> trend towards “open
innovation”, including at least four aspects <strong>of</strong> openness: <strong>the</strong> involvement <strong>of</strong> relevant stakeholders from
within and outside <strong>the</strong> client organisation; openness beyond a single sector environment; a process
organised in an open-ended manner which does not end when a specific project has been achieved,
but ra<strong>the</strong>r continuously overhauls and re-invents itself; and finally as an on-going process that acts as
an “irritant” for <strong>the</strong> organisation (Georghiou 2007). The growing openness contributes to <strong>the</strong>
achievement <strong>of</strong> <strong>the</strong> initially requested adaptation and interaction <strong>of</strong> a system (e.g. <strong>the</strong> organisation)
with its environment, so as to successfully position itself, sharpen its senses, identify and use broader
developments for its own behaviour and assure sustainable decision making.
References
Glenn, J. C. & Gordon, T. J. (2006). “2006 State <strong>of</strong> <strong>the</strong> Future”. DC, United States: American Council for <strong>the</strong>
United Nations University Millenium Project, 10th anniversary edition.
Barré, R. & Keenan, M. (2006). “Evaluation, Impact and Learning”, Second International Seville Seminar on
Future-Oriented Technology Analysis: Impact <strong>of</strong> FTA Approaches on Policy and Decision-Making –
SEVILLE, 28-29 SEPTEMBER, 2006.
Boles, T. (1999). Themes and variations in shared cognition in organizations. In L. L. Thompson, J. M. Levine &
D. M. Messick (Hrsg.), Shared cognition in organizations, pp 327-348. Mahwah, NJ: Lawrence Erlbaum.
Cook, S. D. N. & Brown, John S. (1999). Bridging Epistemologies: The Generative Dance Between
Organizational Knowledge and Organizational Knowing. ORGANIZATION SCIENCE, Vol. 10, No. 4, pp.
381-400.
Coombs, R. and Georghiou, L. (2007). A New “Industrial Ecology” SCIENCE VOL 296, 19 April 2002.
Difu (2007), “RICARDA. Intellectual Capital Reporting for Regional Clusters and Network Initiatives. Manual on
<strong>the</strong> RICARDA Methodology”, www.ricarda-project.org
<strong>European</strong> Commision (2006). “RICARDIS: Reporting Intellectual Capital to Augment Research, Innovation and
Development in SMEs”, http://ec.europa.eu/invest-in-research/policy/capital_report_en.htm
Flicker, A. & Pook, K. (2007). Into <strong>the</strong> flow: Intellectual Capital Management at reinisch AG. IC Congress,
Amsterdam/Ne<strong>the</strong>rlands, May 3-4, 2007. http://www.iccongress.com
Furnham, A. and Ribchester, T. (1995). "Tolerance <strong>of</strong> Ambiguity: A review <strong>of</strong> <strong>the</strong> concept, its measurement and
applications." Current Psychology, Vol. 14, No. 3, pp. 179-199.
Georghiou, L. (2007). “Future <strong>of</strong> Foresighting for economic development”, UNIDO Technology Foresight Summit
2007 (Ch 3).
German Federal Ministry <strong>of</strong> Economics and Labour (2004). “Intellectual capital statement – Made in Germany.
Guideline”, Berlin.
Gibbons, M. et al. (1994). “The New Production <strong>of</strong> Knowledge”. London: Sage.
Howe, K. R. & Berv, J. (2000). Constructing constructivism, epistemological and pedagogical. In D. C. Philipps
(Ed.), Constructivism in education: Opinions and second opinions on controversial issues, (pp. 19-40).
Chicago, Illinois: University <strong>of</strong> Chicago Press.
Keenan, M. & Popper, R. (Eds) (2007). “Integrating Foresight in RI Policy Formulation”, ForeIntegra-RI.
Larsen, C. F. (2000). “R&D in industry 1999” (Washington DC: Industrial Research Institute, p. 6;
www.iriinc.org/webiri/publications/99aaasreport2.doc
341

Katja Pook and Campbell Warden
Lazlo, E., Lazlo, C., Liechtenstein, A. v., Eds. (1992). Evolutionäres Management: Globale Handlungskonzepte.
Fulda: Paidia Verlag.
Lev, B. (2001). Intangibles. Washington D.C.: Brookings Institution Press.
Loveridge, D. & Street, P. (2006) “Inclusive foresight”, Foresight - The journal <strong>of</strong> future studies, strategic thinking
and policy, Vol. 7, No. 3. (March 2005), pp. 31-47.
Nonaka, I. & Kono, N.(1998) “The concept <strong>of</strong> ba: building a foundation for knowledge creation”, California
Management Review, 40 (3), Spring: p. 40-54.
Popper, R. (2007). “Foresight Mehodology” in Georghiou, L. et al, The Handbook <strong>of</strong> Technology Foresight,
Edward Elgar, UK.
Resnick, L. B., Levine, J. M. & Teasley, S. D., Eds. (1991). Perspectives on socially shared cognition.
Washington DC, American Psychological Association.
Saritas (2007) Private communication
Schneider, S. (2007). “The future <strong>of</strong> foresight in innovation and competitiveness”, UNIDO Expert Group Meeting
on Future <strong>of</strong> Technology Foresight, Vienna, May 29 th and 30 th , 2007.
UNIDO (2005). “UNIDO Technology Foresight Manual”, United Nations Industrial Development Organisation.
http://www.unido.org/data/forms.cfm?formcode=TF-MANUAL-REG
Weber, K.M. & Havas, A. (2007). “Experiences and practices <strong>of</strong> TF in <strong>the</strong> <strong>European</strong> Region”, UNIDO Expert
Group Meeting on Future <strong>of</strong> Technology Foresight, Vienna, May 29 th and 30 th , 2007.
Weismann, A. & Feige, J. (1997). Sinnergie. Wendezeit für das Management. Zurich: Orell-Fuessli.
342

Human Capital and Relational Capital Dynamics Within a
University
Nicolae Al. Pop, Adrian Tantau, Corina Pelau and Irina Bena
Academy <strong>of</strong> Economic Studies Bucharest, Romania
nicolae_al_pop@yahoo.com
ad_tantau@yahoo.com
corinapelau@yahoo.com
irina.bena@gmail.com
Abstract: One <strong>of</strong> <strong>the</strong> most important aspects for <strong>the</strong> development <strong>of</strong> <strong>the</strong> intellectual capital <strong>of</strong> a university is <strong>the</strong>
quality <strong>of</strong> its human capital and its capability to build relations. One <strong>of</strong> <strong>the</strong>se relations is <strong>the</strong> one between <strong>the</strong>
students and <strong>the</strong> pr<strong>of</strong>essors. This relationship is important because only by a good communication between
<strong>the</strong>se parties, <strong>the</strong> students can increase <strong>the</strong>ir performances both at university and in <strong>the</strong>ir future job and
contribute by this to <strong>the</strong> image <strong>of</strong> <strong>the</strong> university. Especially in a time, where competition between universities
becomes more intense, it is important to keep a good relation with its students, because <strong>the</strong>y influence <strong>the</strong> image
<strong>of</strong> <strong>the</strong> university and also its success. The premise for a good relation with its students is achieving <strong>the</strong>ir
satisfaction. Satisfied students are <strong>the</strong> ones, who recommend <strong>the</strong> university to o<strong>the</strong>rs. For building a relational
capital, especially <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong>ir relation to <strong>the</strong> pr<strong>of</strong>essors is very important. This
article presents <strong>the</strong> perception <strong>of</strong> <strong>the</strong> students regarding <strong>the</strong>ir relation and evaluation <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors <strong>of</strong> a
university and it is based on a satisfaction study done within a university from Romania. Besides this, it presents
also <strong>the</strong> impact and <strong>the</strong> influence <strong>of</strong> <strong>the</strong> quality <strong>of</strong> <strong>the</strong> relation on <strong>the</strong> general image <strong>of</strong> <strong>the</strong> university. Within <strong>the</strong>
study <strong>the</strong>re are analyzed aspects like <strong>the</strong> competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors, <strong>the</strong> teaching style, pedagogical skills,
implication <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors in <strong>the</strong> courses and seminars, attitude <strong>of</strong> pr<strong>of</strong>essors towards students,
communication, availability and <strong>the</strong>ir impact on <strong>the</strong> overall satisfaction <strong>of</strong> students with <strong>the</strong> university and <strong>the</strong>ir
willingness to recommend or to continue <strong>the</strong>ir studies at <strong>the</strong> same university. It is also analyzed <strong>the</strong> impact <strong>of</strong> all
<strong>the</strong>se elements on <strong>the</strong> performance <strong>of</strong> <strong>the</strong> students. In <strong>the</strong> end <strong>the</strong>re are presented <strong>the</strong> conclusions and <strong>the</strong>
recommendations for <strong>the</strong> university and <strong>the</strong> measures it should take in order to increase <strong>the</strong> dynamics <strong>of</strong> its
human and relational capital.
Keywords: relational capital, human capital, intellectual capital, satisfaction, relation
1. Introduction
The competition on <strong>the</strong> market for educational services has increased in <strong>the</strong> past years because <strong>of</strong>
<strong>the</strong> new dynamics in this field. On one hand <strong>the</strong> shrinking demographics influences in a negative way
<strong>the</strong> demand for educational services. On <strong>the</strong> o<strong>the</strong>r hand <strong>the</strong> appearance <strong>of</strong> o<strong>the</strong>r forms <strong>of</strong> education
such as private universities or training institution has diversified <strong>the</strong> <strong>of</strong>fer on this market and
consequently increased <strong>the</strong> competition. In order to face <strong>the</strong>se changes <strong>the</strong> management <strong>of</strong> <strong>the</strong>
universities has to take measures in order to maintain <strong>the</strong>ir position on <strong>the</strong> market and also to keep its
main customers, <strong>the</strong> students.
Offering high quality educational services are premises for generating and enhancing customer
loyalty. Satisfied students are more likely to engage passionately in <strong>the</strong>ir studying activities and to
keep <strong>the</strong>ir contact with <strong>the</strong> university by ei<strong>the</strong>r enrolling in Master or Doctorate Programmes or
involving <strong>the</strong>mselves in different Alumni activities. Both directions are crucial to <strong>the</strong> construction <strong>of</strong>
institutional image and reputation. They generate positive word <strong>of</strong> mouth and social media content
and thus help attract not only new students but also sponsorship funding and diverse projects.
Within <strong>the</strong> mentioned framework <strong>the</strong> construct <strong>of</strong> intellectual capital <strong>of</strong>fers a holistic approach to <strong>the</strong>
allocation <strong>of</strong> intangible resources with <strong>the</strong> aim <strong>of</strong> gaining competitive advantage. The present paper
focuses on students’ satisfaction as an indicator <strong>of</strong> <strong>the</strong> third dimension (external dimension) <strong>of</strong> <strong>the</strong>
intellectual capital model. It analyses <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students <strong>of</strong> a university with its teaching
staff.
The research aimed to evaluate <strong>the</strong> performance <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors for <strong>the</strong> teaching part <strong>of</strong> <strong>the</strong>ir
activity and to determine <strong>the</strong> overall satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> university, as a premise for
future collaboration. There are several methods and instruments used to evaluate and monitor <strong>the</strong>
research activity done by pr<strong>of</strong>essors, but it is also important to measure <strong>the</strong>ir performance at courses
and seminars as students are a university’s direct customers for educational service. In order to
determine <strong>the</strong> mentioned teaching performance, <strong>the</strong> study was done with <strong>the</strong> purpose <strong>of</strong> analysing <strong>the</strong>
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Nicolae Al. Pop et al.
satisfaction <strong>of</strong> <strong>the</strong> students with several aspects regarding <strong>the</strong> teaching process, as for instance
transmitted knowledge and communication. This kind <strong>of</strong> satisfaction study can point out <strong>the</strong>
malfunctioning elements, hence <strong>of</strong>fering <strong>the</strong> opportunity to take improvement measures. Practically by
eliminating <strong>the</strong> weak elements <strong>of</strong> <strong>the</strong> teaching process, <strong>the</strong> intellectual capital <strong>of</strong> a university can be
developed. Fur<strong>the</strong>rmore, by measuring <strong>the</strong> satisfaction, a university can lay <strong>the</strong> grounds for a good
relationship to <strong>the</strong> students. Revealing <strong>the</strong>ir preferences and concerns allows a better structure <strong>of</strong> <strong>the</strong>
<strong>of</strong>fer, showing interest in <strong>the</strong>ir opinion helps building up trust – all <strong>of</strong> which can bring long term
benefits to <strong>the</strong> organization.
The literature review presents <strong>the</strong> main <strong>the</strong>oretic concepts as <strong>the</strong> basis for <strong>the</strong> following research
study.
2. Literature review
The present paper focuses on three different constructs: intellectual capital, higher education services
and customer satisfaction. All <strong>of</strong> <strong>the</strong>m define <strong>the</strong> research conducted and are thus presented in <strong>the</strong>
following paragraphs.
2.1 Intellectual capital
According to Bontis (Bontis 1998), <strong>the</strong> research on <strong>the</strong> concept <strong>of</strong> intellectual capital has evolved as a
reaction to <strong>the</strong> “desire <strong>of</strong> practitioners”. He argues that, on one hand, <strong>the</strong>re were “popular press
articles in business magazines and national newspapers” and, on <strong>the</strong> o<strong>the</strong>r, a new job title was
making its way on companies annual reports and job announcements: chief knowledge <strong>of</strong>ficer (CKO).
The companies in question regarded intellectual capital an “essential source <strong>of</strong> competitive
advantage”. The same idea is also presented by Nonaka in his Harvard Business Review article
(Nonaka 1991): “Successful companies are those that consistently create new knowledge,
disseminate it widely throughout <strong>the</strong> organization, and quickly embody it in new technologies and
products.”
As Sveiby pointed out in 1997 (cited by Akhilesch 2008) <strong>the</strong> concept <strong>of</strong> “intellectual capital has been
understood by a very few, and formally valued by practically no one”. It is consequently <strong>of</strong> no surprise
that <strong>the</strong> academics were challenged to put <strong>the</strong> phenomenon into a frame. The concept evolved in <strong>the</strong>
last years, from a semantic and an operational point <strong>of</strong> view, almost exponentially (Brătianu 2009).
The term intellectual capital refers to “<strong>the</strong> intangible assets that a business can use to create value”
(Al-Ali 2003). The Swedish financial and insurance services company, Skandia, was <strong>the</strong> first to use
<strong>the</strong> term, referring to “all intangible resources that <strong>the</strong> organization has, including human, process and
organizational capital”. In <strong>the</strong> absence <strong>of</strong> accounting specific methods to determine <strong>the</strong> elements <strong>of</strong>
<strong>the</strong> new form <strong>of</strong> capital, authors proposed various templates (O’Regan and O’Donnel 2000). O’Regan
and O’Donnel provide an outline <strong>of</strong> three models <strong>the</strong>y consider to be more advanced:
Sveiby’s Model with people’s competence, internal and external structure;
Kaplan and Norton’s Model with its three perspectives: learning and growth, internal process and
customer;
Edvinsson’s Model with three types <strong>of</strong> capital: human, organizational and customer.
All <strong>the</strong>se models have one thing in common – <strong>the</strong>y assume a three way distinction between <strong>the</strong>
People dimension, <strong>the</strong> Internal dimension and <strong>the</strong> External dimension. For each dimension O’Regan
and O’Donnel also list common indicators, like for instance:
Employee satisfaction, Value Added per employee, Level <strong>of</strong> education, Training and Education
costs for <strong>the</strong> People dimension;
Number <strong>of</strong> patents, Investment in IT and R&D expense for <strong>the</strong> Internal dimension;
Customer Satisfaction, Brand loyalty and Frequency <strong>of</strong> repeat orders for <strong>the</strong> External dimension.
The present paper focuses on <strong>the</strong> third dimension and presents satisfaction levels for students with
regard to <strong>the</strong> performance <strong>of</strong> <strong>the</strong> teaching stuff in a Romanian university.
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2.2 Higher education services
Nicolae Al. Pop et al.
Students are considered to be <strong>the</strong> “primary customers” <strong>of</strong> universities (Douglas, Douglas and Barnes
2006). They are direct recipients <strong>of</strong> <strong>the</strong> educational service provided. In <strong>the</strong> United Kingdom <strong>the</strong>ir
status as customers is confirmed by <strong>the</strong> fact that <strong>the</strong> Higher Education Funding Council for England
has introduced a National Student Survey.
Higher education services are considered to be mental stimulus processing, <strong>the</strong>ir direct recipients
being <strong>the</strong> students (Lovelock and Wirtz 2004, Bena 2010).The main element in <strong>the</strong> service
performance is an intangible action, but higher education also relies on a series <strong>of</strong> tangible elements
like campus infrastructure, library stock and technology. The quality <strong>of</strong> staff – preparation, knowledge,
abilities and skills – influences significantly <strong>the</strong> quality <strong>of</strong> all <strong>the</strong> delivered services. Ano<strong>the</strong>r set <strong>of</strong>
important determinants <strong>of</strong> <strong>the</strong> variety <strong>of</strong> operational outputs are represented by <strong>the</strong> time investment
from <strong>the</strong> student’s part and <strong>the</strong> interaction students-staff.
The market <strong>of</strong> higher education services undergoes shifts similar to o<strong>the</strong>r markets. As DeShields et al.
point out (DeShields, Kara and Kaynak 2005) <strong>the</strong> advancement <strong>of</strong> technology, <strong>the</strong> more educated
consumer demand, <strong>the</strong> changing delivery methods, <strong>the</strong> increased competition and <strong>the</strong> shrinking
markets present new challenges for universities. They need to manage enrolments from <strong>the</strong> point <strong>of</strong>
initial student contact to <strong>the</strong> point <strong>of</strong> graduation.
2.3 Satisfaction construct
DeShields et al. stress out <strong>the</strong> importance <strong>of</strong> satisfaction for higher education services (DeShields,
Kara and Kaynak 2005). Customers are regarded by <strong>the</strong> authors from a broad perspective and may
be not only students but also parents <strong>of</strong> students, alumni or employees. In order to create customer
value and economic value, universities should have as a primary goal <strong>the</strong> insurance <strong>of</strong> <strong>the</strong>ir customer
satisfaction.
Referring to students as <strong>the</strong> customers <strong>of</strong> universities, Appleton-Knapp and Krentler (Appleton-Knapp
and Krentler 2006) regard <strong>the</strong>ir satisfaction with <strong>the</strong> educational experience to be <strong>the</strong> result <strong>of</strong> <strong>the</strong>
confirmation/disconfirmation paradigm and fur<strong>the</strong>rmore <strong>the</strong> result <strong>of</strong> a complex set <strong>of</strong> influencing
factors – one <strong>of</strong> <strong>the</strong>m being <strong>the</strong> interaction teaching staff/students. The management <strong>of</strong> universities
needs to understand how those factors act and combine. Students’ satisfaction is, in addition to
learning, a desired and important outcome <strong>of</strong> <strong>the</strong> educational service.
3. Research regarding <strong>the</strong> relation between students and pr<strong>of</strong>essors at a
university
The main objective <strong>of</strong> <strong>the</strong> research project was to determine <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students at <strong>the</strong>
Bucharest Academy <strong>of</strong> Economic Studies (ASE), Romania, and its impact on <strong>the</strong> attitude <strong>of</strong> <strong>the</strong>
students towards future attendance <strong>of</strong> different study programmes and <strong>the</strong>ir recommendations to
potential students. It was done following prior surveys which sought to reveal <strong>the</strong> intention <strong>of</strong> third
year Bachelor students to enrol for Master Programmes. As <strong>the</strong>se surveys did not include questions
about students’ satisfaction, <strong>the</strong> need for a more elaborate study came up.
The study was conducted on a sample <strong>of</strong> 1200 students from all faculties <strong>of</strong> ASE, from both <strong>the</strong>
Bachelor and <strong>the</strong> Master programs. There were asked questions about <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students
with <strong>the</strong> courses and <strong>the</strong> seminars, <strong>the</strong> competences and <strong>the</strong> attitude <strong>of</strong> <strong>the</strong> teachers and all o<strong>the</strong>r
facilities <strong>of</strong> <strong>the</strong> university such as canteen, dorms, library, scholarships and so on. The research was
done in <strong>the</strong> period April-May 2010 at <strong>the</strong> university. The survey contains both Likert-scale, multiple
choice and open questions. The questions regarding <strong>the</strong> satisfaction with several items in ASE were
scaled from 1 to 7, where 7 was “very satisfied” and 1 “totally dissatisfied”. Besides <strong>the</strong> satisfaction <strong>of</strong>
<strong>the</strong> students, <strong>the</strong>re were also asked questions about demographic data, such as age, faculty.
In this article <strong>the</strong>re were analyzed <strong>the</strong> results which present <strong>the</strong> relation between <strong>the</strong> pr<strong>of</strong>essors and
<strong>the</strong> students and its impact on <strong>the</strong> overall satisfaction <strong>of</strong> <strong>the</strong> students and <strong>the</strong>ir recommendation
potential. For this we analyze <strong>the</strong> following items: competences <strong>of</strong> pr<strong>of</strong>essors, teaching style,
pedagogical skills, implication <strong>of</strong> pr<strong>of</strong>essors, attitude <strong>of</strong> pr<strong>of</strong>essors, communication between
pr<strong>of</strong>essors and students and availability <strong>of</strong> pr<strong>of</strong>essors. All <strong>the</strong>se aspects have been related to <strong>the</strong>
overall satisfaction with <strong>the</strong> university and <strong>the</strong> satisfaction <strong>of</strong> choosing it as well as <strong>the</strong> will to continue
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Nicolae Al. Pop et al.
<strong>the</strong> studies at <strong>the</strong> same university or <strong>the</strong> recommendation potential. In fig. 1 we can observe <strong>the</strong>
absolute satisfaction <strong>of</strong> <strong>the</strong>se items, on a scale from 1 to 7, where 7 means very satisfied and 1
means totally dissatisfied.
5.2
5
4.8
4.6
4.4
4.2
4
3.8
Competences
5.06
Teaching Style
4.4
Pedagogical Skills
4.67
Implication
4.38
Satisfaction
Attitude
4.42
Communication
4.24
Availability
Figure 1: Satisfaction with <strong>the</strong> competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors at a university (on a scale <strong>of</strong> 1 to 7,
where 7=very satisfied and 1=totally dissatisfied)
As we can observe in fig. 1 <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors
have values between 4 (average satisfaction) and 5 (ra<strong>the</strong>r satisfied). Although <strong>the</strong>re is no high
variation between <strong>the</strong> items, we can observe that <strong>the</strong> students are most satisfied with <strong>the</strong>
competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors (5.06) and with <strong>the</strong> pedagogical skills (4.67) and least satisfied with
<strong>the</strong> communication between <strong>the</strong> pr<strong>of</strong>essors and <strong>the</strong> students (4.24) and <strong>the</strong> availability <strong>of</strong> pr<strong>of</strong>essors
for discussions (4.32). The values presented correspond to <strong>the</strong> average item “satisfied that you chose
this university”, which has a value <strong>of</strong> 4.83. It is interesting to observe that <strong>the</strong> value <strong>of</strong> this item, asked
at <strong>the</strong> end <strong>of</strong> <strong>the</strong> questionnaire is higher than <strong>the</strong> overall satisfaction, asked at <strong>the</strong> beginning <strong>of</strong> <strong>the</strong>
questionnaire, which has a value <strong>of</strong> 3.16. This indicates that <strong>the</strong> cognitive satisfaction (after taking in
consideration all aspects regarding <strong>the</strong> university) is higher than <strong>the</strong> emotional satisfaction (a value
given, without taking in consideration all items). The university should take this result in consideration
and improve its image by marketing more several positive aspects. Because <strong>of</strong> this result we will take
in consideration in <strong>the</strong> fur<strong>the</strong>r analysis <strong>the</strong> item “satisfied that you chose this university”.
In order to see <strong>the</strong> influence <strong>of</strong> all <strong>the</strong>se factors on <strong>the</strong> satisfaction with <strong>the</strong> university, we have done a
regression analysis with <strong>the</strong> help <strong>of</strong> <strong>the</strong> SPSS. In this analysis we had as dependent variable <strong>the</strong> item
“satisfied that you chose this university” and <strong>the</strong> independent variables <strong>the</strong> items presented in fig. 1.
The results <strong>of</strong> <strong>the</strong> regression analysis are presented in fig. 2.
According to <strong>the</strong> value <strong>of</strong> <strong>the</strong> R-Square obtained in <strong>the</strong> regression analysis we can state that 26% <strong>of</strong>
<strong>the</strong> dependent variable can be explained by <strong>the</strong> analyzed factors. Although at <strong>the</strong> first glance this
value is not very high, if we take in consideration <strong>the</strong> fact that in <strong>the</strong> study, <strong>the</strong>re have been
considered 80 satisfaction items, this value is a significant one. This value is also confirmed by <strong>the</strong> R-
Square change. Also <strong>the</strong> F-Test in <strong>the</strong> ANOVA Table shows a significance <strong>of</strong> <strong>the</strong> regression <strong>of</strong> 99%.
According to <strong>the</strong> results <strong>of</strong> <strong>the</strong> Regression analysis and assuming that all o<strong>the</strong>r factors are constant
we have <strong>the</strong> following regression function:
Satisfaction = 1.66 + 0.21*competences + 0.12*teaching_style – 0.28*pedagogical_skills +
0.12*implication + 0.03*attitude + 0.12*communication + 0.08*availability
So we can observe that <strong>the</strong> highest influence on <strong>the</strong> overall satisfaction has <strong>the</strong> competences <strong>of</strong> <strong>the</strong>
pr<strong>of</strong>essors and <strong>the</strong> least influence has <strong>the</strong> attitude <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors towards <strong>the</strong> students. The next
highest influence has <strong>the</strong> teaching style, <strong>the</strong> implication and <strong>the</strong> communication <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors
towards <strong>the</strong> students. The BETA-test in <strong>the</strong> SPSS analysis shows also <strong>the</strong> highest influence for <strong>the</strong>
item competences <strong>of</strong> pr<strong>of</strong>essors. With <strong>the</strong> exception <strong>of</strong> <strong>the</strong> items “pedagogical skills” and “attitude”, for
all o<strong>the</strong>r factors <strong>the</strong> significance has a value close to “0” so that we can reject <strong>the</strong> Zero-Hypo<strong>the</strong>sis.
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Nicolae Al. Pop et al.
Consequently, with <strong>the</strong> exception <strong>of</strong> <strong>the</strong> two mentioned factors, all o<strong>the</strong>r factors have a significant
influence on <strong>the</strong> dependent variable. Ano<strong>the</strong>r aspect which confirms this relation is <strong>the</strong> t-test, which
also shows an influence <strong>of</strong> all factors on <strong>the</strong> dependent variable, with <strong>the</strong> exception <strong>of</strong> “pedagogical
skills” and “attitude” <strong>of</strong> pr<strong>of</strong>essors towards students. The correlation table between <strong>the</strong> independent
variables shows no significant dependence between <strong>the</strong> analyzed items.
Model R
1
R
Square
Adjusted
R Square
Model Summary b
Change Statistics
Std. Error <strong>of</strong> R Square
<strong>the</strong> Estimate Change F Change df1 df2
Sig. F
Change
Durbin-
Watson
1 .515 a .265 .261 1.18156 .265 59.411 7 1152 .000 1.566
a. Predictors: (Constant), availability pr<strong>of</strong>essors, competences pr<strong>of</strong>essors, pedagogical skills, attitude
pr<strong>of</strong>essors, teaching style, implication, communication
b. Dependent Variable: satisfied that you chose ASE
1
ANOVA b
Model Sum <strong>of</strong> Squares df Mean Square F Sig.
Regression 580.603 7 82.943 59.411 .000 a
Residual 1608.286 1152 1.396
Total 2188.889 1159
a. Predictors: (Constant), availability pr<strong>of</strong>essors, competences pr<strong>of</strong>essors, pedagogical skills, attitude
pr<strong>of</strong>essors, teaching style, implication, communication
b. Dependent Variable: satisfied that you chose ASE
Coefficients a
Unstandardized Coefficients
Standardized
Coefficients
Model B Std. Error Beta t Sig.
(Constant) 1.663 .168 9.878 .000
competences pr<strong>of</strong>essors .219 .035 .193 6.221 .000
teaching style .129 .039 .118 3.314 .001
pedagogical skills -.028 .038 -.027 -.740 .459
implication .127 .037 .126 3.397 .001
attitude .038 .037 .039 1.038 .299
communication .127 .037 .133 3.482 .001
availability .084 .033 .088 2.563 .010
a. Dependent Variable: satisfied that you chose ASE
Figure 2: Results <strong>of</strong> <strong>the</strong> regression analysis
If we analyze <strong>the</strong> willingness <strong>of</strong> <strong>the</strong> students to continue <strong>the</strong>ir studies within <strong>the</strong> same university, we
can observe that more satisfied students ra<strong>the</strong>r want to continue <strong>the</strong>ir studies. As fig. 3 shows only
50% <strong>of</strong> <strong>the</strong> dissatisfied students want to continue <strong>the</strong>ir studies within <strong>the</strong> same university, while over
62% <strong>of</strong> <strong>the</strong> students from <strong>the</strong> ra<strong>the</strong>r satisfied students have <strong>the</strong> intention to remain <strong>the</strong> same
university.
As this study shows, <strong>the</strong> human capital and <strong>the</strong> relational capital <strong>of</strong> a university are very important for
its image and success on <strong>the</strong> higher education services market. Since <strong>the</strong> delivered services rely on
<strong>the</strong> human capital, <strong>the</strong> quality <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors performing teaching activities represents a core asset
<strong>of</strong> a university. By <strong>the</strong>ir knowledge and competence <strong>the</strong>y contribute directly to <strong>the</strong> improvement <strong>of</strong> <strong>the</strong>
relationship with <strong>the</strong> students.
The findings point out that <strong>the</strong> perceived competence, <strong>the</strong> teaching style and <strong>the</strong> implication have <strong>the</strong>
most influence on <strong>the</strong> students’ overall satisfaction level. So does <strong>the</strong> communication between <strong>the</strong>
pr<strong>of</strong>essors and <strong>the</strong> students, which scored <strong>the</strong> lowest specific satisfaction level. Two main ideas for
fur<strong>the</strong>r consideration arise: The positive aspect is that <strong>the</strong> factor with most influence on <strong>the</strong> overall
347

Nicolae Al. Pop et al.
satisfaction level, competence, also scores <strong>the</strong> best specific satisfaction. The university management
should try to keep competence and fur<strong>the</strong>r enhance it. Measures <strong>of</strong> motivation and differentiated pay
and measures <strong>of</strong> continuous learning are some <strong>of</strong> <strong>the</strong> instruments to apply for <strong>the</strong> purpose. The
negative aspect, <strong>the</strong> lowest specific satisfaction level and a significant influence on <strong>the</strong> overall
satisfaction level <strong>of</strong> <strong>the</strong> communication factor, needs to be addressed urgently. In times <strong>of</strong> rapid
information flux and multi-media communication, with a generation <strong>of</strong> students used to interacting in
private and pr<strong>of</strong>essional life by various means, <strong>the</strong> university management has to adapt quickly.
100%
80%
60%
40%
20%
0%
1 2 3 4 5 6 7
Figure 3: Willingness <strong>of</strong> continuing <strong>the</strong> studies at <strong>the</strong> same university depending on satisfaction
4. Conclusion and outlook
The value <strong>of</strong> item “satisfied that you chose this university”, asked at <strong>the</strong> end <strong>of</strong> <strong>the</strong> questionnaire is
higher than <strong>the</strong> overall satisfaction, asked at <strong>the</strong> beginning <strong>of</strong> <strong>the</strong> questionnaire. This indicates that
<strong>the</strong> cognitive satisfaction is higher than <strong>the</strong> emotional satisfaction. While more satisfied students than
dissatisfied ones mentioned <strong>the</strong>y would continue <strong>the</strong>ir studies within <strong>the</strong> same university, still <strong>the</strong>
number <strong>of</strong> dissatisfied students wanting to continue is surprisingly and apparently unreasonably high
(50%). Cognitive satisfaction may explain some <strong>of</strong> <strong>the</strong> result. Fur<strong>the</strong>r studies should try to find out
what is <strong>the</strong> reason behind <strong>the</strong>se responses.
Base on <strong>the</strong> findings, internal marketing, human resources development programmes and integrated
communication are some <strong>of</strong> <strong>the</strong> steps <strong>the</strong> university management can develop and take. Additionally,
<strong>the</strong> need for systematic, regular and in depth satisfaction studies arises. The consequent data are
grounds for intellectual capital management.
Acknowledgement
This work was supported from <strong>the</strong> <strong>European</strong> Social Fund through Sectoral Operational Programme
Human Resources Development 2007-2013, project number POSDRU/ 89/ 1.5/ S/ 59184
“Performance and excellence in postdoctoral research in Romanian economics science domain”.
References
Aldridge, S; Rowley, J. (1998): Measuring customer satisfaction in higher education, in: Quality Assurance in
Education, Volume 6, Number 4, 1998, pp. 197–204.
Akhilesh, K. (2008) „Modeling Intellectual Capital From a Bottom-Up Perspective”. In: O’Sullivan, K. (Ed.) 5th
International <strong>Conference</strong> on Intellectual Capital, Knowledge Management and Organizational Learning,
New York Institute <strong>of</strong> Technology, New York, pp 17-24.
Al-Ali, N. (2003) Comprehensive Intellectual Capital Management, John Wiley & Sons, Hoboken NJ.
Appleton-Knapp, S.L. and Krentler, K.A. (2006) „Measuring Student Expectations and Their Effects on
Satisfaction: The Importance <strong>of</strong> Managing Student Expectations”, Journal <strong>of</strong> Marketing Education, Vol. 28,
No. 3, December, pp 254-264.
Athiyaman, A. (1997): Linking student satisfaction and service quality perceptions: <strong>the</strong> case <strong>of</strong> university
education, in: <strong>European</strong> Journal <strong>of</strong> Marketing, Vol. 31 No. 7, 1997, pp. 528-540.
Bena, I. (2010): Evaluation <strong>of</strong> Students’ Expectations within <strong>the</strong> Satisfaction Measurement in Higher Education
Services, in: Brătianu, C.; Lixăndroiu, D. and Pop, N. Al. (Ed.) <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 5th International
<strong>Conference</strong> on Business Excellence, Vol. 1, INFOMARKET, Brașov, pp. 63-66.
Bontis, N. (1998) “Intellectual capital: an exploratory study that develops measures and models”, Management
Decision, Vol. 36, No. 2, pp 63-76.
Bratianu, C. (2009), Dinamica cunostintelor, in Bratianu, C. (coord): Capitalul intelectual organizational, Editura
ASE, Bucuresti, pp. 9-38.
Brătianu, C. (2009) Capitalul intelectual organizational, Editura ASE, Bucuresti.
348
No
Yes

Nicolae Al. Pop et al.
DeShields, O.W. Jr; Kara, A. and Kaynak, E. (2005) “Determinants <strong>of</strong> business student satisfaction and retention
in higher education: applying Herzberg’s two-factor <strong>the</strong>ory”, International Journal <strong>of</strong> Educational
Management, Vol. 19, No. 2, pp 128-139.
Douglas, J.; Douglas, A. And Barnes, B. (2006) “Measuring student satisfaction at a UK university”, Quality
Assurance in Education, Vol. 14, No. 3, pp 251-267.
Libbey, H.P. (2004): Measuring Student Relationships to School: Attachment, Bonding, Connectedness and
Engagement, in: Journal <strong>of</strong> School Health, September 2004, Vol. 74, No. 7, pp. 274-283.
Lovelock, C.H., Wirtz, J. (2004): Services marketing – People, technology, strategy, Pearson Prentice Hall, 5th
Edition.
Nonaka, I. (1991) “The Knowledge-Creating Company”, Harvard Business Review, November-December, pp 96-
104.
Oldfield, B. M., Baron, S. (2000): Student perceptions <strong>of</strong> service quality in a UK university business and
management faculty, in: Quality Assurance in Education, Volume 8, Number 2,. pp. 85-95
O’Regan, P. and O’Donnel, D. (2000) “Intangible Asset Management: Recognizing, Valuing and Managing
Intellectual Capital”. In: Standford-Smith, B. and Kidd, P.T. (Eds.) E-business: key issues, applications and
technologies, IOS Press, Amsterdam, pp 353-366.
Pelau, C. (2010): The Relation between <strong>the</strong> Performance and Satisfaction <strong>of</strong> Students in Universities, in Bratianu,
C.; Lixandroiu, D.; Pop, N. Al.: Business Excellence, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 5th International <strong>Conference</strong> on
Business Excellence, Brasov, pg. XX
Pelau, C; Vladoi, A. D.; Fufezan, M.; Dinca, V.; Ghinea, V. (2010): The Influence <strong>of</strong> Knowledge Dynamics on
Consumer Behavior, in: <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 2nd <strong>European</strong> <strong>Conference</strong> on Intellectual Capital, Lisbon,
Portugal, pg. 465-471.
Pop, N. Al.; Tanţău A.; Pelau, C. (2010): Education and New Collaborative Methods. Case Study: MBA
“Entreprenuership and Innovation Management, in: Rusu, C. (ed.): Quality Management in Higher
Education, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 6th International Seminar on <strong>the</strong> Quality Management in Higher Education,
Tulcea, Romania, 2010, pg. 659-662.
349

Knowledge Cities: A Portuguese Case
Katia Rodrigues and Eduardo Tomé
CLEGI Universidade Lusíada de Vila Nova Famalicão
lamisskatia@msn.com
Eduardo.tome@clix.pt
Abstract: The paper analyzes <strong>the</strong> question <strong>of</strong> knowledge cities in north <strong>of</strong> Portugal. In modern societies,
knowledge is seen as essential. To put toge<strong>the</strong>r cities and knowledge is also important because trends <strong>of</strong>
urbanity are virtually irreversible. In late 2008, half <strong>the</strong> world population lived in cities, according to a demographic
study by <strong>the</strong> ONU. In this paper, firstly, we describe <strong>the</strong> <strong>the</strong>ory and <strong>the</strong> concept <strong>of</strong> knowledge cities relying on
various authors. We also explain <strong>the</strong> shift from knowledge city to intelligent city, because <strong>the</strong>re are some
differences between those notions. Usually it is thought that to be considered as knowledge city, a city needs
urban scale. But a study from 2007 contradicts this idea using <strong>the</strong> notion <strong>of</strong> <strong>European</strong> Smart Cities. That study
argues that <strong>the</strong> medium-sized cities can also be intelligent. Secondly, we apply <strong>the</strong> method <strong>of</strong> smart cities to <strong>the</strong>
city Braga. Given that <strong>the</strong> study <strong>of</strong> <strong>European</strong> Smart Cities does not disclose <strong>the</strong> numerical values assigned to
each city in <strong>the</strong> indicators only its ranking, it was necessary to establish a baseline, achieved by <strong>the</strong> inclusion in
<strong>the</strong> study <strong>of</strong> best and worst Smart City (Luxembourg and Ruse respectively). Braga is a medium size city located
in <strong>the</strong> North <strong>of</strong> Portugal. We conclude that Braga is not yet smart city and not even a knowledge city and also that
<strong>the</strong> city can win investing in Knowledge.
Keywords: knowledge cities, a Portuguese case
1. Introduction
In <strong>the</strong> end <strong>of</strong> <strong>the</strong> first decade <strong>of</strong> <strong>the</strong> 21 st century knowledge is already <strong>the</strong> main economic asset.
Knowledge implies prosperity. Countries are ranked by <strong>the</strong>ir income per head as well as by <strong>the</strong>ir
knowledge economy indicator. Fur<strong>the</strong>rmore people tend to live in cities, and <strong>the</strong>refore knowledge
cities are an increasingly important economic topic. Portugal is a member <strong>of</strong> <strong>the</strong> Eurozone, and is
dominated by Lisbon and Porto. However <strong>the</strong> country has also several medium scale cities, namely
Évora, Faro, Coimbra, Aveiro, Braga and Funchal. Those medium scale cities are essential for <strong>the</strong>
economic sustainability <strong>of</strong> <strong>the</strong> country. In this paper we apply <strong>the</strong> relevant <strong>the</strong>ories about knowledge
cities to <strong>the</strong> Braga city.
The paper will be divided in three main sections. In <strong>the</strong> first section, <strong>the</strong> concept <strong>of</strong> knowledge and
knowledge cities will be presented (2.1); fur<strong>the</strong>rmore types <strong>of</strong> knowledge cities will be enumerated
(2.2); afterwards <strong>the</strong> factors explaining knowledge cities are summarized (2.3); <strong>the</strong>n <strong>the</strong> difference
between knowledge cities and intelligent cities is explained (2.4); finally <strong>the</strong> explanation <strong>of</strong> existence
<strong>of</strong> smart cities is given (2.5). In <strong>the</strong> second section we describe <strong>the</strong> methodology <strong>of</strong> smart cities
(3.1.1),<strong>the</strong> cases we choose, namely Braga, Luxembourg and Ruse (3.1.2) and <strong>the</strong> respective
national setting (3.1.3); after a generic description <strong>of</strong> three cities included in <strong>the</strong> study (3.1.4 ) we
apply <strong>the</strong> methodology (3.1.5); . Finally, in <strong>the</strong> third section we present <strong>the</strong> conclusions (4.1), <strong>the</strong>
limitations <strong>of</strong> <strong>the</strong> study (4.2); and some inroads to fur<strong>the</strong>r research (4.3).
2. Theoretical background
2.1 Knowledge and knowledge cities
An economy based in Knowledge is <strong>the</strong> one that "encourages organizations and people to acquire,
create, disseminate and use more effectively, knowledge (codified or tacit) in order to obtain a greater
economic and social development” (Dahlman 2007). Knowledge can reach people, companies, public
organizations, <strong>the</strong> regions and affects <strong>the</strong> cities too. And <strong>of</strong> course, in <strong>the</strong> current economic setting,
sciences, technology, innovation, training <strong>of</strong> human resources are factors <strong>of</strong> economic growth and
regional development.
Cities are a reflection <strong>of</strong> who inhabits <strong>the</strong>m. Knowledge cities exist when people, companies, public
organizations and <strong>the</strong> surrounding region are based on knowledge. A city with no skilled human
resources, and with traditional companies with no prospect <strong>of</strong> future, will never be a knowledge city. In
that context, public investments are needed primarily to <strong>the</strong> creation <strong>of</strong> universities, and to <strong>the</strong>
planning <strong>of</strong> cities. But support for knowledge cities also must come from <strong>the</strong> private sector. Managers
give importance to innovation and to <strong>the</strong> creativity <strong>of</strong> <strong>the</strong> human resources <strong>the</strong>y manage.
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In a limited approach, knowledge cities are seen only as cities that have research centers,
educational institutions and companies operating internationally that are defined by <strong>the</strong> knowledge
and <strong>the</strong> potential <strong>the</strong>y possess, and <strong>the</strong> quality <strong>of</strong> its human resources; in a more comprehensive
approach, knowledge cities are able to use <strong>the</strong> technological innovations generated elsewhere, boost
a variety <strong>of</strong> Creative Industries, and to renew <strong>the</strong> operating mode <strong>of</strong> <strong>the</strong> city and all its activities
(Martins et al, 2007).
2.2 Types <strong>of</strong> knowledge cities
In a knowledge city, <strong>the</strong> critical piece is <strong>the</strong> individual. This happens because for a creative city to be
successful, a creative class is needed (Florida, 2002). Clearly, all individuals are different and <strong>the</strong>
results <strong>of</strong> <strong>the</strong>se sets <strong>of</strong> people are also different. So all <strong>the</strong> cities <strong>of</strong> knowledge are not equal. A
possible typology <strong>of</strong> cities according to <strong>the</strong>ir status in <strong>the</strong> knowledge economy is <strong>the</strong> following
(Figueiredo and al. (2007), Winden and Berg (2004), and Sassen (2007).
Table 1: Types <strong>of</strong> knowledge cities
Type <strong>of</strong> city Meaning
Global Cities Prominent cities in <strong>the</strong> world economy, with a
universe <strong>of</strong> values and cultures <strong>of</strong> different ethnic
groups.
Knowledge Stars Cities with excellent standards <strong>of</strong> quality <strong>of</strong> life, and
large urban diversity, which confers high-level
knowledge and local innovations.
Metropoles in Transition Traditionally industrial cities that go to processes <strong>of</strong>
renewal <strong>of</strong> <strong>the</strong> urban system, seeking knowledge
through cultural events, business and sports.
Knowledge Pearls Cities recognized worldwide as centers <strong>of</strong> technology
and development; <strong>the</strong> urban planning associated with
high population endowed with knowledge, <strong>the</strong>se
places stand out as cities <strong>of</strong> <strong>the</strong> future.
Star Technotowns/Star Nicheplayers Smaller cities than <strong>the</strong> metropolis, characterized by a
technological specialization, but low economic
diversity.
Technotowns in Transition/Nicheplayers in Transition Cities that go towards <strong>the</strong> development <strong>of</strong> knowledge,
making partnerships with o<strong>the</strong>r locations to leverage
<strong>the</strong> growth <strong>of</strong> knowledge and technology.
University Towns/Intellectuals Cities in which major universities, but without <strong>the</strong>
business structure to boost <strong>the</strong> economy and
innovation processes in place.
Source: Junior F, (2009).
2.3 Factors explaining knowledge cities
In order for a city to be transformed in a knowledge city, several structural changes are needed; pillars
such as education, economy, quality <strong>of</strong> life, communications have to be built. It is <strong>the</strong> junction <strong>of</strong> <strong>the</strong>se
pillars that effectively leads to knowledge cities.
The analysis <strong>of</strong> those factors has been done by various authors: Albagli (1999); Cassiolato Szapiro
(2002); Castells and Hall, 1994; Diniz and Gonçalves, 2005; Duarte, 2002; Granoveter, 1985, Florida
(2002); Krugman (1991),Winder and Berg, 2004; Knowledge cities can be understood as urban areas
where knowledge is created and applied, based on <strong>the</strong> attraction <strong>of</strong> knowledge workers, and leading
to <strong>the</strong> formation <strong>of</strong> clusters <strong>of</strong> activities that produce goods and / or innovative and competitive
services. The activities <strong>of</strong> knowledge should give uniqueness to each city's knowledge, in <strong>the</strong> sense
that it conveys a distinctive trademark .
According to Winder and Berg, 2004, <strong>the</strong> foundations <strong>of</strong> knowledge cities are <strong>the</strong> knowledge base, <strong>the</strong>
economic base, <strong>the</strong> quality <strong>of</strong> life, <strong>the</strong> connectivity and accessibility, <strong>the</strong> urban diversity , <strong>the</strong> urban
scale and <strong>the</strong> social equity (see Figure 1). Namely:
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Katia Rodrigues and Eduardo Tomé
The knowledge base consists in <strong>the</strong> creative and educational levels <strong>of</strong> <strong>the</strong> whole population, <strong>the</strong>
prestige <strong>of</strong> universities and research centers, <strong>the</strong> knowledge management, <strong>the</strong> organizational
skills and <strong>the</strong> artistic and cultural creativity;
The economic base includes <strong>the</strong> various economic activities, <strong>of</strong>ten organized into clusters, <strong>the</strong> city
has to <strong>of</strong>fer to <strong>the</strong> outside world and which distinguish it from o<strong>the</strong>r cities;
The quality <strong>of</strong> life is essential to attract knowledge and creative workers;
Connectivity and accessibility are essential for a high level <strong>of</strong> physical and digital accessibility,
including excellent telecommunications services and access to international airports and excellent
mobility solutions in its interior and also pervasive digital connectivity for its residents;
Urban diversity results from <strong>the</strong> diversity <strong>of</strong> <strong>the</strong> population in several respects (cultural, ethnic,
national, lifestyle, etc.). Studies show that <strong>the</strong> creative class prefers cities with a thriving cultural
life, a cosmopolitan orientation and high levels <strong>of</strong> human and social development;
The urban scale means that <strong>the</strong> size <strong>of</strong> <strong>the</strong> city accounts for its opportunities in <strong>the</strong> "Knowledge
Economy". Not all cities can be knowledge cities, and this impossibility is is more likely to exist in
<strong>the</strong> case <strong>of</strong> small cities. However one can’t deduce from this statement that all big cities are cities
<strong>of</strong> knowledge. In fact even medium-sized cities can be knowledge cities especially if <strong>the</strong>y can
benefit from externalities. The concept <strong>of</strong> urban scale will be important is <strong>the</strong> analysis <strong>of</strong> smart
cities (see 2.5)
Social equity results from creating conditions that minimize <strong>the</strong> risks <strong>of</strong> social dividing that are a
byproduct <strong>of</strong> <strong>the</strong> "Knowledge Economy".
Figure 1: Knowledge cities (source: Winden and Berg 2004)
According to Castells and Hall (1994), local knowledge is present in <strong>the</strong> society and <strong>the</strong> agents living
in each region. The city area is a corridor <strong>of</strong> <strong>the</strong> flow <strong>of</strong> knowledge that permeates <strong>the</strong> local society,
within a decentralized territory that is integrated with <strong>the</strong> outside environment. O<strong>the</strong>r authors point out
that knowledge streng<strong>the</strong>ns <strong>the</strong> cities, through cultural, historical and human factors (Diniz and
Gonçalves, 2005). Also, cities are formed by diversity, attracting, creating and transforming value
(Duarte, 2002).
Social embeddedness postulates that <strong>the</strong> attractiveness <strong>of</strong> a location depends on a set <strong>of</strong> systemic
elements; those are <strong>the</strong> local, economic, social, cultural and political factors that generate unique
identity <strong>of</strong> <strong>the</strong> region (Granoveter,1985).
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Katia Rodrigues and Eduardo Tomé
In <strong>the</strong> view <strong>of</strong> Cassiolato and Szapiro (2002), <strong>the</strong> capacity for innovation is a key element for <strong>the</strong>
success <strong>of</strong> local and companies residents. Albagli (1999) states that <strong>the</strong> process <strong>of</strong> innovation is <strong>the</strong>
driving motor for economic development. Innovation is widely discussed in <strong>the</strong> evolutionary discussion
about technology and economic development, and is based in <strong>the</strong> systemic characteristics <strong>of</strong> <strong>the</strong> local
sphere resulting in <strong>the</strong> interaction <strong>of</strong> public and private flows <strong>of</strong> foreign knowledge, and having in mind
<strong>the</strong> learning ability (Diniz, 2001). In this context, according to Krugman (1991), cities are seen as
informational entities that allow an acceleration <strong>of</strong> flows <strong>of</strong> knowledge, through innovation and human
capital externalities. Finally, in a different vein, Florida (2002) gives a strategic role to cities, stressing
<strong>the</strong> importance <strong>of</strong> proximity, diversity and creativity to generate dynamics <strong>of</strong> innovation, providing a
sustainable flow <strong>of</strong> ideas between individuals and companies and promote <strong>the</strong> pace <strong>of</strong> innovation.
2.4 Knowledge cities and intelligent cities
The concept <strong>of</strong> intelligent city and concept <strong>the</strong> knowledge city differ from one ano<strong>the</strong>r. An intelligent
city It is <strong>the</strong> intersection <strong>of</strong> <strong>the</strong> knowledge city with <strong>the</strong> digital city Komninos (2006). Digital City is a
"community space that is used to facilitate and enhance <strong>the</strong> activities and functions that occur in
physical space <strong>of</strong> <strong>the</strong> city". The intelligent city is defined as "knowledge city committed to
technological innovation and <strong>the</strong> creativity <strong>of</strong> its inhabitants, with a strong institutional leadership and
organizational capacity, in seeking solutions to increase <strong>the</strong>ir competitiveness and sustainability,
considering that it can cover a range <strong>of</strong> activities wider than is normally referred to knowledge cities”.
Fur<strong>the</strong>rmore intelligent cities are areas "with high capacity for learning and innovation, which is
constructed by <strong>the</strong> creativity <strong>of</strong> its people, its institutions knowledge creation and its digital
infrastructure for communication and knowledge management".
Figure 2: Knowledge cities, digital cities, intelligent cities. smart cities
2.5 The smart cities
For many authors, knowledge requires scale: to be able to speak in cities in <strong>the</strong> knowledge we need a
large urban scale or medium scale with links to major cities. But for o<strong>the</strong>r authors (Giffinger and al,
2007) medium cities are a fascinating target group. Around 120 million people live in some 600 cities
<strong>of</strong> this size in Europe. Those cities have enormous potential, but never<strong>the</strong>less are <strong>of</strong>ten in <strong>the</strong> shadow
<strong>of</strong> large cities. They have difficulties in positioning <strong>the</strong>mselves at times, struggling with issues <strong>of</strong> brand
and are forgotten by investors. But <strong>the</strong>y have an important advantage: because <strong>of</strong> <strong>the</strong>ir size, <strong>the</strong>y are
flexible and can transmit <strong>the</strong>ir wits (Giffinger and al, 2007). Therefore smart cities are medium size
intelligent cities.
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3. The empirical study
3.1 Methodology
Katia Rodrigues and Eduardo Tomé
3.1.1 The smart cities methodology
In this study we follow <strong>the</strong> smart cities methodology (Giffinger and al, 2007). Smart or knowledge
cities reflect <strong>the</strong> need <strong>of</strong> a radical reformulation <strong>of</strong> cities, as a consequence <strong>of</strong> <strong>the</strong> change <strong>the</strong> world
faced in <strong>the</strong> Knowledge Era, and when it entered <strong>the</strong> Knowledge Based Economy. Smart cities score
high in <strong>the</strong> following items: smart economy (innovation, entrepreneurship, productivity, branches,
flexibility, international integration); smart mobility (local accessibility, national accessibility, availability
<strong>of</strong> ICT infra-structures, transport systems); smart living (cultural equipments, health conditions, quality
<strong>of</strong> housing, individual safety, educational facilities, touristic attraction, and social cohesion); smart
Governance (participation in <strong>the</strong> decision making process, level <strong>of</strong> public social services,
transparency, strategy and perspectives); smart Environment (natural conditions, pollution,
environmental protection, management <strong>of</strong> natural resources); smart people (skills, lifelong learning,
ethnic plurality, creativity, cosmopolitism, participation in <strong>the</strong> working life) (Giffinger and al, 2007).
3.1.2 The chosen cases
This practical part is based on statistical data related to three cities: Braga (PT), Luxembourg (LU)
and Ruse (BG). Braga is our case study, <strong>the</strong> o<strong>the</strong>r two cities were chosen because <strong>of</strong> <strong>the</strong>ir positions
in <strong>the</strong> ranking <strong>of</strong> "european smart cities" (Giffinger and al, 2007). The city <strong>of</strong> Luxembourg occupies <strong>the</strong>
first place and <strong>the</strong> city <strong>of</strong> Ruse occupies <strong>the</strong> last place. So we will compare <strong>the</strong> reality <strong>of</strong> Braga with
<strong>the</strong> best smart city and <strong>the</strong> worst smart city. The three medium-sized cities have at least one
university: University <strong>of</strong> Minho (Braga), Angel Kanchev University <strong>of</strong> Ruse (Ruse) and University <strong>of</strong>
Luxembourg (Luxembourg).
3.1.3 The national setting
We consider to be important to describe briefly <strong>the</strong> three countries in which <strong>the</strong> three cities are located
in terms <strong>of</strong> broad economic indicators. The indicators used are those used in <strong>the</strong> study european
smart cities. But unfortunately we were not able to find information for all fields used in that
methodology. To overcome that problem we added variables as <strong>the</strong> HDI, and also governance
indicators. The data we collected are shown in Table 2
Table 2: Broad economic indicators for case study countries
Portugal Luxembourg Bulgaria
HDI (a) 0,897 0,944 0,824
GDP ($US CURRENT
millions ) (b)
242 689 54 257.3 49 900.4
Voice and Accountability
(c)
89.1 97.6 64.0
Political Stability (c) 74.5 96.2 62.7
Government
Effectiveness (c)
85.2 96.2 59.0
Regulatory Quality (c) 80.5 95.7 71.4
Rule <strong>of</strong> Law (c) 83.5 97.6 53.8
Control <strong>of</strong> Corruption (c) 81.9 95.2 54.3
Source: (a) United Nations Development Program 2007 (b) World bank 2008 (c) World bank 2009 (c)
Percentile Rank (0-100)
Luxembourg (country) is positioned in <strong>the</strong> first place in all indicators in relation to Portugal and
Bulgaria. Luxembourg has excellent results in <strong>the</strong> HDI, <strong>the</strong> GDP (U.S. $ millions current), in Voice and
Accountability in Political Stability, Government Effectiveness in <strong>the</strong> Regulatory Quality Rule <strong>of</strong> Law
and <strong>the</strong> Control <strong>of</strong> Corruption. Portugal performs better than Bulgaria in all indicators. These
indicators are very important to describe <strong>the</strong> social, economic and political <strong>of</strong> <strong>the</strong> countries. Most
investors give immense relief to <strong>the</strong>se economic indicators. Before realizing microeconomic is
necessary to understand macroeconomic. These indicators are developed by <strong>the</strong> World Bank and <strong>the</strong>
United Nations Development Program.
354

3.1.4 Cases description
a) Braga
Katia Rodrigues and Eduardo Tomé
Braga is <strong>the</strong> oldest Portuguese city and one <strong>of</strong> <strong>the</strong> oldest Christian cities <strong>of</strong> <strong>the</strong> world, founded in
Roman times as Bracara Augusta, has more than 2000 years <strong>of</strong> history as a city. Located in nor<strong>the</strong>rn
Portugal, more specifically in <strong>the</strong> Valley Cávado, Braga has 177 183 residents in his county, being <strong>the</strong>
center <strong>of</strong> <strong>the</strong> Minho region with more than one million inhabitants (2009). The county is densely
populated with 960 inhabitants per km ² is one <strong>of</strong> <strong>the</strong> most populous <strong>of</strong> Portugal (INE 2010). Braga
has <strong>the</strong> University <strong>of</strong> Minho (Gualtar) and Catholic University (St. Vincent).
In <strong>the</strong> area <strong>of</strong> mass transportation, <strong>the</strong> county <strong>of</strong> Braga is served by <strong>the</strong> public transport TUB. The
TUB has a fleet <strong>of</strong> 115 vehicles. The network covers <strong>the</strong> entire county with stops in 1590, and 238.15
km on 76 lines where each year it travels 5,365 km with 11 292 million passengers. Braga also has a
bus station near <strong>the</strong> city's circle, where <strong>the</strong>re are daily connections to all regional Minho, west <strong>of</strong> Trasos-Montes
and Alto Douro, and Douro Litoral. In <strong>the</strong> central connections can also be found daily in <strong>the</strong>
Express network and Renex weekly for <strong>the</strong> whole country and for Europe. (TUB 2010)
The nearest international airports are: Francisco Sá Carneiro Airport (50 km) Portela Airport (350 km),
and in neighboring Spain, Vigo Airport (125 km). The two major seaports nearby are <strong>the</strong> Port <strong>of</strong> Viana
(50 km) and Port <strong>of</strong> Leixões (50 km). The rate <strong>of</strong> economically active population in 2001 was 51.9%,
or 85,194 individuals distributed in <strong>the</strong> following sectors: 893 individuals in <strong>the</strong> primary, 31,374
secondary sector, tertiary sector 47,031 <strong>of</strong> which 24,655 individuals were linked to economic activities
(Statistics Portugal, 2001).
There are several industrial parks and business centers on <strong>the</strong> outskirts <strong>of</strong> <strong>the</strong> city, such as Complex
Grundig / Blaupunkt, Blacksmith's business center, and industrial park Adaúfe. With <strong>the</strong> construction
<strong>of</strong> <strong>the</strong> Braga International Iberian Nanotechnology Laboratory (INL) and deployment <strong>of</strong> <strong>the</strong> Business
Development Institute <strong>of</strong> <strong>the</strong> Atlantic, and <strong>the</strong> installation <strong>of</strong> several dozen technology-based
companies a big boost is expected for economy <strong>of</strong> Braga (Pme online 2010). The city <strong>of</strong> Braga have
many companies to <strong>the</strong> s<strong>of</strong>tware, some <strong>of</strong> great renown, namely: Primavera S<strong>of</strong>tware (<strong>the</strong>
Portuguese company leader in s<strong>of</strong>tware production in Portugal and among <strong>the</strong> 500 largest <strong>European</strong>
companies with potential growth (Primavera 2006) and Edigma, Portugal's leading project
management and digital interactivity (Diario economico 2007)
b) Luxembourg
Luxembourg is a commune <strong>of</strong> Luxembourg with city status, belonging to <strong>the</strong> district <strong>of</strong> Luxembourg
and <strong>the</strong> canton <strong>of</strong> Luxembourg. Luxembourg is a very developed city in its trade and industries. The
city <strong>of</strong> Luxembourg has 483 799 inhabitants, with population density <strong>of</strong> 194.1 inhabitants per km ².
(Statistics Luxembourg 2010). Luxembourg economic and social indicators are among <strong>the</strong> highest in
<strong>the</strong> <strong>European</strong> Un ion.
c) Ruse
Ruse is <strong>the</strong> fifth largest city in Bulgaria with a population <strong>of</strong> nearly 157,000 inhabitants. The city was
called until independence <strong>of</strong> Bulgaria in 1878, Roustchouk (Rusçuk inTurkish). The city <strong>of</strong> Ruse is
situated in <strong>the</strong> nor<strong>the</strong>ast, opposite <strong>the</strong> Romanian city <strong>of</strong> Giurgiu. It has <strong>the</strong> largest river port in
significant in Bulgaria, serving an important part <strong>of</strong> <strong>the</strong> country's international trade.( University <strong>of</strong>
Ruse ,2003)
3.1.5 Statistical analysis
The result <strong>of</strong> <strong>the</strong> application <strong>of</strong> <strong>the</strong> smart cities methodology to <strong>the</strong> mentioned three cities is shown in
Table 3:
In <strong>the</strong> category "Smart Economy", <strong>the</strong> City <strong>of</strong> Luxembourg is <strong>the</strong> best performer in <strong>the</strong> first three
indicators. The percentage <strong>of</strong> GDP spent in R & D in Braga nears that <strong>of</strong> Luxembourg: 1.20% and
1.58% respectively. The rate <strong>of</strong> employment in knowledge intensive sectors is broadly lower in Braga
(2.20%) than in <strong>the</strong> City <strong>of</strong> Luxembourg (13.23%) and in <strong>the</strong> city <strong>of</strong> Ruse (2,15%). The same happens
in relation to <strong>the</strong> patent applications per capita: Braga (0.13%) and Luxembourg (7.24%).
355

Table 3: Smart cities – application <strong>of</strong> methodology
Katia Rodrigues and Eduardo Tomé
BRAGA LUXEMBOURG RUSE
1.SMART ECONOMY
R&D expenditure in % <strong>of</strong> GDP (R) 1,20% 1,58% 0,52%
Employment rate in knowledge-intensive sectors (R ) 2.20% 13,23% 2,15%
Patent applications per inhabitant (R ) 0,13% 7,24% .
Self-employment rate (L) 1.58% 7.6% .
New businesses registered in proportion <strong>of</strong> existing
companies (L) 13.55% 11,80% .
GDP per head (€) (R ) € 10.629 48.688 € 1.673,00€
Unemployment rate (L) 11,50% 5,80% 14%
2.SMART PEOPLE
Gross enrollment rate in higher education (%) (L) 74,40% 8,42% 41,22%
Share <strong>of</strong> foreigners (L) 1 219 78749 .
People working in creative industries (N) 1,40% . .
Voters turnout at <strong>European</strong> elections (L) 44,70% 90,75% .
Voters turnout at city elections(L) 68% 83% 34%
3. SMART GOVERNANCE
Perception on transparency <strong>of</strong> bureaucracy (N) 6 8.5 3.6
Perception on fight against corruption (N) 81.9 95.2 54.3
4. SMART MOBILITY
Computers in households (N) 48.8% 88% 20%
Broadband internet access in households(N) 96% 82% 23,50%
5. SMART ENVIRONMENT
Green space share (L)
13 m2 per
capita
30 m2 per
capita .
Summer smog (L) 29 53 1
Fatal chronic lower respiratory diseases(L) 1312 hab 314 hab .
6. SMART LIVING
Visits to museums (L) 20 058 339862 4373
Life expectancy (N) 75years 79years 71years
Hospital beds per inhabitant (L) 3,2%0 6.7 %0 7,4%0
Crime rate (L) 37,3 %0 53,35%0
Doctors per inhabitant (L) 3,58 2,9 3,4
Share <strong>of</strong> housing fulfilling minimal standards (L) 85 670 168198
Students per inhabitant (L) 30% 18,22%
Poverty rate (N) 19% 14,90% 14,70%
Poverty line (N) 400 EUR 1.484 EUR 230 EUR
Source: Statistics Portugal (www.ine.pt), Urban audit Braga, Urban audit Luxembourg, Urban audit
Ruse, Statistics Luxembourg (www.statistiques.public.lu), Statistics Bulgaria (www.nsi.bg)
Note: Local (L), Regional (R ) National (N)
But with respect to <strong>the</strong> rate <strong>of</strong> self-employment (1.58%) and <strong>the</strong> number <strong>of</strong> new businesses registered
in <strong>the</strong> proportion <strong>of</strong> existing firms (13.55%), Braga takes a relatively good advantage. Finally in what
concerns <strong>the</strong> GDP per capita and <strong>the</strong> unemployment rate, Braga is situated between two o<strong>the</strong>r cities.
In <strong>the</strong> category "Smart People," Braga has good results in <strong>the</strong> gross enrollment rate in higher
education with 74.40%. Braga has a small number <strong>of</strong> foreigners (1219) instead <strong>of</strong> Luxembourg
(78,749). The percentage <strong>of</strong> people working in creative industries in Portugal is 1.40%. Voter
participation in Braga is always less than Luxembourg but always above <strong>the</strong> city <strong>of</strong> Ruse.
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Katia Rodrigues and Eduardo Tomé
In <strong>the</strong> category "Smart Governance", Luxembourg provides results superior to Braga. But Braga
presents better results than Ruse.
In <strong>the</strong> category "Smart Mobility", Braga and Luxembourg compete for best results. Luxembourg has
more computers at home (88%) but Braga has greater access to broadband Internet in homes (96%).
In <strong>the</strong> category "Smart Environment", Braga has worse results than Luxembourg in <strong>the</strong> division <strong>of</strong>
green space and <strong>the</strong> number <strong>of</strong> deaths due to respiratory problems. But in relation to <strong>the</strong> Summer
smog analysis Braga shows better result than Luxembourg but worse than Ruse.
Finally in <strong>the</strong> category "Smart Living", Luxembourg displays more visits to museums and a life
expectancy greater than Braga. Ra<strong>the</strong>r Braga shows better results in doctors per capita in 1000 and
<strong>the</strong> number <strong>of</strong> students per capita, 3.58 and 30% respectively. In terms <strong>of</strong> poverty rate Portugal has
<strong>the</strong> worst outcome with 19%, but it is important to note that <strong>the</strong> poverty lines are different in <strong>the</strong> three
countries.
4. Concluding comments
4.1 Conclusions
In short, Braga has not yet reached <strong>the</strong> level <strong>of</strong> development <strong>of</strong> Luxembourg, but lies in a better
position than <strong>the</strong> city <strong>of</strong> Ruse. Some indicators give a positive note to Braga, like <strong>the</strong> educational
levels, young population, and a good access to ICT. Braga but still has difficulty connecting
universities to <strong>the</strong> business environment. This means that still only a few partnerships exist between
companies and universities, a situation which is also hampered by <strong>the</strong> lack <strong>of</strong> planning Braga.
Fur<strong>the</strong>rmore <strong>the</strong>re are still no real signs <strong>of</strong> urban regeneration, and <strong>the</strong> transport system is in general
not very efficient. This means that <strong>the</strong>re are still many aspects to be improved in order to make Braga
dynamic and efficient in <strong>the</strong>n use <strong>of</strong> knowledge resources.
But fortunately <strong>the</strong>re are some investments that carry a positive note. One <strong>of</strong> <strong>the</strong>m is <strong>the</strong> idea to
create a business incubator (Idea-Atlantic), which stands out as a business center. Priority will be
given start-ups with a strong and innovative technology aimed at <strong>the</strong> development <strong>of</strong> new products,
services or processes and associated technology, innovation and applied research. Companies may
be incubating in any region <strong>of</strong> <strong>the</strong> country or even abroad, as <strong>the</strong> Business Center "<strong>of</strong>fers <strong>the</strong>
necessary conditions for business to operate in a network or with o<strong>the</strong>r co-development with ei<strong>the</strong>r
<strong>the</strong> headquarters or o<strong>the</strong>r subsidiaries with enormous flexibility.” (Pme online 2010). Secondly, <strong>the</strong>
construction <strong>of</strong> a center <strong>of</strong> international Iberian Nanotechnology on <strong>the</strong> University <strong>of</strong> Minho is also
viewed positively. This lab has an estimated annual investment <strong>of</strong> 30 million and is <strong>the</strong> result <strong>of</strong> a
memorandum <strong>of</strong> understanding between <strong>the</strong> Ministry <strong>of</strong> Science, Technology and Higher Education in
Portugal and <strong>the</strong> Ministry <strong>of</strong> Education and Science <strong>of</strong> Spain for <strong>the</strong> creation and joint operation <strong>of</strong> an
Institute for Research and Development. The city <strong>of</strong> Braga will create nearby a Technological Park <strong>of</strong>
Excellence TechValley integrated in <strong>the</strong> project for <strong>the</strong> installation <strong>of</strong> companies with technological
base. (INL, 2010). Thirdly, <strong>the</strong> creation <strong>of</strong> <strong>the</strong> "Digital braga" relies on numerous projects such as <strong>the</strong>
portal bragadigital, <strong>the</strong> operating system <strong>of</strong> urban companies, telemetry ecopoints, virtual museums,
an educational portal, a ring <strong>of</strong> broadband and fiber optics, etc.. Some <strong>of</strong> <strong>the</strong>se projects are already
operational. (Braga Digital 2010,www.bragadigital.pt). Finally <strong>the</strong> city <strong>of</strong> Braga has just formally, with
<strong>the</strong> <strong>European</strong> Youth Forum, is applying to organize <strong>the</strong> <strong>European</strong> Capital <strong>of</strong> Youth in 2012
(Municipality <strong>of</strong> Braga www.cm-braga.pt).
The projects just mentioned will only have long-term effects. It is hoped that with a greater
involvement <strong>of</strong> <strong>the</strong> municipality Braga will be able to became Smart.
4.2 Limitations
This study has some limitations. It was impossible to obtain many indicators indicated in <strong>the</strong>
methodology <strong>of</strong> <strong>the</strong> "<strong>European</strong> Smart Cities". And, many important investments made in Braga have
emerged recently and will only have effects in <strong>the</strong> long run.
357

4.3 Suggestions to future work
Katia Rodrigues and Eduardo Tomé
Because this subject have pleased me want to expand my study to o<strong>the</strong>r medium sized cities such as
Portugal Évora (Alentejo), Faro (Algarve), Coimbra (Beira Litoral), Aveiro (Beira Litoral) and Funchal
(Madeira island). All <strong>of</strong> <strong>the</strong>m have o<strong>the</strong>r characteristics different from those found in Braga. Obviously,
Portugal is still not at <strong>the</strong> forefront <strong>of</strong> intelligent cities but all cities have <strong>the</strong>ir own specific media and
different capabilities.
References
Albagli, S. (1999) Informação e Globalização na era do conhecimento. Rio de Janeiro: Campus.
Braga Digital (www.bragadigital.pt)
Castells, M.; Hall, P. (1994) Technopoles <strong>of</strong> <strong>the</strong> world: <strong>the</strong> making <strong>of</strong> twenty-first-century industrial complexes.
London: Routledge,.
Cassiolato, J.; Szapiro, M. (2002) Arranjos e sistemas produtivos e inovativos locais do Brasil. Rio de Janeiro:
UFRJ,.
Dahlman, A. (2007),“<strong>European</strong> Cities in <strong>the</strong> Knowledge Economy: Towards a Typology”, Urban Studies, Volume
44, Issue 3, March 2007, pages 525-549.
Diario economico 2007: Edigma.com lança empresa nos Estados Unidos
(http://diarioeconomico.sapo.pt/edicion/diarioeconomico/nacional/empresas/pt/desarrollo/735390.html)
Diniz, C. C. (2001) O papel das inovações e das instituições no desenvolvimento local. In: XXIX ENCONTRO
NACIONAL DE ECONOMIA – ANPEC (Associação Nacional do Centros de Pós-graduação em Economia
[Brazilian Association <strong>of</strong> Graduate Programs in Economics)...<strong>Proceedings</strong>. Salvador-BA, n. 085,.
Duarte, F. (2002) Crise das matrizes espaciais. São Paulo: Perspectiva.
Figueiredo, C.; Azevedo, F.; Ribeiro, F.; Proença, M.; Abreu, M.J. (2007) Cidades Inovadoras e Competitivas
para o Desenvolvimento Sustentável. Departamento de Prospectiva e Planeamento e Relações
Internacionais. Ministério do Ambiente, do Ordenamento do Território e do Desenvolvimento Regional.
Lisboa.
Florida, R. (2002), The Rise <strong>of</strong> <strong>the</strong> Creative Class, and How It's Transforming Work, Leisure and Everyday Life,
New York, Basic Books.
Giffinger, R.; Christian F., Hans K., Robert K., Nataša P., Evert M., (2007). "Smart cities – Ranking <strong>of</strong> <strong>European</strong>
medium-sized cities". http://www.smart-cities.eu/. Vienna: Centre <strong>of</strong> Regional Science. http://www.smartcities.eu/download/smart_cities_final_report.pdf.
Granoveter, M. (1985) Economic action and social structure: <strong>the</strong> problem <strong>of</strong> embeddedness. American Journal <strong>of</strong>
Sociology, Chicago, v. 91, n.3.
INL, International Iberian Nanotechnology, 2010, (http://www.inl.int)
Junior F , (2009); Fatores locais para geração de inovação na economia do conhecimento
Komninos, N. (2006), The architecture <strong>of</strong> intelligent cities; Integrating human, collective, and artificial intelligence
to enhance knowledge and innovation; 2 nd International <strong>Conference</strong> on Intelligent Environments, Institution
<strong>of</strong> Engineering and Technology, A<strong>the</strong>ns, 5-6 July 2006, pp. 13-20
Krugman P. (1991) Geography and trade. Mass: MIT Press, Cambridge
Martins, N.; Figueiredo, C.; Azevedo, F.; Ribeiro, F.; Proença, M.; Abreu,, M.J. PDF: PROJECTO “CIDADES
INTELIGENTES”(2007) Orientações de Política de Revitalização Urbana para a Competitividade e
Sustentabilidade das Cidades
Pme online 2010: IDEIA-ATLÂNTICO CRIA CENTRO DE NEGÓCIOS NO NORTE
(http://www.pme.online.pt/noticias/detalhes.php?id=280)
Primavera 2006: PRIMAVERA entre as 500 com maior potencial de crescimento
(http://www.primaverabss.com/pt/PortalRender.aspx?PageID={83e07ddc-6105-4330-998bce386c8231c1}&PressReleaseID={6a914c2e-a483-428b-ae81-761f83ec14da}
Sassen, S. (2007)“The Repositioning <strong>of</strong> Cities and Urban Regions in a Global Economy: Pushing Policy and
Governance Options”, OECD International <strong>Conference</strong>: What policies for globalising cities? Rethinking <strong>the</strong>
urban policy agenda, Madrid,.
Statistics Bulgaria (www.nsi.bg)
Statistics Luxembourg (www.statistiques.public.lu)
Statistics Portugal (www.ine.pt)
United Nations Development Program (2007) Human Development, Report 2007(hdr.undp.org)
Windem, W. van, Berg, L. van den (2004), Cities in <strong>the</strong> knowledge economy: New governance challendges,
Discussion paper, EURICUR, Project STRIKE.
World bank 2009 (www.worldbank.org) Governance indicators
University <strong>of</strong> Ruse , 2003,Welcome to ruse ,(www.uni-ruse.bg/en/rousse.php
358

Governance <strong>of</strong> Networks <strong>of</strong> Small Enterprises: A
Knowledge Perspective - Some Case Studies in <strong>the</strong>
Mechanical Industry in Italy
Anna Romiti and Daria Sarti
University <strong>of</strong> Florence, Italy
anna.romiti@unifi.it
daria.sarti@unifi.it
Abstract: The idea <strong>of</strong> this work stems from <strong>the</strong> growing attention given to networks <strong>of</strong> small specialized firms, as
an alternative way <strong>of</strong> governance <strong>of</strong> <strong>the</strong> formal cooperative relations between enterprises in a context <strong>of</strong> market
crisis. In this paper we focus on <strong>the</strong> manufacturing networks defined as groups <strong>of</strong> organizations, most <strong>of</strong> <strong>the</strong> time
small-sized, that combine <strong>the</strong>ir competencies and knowledge in order to achieve competitive advantages that
would be difficult to reach on an individual basis. We focus primarly on concepts drawn from <strong>the</strong> RBV (resourcesbased
view) and KBV (Knowledge- based view) <strong>of</strong> firms. These <strong>the</strong>ories suggest that a firm’s competitive
advantage comes from idiosyncratic resources and knowledge and its ability to manage, combe and absorbe
<strong>the</strong>m. The methodology <strong>of</strong> multiple case studies is used with <strong>the</strong> purpose to understand <strong>the</strong> business success in
a SME context. The cases were selected among <strong>the</strong> most significant cases <strong>of</strong> manufacturing networks in <strong>the</strong>
mechanical industry in central Italy. The study shows five factors that, according to previous literature, are
considered key factors in <strong>the</strong> survival and development <strong>of</strong> networks: Commitment, Governance mechanisms,
Proactivity, Broker roles and Absorptive capacity potential. Our aim is to explore factors affecting alliance
development and success and particularly those related to differences in two kinds <strong>of</strong> networks: hard and s<strong>of</strong>t
networks. On <strong>the</strong> contrary to what emerges in previous evidence, we found some <strong>of</strong> <strong>the</strong> factors considered more
relevant in s<strong>of</strong>t than in hard networks. This can be explained because s<strong>of</strong>t network have a higher vocation in
exploration than in exploitation that characterizes hard network. These factors are: degree <strong>of</strong> commitment (both
economic and behavioral) and degree <strong>of</strong> potential absorptive capacity. At <strong>the</strong> same time, brokership and
hierarchical control do not seem to play a different role in <strong>the</strong> two kinds <strong>of</strong> network. Since <strong>the</strong>re is no in-depth
analysis for this topic in <strong>the</strong> Italian context, this paper is intended to provide empirical prior evidence for future
research as well as <strong>the</strong>oretical insights. From a practical perspective, <strong>the</strong> results <strong>of</strong> <strong>the</strong> survey may provide
significant support, in terms <strong>of</strong> managerial and policy implications, about how firms can manage knowledge
practices in order to sustain <strong>the</strong> creation <strong>of</strong> successful manufacturing networks in periods <strong>of</strong> crisis.
Keywords: manufacturing networks, governance mechanisms, small enterprises, intellectual capital, knowledge
management
1. Introduction
New trends such as trade liberalization, intensified competition, information and communication
technologies, growing significance <strong>of</strong> knowledge as a source <strong>of</strong> value creation and competitive
advantage have heavily affected, in <strong>the</strong> last decades, <strong>the</strong> competitive scenario. Due to <strong>the</strong>se
challenges, firms, in particular <strong>of</strong> small-size across many sectors, are moving towards <strong>the</strong> adoption <strong>of</strong>
new organizational forms founded on cooperative strategies.
According to recent literature on SMEs, collaboration among small firms represents a key strategic
decision for <strong>the</strong>ir survival and growth and provides a viable means for small-sized enterprises <strong>of</strong>
combining resources in order to exploit and explore new business opportunities.
Authors have highlighted a relative lack <strong>of</strong> research examining <strong>the</strong> critical factors affecting networking
within SMEs (Sherer 2003; Human and Provan 1997; Brunetto and Farr-Wharton, 2007). This,
according to Brunetto and Farr-Wharton (2007), both in terms <strong>of</strong> s<strong>of</strong>t/explorative or hard/exploitative
networks.
The idea <strong>of</strong> this work stems from <strong>the</strong> growing attention given to networks <strong>of</strong> small specialized firms, as
an alternative way <strong>of</strong> governance <strong>of</strong> <strong>the</strong> formal cooperative relations between enterprises in a context
<strong>of</strong> market crisis. In particular in this paper we will refer to manufacturing networks defined as groups
<strong>of</strong> organizations, most <strong>of</strong> time small-sized, that combine <strong>the</strong>ir competencies and knowledge in order to
achieve competitive advantage that would be difficult to reach on an individual basis.
Our aim in this paper is to explore factors affecting alliance development and success and particularly
those related to differences in two kinds <strong>of</strong> networks: hard and s<strong>of</strong>t networks.
359

Anna Romiti and Daria Sarti
2. Organizational learning and knowledge-based activities in small enterprises
Authors have argued that resource and knowledge-based views <strong>of</strong> <strong>the</strong> firm represent a useful
<strong>the</strong>oretical framework for understanding collaborative relations (i.e. networks) between firms (Grant
and Baden-Fuller, 1995).
According to current debate, knowledge-based activities are considered as <strong>the</strong> main source <strong>of</strong>
sustainable competitive advantage in today’s economy (Grant, 1996). Resource and knowledge
based <strong>the</strong>ories argue that <strong>the</strong> key role <strong>of</strong> organizations is to create, store and apply new and existing
knowledge. Fur<strong>the</strong>rmore, many authors highlight, within <strong>the</strong> debate on small enterprises, that
cooperation strategies among SMEs are seen as means that allow <strong>the</strong>m to compete and survive in
dynamic environments; while partner learning is considered as a key element for <strong>the</strong> success <strong>of</strong>
networks. Moreover, small firms involved in networks tend to adopt a higher-order learning style,
contrary to non-network firms which show a lower-level learning (Chaston and Mangles, 2000).
However, for SMEs knowledge and network management can be difficult to manage because <strong>of</strong> <strong>the</strong>ir
structural and knowledge characteristics. In fact, a SMEs knowledge is usually concentrated with few
key people (i.e. <strong>the</strong> entrepreneur) and is characterized by a high degree <strong>of</strong> specialization regarding
technical-operational competencies.
A review on current literature shows a lack <strong>of</strong> studies on small business organizational learning
(Chaston and Mangles, 2000) and on managing knowledge base in networks <strong>of</strong> SMEs (Valkockary
and Helander, 2007).
3. Manufacturing networks
According to Mohr and Spekman (1994) <strong>the</strong> objective <strong>of</strong> strategic partnerships is <strong>the</strong> achievement <strong>of</strong>
a set <strong>of</strong> goals. Particularly, <strong>the</strong> authors distinguish between two types <strong>of</strong> networks: hard and s<strong>of</strong>t.
Brunetto and Farr-Wharton (2007) refer to <strong>the</strong> former as an exploitative network and <strong>the</strong> latter as
explorative network.
In hard or exploitative networks <strong>the</strong> objective is to co-purchase, co-make or co-produce products and
services (Sherer, 2003). According to Brunetto and Farr-Wharton (2007) “exploitative networks are
those that involve interdependent firms operating in similar activities that participate in joint production
and marketing ventures […] in order to benefit from a new innovation […]. This means that <strong>the</strong>y share
technologies, knowledge, and skills.” (p. 363). According to Sherer (2003) exploitation (hard) networks
require a high degree <strong>of</strong> interdependency and commitment amongst firms since a specific objective is
defined. Moreover, hard networks involve sharing <strong>of</strong> competitive knowledge and expertise, which
leads to greater opportunism and operations risk (Clemons, Reddi, and Row 1993). Exploitative
(hard) networks embrace new innovations by bridging businesses with similar characteristics and skill
set to achieve favorable production and marketing efficiencies (Brunetto and Farr-Wharton, 2007;
Nooteboom, 2004; Sherer, 2003; Kosa and Lewin, 1998).
On <strong>the</strong> o<strong>the</strong>r side, in s<strong>of</strong>t or explorative networks, also considered as learning networks, “firms seek
cooperatively to learn about some <strong>of</strong> <strong>the</strong> complex changes essential to competitiveness, and resource
sharing networks, where firms pool resources such as waste management, insurance, training, and
equipment.” (Sherer, 2003, p 330). Explorative (s<strong>of</strong>t) networks, also embrace new innovations and
focus on cost reduction while retaining each partner’s unique business methodology (Brunetto and
Farr-Wharton, 2007; Nooteboom, 2004; Sherer, 2003; Kosa and Lewin, 1998).
4. Factors affecting alliance development
In <strong>the</strong> literature on collaborative networks <strong>of</strong> SMEs are highlighted several factors that play an
important role on <strong>the</strong> network development are highlighted (see table 1). In particular Sherer (2003)
distinguishes between factors that are more important to hard networks from those that are more
critical to s<strong>of</strong>t networks.
As for trust, it is expected that it is more critical in hard networks compared to s<strong>of</strong>t, because <strong>the</strong>
members <strong>of</strong> hard networks are more vulnerable due to <strong>the</strong> higher interdependence and sharing <strong>of</strong>
sensible knowledge (Mayer, Davis and Schoorman 1995). Also, commitment is more critical in hard
networks since <strong>the</strong>ir functioning <strong>of</strong>ten require more changes in internal operating procedures (Parkhe,
1993). O<strong>the</strong>r authors used partner characteristics (e.g. partner reputation) to explain strategic alliance
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outcomes (Saxton, 1997). Members’ selection, is particularly important to hard networks in order to
lower operation risks. Finally, information technology is more important in hard networks because it is
useful in facilitating <strong>the</strong> coordination <strong>of</strong> more interdependent activities. What Sherer (2003) suggests
implies, in an indirect manner, a critical role played also by intermediaries (i.e. brokers) and control
mechanism (i.e. governance mechanisms – Makadok and C<strong>of</strong>f, 2009) in <strong>the</strong> coordination <strong>of</strong> hard
networks.
Lane and Lubatkin (1998) found relative absorptive capacity measures positively related to
interorganizational learning. Fur<strong>the</strong>rmore, <strong>the</strong> way firms behave, according to environmental and
internal characteristics from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> proactivity, has an important impact on <strong>the</strong> formation
and development <strong>of</strong> networks (Weaver and Dickson, 1997; Sherer, 2003; Park and Zhou, 2005;
Parkhe, Wasserman and Ralston, 2006).
For <strong>the</strong> current study we decided not to include some <strong>of</strong> <strong>the</strong> above mentioned factors (i.e. information
techonolgy, trust and partner characteristics) but only five out <strong>of</strong> <strong>the</strong>se.
In fact, according to Sherer (2003) small-sized firms may not have <strong>the</strong> time or <strong>the</strong> resources to build
trust and many networks <strong>of</strong> SMEs appear to be driven mainly by intermediaries. Fur<strong>the</strong>rmore, <strong>the</strong>
networks studied present analogous levels <strong>of</strong> trust due to <strong>the</strong> similarity <strong>of</strong> context conditions (i.e. <strong>the</strong>y
belong to similar local systems <strong>of</strong> small enterprises and to <strong>the</strong> same small-enterprise national
association). Partner characteristics were not included in this first stage <strong>of</strong> analysis due to <strong>the</strong>
necessity <strong>of</strong> more in depth interviews. Information technology was not included for <strong>the</strong> similarity <strong>of</strong> this
condition among <strong>the</strong> four networks.
4.1 Proactivity
External relationships are considered relevant for small firms (BarNir and Smith, 2001) and in some
case also determinant <strong>of</strong> small business survival. Indeed small firms have limited resources and
limited market presence. By means <strong>of</strong> an interfirm alliance, small firms can access to needed
resources (Oliver, 1990) and build a strategic block to defend <strong>the</strong>mselves from competition (Nohria
and Garcia-Pont, 1991). In this case <strong>the</strong> strategy <strong>of</strong> <strong>the</strong> network firms is defensive.
Small firms can decide to form a strategic alliance to improve competitive position as well (Park and
Zhou, 2005), for example to capture windows <strong>of</strong> market opportunities in favourable markets and
outmatch a stronger competitor (BarNir and Smith, 2001). In this case <strong>the</strong> behaviour <strong>of</strong> <strong>the</strong> network
firms is <strong>of</strong>fensive.
Firms can also call for o<strong>the</strong>r firms to join <strong>the</strong>ir efforts (even in terms <strong>of</strong> joint investment) with <strong>the</strong> aim to
create new firms. The result in this later case is an entrepreneurship development by means <strong>of</strong>
network.
4.2 Governance mechanisms
Gulati and Singh (1988: 781) define <strong>the</strong> governance structure <strong>of</strong> <strong>the</strong> alliance as “<strong>the</strong> formal
contractual structure participants used to formalize it”. Different factors can affect <strong>the</strong> choice <strong>of</strong>
governance mode <strong>of</strong> an alliance: trust between <strong>the</strong> partners, <strong>the</strong> purpose <strong>of</strong> <strong>the</strong> alliance, <strong>the</strong>
symmetry <strong>of</strong> assets among partners (Kuittinen et al, 2008); <strong>the</strong> amount <strong>of</strong> property or knowledge base
involved in <strong>the</strong> assets <strong>of</strong> <strong>the</strong> network (Hoethker and Mellewigt, 2009); <strong>the</strong> appropriation concerns
(Pisano, Russo and Teece, 1988, Williamson, 1991); anticipated coordination costs in contests <strong>of</strong>
high interdependence and coordination (Thompson, 1967).
Our focus is based on <strong>the</strong> prevalence <strong>of</strong> market or hierarchies inside <strong>the</strong> alliance. On this basis,
networks are considered hybrid governance forms. There are three key dimensions that differentiate
markets from hierarchies: ownership, level <strong>of</strong> authority (or hierarchy) and rewards system (Makadok
and C<strong>of</strong>f, 2009). In <strong>the</strong> first dimension (<strong>the</strong> ownership), alliances can present two types <strong>of</strong>
governance: equity sharing and non-equity sharing (Kuittinen et al, 2008; Gulati and Singh, 1998;
Makadok and C<strong>of</strong>f, 2009). Regarding <strong>the</strong> second dimension, hierarchy in alliances refers to <strong>the</strong>
presence <strong>of</strong> several elements: use <strong>of</strong> authority and legal contracts (Powell, 1990; Ring and Van de
Ven, 1994), command structure, systems for certifying <strong>the</strong> authority <strong>of</strong> communications, incentive
systems that link rewards to performance, standardization <strong>of</strong> procedures (Stinchombe, 1985);
contracts and non-market pricing (Gulati and Singh, 1998). Alternatively governance mechanisms are
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based on market when for example, incentives, market price and competition regulate <strong>the</strong>
relationships among partners inside <strong>the</strong> network.
Finally, reward systems inside a network are referred to incentives according to output produced or
input provided to a network. Strong productivity incentives are close to <strong>the</strong> pure market while weak
productivity incentives are close to hierarchy (Makadok and C<strong>of</strong>f, 2009). This can depend on <strong>the</strong>
decision-making system inside <strong>the</strong> network. For <strong>the</strong> purpose <strong>of</strong> our study we referred to reward
systems in particular to <strong>the</strong> possibility members have to be project leaders and/or part <strong>of</strong> <strong>the</strong> board <strong>of</strong>
director and/or <strong>the</strong> possibility to take part in o<strong>the</strong>r mechanisms to share <strong>the</strong> decision-making process
inside <strong>the</strong> network. Indeed in <strong>the</strong>se cases members can be involved in decisions taken inside <strong>the</strong>
network and <strong>the</strong>reby to reward system.
4.3 Commitment
Social exchange <strong>the</strong>ory stresses <strong>the</strong> importance <strong>of</strong> commitment to informal and social networks,
which are central to <strong>the</strong> entrepreneurial process (Dubini and Aldrich, 1991). According to D’Cruz and
Ruman (1994) commitment is an important factor in managing networking relations. Fur<strong>the</strong>r, it is
considered as a key element in streng<strong>the</strong>ning network relations (Mohr and Spekman, 1994).
Commitment is defined by Carson, Gilmore and Roks (2004) in terms <strong>of</strong> time and effort spent by firms
in maintaining network linkages. Here we consider economic commitment as a proxi <strong>of</strong> <strong>the</strong> firms’
commitment and legitimacy.
4.4 Network broker roles
The network broker role is important for SMEs. In fact, increased global competition has lead to an
increase in knowledge specialization <strong>of</strong> firms. This has caused leading organizations to have a
smaller knowledge base in common, a large cognitive distance and a lack <strong>of</strong> resources to invest in
acquiring new knowledge. All <strong>the</strong>se aspects imply difficulties in communication and cooperation
among firms. As a consequence, intermediaries have emerged as key players in assisting
entrepreneurs in coping with <strong>the</strong>se challenges.
In our paper, we consider individual formal brokers having an “<strong>of</strong>ficial status” dedicated to network
formation, facilitation and management. The network broker concept has been previously studied in
contributions about inter-organizational network formation process (Snow, Miles and Coleman, 1992;
Human and Provan, 1997) highlighting <strong>the</strong> brokers’ roles and functions (Suarez-Villa, 1998; Saxenian,
1990; Malecki and Tootle 1996).
Snow, Miles and Coleman (1992) highlight three broker roles that are especially important for <strong>the</strong>
success <strong>of</strong> <strong>the</strong> network: <strong>the</strong> architect, <strong>the</strong> lead operator and <strong>the</strong> caretaker.
The role <strong>of</strong> architect refers to a person who “facilitate <strong>the</strong> emergence <strong>of</strong> specific operating networks
[…].”. (Snow et al., 1992, p. 15). The architect is <strong>the</strong> person who has <strong>the</strong> concept <strong>of</strong> <strong>the</strong> product and
<strong>the</strong> value chain in order to produce it in mind.
The role <strong>of</strong> lead operator “formally connects specific firms toge<strong>the</strong>r into an operating network […] by
linking all <strong>the</strong> value-chain components needed for a given product or service” (p. 18) . This implies
“conceptual and organizational skills as well as skill to negotiate mutually beneficial returns” (p. 18).
Architect and lead operator may be played by <strong>the</strong> same person.
Caretakers play a substantial role maintaining and enhancing an existing network. He/she has to
monitor relationships and share information among firms, help <strong>the</strong> network plan and learn and control
firms to behave in an appropriate manner also developing a sense <strong>of</strong> community among <strong>the</strong> members
<strong>of</strong> <strong>the</strong> network.
4.5 Absorptive capacity potential
Since organizational learning plays a critical role within networks formation and development
(Chaston and Mangles, 2000), in this paper we use <strong>the</strong> concept <strong>of</strong> absorptive capacity first
introduced by Cohen and Levinthal (1990) and defined as <strong>the</strong> firm’s ability to recognize valuable
information, assimilate and apply it. Absorptive capacity is considered as having relevant relation with
organizational performance (Woiceshyn and Daellenbach, 2005) and innovation (Tsai, 2001).
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Previous researches highlight <strong>the</strong> importance <strong>of</strong> formal integration mechanisms such as task force
(Gupta and Govindarajan, 2000) as well as gatekeepers (Cohen and Levinthal, 1990) as support for
<strong>the</strong> organizational absorptive capacity and learning.
5. Propositions
All five factors we have considered represent, according to previous literature, key factors in <strong>the</strong>
survival and development <strong>of</strong> networks. Moreover, according to Sherer (2003) <strong>the</strong>se are more
important to hard networks than to s<strong>of</strong>t. On <strong>the</strong> contrary, in our study that consider a knowledge and
learning perspective, some <strong>of</strong> <strong>the</strong> factors taken into account are more relevant in s<strong>of</strong>t ra<strong>the</strong>r than in
hard networks, since <strong>the</strong>ir prevailing vocation is in exploration ra<strong>the</strong>r than in exploitation. These are:
degree <strong>of</strong> commitment, both in terms <strong>of</strong> economic commitment and <strong>of</strong> firms’ proactivity, and degree <strong>of</strong>
potential absorptive capacity.
Proposition 1: The level <strong>of</strong> commitment represents a critical factor which is more important in s<strong>of</strong>t
networks than in hard networks.
Proposition 2: Potential absorptive capacity is a critical factor which is more important in s<strong>of</strong>t networks
than in hard networks.
On <strong>the</strong> o<strong>the</strong>r hand,,brokership and hierarchical control are more relevant in hard networks than in s<strong>of</strong>t
networks (Sherer, 2003). The relevant role <strong>of</strong> <strong>the</strong> former for hard networks, could be due to <strong>the</strong> need
for coordination <strong>of</strong> highly interdependent activities; for <strong>the</strong> role played by <strong>the</strong> latter in hard networks,
this could be due to <strong>the</strong> sharing <strong>of</strong> sensitive knowledge for which a higher degree <strong>of</strong> control could be
needed.
Proposition 3: Hierarchical control is a critical factor which is more important in hard networks than in
s<strong>of</strong>t networks.
Proposition 4: Brokership is a critical factor which is more important in hard networks than in s<strong>of</strong>t
networks.
6. Method
The methodology <strong>of</strong> multiple case studies is used, according to Yin (1994), with <strong>the</strong> aim to understand
<strong>the</strong> business success in a SME context. The unit <strong>of</strong> analysis was manufacturing networks. The
research data consists <strong>of</strong> interviews to <strong>the</strong> chief executive (or president) <strong>of</strong> <strong>the</strong> network, public
information about <strong>the</strong> case companies, annual accounts <strong>of</strong> <strong>the</strong> case companies and observation
during <strong>the</strong> visit. The analysis <strong>of</strong> <strong>the</strong> information obtained through <strong>the</strong> interviews was guided by <strong>the</strong>
<strong>the</strong>mes <strong>of</strong> <strong>the</strong> interview framework. All <strong>the</strong> interviews were taped and transcribed. We used replication
approach with <strong>the</strong> aim to assure <strong>the</strong> internal and external validity (Yin, 1994; Forsman, 2008). The
cases were selected among <strong>the</strong> most significant cases <strong>of</strong> manufacturing networks in <strong>the</strong> mechanical
industry in central Italy, as reported by an opinion leader operating in one <strong>of</strong> <strong>the</strong> two main small firm
associations in Italy. The four cases here reported represent roughly <strong>the</strong> total number <strong>of</strong> cases
referred to by <strong>the</strong> opinion leader. These case networks are later called case A, case B, case C and
case D. The explorative purpose <strong>of</strong> this paper means that <strong>the</strong> aim here is not to investigate all <strong>the</strong>
characteristics <strong>of</strong> networks but ra<strong>the</strong>r to deepen some <strong>of</strong> <strong>the</strong> most interesting for our analysis.
Fur<strong>the</strong>rmore, we consider two kinds <strong>of</strong> networks (i.e. hard e s<strong>of</strong>t networks) in order to highlight <strong>the</strong>
main differences in terms <strong>of</strong> factors affecting <strong>the</strong>ir development and success.
7. Measures
We developed a framework to characterize <strong>the</strong> cases on <strong>the</strong> basis <strong>of</strong> five dimensions that were
conceptually meaningful to <strong>the</strong> purpose <strong>of</strong> our analysis (Miles and Huberman, 1994).
Proactivity is referred to <strong>the</strong> kind <strong>of</strong> strategy <strong>the</strong> firms in <strong>the</strong> network decide to apply to develop <strong>the</strong>ir
business as response to market change considering <strong>the</strong>ir internal resources. We identify three
variables to measure proactivity. The first is referred to <strong>the</strong> <strong>of</strong>fensive or defensive nature <strong>of</strong> <strong>the</strong> reason
why firms create a network. The second is <strong>the</strong> potential excess and <strong>the</strong> third is <strong>the</strong> entrepreneurship
development. The highest scores show <strong>the</strong> proactivity <strong>of</strong> <strong>the</strong> network towards development.
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Governance mechanism is relative to <strong>the</strong> variables that differentiate markets from hierarchies:
authority, ownership and rewards. The level <strong>of</strong> authority refers to <strong>the</strong> number <strong>of</strong> elements a network
has to keep hierarchical control. The ownership is <strong>the</strong> presence or absence <strong>of</strong> equity. The last
variable concerns rewards in terms <strong>of</strong> incentives to be involved in <strong>the</strong> decision-making <strong>of</strong> <strong>the</strong> network.
The presence <strong>of</strong> <strong>the</strong> latter mechanism inside <strong>the</strong> network makes network governance more market
oriented. The higher <strong>the</strong> total score is on <strong>the</strong>se three elements, <strong>the</strong> higher <strong>the</strong> level <strong>of</strong> hierarchy inside
<strong>the</strong> network is.
Brokership role is referred to <strong>the</strong> presence inside <strong>the</strong> network <strong>of</strong> an individual who plays an important
role for <strong>the</strong> network start up and development. To measure this dimension we used three network
roles by Snow, Miles and Coleman (1992). The network in which all <strong>the</strong> network roles are covered by
a member have <strong>the</strong> highest score.
Commitment, is referred to <strong>the</strong> effort in maintaining network linkages in terms <strong>of</strong> economic
commitment (i.e. measure <strong>of</strong> investments in <strong>the</strong> network by its members). The higher <strong>the</strong> investment
<strong>the</strong> greater <strong>the</strong> commitment.
Absorptive capacity potential is referred to <strong>the</strong> potential <strong>of</strong> <strong>the</strong> network to absorb knowledge. This item
is measured in terms <strong>of</strong> existence <strong>of</strong> formal integration mechanisms (e.g. task force) as well as <strong>the</strong>
presence <strong>of</strong> a diffused function <strong>of</strong> gatekeeper. The first item, i.e. formal integration mechanisms, was
measured on a basis <strong>of</strong> a 3-point-likert scale (1=low use <strong>of</strong> permanent teams/low formalized
frequency <strong>of</strong> meetings; 3=highly formalized teams and high formalized frequency <strong>of</strong> meetings);
second item, i.e. diffused gatekeeper function was measured on <strong>the</strong> basis <strong>of</strong> a yes or no question.
Table 1: Characteristics <strong>of</strong> <strong>the</strong> four networks
Main objective <strong>of</strong> <strong>the</strong>
network
Degree <strong>of</strong>
interdependence
among <strong>the</strong> firms <strong>of</strong>
<strong>the</strong> network
Number <strong>of</strong> firms
belonging to <strong>the</strong>
network (current)
Level <strong>of</strong> members
turnover (*)
Type <strong>of</strong> business
organizations
Total network
turnover (2008)
Broker turnover
(2008)
Year <strong>of</strong> foundation <strong>of</strong>
<strong>the</strong> network
Members
Investments in
broker firm (Equity)
Total assets <strong>of</strong> <strong>the</strong>
network
Case A Case B Case C Case D
Supply chain
integration by
means <strong>of</strong>
entrepreneurship
development
New business
development
Low-Medium Low
Integration to
produce
complex
products
Integration to
produce
complex
products
High High
18 11 9 12
Low Low Medium High
Corporation
(Limited
company)
n.a.
12.019.685 €
Corporation
(Limited
company)
881.041 €
13.557.978 €
Consortium
(Limited
company)
477.826 €
1.536.888 €
Cooperative
(Limited
company)
1.576.345 €
n.a.
1993 2006 2006 2002
64.711 €
Firms have
exchange equity
among <strong>the</strong>m as
well that is not
included
10.690.574 € 9.035.824 €
(*) Level <strong>of</strong> members turnover since network foundation.
2.050.000 € 10.000 € 650 €
364
67.177 € 1.004.911 €

8. Discussion and conclusions
Anna Romiti and Daria Sarti
Results highlight that all five factors are relevant for s<strong>of</strong>t (explorative) networks (see figure 1) and that
<strong>the</strong>re are differences in <strong>the</strong> importance <strong>of</strong> critical factors for hard and s<strong>of</strong>t networks. Specifically, <strong>the</strong>
factors which behave differently are: economic commitment, proactivity and potential asborptive
capacity (see figure 1 and 2). These three factors play a more relevant role in <strong>the</strong> evolution <strong>of</strong> s<strong>of</strong>t
networks than in hard networks.
absorptive
potential
commitment
proactivity
3
2,5
2
1,5
1
0,5
0
Case A Case B
Figure 1: The five dimensions for s<strong>of</strong>t or explorative networks
absorptive
potential
commitment
proactivity
3
2,5
2
1,5
1
0,5
0
Case C Case D
Figure 2: The five dimensions for hard or exploitative networks
brokership
brokership
hyerarchical
control
hyerarchical
control
While s<strong>of</strong>t networks (case A and B) show an <strong>of</strong>fensive response to external stimuli, hard networks
(case C and D) show a defensive behaviour. At <strong>the</strong> same time, while s<strong>of</strong>t networks show a higher
degree <strong>of</strong> entrepreneurship development, hard networks do not. Fur<strong>the</strong>r, considering <strong>the</strong> amount <strong>of</strong>
equity as an economic commitment dimension, results show that while hard networks show a
medium-low level <strong>of</strong> investment, s<strong>of</strong>t networks invest heavily in network creation and development.
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Therefore, <strong>the</strong> creation <strong>of</strong> s<strong>of</strong>t networks <strong>of</strong> firms leads to higher initial investments, both for <strong>the</strong>
acquisition <strong>of</strong> resources (commitment) and in terms <strong>of</strong> behaviour (proactive behaviour) in order to
cope with environmental issues.
Hard networks use <strong>the</strong>ir own pre-existing competencies (exploitation) and move in a logic <strong>of</strong> response
to market changes. In <strong>the</strong> face <strong>of</strong> considerable investment, s<strong>of</strong>t networks (case A and B) experience
more innovative potential coming from a potential absorptive capacity that instead is not experienced
by hard networks. In fact, s<strong>of</strong>t networks use integration mechanisms as well as gatekeeper function in
a more frequent and formalized way, compared to hard networks..
This evidence is in contrast with current literature (Sherer, 2003) according to which, commitment and
intermediaries are more relevant in hard than in s<strong>of</strong>t networks.
Therefore, proposition 1 and 2 are satisfied.
Results show that <strong>the</strong> two groups <strong>of</strong> networks (s<strong>of</strong>t and hard) do not differ significantly considering
brokership and hierarchical control (governance) dimensions. This means that propositions 3 and 4
are not met.
In fact, Case C is substantially different from all <strong>the</strong> o<strong>the</strong>r networks due to <strong>the</strong> reduced dimension <strong>of</strong>
brokership. Fur<strong>the</strong>rmore, case B and C have a lower level <strong>of</strong> hierarchical control respect to case A
and D. This means that hierarchical control is not dependent - contrary to what Sherer (2003)
suggests - on network forms but ra<strong>the</strong>r on o<strong>the</strong>r elements. According to our case study <strong>the</strong>
explanation can be found in <strong>the</strong> fact that a high number <strong>of</strong> <strong>the</strong> members <strong>of</strong> networks B and C did not
know each o<strong>the</strong>r previously. For <strong>the</strong> foundation <strong>of</strong> this network being a member <strong>of</strong> <strong>the</strong> association
was determinant. On <strong>the</strong> basis <strong>of</strong> <strong>the</strong> findings, <strong>the</strong> lack <strong>of</strong> previous productive cooperation among
firms leads to less use <strong>of</strong> brokership and hierarchical control. This allows <strong>the</strong> network to facilitate trust
creation.
In conclusion, according to previous literature, in times <strong>of</strong> crisis, alliance among SMEs has good
impact on a firm’s performance and its survival. In particular critical factors for <strong>the</strong> success <strong>of</strong> <strong>the</strong>se
networks depend on <strong>the</strong> form <strong>of</strong> a network entrepreneur choose to cope with difficult times.
The entrepreneur that decides to form a hard network has to consider to all <strong>the</strong> dimension in our
analysis, that are: proactivity, governance mechanisms, brokership, commitment and absorptive
capacity potential. On <strong>the</strong> o<strong>the</strong>r hand in <strong>the</strong> hard network an important role is played by <strong>the</strong>
governance mechanisms and <strong>the</strong> brokership.
Acknowledgements
Anna Romiti and Daria Sarti share <strong>the</strong> final responsibility for this paper. Anna Romiti wrote
paragraphs 4.1, 4.2, 6 and 7; Daria Sarti wrote paragraphs 1, 2, 3, 4.3, 4.4, 4.5 and 5; both authors
wrote paragraph 8. The authors thank Dr. Volpi who gave <strong>the</strong> references <strong>of</strong> <strong>the</strong> networks and <strong>the</strong>
anonymous referees for useful suggestions during <strong>the</strong> drafting <strong>of</strong> this paper.
References
BarNir, A. and Smith, K. (2002) “Interfirm Alliance in <strong>the</strong> Small Business: The role <strong>of</strong> Social Network”, Journal <strong>of</strong>
small business management, Vol. 40, No. 3, pp 219-232.
Brunetto, Y. and Farr-Wharton, R. (2007) “The Moderating Role <strong>of</strong> Trust in SME Owner/Managers’ Decision-
Making about Collaboration”, Journal <strong>of</strong> Small Business Management, Vol. 45, No. 3, pp 362–387.
Carson, D., Gilmore, A. and Rocks, S. (2004), “SME marketing networking: a strategic approach”, Strategic
Change, Vol. 13, pp 369–382.
Chaston I. and Mangles, T. (2000) “Business networks: Assiting Knowledge Management and Competence
Acquisition within UK Manufacturing Firms”, Journal <strong>of</strong> Small Business Enterprise Development, Vol. 7, No.
2, pp 160-170.
Clemons, E. K., Reddi, S. and Row, M. (1993) “The Impact <strong>of</strong> Information Technology on <strong>the</strong> Organization <strong>of</strong>
Economic Activity: The Move to <strong>the</strong> Middle Hypo<strong>the</strong>sis”, Journal <strong>of</strong> Management Information Systems, Vol
10, No. 2, pp 9–35.
Cohen W. M. and Levinthal, D. A. (1990) “Absorptive capacity: a new perspective on learning and innovation”,
Administrative Science Quarterly, Vol. 35, No. 1, 128-152.
D’Cruz, J.R. and Ruman, A.M. (1994) “Business network <strong>the</strong>ory and <strong>the</strong> Canadian telecommunications industry”,
International Business Review, Vol. 3, No. 3, pp 275-288.
366

Anna Romiti and Daria Sarti
Dubini, P. and Aldrich, H. (1991) “Personal and Extended Networks Are Central to <strong>the</strong> Entrepreneurial Process”,
Journal <strong>of</strong> Business Venturing, Vol. 6, No. 5, pp 305–313.
Forsman, H. (2008) “Business development success in SMEs: a case study approach”, Journal <strong>of</strong> Small
Business and Enterprise Development, Vol. 15, No. 3, pp 606-622.
Grant R.M. and Baden-Fuller, C. (1995) “A knowledge based <strong>the</strong>ory <strong>of</strong> interfirm collaboration”, Academy <strong>of</strong>
Management Best Paper <strong>Proceedings</strong>, Vol. 38, pp 17-21.
Grant R.M. (1996) “Toward a knowledge-based <strong>the</strong>ory <strong>of</strong> <strong>the</strong> firm”, Strategic Management Journal, Vol. 17, pp
109-122.
Gulati R. and Singh, H. (1998) “The Architecture <strong>of</strong> Cooperation: Managing Coordination Costs and Appropriation
Concerns in Strategic Alliances”, Administrative Science Quarterly, Vol. 43, pp 781-814.
Gupta A. K., and Govindarajan, V. (2000) “Knowledge flows within multinational corporations”, Strategic
Management Journal, Vol. 21, No. 4, pp 473-496.
Human, S. and Provan, K. (1997) “An Emergent Theory <strong>of</strong> Structure and Outcomes in Small-Firm Strategic
Manufacturing Networks”, Academy <strong>of</strong> Management Journal, Vol. 40, No. 2, pp 369–403.
Hoethker G. and Mellewigt, T. (2009) “Choice and performance <strong>of</strong> governance mechanisms: matching alliance
governance to asset type”, Strategic Management Journal, Vol. 30, pp 1025-1044.
Kosa, M. and Lewin, A. (1998). “The Co-Evolution <strong>of</strong> Strategic Alliances” Organization Science, Vol. 9, pp. 255–
264.
Kuittinen H., Kylaheiko, K., Sandstrom, J. and Jauntunen, A. (2008) “Cooperation governance mode: an
extended transaction cost approach”, Journal <strong>of</strong> Management and Governance, Vol 4, pp 303-323.
Lane, P.J. and Lubatkin, M. (1998) “Relative absorptive capacity and interorganizational learning”, Strategic
Management Journal, Vol. 19, No. 5, pp 461–477.
Malecki, E. and Tootle, D. (1996) “The Role <strong>of</strong> Networks in Small-Firm Competitiveness”, International Journal
Technology Management, Vol. 11, No. 1/2, pp 43–57.
Makadok, R. and C<strong>of</strong>f, R. (2009) “Both market and hierarchy: an incentive-system <strong>the</strong>ory <strong>of</strong> hybrid governance
forms”, Academy <strong>of</strong> management review, Vol. 34, No. 2, pp 297–319.
Mayer, R., Davis, J. and Schoorman, F. (1995) “An Integrative Model <strong>of</strong> Organizational Trust”, Academy <strong>of</strong>
Management Review, Vol. 20, No. 3, pp 709–734.
Miles, M.B. and Huberman, A.M. (1994). Qualitative data analysis (2nd ed.), Thousand Oaks, CA: Sage.
Mohr, J. and Spekman, R. (1994) “Characteristics <strong>of</strong> Partnership Success: Partnership Attributes,
Communication Behavior, and Conflict Resolution Techniques”, Strategic Management Journal Vol. 15, No.
2, pp 135–143.
Nohria, N. and Garcia-Pont, C. (1991) “Global strategic linkages and industry structure”, Strategic Management
Journal, Vol. 12, pp 105-124.
Nooteboom, B. (1994) “Innovation and diffusion in small firms: <strong>the</strong>ory and evidence”, Small Business Economics,
Vol. 6, No. 5, pp 327-347.
Oliver, C. (1990) “Determinants <strong>of</strong> interorganizational relationship: Integration and future directions”, Academy <strong>of</strong>
Management Review, Vol. 15, pp 241-265.
Park, S. H. and Zhou, D. (2005) “Firm heterogeneity and competitive dynamics in alliance formation”, Academy <strong>of</strong>
Management Review , Vol. 30, No. 3, pp 531–554.
Parkhe, A. (1993) “‘Messy’ Research, Methodological Predispositions, and Theory Development in International
Joint Ventures”, Academy <strong>of</strong> Management Review, Vol. 19, No.2, 227–269.
Parkhe, A., Wasserman, S. and Ralston, D.A. (2006) “New frontiers in network <strong>the</strong>ory development”, Academy <strong>of</strong>
Management Review, Vol. 31, No. 3, pp 560-568.
Pisano, G.P., Russo, M. V. and Teece, D. (1988) “Joint venture and collaboration agreement in <strong>the</strong>
telecommunication equipment industry”. In David Mowery (ed.), International Collaborative Ventures in U.S.
Manufacturing: 23-70. Cambridge, MA:Ballinger.
Powell, W.W. (1990) “Nei<strong>the</strong>r market nor hierarchy: Network forms <strong>of</strong> organization”. In B.M. Staw and L.L.
Cummings (eds.), Research in Organizational Behavior, 12: 295-336. Greenwich, CT: JAI Press.
Ring, P.S. and Van de Ven, A. (1994) “Developmental Processes <strong>of</strong> Cooperative Interorganizational
Relationships”, Academy <strong>of</strong> Management Review, Vol. 19, No. 1, pp 90–118.
Saxenian, A. (1990) “Regional Networks and <strong>the</strong> Resurgence <strong>of</strong> Silicon Valley”, California Management Review,
Vol. 33, No. 1, pp 89–112.
Saxton, T. (1997) “The Effects <strong>of</strong> Partner and Relationship Characteristics on Alliance Outcomes”, Academy <strong>of</strong>
Management Journal, Vol. 40, No. 2, pp 443–461.
Sherer, S.A. (2003) “Critical Success Factors for Manufacturing Networks as Perceived by Network
Coordinators”, Journal <strong>of</strong> Small Business Management, Vol. 41, No. 4, pp 325–345.
Snow, C.C., Miles, R.E. and Coleman, H.J. (Jr.), (1992), “Managing 21st Century Network Organizations”,
Organizational Dynamics, Vol. 20 No.3, pp 5-20
Stinchombe, A. (1985) “Contracts as hierarchical documents”, in A. Stinchombe and C. Heimer (eds.),
Organization Theory and Project Management: 121-171. Bergen, Norway: Norwegian University Press.
Suarez-Villa, L. (1998) “The Structures <strong>of</strong> Cooperation: Downscaling, Outsourcing, and <strong>the</strong> Networked Alliance”,
Small Business Economics, Vol. 10, No. 1, pp 5–16.
Thompson, J.D. (1967) Organizations in Action: Social Science Bases <strong>of</strong> Administration. New York: McGraw-Hill.
Tsai W. (2001), “Knowledge transfer in intraorganizational networks: effects <strong>of</strong> network position and absorptive
capacity on business unit innovation and performance”, Academy <strong>of</strong> Management Journal, Vol. 44, No. 5,
pp 996-1004.
367

Anna Romiti and Daria Sarti
Valkokari, K. and Helander, N. (2007) “Knowledge management in different types <strong>of</strong> strategic SME networks”,
Management Research News, Vol. 30, No. 8, pp 597-608.
Weaver K.M., and Dickson P. (1997) “Environmental Determinants and Individual Level Moderators <strong>of</strong> Alliances”,
Journal <strong>of</strong> Business Ethics, Vol. 17, No. 9/10, pp 987-994.
Williamson, O.E. (1991) “Comparative economic organization: The analysis <strong>of</strong> discrete structural alternatives”,
Administrative Science Quarterly, Vol. 36, pp 269-296.
Woiceshyn, J.and Daellenbach, U. (2005) “Integrative capability and technology adoption: evidence from oil
firms”, Industrial and Corporate Change, Vol. 14, No. 2, pp 307-342.
Yin, R. (1994) Case study research. Beverly Hills, CA: Sage Publications.
368

Organizational Development Activities and Social Capital
Accumulation: Exploring Relationships in Canadian
Healthcare Organizations
Kent Rondeau 1 and Terry Wagar 2
1 University <strong>of</strong> Alberta, Edmonton, Alberta, Canada
2 St Mary’s University, Halifax, Nova Scotia, Canada
kent.rondeau@ualberta.ca
Abstract: Background: In <strong>the</strong> past few years, many organizations including those delivering healthcare services,
have introduced a number <strong>of</strong> organizational development initiatives as a means <strong>of</strong> improving <strong>the</strong> quality <strong>of</strong> <strong>the</strong>ir
products and services, increasing <strong>the</strong>ir operating efficiency, or as a means <strong>of</strong> enhancing customer and employee
satisfaction. Yet, <strong>the</strong>re is little empirical research on how planned organizational change initiatives have <strong>the</strong>
potential to impact <strong>the</strong> accumulations <strong>of</strong> employee social capital. Although a complex concept, social capital can
be conceived <strong>of</strong> as consisting <strong>of</strong> <strong>the</strong> actual and potential resources embedded within, available through, and
derived from <strong>the</strong> network <strong>of</strong> relationships possessed by an individual or individuals in a social unit. Organizations
which effectively accumulate employee social capital are able to realize a number <strong>of</strong> important benefits.
Never<strong>the</strong>less, organizational development programs have <strong>the</strong> potential to disrupt social capital accumulations
when <strong>the</strong>se initiatives positively or adversely change <strong>the</strong> patterns, textures and compositions <strong>of</strong> social actors in
<strong>the</strong> workplace. The potential <strong>of</strong> specific organizational change initiatives to impact social capital accumulation in
nurse workplaces is examined in a large sample <strong>of</strong> Canadian healthcare organizations. Method: Data for this
study was collected by means <strong>of</strong> a two-wave mail questionnaire sent to <strong>the</strong> director <strong>of</strong> nursing in 2208 hospitals
and long-term care establishments <strong>of</strong> more than 25 beds, drawn from all ten Canadian provinces and three
territories. After subtracting for refusals, duplicates, and incorrect addresses, 705 valid questionnaires were
returned, yielding a response rate <strong>of</strong> 32%. Ethics approval for this study was secured from <strong>the</strong> Health Research
Ethics Board at <strong>the</strong> University <strong>of</strong> Alberta, Edmonton, Canada. After controlling for establishment size, location,
type and turnover among registered nurses (RNs), a three-step ordinary least squares analysis was used to
assess <strong>the</strong> independent and combined contribution <strong>of</strong> particular organizational change and development
initiatives on <strong>the</strong> accumulation <strong>of</strong> social capital in nursing sub-units. Results: Canadian healthcare organizations
can be differentiated on <strong>the</strong>ir ability to accumulate social capital among <strong>the</strong>ir nurse personnel. Establishments
which report having more nurse social capital in <strong>the</strong>ir workplaces are found to have lower levels <strong>of</strong> voluntary RN
turnover (p

Kent Rondeau and Terry Wagar
planned change programs may have a deleterious effect on accumulations <strong>of</strong> workplace social
capital. Planned organizational change and development activities will undermine employee social
capital accumulations when <strong>the</strong> change programs being introduced cause employee bonds and
relationships to be severed or act to perturb or shrink <strong>the</strong> employee social networks in which social
capital is accumulated. In order to understand how planned organizational change programs may
serve to impact employee workplace social capital accumulations, it is useful to examine <strong>the</strong> complex
(and contentious) notion <strong>of</strong> workplace social capital.
1.1 Social capital in <strong>the</strong> workplace
The concept <strong>of</strong> social capital is an important concept for understanding relationships in social
networks (Bartkus & Davis, 2009). Although not without controversy in its purported usefulness as a
<strong>the</strong>oretical idea or certainty in its definition, social capital remains a salient notion in social science
research. Skeptics have characterized <strong>the</strong> concept <strong>of</strong> social capital as an overly “elastic term” (Lappe
& DuBois, 1997: 119), and a notion with an uncomfortably low level <strong>of</strong> certainty in its meaning. Yet
social capital, as defined by its principal <strong>the</strong>orists (Bourdieu, 1986; Coleman, 1988; Putnam, 1993),
comprises an array <strong>of</strong> features associated with social organization, including <strong>the</strong> number and
magnitude <strong>of</strong> interpersonal networks, high levels <strong>of</strong> interpersonal trust, and workplace norms <strong>of</strong>
reciprocity, extra-role behaviours, and mutual assistance. Toge<strong>the</strong>r, <strong>the</strong>se forms act as resources for
organizational participants to facilitate collective action (Ostrom & Ahn, 2003).
The large number <strong>of</strong> complementary and competing definitions <strong>of</strong> social capital is dramatically
demonstrated when we examine its many formulations that have been advanced in <strong>the</strong> scholarly
literature. This diversity in its conceptual meaning creates real challenges in how it is operationalized
and an even greater difficulty in how social capital is empirically assessed. Social capital has been
characterized as being embedded in social structure. According to Adler and Kwon (2002: 18), social
structure is reflected in three types <strong>of</strong> relations: a) market relations in which products and services are
exchanged for money or are bartered; b) hierarchical relations in which obedience to authority is
exchanged for material, spiritual and psychological security, and c) social relations in which favours
and gifts are exchanged. Within social organization, especially public-sector organizations, <strong>the</strong> latter
two forms <strong>of</strong> social structure are most predominant.
Social capital’s sources lie in <strong>the</strong> social structures within which an organizational member is located.
Social capital accumulations produce benefits that are available to both <strong>the</strong> individual (embedded in
<strong>the</strong> social network) as well as <strong>the</strong> network as a whole. Most definitions <strong>of</strong> social capital vary
depending on whe<strong>the</strong>r <strong>the</strong>y focus on <strong>the</strong> sources, <strong>the</strong> substance, or <strong>the</strong> effects. Definitions can also
vary depending upon whe<strong>the</strong>r <strong>the</strong> focus in on a) <strong>the</strong> relations an organizational member maintains
with o<strong>the</strong>r members, 2) <strong>the</strong> structure <strong>of</strong> relations among members <strong>of</strong> a collectivity, network or
community-<strong>of</strong>-practice, or 3) both types <strong>of</strong> linkages.
Investments in social capital <strong>of</strong>ten generate individual-level or personal social capital when <strong>the</strong>
benefits <strong>of</strong> being part <strong>of</strong> a social network are able to be harvested by <strong>the</strong> individual member. A second
level <strong>of</strong> social capital is bonding social capital which is communally available within a defined social
network. As Putnam (2000: 22) argues “bonding social capital is good for undergirding specific
reciprocity and mobilizing solidarity within important proximate groups to which an individual belongs.”
Fur<strong>the</strong>rmore, Putnam (1995: 67) argues that this form <strong>of</strong> social capital “features social organization
such as networks, norms, and social trust that facilitates coordination and cooperation for mutual
benefit.” Bridging social capital is characterized by Putnam (1995; 2000) as social capital that is more
inclusive <strong>of</strong> people across social distinctions. As Knoke (1999: 18) suggests it is this form <strong>of</strong> social
capital that defines “<strong>the</strong> process by which social actors create and mobilize <strong>the</strong>ir network connections
within and between organizations to gain access to o<strong>the</strong>r social actors’ resources.” When
summarizing <strong>the</strong> difference in <strong>the</strong>se two forms <strong>of</strong> social capital, Putnam (2000: 23) argues that
bridging social capital has <strong>the</strong> potential to “generate broader identities and reciprocity, whereas
bonding social capital bolsters our narrower selves.”
The past decade has witnessed a veritable explosion in social capital research (see Barkus & Davis,
2009; Ostrom & Ahn, 2003; Westlund, 2006). Social capital is proving to be an important concept
when explaining people’s relative success in and across organizations. Social capital has been shown
to be involved in a large number <strong>of</strong> organizational successes that are shared by employees. For
instance, social capital influences career success (Gabbay & Zuckerman, 1998), assists employees to
locate and secure employment (Lin and Dumin, 1996) and stay longer on <strong>the</strong> job (Krackhardt &
370

Kent Rondeau and Terry Wagar
Hanson, 1993). Within organizations, social capital facilitates resource exchange between units while
enhancing innovation and entrepreneurship (Chong & Gibbons, 1997). Social capital also assists
organizations in attaining greater effectiveness on a wide variety <strong>of</strong> human resources employment
practices, including innovative workplace practices.
Indeed, Leana and Van Buren (1992) suggest that workplace or organizational social capital has a
number <strong>of</strong> important benefits. First, organizational social capital has <strong>the</strong> potential to provide <strong>the</strong>
individual with a basis for deferring his or her immediate individual interests in favour <strong>of</strong> a group or
organization goals. From agency <strong>the</strong>ory perspective, workplace social capital provides a rationale for
members to become “good agents” (Eisenhardt, 1989). Second, social capital is an important
facilitator <strong>of</strong> a flexible work organization (Evans and Davis, 2005). High involvement human resource
system, with its emphasis on employee empowerment, participation and engagement, may assist
workplaces in <strong>the</strong>ir ability to accumulate social capital because <strong>the</strong>y facilitate both <strong>the</strong> creation and
utilization <strong>of</strong> social networks (Cox, Zagelmeyer & Marchington, 2006). Third, social capital can be
seen as a means <strong>of</strong> managing collective action. Stable employment relationships can be seen as an
efficient solution to <strong>the</strong> uncertainty and hazards <strong>of</strong> long-term organizational viability. Because social
capital represents an existing pool <strong>of</strong> employee trust, reciprocity, goodwill that has been created in <strong>the</strong>
past, it is available to <strong>the</strong> organization (or to its members) to be drawn upon in <strong>the</strong> future when <strong>the</strong>
need arises. Finally, social capital may act as a facilitator <strong>of</strong> intellectual capital (Edvinsson & Malone,
1997). Various forms <strong>of</strong> bonding and bridging social capital can facilitate <strong>the</strong> development <strong>of</strong>
intellectual capital within <strong>the</strong> organization by providing an environment conducive to <strong>the</strong> combination
and exchange <strong>of</strong> information and knowledge (Nahapiet & Ghoshal, 1998). It also helps creates <strong>the</strong>
conditions <strong>of</strong> mutual trust and respect that is needed to make <strong>the</strong>se exchanges possible. Social
capital may also be an important feature in <strong>the</strong> establishment <strong>of</strong> employee psychological contracts
that help ensure long-term organizational stability through a reduction in employee turnover.
1.2 Social capital and organizational change and development
In <strong>the</strong> past few years, many healthcare organizations have introduced planned change and
development programs as a means <strong>of</strong> improving operating efficiencies, increasing service quality, and
enhancing employee and patient satisfaction. Many <strong>of</strong> <strong>the</strong>se planned change programs have <strong>the</strong>
potential to disrupt social capital accumulations when <strong>the</strong>se initiatives positively or adversely change
<strong>the</strong> patterns, textures and compositions <strong>of</strong> social actors in <strong>the</strong> workplace. Although many <strong>of</strong> <strong>the</strong>se
programs are done concurrently, it is important to understand <strong>the</strong> independent and combined
contribution <strong>of</strong> <strong>the</strong>se programs on workplace employee social capital accumulations. The potential <strong>of</strong>
specific organizational change initiatives to impact social capital accumulation in nurse workplaces is
examined in a large sample <strong>of</strong> Canadian healthcare organizations.
2. Methods
After receiving ethics approval from <strong>the</strong> University <strong>of</strong> Alberta Health Research Ethics Committee, a
survey questionnaire was mailed to 2241 Canadian hospitals and long-term care organizations
(nursing homes) operating in all ten provinces and <strong>the</strong> three territories. The database <strong>of</strong> participant
healthcare organizations was found in <strong>the</strong> Guide to Canadian Healthcare Facilities 2001-2002
(Canadian Healthcare Association, 2001), and contained identifying information on all relevant
organizations with over 25 staffed nursing beds. The survey and cover letter were sent by regular mail
to <strong>the</strong> site administrator for each facility who was asked to forward it to <strong>the</strong> individual responsible for
<strong>the</strong> management <strong>of</strong> <strong>the</strong> nursing function at that establishment. All participants were told about <strong>the</strong>
nature <strong>of</strong> <strong>the</strong> study and its objectives, and informed that <strong>the</strong>ir participation would remain voluntary and
confidential. Approximately six weeks after <strong>the</strong> initial mailing, a second wave questionnaire was resent
to those organizations that did not respond to <strong>the</strong> first request for participation. The data for this study
was derived from 713 useable questionnaires and comprises 232 hospitals representing those
designated as acute, chronic and rehabilitative in designation, along with 473 long-term care facilities
(nursing homes). When refusals, duplicates, and non-deliverables were subtracted, a response rate <strong>of</strong>
32.2 percent was attained. Non-responses bias was examined by comparing early responders (first
wave) and later responders (second wave) according to organizational type (hospital versus long-term
care facility), size (natural log <strong>of</strong> number <strong>of</strong> beds) and location (rural versus urban). Early responders
were not found to show statistically significant differences with respect to any <strong>of</strong> <strong>the</strong>se characteristics
with later respondents.
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2.1 Study measures
Kent Rondeau and Terry Wagar
The objective <strong>of</strong> this research study is to investigate <strong>the</strong> independent and <strong>the</strong> combined impact <strong>of</strong> a
variety <strong>of</strong> organizational development and change initiatives on <strong>the</strong> accumulation <strong>of</strong> workplace social
capital among nurses. Social capital, our dependent variable, was measured by five-items across a
seven-point strongly disagree to strong agree continuum, as adapted from <strong>the</strong> work <strong>of</strong> Subramaniam
and Youndt (2005). Two sample questions from this scale are “Our nurses apply knowledge learned
in one area <strong>of</strong> our organization to problems and opportunities in o<strong>the</strong>r areas” and “our nurses are
skilled at collaborating with each o<strong>the</strong>r to diagnose and solve problems.” Our social capital scale
produced a Cronbach alpha <strong>of</strong> .95 indicating a high degree <strong>of</strong> internal reliability.
We are interested in examining <strong>the</strong> impact <strong>of</strong> formal organizational change and development
initiatives on <strong>the</strong> accumulation and destruction <strong>of</strong> social capital in nursing sub-units. Nurse managers
were asked to respond to <strong>the</strong> degree to which <strong>the</strong>ir facilities had undertaken a number <strong>of</strong>
organizational development activities in <strong>the</strong> preceding two year period. Using a five-point scale where
1= none and 5=a lot, nurse managers were asked to estimate <strong>the</strong> degree to which <strong>the</strong>ir
establishments had, for instance, increased <strong>the</strong> use <strong>of</strong> part-time nurses, decentralized decision
making to front-line nursing staff from management, reduced or downsized <strong>the</strong>ir nursing workforce, or
redesigned nursing jobs in <strong>the</strong> past two years. Organizationally sponsored “top-down” organizational
change initiatives were selected for evaluation in this study (such as downsizing <strong>of</strong> <strong>the</strong> nursing
workforce, and <strong>the</strong> increasing <strong>the</strong> use <strong>of</strong> contract or temporary nursing staff), in addition to more
grass-roots “bottom-up” development initiatives (such as decentralizing <strong>of</strong> decision making to nursing
staff, and engaging nurses in cross-training activities).
A number <strong>of</strong> organizational variables were controlled because <strong>of</strong> <strong>the</strong>ir potential to be associated with
employee social capital accumulation or with an establishment’s potential to conduct organizational
change and development activities. Establishment size, measured as <strong>the</strong> natural log <strong>of</strong> <strong>the</strong> number <strong>of</strong>
establishment beds, was controlled in our analysis because social capital potentially accumulates
differentially in workplaces and organizations <strong>of</strong> varying size. Additionally, larger organizations may
potentially have a greater ability to resource organizational development initiatives than smaller ones.
Establishment location (1=rural to 5=metropolitan urban) and type (1=hospital and 2=nursing home)
was controlled because social capital accumulates differentially in workplaces and organizations
characterized in <strong>the</strong>se ways. Establishment voluntary turnover for registered nurses was also
controlled in our analysis because social capital accumulation is eroded in organizations with a large
annual turnover <strong>of</strong> <strong>the</strong>ir employees.
2.2 Analysis
We are interested in examining <strong>the</strong> contribution <strong>of</strong> organizational change and development activities
on social capital accumulation for nursing personnel in long-term care organizations. A bi-variate
correlational analysis was conducted, using SPSS for Windows (SPSS Inc., Chicago) Version 7.0, to
examine <strong>the</strong> strength and significance <strong>of</strong> association <strong>of</strong> our study variables. A hierarchical (sequential)
ordinary least squares (OLS) regression analysis was performed with social capital serving as <strong>the</strong>
dependent variable. Under this procedure, three sequential OLS regressions were entered. The first
regression (Model A) accounted for <strong>the</strong> relative contribution <strong>of</strong> <strong>the</strong> three structural control variables on
<strong>the</strong> dependent variable, while <strong>the</strong> second regression (Model B) added <strong>the</strong> voluntary establishment RN
turnover variable. Turnover was added independently <strong>of</strong> our establishment control variables because
it was found to produce significance (p

Kent Rondeau and Terry Wagar
The results <strong>of</strong> <strong>the</strong> correlation matrix <strong>of</strong> study variables can be found in Table 2. Our results show that
healthcare establishments that report greater accumulations <strong>of</strong> social capital in <strong>the</strong>ir nursing
workplaces are more likely to have lower voluntary turnover (p

Kent Rondeau and Terry Wagar
contribution <strong>of</strong> each organizational development activity on social capital accumulation is positive and
significant for establishments in our study sample which have, in <strong>the</strong> preceding two year period,
decentralized decision making authority to <strong>the</strong>ir nursing staff (p

Kent Rondeau and Terry Wagar
Table 3: OLS regression results for nursing social capital
Model A Model B Model C
Establishment Factors
Establishment Size (ln beds) - .019 -. 006 -. 024
(058) (.057) (.058)
Establishment Location a -.063 -.058 - .042
.040) (.039) (.039)
Establishment type b 181* .121 .193*
.086) (.086) (.093)
Establishment turnover
Establishment RN turnover (voluntary) -.193*** -.161**
(.049) (.049)
Establishment Change Variables
Increased use <strong>of</strong> part-time nurses -.013
Model A Model B Model C
(.031)
Decentralized decision making to nurses .108**
(.041)
Increased nurse cross-training .087*
(.039)
Increased use <strong>of</strong> contract/temporary nurses -.075*
(.037)
Downsized nursing workforce -.131**
(.040)
Redesigned nursing jobs -.048
(.036)
Automated nursing paper work .017
(.031)
Introduced new programs or services .030
(.037)
Constant 4.964*** 5.337*** 5.005***
.277) (.296) (.329)
Adjusted R-square 010 .031 .081
∆ R-square -- .021 .050
F statistic 3.136 6.249 5.739
a
(Regression coefficient with standard errors in paren<strong>the</strong>sis)
a
* p

Kent Rondeau and Terry Wagar
Our results are not surprising. When healthcare organizations decentralize nurse decision making and
increase <strong>the</strong> use <strong>of</strong> nurse cross-training <strong>the</strong>y are contributing to <strong>the</strong> expansion <strong>of</strong> social capital. These
workplace change programs function in two distinct ways. First, <strong>the</strong>y act by enlarging and enriching
social networks when decision making authority is expanded and when work roles are shared and job
routines are blurred between members. Second, within existing social networks, each <strong>of</strong> <strong>the</strong>se
change programs contributes to a more rapid accumulation <strong>of</strong> shared trust, goodwill, associability and
reciprocity among nurse members. Flexible and empowering approaches to human resource
management have <strong>the</strong> potential to bring people toge<strong>the</strong>r and to streng<strong>the</strong>n employee bonds.
Workplace employee social capital accumulations also make <strong>the</strong>se human resource management
practices more effective. This is well-summarized by Leana and Van Buren (1999: 549) when <strong>the</strong>y
state that instead <strong>of</strong> “hierarchical control mechanisms, individuals can effectively operate as collective
because <strong>of</strong> general understandings <strong>of</strong> work organization, implicit norms, and generalized, resilient
trust. In this regards, organizational social capital can make collective action more efficient, because it
becomes a substitute for <strong>the</strong> formal contracts, incentives, and monitoring mechanisms that are
necessary in systems with little or no social capital among organizational members.”
If certain workplace change programs act by streng<strong>the</strong>ning existing social networks (bonding social
capital) or by spurring <strong>the</strong> creation <strong>of</strong> new social contacts (bridging social capital), o<strong>the</strong>r workplace
change initiatives may have a contrary association. Many healthcare organizations that have reduced
<strong>the</strong>ir workforces and <strong>the</strong>n populated <strong>the</strong>ir depleted ranks with casual, temporary and contract
employees are (inadvertently) impacting workplace employee social capital. When people are let go,
social networks are inevitably broken. New hires that are temporary, casual or contracted are unable
to plug into <strong>the</strong> same social networks (or bridge across existing social networks) now ruptured by
departing employees. Job security can be a potential cost <strong>of</strong> maintaining social capital. Leana and
Van Buren (1999: 550) state that “one unfortunate by-product <strong>of</strong> practices such as downsizing is <strong>the</strong>
sanctioning <strong>of</strong> individualistic behavior on <strong>the</strong> part <strong>of</strong> organizations and individuals… Damaged in <strong>the</strong>
process is collective identity.” Fur<strong>the</strong>rmore, maintaining organizational social capital requires some
level <strong>of</strong> slack resources that can be used to promote member reciprocity, associability and trust.
Organizations undergoing planned workforce reductions have fewer <strong>of</strong> <strong>the</strong>se resources available that
would normally be needed to secure employee compliance and goodwill.
Overall, <strong>the</strong> results <strong>of</strong> this research suggest that organizations interested in maintaining employee
social capital may need to take a longer-term view <strong>of</strong> employee relations when <strong>the</strong>y consider <strong>the</strong>
implementation <strong>of</strong> various change and development programs. Treating employees as assets to be
developed ra<strong>the</strong>r than as costs to be minimized has strong consequences for how employee social
capital is maintained, enhanced or depleted (Pfeffer, 1998). Cost-based human resource
management practices serves to both de-value both <strong>the</strong> individuals within an organization and <strong>the</strong>
benefit <strong>of</strong> interpersonal relationships. On <strong>the</strong> o<strong>the</strong>r hand, an asset-based view <strong>of</strong> human resource
management permits <strong>the</strong> organization to make investments not only in individuals but also in
interpersonal relationship formation as well.
4.1 Limitations <strong>of</strong> <strong>the</strong> research
There are limitations in <strong>the</strong> design and administration <strong>of</strong> this study that need to be identified. The data
collected reflects <strong>the</strong> subjective assessments <strong>of</strong> nurse managers and thus captures <strong>the</strong>ir innate
biases. Because <strong>the</strong> dataset is assembled from a single source, common method variance has <strong>the</strong>
potential to confound results. We have attempted to minimize this bias by asking factually-based
questions wherever possible.
Social capital is a complex phenomenon that reflects individual as well as group benefits. Our
measure <strong>of</strong> social capital, a simple five-item measure, may not be broad enough to fully capture <strong>the</strong>
multi-dimensional nature <strong>of</strong> <strong>the</strong> concept. For instance, our measure appears to focus more on certain
aspects <strong>of</strong> social capital (ie. friendship, goodwill, associability) and less on o<strong>the</strong>r aspects (ie. trust,
reciprocity). It also may not adequately account for <strong>the</strong> density <strong>of</strong> workplace social networks. Although
our measure has been used in previously published empirical studies, fur<strong>the</strong>r research should be
done with a more refined and exacting measure <strong>of</strong> employee workplace social capital.
The conceptualization and measurement <strong>of</strong> formal organizational change and development programs
is problematic. For instance, managers in our study may have very different understandings <strong>of</strong> what
constitutes, for instance, nurse cross-training, redesigned nursing jobs, or automation <strong>of</strong> nursing work
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Kent Rondeau and Terry Wagar
functions. We have also not assessed <strong>the</strong>se workplace change programs with respect to how
successfully <strong>the</strong>y were implemented or <strong>the</strong> how deeply <strong>the</strong>y were embedded in <strong>the</strong> workplace.
Finally, <strong>the</strong> design <strong>of</strong> this study is retrospective and, as such, reflects merely a snapshot in time. We
are unable to demonstrate causality between variables <strong>of</strong> interest. It cannot be concluded that specific
change programs “cause” employee social capital to be enhanced or depleted. Indeed, even if
causality could permit us to infer causality, it is impossible using this design to tell anything about its
directionality. For instance, does <strong>the</strong> introduction <strong>of</strong> shared decision making approaches enhance
social capital accumulations among those so engaged, or do social capital accumulations make <strong>the</strong>se
human resource management approaches more easily adopted in <strong>the</strong> workplace?
Although tentative and preliminary, <strong>the</strong> results <strong>of</strong> this research suggest that organizations need to
take caution when selecting workplace change programs if <strong>the</strong>y want to maintain employee social
capital. Maintaining a highly motivated and effective workforce during planned change is <strong>the</strong> ultimate
goal <strong>of</strong> every employer.
References
Adler, P.S., and Kwon, S.W. (2002). Social capital: prospects for a new concept. Academy <strong>of</strong> Management
Review, 27(1): 17-40.
Bartkus, V.O., & Davis, J.H. (2009). Social capital: reaching out, reaching in. Cheltenham, UK: Edward Elgar.
Bourdieu, P. (1986). The forms <strong>of</strong> capital. In Richardson, J.G. (Ed.). Handbook <strong>of</strong> <strong>the</strong>ory and research for <strong>the</strong>
sociology <strong>of</strong> education. New York: Greenwood, pp. 241-258.
Canadian Healthcare Association. (2001). Guide to Canadian healthcare facilities, 2001-2002. Ottawa: Canadian
Healthcare Association.
Coleman, J.S. (1988). Social capital in <strong>the</strong> creation <strong>of</strong> human capital. American Journal <strong>of</strong> Sociology, 94(Suppl):
S95-S121.
Cox, A., Zagelmeyer, S., & Marchington, M. (2006). Embedding employee involvement and participation at work.
Chong, L., & Gibbons, P. (1997). Corporate entrepreneurship: <strong>the</strong> role <strong>of</strong> ideology and social capital. Group and
Organization Management, 22: 10-30.
Edvinsson, L., & Malone, M.S. (1977). Intellectual capital. New York: Harper-Collins.
Eisenhardt, K. (1989). Agency <strong>the</strong>ory: an assessment and review. Academy <strong>of</strong> Management Review, 14: 57-74.
Evans, W.R., & Davis, W.D. (2005). High-performance work systems and organizational performance: <strong>the</strong>
mediating role <strong>of</strong> internal social structure. Journal <strong>of</strong> Management, 31(5): 758-775.
Gabbay, S.M., & Zuckerman, E.W. (1998). Social capital and opportunity in corporate R&D: <strong>the</strong> contingent effect
<strong>of</strong> contract density on mobility expectations. Social Science Research, 27: 189-217.
Knoke, D. (1999). Organizational networks and corporate social capital. In Leenders, R.Th.A.J., and Gabbay,
S.M. Corporate social capital and liability. Boston: Kluwer, 17-42.
Krackhardt, D., & Hanson, J.R. (1993). Informal networks and organizational crises: An experimental simulation.
Harvard Business Review, 71(4): 104-111.
Lappe, F.M., & Dubois, P.M. (1997). Building social capital without looking backward. National Civic Review, 86:
119-128.
Lin, N., & Dumin, M. (1996). Access to occupations through social ties. Social Networks, 8: 365-385.
Leanna, C.R., & Van Buren, H.J. III. (1999). Organizational social capital and employment practices. Academy <strong>of</strong>
Management Review, 24: 538-555.
Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and <strong>the</strong> organizational advantage.
Academy <strong>of</strong> Management Review, 23: 115-132.
Ostrom, E., & Ahn, T.K. (2003). Foundations <strong>of</strong> social capital. Cheltenham, UK: Edward Elgar.
Pfeffer, J. (1998). The human equation. Cambridge University Press.
Putnam, R.D. (1993). The prosperous community: social capital and public life. American Prospect, 13(Spring):
35-42.
Putnam, R.D. (1995). Bowling alone: America’s declining social capital. Journal <strong>of</strong> Democracy, 6(1): 65-78.
Putnam, R.D. (2000). Bowling alone: <strong>the</strong> collapse and revival <strong>of</strong> American community. New York: Simon and
Shuster.
Subramaniam, M., & Youndt, M.A. (2005). The influence <strong>of</strong> intellectual capital on <strong>the</strong> types <strong>of</strong> innovative
capabilities. Academy <strong>of</strong> Management Journal, 48(3): 450-463.
Westlund, H. (2006). Social capital in <strong>the</strong> knowledge economy. Berlin: Springer-Verlag.
377

Intellectual Capital and a Firm’s Innovativeness
Helena Santos-Rodrigues 1 , Pedro Figueroa Dorrego 2 and Carlos Maria Jardon 2
1 ESTG-IPVC, Portugal
2 Universidade de Vigo, Pontevedra, Spain.
Hsantos@estg.ipvc.pt
Figueroa@uvigo.es
cjardon@uvigo.es
Abstract: Intellectual capital is increasingly considered a source <strong>of</strong> competitive advantage and is considered a
major issue on <strong>the</strong> management and organization research. There is a lack <strong>of</strong> evidence about which are <strong>the</strong> main
components that are more relevant to achieve and maintain a competitive advantage, such as innovation. There
are different models and approaches that try to identify <strong>the</strong> effect <strong>of</strong> intellectual capital on a firm’s performance.
This paper focuses on <strong>the</strong> influence <strong>of</strong> <strong>the</strong> human, structural and relational capital on <strong>the</strong> product- process and
management innovativeness <strong>of</strong> <strong>the</strong> firm. A global model including <strong>the</strong> variables used in <strong>the</strong> previous literature is
used and we establishes hypo<strong>the</strong>ses for testing this model and use statistic technique to estimate <strong>the</strong> parameters
<strong>of</strong> <strong>the</strong> model in a sample. To do so, we use a survey from 68 firms working on <strong>the</strong> auto components sector,
established in <strong>the</strong> Nor<strong>the</strong>rn Spain and Nor<strong>the</strong>rn Portugal. We found firstly, that innovativeness has two main
dimensions, perfectly differentiated, <strong>the</strong> product-process innovation and <strong>the</strong> management innovation; secondly
that <strong>the</strong> intellectual capital components influences differently each type <strong>of</strong> innovation capacity (innovativeness).
We also concluded that <strong>the</strong> human and relational capital influence positive and directly <strong>the</strong> product-process
innovativeness and that <strong>the</strong> structural capital influences positive and directly <strong>the</strong> management innovativeness.
These results highlight <strong>the</strong> importance and influence <strong>of</strong> <strong>the</strong> intellectual capital on <strong>the</strong> innovativeness, and more
broadly, <strong>the</strong> value <strong>of</strong> intellectual capital as a competitive advantage in contemporary time. Moreover, point out <strong>the</strong>
different character <strong>of</strong> product-process and management innovativeness.
Keywords: intellectual capital, innovativeness, human capital, structural capital, relational capital, innovation
1. Introduction
We are moving towards a knowledge-based economy where intangible assets and investments are
seen as essential elements to value creation in companies. Carbone et al. (2005) affirm that, in an
increasingly globalized world, <strong>the</strong> survival <strong>of</strong> companies depends on <strong>the</strong>ir capacity for innovation
derived from <strong>the</strong>ir organizational intelligence, which is represented by <strong>the</strong>ir information and knowledge
systems, <strong>the</strong> competencies <strong>of</strong> <strong>the</strong>ir employees, <strong>the</strong> quality <strong>of</strong> <strong>the</strong>ir production processes and <strong>the</strong>ir
customer service. Moreover to Success in this context, or simply remain viable, companies must
respond with innovation (Govindarajan & Trimble, 2005), because knowledge has become a critical
ingredient for gaining a competitive advantage, particularly in <strong>the</strong> new economic landscape (Grant,
1996; Kane, Argote, & Levine, 2005). The source <strong>of</strong> economic value and wealth is <strong>the</strong> creation and
management <strong>of</strong> intangible assets, frequently grouped under <strong>the</strong> generic term “knowledge”,
“intangibles”, or “intellectual capital” (Lev, 2001a, 2001b). Carbone et al. (2005) affirm that knowledge
has come to be seen as a major production differential and that <strong>the</strong> companies’ management <strong>of</strong> <strong>the</strong>se
intangible assets are determinants for <strong>the</strong>ir growth and sustainability.
The main objective <strong>of</strong> this study will be to verify whe<strong>the</strong>r <strong>the</strong> human, structural and relational capital
influence <strong>the</strong> innovativeness <strong>of</strong> <strong>the</strong> firms. Therefore, our research question is:
Does <strong>the</strong> intellectual capital influence <strong>the</strong> product and process innovativeness?
The structure <strong>of</strong> this article is indicated in <strong>the</strong> following. After introduction <strong>of</strong> <strong>the</strong> topic, <strong>the</strong>
bibliographical review is presented addressing <strong>the</strong> conceptualization <strong>of</strong> intellectual capital and
innovativeness. Based on this bibliographical review, <strong>the</strong> research hypo<strong>the</strong>sis to be subsequently
tested is formulated. Next, <strong>the</strong> research method adopted is described. Then, <strong>the</strong> data collected are
analyzed and <strong>the</strong> research hypo<strong>the</strong>sis is tested. By way <strong>of</strong> conclusion, final conclusions are presented
and future research steps are recommended to assist in testing <strong>the</strong> exploratory propositions
formulated in this work.
2. Intellectual capital and innovativeness
The research interest on intellectual capital has been growing fast in later years, especially in firms
were benefits derive majority from innovation and knowledge intensive services (Edvinsson &
Sullivan, 1996). The literature consider that firms with superior intellectual resources understand,
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Helena Santos-Rodrigues et al.
better than <strong>the</strong> competitors, how to explore, deploy, combine and configure resources and capacities
on a distinct way, that gives to clients more value than <strong>the</strong> competitors (Spender & Marr, 2005; Teece,
Pisano, & Shuen, 1997). Innovation that may serve as <strong>the</strong> basis for competitive advantage
(Khazanchi, Lewis, & Boyer, 2007), is strongly linked to knowledge (Levinthal & March, 1993;
McGrath, 2001; Peng, Schroeder, & Shah, 2008).
Intellectual capital <strong>of</strong> a company is defined as all non-monetary and non-physical resources that are
fully or partly controlled by <strong>the</strong> organisation and that contribute to <strong>the</strong> value creation <strong>of</strong> <strong>the</strong>
organisation (G. Roos, Pike, & Fernström, 2005). The concept <strong>of</strong> intellectual capital helps to let
intangible resources <strong>of</strong> a company be measured, communicated and interpreted (see: Andriessen,
2004) (G. Roos, et al., 2005). Even though <strong>the</strong> debate about <strong>the</strong> components <strong>of</strong> <strong>the</strong> Intellectual
Capital is still partially open, <strong>the</strong> Intellectual Capital components, recognized and mainly accepted in
most <strong>of</strong> <strong>the</strong> literature, are human capital, structural capital and relational capital (Edvinsson & Malone,
1997; I.A.D.E., 2003; Santos Rodrigues, 2008).
In this sense, <strong>the</strong> human capital represent <strong>the</strong> value <strong>of</strong> <strong>the</strong> knowledge and talent which is embodied in
people who make up <strong>the</strong> organization, representing it know-how, <strong>the</strong> capacities, <strong>the</strong> knowledge,
talent, competence, attitude, intellectual agility, creativity, and o<strong>the</strong>rs (Santos Rodrigues, 2008)
(Bontis & Fitz-enz, 2002; Edvinsson & Malone, 1997; I.A.D.E., 2003; Goran Roos & Roos, 1997).
Structural capital is defined as knowledge, skills, experiences and information, institutionalized,
codified, and used by databases, patents, manuals, structures, systems, routines and processes
(Youndt, Subramaniam, & Snell, 2004).
On <strong>the</strong> o<strong>the</strong>r side, through relation with business partners, firms can gain access to external
knowledge, and <strong>the</strong>re’s some evidence, for instance, that spatial proximity between organizations
facilitates <strong>the</strong> interactions (Torre & Rallet, 2005), and, consequently firms could exchange more
knowledge and eventually have a higher innovative performance (Weterings & Boschma, 2009). Pike
et al. (2005) cite various empirical studies that show that encouraging and maintaining <strong>the</strong> existence
knowledge flows beyond <strong>the</strong> boundaries <strong>of</strong> enterprise and across different scientific areas, becomes
more productive efforts <strong>of</strong> R & D.
Innovation that may serve as <strong>the</strong> basis for competitive advantage (Khazanchi, et al., 2007), is strongly
linked to knowledge (Levinthal & March, 1993; McGrath, 2001; Peng, et al., 2008). Peng et al. (2008)
describe <strong>the</strong> innovation-knowledge linkage as <strong>the</strong> essence <strong>of</strong> innovation has been characterized as
pursuit <strong>of</strong> new knowledge for discovery. Therefore, <strong>the</strong> alignment <strong>of</strong> knowledge, as an intangible
resource, with <strong>the</strong> innovation strategy could enhance performance and culminate in a competitive
advantage. The innovative firm is one that has implemented an innovation (product, process,
marketing or organisational innovation) during <strong>the</strong> period under review (OCDE/UE, 2005).
3. Hypo<strong>the</strong>sis
Knowledge assets <strong>of</strong> enterprises are positively related to <strong>the</strong>ir level <strong>of</strong> innovation (Thornhill, 2006).
So, to create new or better products, firms must reallocate resources, combine new resources or
combine existing resources both inside and outside firms in new ways (Tsai & Ghoshal, 1998).
Thus, we predict <strong>the</strong> following:
H1: Human capital is positively related with <strong>the</strong> innovativeness <strong>of</strong> <strong>the</strong> firm.
H2: Structural capital is positively related with <strong>the</strong> innovativeness <strong>of</strong> <strong>the</strong> firm.
H3: Relational capital is positively related with <strong>the</strong> innovativeness <strong>of</strong> <strong>the</strong> firm.
Figure 1 display our hypo<strong>the</strong>sised relationship between intellectual capital and <strong>the</strong> tree types <strong>of</strong>
innovativeness considered.
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Figure 1: Hypo<strong>the</strong>sis
4. Methods
4.1 Sample and data collection
Helena Santos-Rodrigues et al.
We tested <strong>the</strong> hypo<strong>the</strong>sis using a survey data collected in 2007 from firms registered on <strong>the</strong> main and
most representative associations <strong>of</strong> <strong>the</strong> sector in Spain and North Portugal. Those associations that
meet <strong>the</strong> requirements were “Fundación Clúster de Empresas de Automoción de Galicia” (CEAGA) in
representation <strong>of</strong> <strong>the</strong> nor<strong>the</strong>rn Spain (Galicia) firms, plus <strong>the</strong> “Associação de Fabricantes de Industria
Automóvel” (AFIA) as representative <strong>of</strong> companies in North Portugal.
We targeted 135 companies, 66 from Galicia and 69 from <strong>the</strong> nor<strong>the</strong>rn <strong>of</strong> Portugal. While obtaining a
sample <strong>of</strong> significant linkage <strong>of</strong> <strong>the</strong> intellectual capital as a strategic resource and it effect on <strong>the</strong>
innovativeness would allow more comprehensive understanding <strong>of</strong> <strong>the</strong> phenomenon, we relied on
upper managers as key expert informants—an established practice in organizational research (Huber
& Power, 1985)- and because are those whom are aware <strong>of</strong> <strong>the</strong> strategic choices.
The survey was constructed in Portuguese and Spanish, while <strong>the</strong> firms were in to different countries.
To assure <strong>the</strong> language consistence <strong>of</strong> <strong>the</strong> survey it was tested with some scholars and specialist <strong>of</strong>
<strong>the</strong> sector. The data collection took place in June 2007 via regular mail to 135 companies. Each
participation request included a description <strong>of</strong> <strong>the</strong> study, a statement <strong>of</strong> confidentiality, and a way
back envelop pre-stamped.
We received 68 responses, for a response rate <strong>of</strong> 50.37% percent. Of <strong>the</strong> responses, 45 came from
<strong>the</strong> Galicia firms, while 23 were obtained from <strong>the</strong> Portuguese firms. Of <strong>the</strong> 68 firms responding, we
were able to obtain archival performance data equivalent, thus 68 was our effective sample size.
4.2 Measures
Both intellectual capital components and <strong>the</strong> capacity for innovation have been regarded as
multidimensional constructs. This implies <strong>the</strong> need to establish a series <strong>of</strong> items to measure <strong>the</strong>m
toge<strong>the</strong>r. As <strong>the</strong>re aren´t valid and tested scales due Intellectual capital, as well as innovativeness, we
have developed new scales for human, structural and relational capital and innovativeness.
We relied on three performance measures <strong>of</strong> <strong>the</strong> innovativeness: <strong>the</strong> product, process and
management innovation (Ahuja, 2000; Davenport, Prusak, & Wilson, 2003; Hii & Neely, 2000;
Ravichandran, 2000). On our analysis we considered <strong>the</strong> relative innovation, meaning that an
innovation is considered new if it is new to <strong>the</strong> firm, and never<strong>the</strong>less it isn’t new to <strong>the</strong> world or
industry.
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4.3 Data analysis
Helena Santos-Rodrigues et al.
To evaluate <strong>the</strong> different constructs we will use <strong>the</strong> principal components technique. This technique
aim to reduce <strong>the</strong> size <strong>of</strong> <strong>the</strong> initial set <strong>of</strong> items that provide common information seeking to praise
<strong>the</strong>m all and create some new variables which collect common information, remaining <strong>the</strong> residual
and more specific information for each <strong>of</strong> <strong>the</strong> original items. The variables with communalities less
than 0.4 were analyzed to be eliminated as <strong>the</strong>y don’t containing information common to <strong>the</strong> rest <strong>of</strong>
items. To select <strong>the</strong> number <strong>of</strong> factors we take into account <strong>the</strong> Kaiser method, <strong>the</strong> scree plot and
those that explain at least 50% <strong>of</strong> <strong>the</strong> total variance (Costelo & Osborne, 2005).
Having reduced <strong>the</strong> information to better understand its meaning, we make use <strong>of</strong> a rotation process
<strong>of</strong> adjusting to <strong>the</strong> different axes original items so no information is lost. Traditionally, it uses a
technique that maintains varimax orthogonal relationship between <strong>the</strong> components involved, ensuring
uncorrelated.
The degree <strong>of</strong> validity <strong>of</strong> this technique is given by two auxiliary instruments: Bartlett test and <strong>the</strong>
coefficient <strong>of</strong> Kaiser-Meyer and Okin (KMO). The first tested whe<strong>the</strong>r <strong>the</strong> correlation matrix between
<strong>the</strong> original items is an identity matrix, i.e. <strong>the</strong>re is no common information between <strong>the</strong>se items and,
<strong>the</strong>refore, cannot find that information. That means that we find this significant test would indicate that
<strong>the</strong>re is common information among <strong>the</strong> items analyzed. The second instrument will measure
sampling adequacy by comparing <strong>the</strong> partial correlation between <strong>the</strong> items involved. If that ratio is
close to 1 is an indicator that <strong>the</strong> partial correlations are almost zero and <strong>the</strong>refore <strong>the</strong> information
items is included in <strong>the</strong> set <strong>of</strong> all <strong>of</strong> <strong>the</strong>m, i.e. <strong>the</strong> specifications <strong>of</strong> each item are small in relation to all.
The values that are usually considered acceptable are those older than 0.6.
Since <strong>the</strong> set <strong>of</strong> items used for each aspect, trying to measure a single construct, to establish <strong>the</strong>
reliability <strong>of</strong> <strong>the</strong> measuring instrument and data collection, we calculated <strong>the</strong> Cronbach alpha
coefficient, through which it was determined internal consistency <strong>of</strong> <strong>the</strong> questionnaire. This method is
based on <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> average correlations among items related to one <strong>the</strong>me, from a single
administration <strong>of</strong> <strong>the</strong> questionnaire. This ratio produces values ranging from zero (0) and one (1). The
closer <strong>the</strong> value one (1), more reliable is <strong>the</strong> instrument. The criteria used for <strong>the</strong> interpretation <strong>of</strong> <strong>the</strong>
Cronbach alpha coefficient values are given by Nunnelly, (1978) less than 0.6 (low), between 0.61
and 0.70 (right), ranging from 0.71 to 0, 80 (good), over 0.80 (high).
To see <strong>the</strong> effect between constructs makes use <strong>of</strong> linear regression techniques that allow us to
evaluate and compare which is <strong>the</strong> direct effect <strong>of</strong> each independent variable on <strong>the</strong> dependent
question (Jardón, Verdugo, & Cal, 1997).
For <strong>the</strong> analysis process, purification and processing <strong>of</strong> data, determining factors and impact
assessment we used <strong>the</strong> Statistical Package for <strong>the</strong> Social Sciences (SPSS version 15).
4.4 Analysis and results
For Human Capital <strong>the</strong> factorial analysis <strong>of</strong> principal components was that <strong>the</strong> 16 initial variables are
explained in 53.277% for 3 common factors obtained from Varimax rotation with Kaiser Normalization
converged in 5 interactions. The KMO indicates a reasonable correlation between <strong>the</strong> items (KMO =
0.710) and <strong>the</strong> test <strong>of</strong> Bartlett's has an associated level <strong>of</strong> significance <strong>of</strong> 0.000 which leads to <strong>the</strong>
rejection <strong>of</strong> <strong>the</strong> hypo<strong>the</strong>sis that <strong>the</strong> correlation matrix is <strong>the</strong> identity matrix (p

Helena Santos-Rodrigues et al.
Normalization converged in 7 interactions. The KMO indicates a reasonable correlation between <strong>the</strong>
items (KMO = 0.759) and <strong>the</strong> test <strong>of</strong> Bartlett's has an associated level <strong>of</strong> significance <strong>of</strong> 0.000 which
leads to <strong>the</strong> rejection <strong>of</strong> <strong>the</strong> hypo<strong>the</strong>sis that <strong>the</strong> correlation matrix is <strong>the</strong> identity matrix (p

Helena Santos-Rodrigues et al.
<strong>the</strong> ability to innovate products and processes are <strong>the</strong> incentives for innovation (0.320 with sig. 0.001)
and <strong>the</strong> Innovative Attitude (0.216 with sig. 0.046).
We will have a variation in <strong>the</strong> capacity Innovative Product and Process <strong>of</strong> 0.399 with each variation
<strong>of</strong> a unit in Clients <strong>of</strong> 0.288 with each variation <strong>of</strong> a unit in collaborative networks <strong>of</strong> 0.320 with each
variation <strong>of</strong> a unit Incentives Innovation and 0.216 for each variation <strong>of</strong> <strong>the</strong> Innovative Attitude holding
<strong>the</strong> remaining independent variables constant or controlled effects.
Before proceeding with our analysis presented below in graphic form <strong>the</strong> conclusions reached in this
section.
Figure 2: Model
As expected in our first hypo<strong>the</strong>sis (H.1.) Human capital is associated with <strong>the</strong> innovativeness <strong>of</strong> <strong>the</strong>
company; in particular we conclude that human capital has an important role in <strong>the</strong> product-process
innovativeness. In line with <strong>the</strong> <strong>the</strong>ory that considers <strong>the</strong> human capital as <strong>the</strong> most important
component <strong>of</strong> Intellectual Capital, in <strong>the</strong> perspective <strong>of</strong> intellectual capital, inputs to <strong>the</strong> process <strong>of</strong>
knowledge creation are provided by <strong>the</strong> Human Capital. But we concluded oppositely on <strong>the</strong>
management innovativeness, as <strong>the</strong> Human Capital don’t appear (at least directly) related with this
type <strong>of</strong> innovativeness. These results (never<strong>the</strong>less) are consistent with some academics, such as
Stewart (1998b) for whom Human Capital has no significant direct impact on business performance
because it needs <strong>the</strong> o<strong>the</strong>r intellectual components, as <strong>the</strong> structural and relational capital to be
processed. Also, Bontis (1998) and Cabrita (2008) found no significant direct relationship between
Human Capital and business performance.
We also validated our second hypo<strong>the</strong>sis H.2. We observed that <strong>the</strong> Structural Capital is directly
related to <strong>the</strong> management innovativeness, <strong>the</strong>se results are validate by <strong>the</strong>oretical arguments
(Davenport, et al., 2003) that consider that is <strong>the</strong> company that turns knowledge into performance.
Businesses should support <strong>the</strong> performance <strong>of</strong> employees through <strong>the</strong>ir infrastructure, information
systems, routines, culture and trust, facilitating <strong>the</strong> dissemination <strong>of</strong> knowledge. Companies must
develop a culture that encourages and promotes <strong>the</strong> retention <strong>of</strong> Human Capital (Cabrita & Bontis,
2008). The relationship between structural capital and <strong>the</strong> innovativeness was also contrasted by
Subramanian and Youndt (2005) (Organizational Capital in <strong>the</strong>ir case) and <strong>the</strong>y verify <strong>the</strong> existence <strong>of</strong>
a significant relationship with incremental innovation capacity (not all types <strong>of</strong> innovative capacity.)
We also validate our hypo<strong>the</strong>sis H.3., noting that <strong>the</strong> Relational Capital is directly related with <strong>the</strong>
product-process innovativeness. The dimensions Collaboration Networks and Clients are directly
related to <strong>the</strong> innovative capacity. The results obtained may reveal <strong>the</strong> specificities <strong>of</strong> <strong>the</strong> automotive
sector, which through its organization and management enhance collaboration between vehicle
manufacturers, allies and suppliers to develop components, modules and solutions.
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Helena Santos-Rodrigues et al.
To sum up, <strong>the</strong> three research hypo<strong>the</strong>ses were validated. We can summarily conclude that our study
supports that Intellectual Capital influences <strong>the</strong> innovativeness <strong>of</strong> <strong>the</strong> company although <strong>the</strong>re are
some nuances worth noting. An important result achieved is that we find a dichotomy between <strong>the</strong>
Innovative Capacity. This dichotomy is very relevant for our finds and conclusions.
5. Conclusion
In this study we found several important contributions for <strong>the</strong>ory. We identify <strong>the</strong>oretical implications <strong>of</strong>
our study, mainly in two subject areas: <strong>the</strong> literature <strong>of</strong> Intellectual Capital and Innovation literature.
For <strong>the</strong> literature <strong>of</strong> intellectual capital, this work produces two major contributions. The first
contribution is that we found that some dimensions <strong>of</strong> Intellectual Capital are relevant for <strong>the</strong>
innovativeness <strong>of</strong> <strong>the</strong> company.
As <strong>the</strong> intellectual capital is accepted as strategic factors that include resources, skills and capabilities
that act and interact to create value, human capital use to be considered a central element <strong>of</strong> <strong>the</strong>
company. Some authors suggest that human capital is <strong>the</strong> central element <strong>of</strong> intellectual capital
(Bontis, 1998; Bontis, Dragonetti, Jacobsen, & Ross, 1999; Bontis & Girardi, 2000; Edvinsson &
Malone, 1997; Stewart, 1998a; Sveiby, 1997). In our study we find that human capital is important
(directly) only for <strong>the</strong> product-process innovativeness <strong>of</strong> <strong>the</strong> company. As Hayton (2005); that
analyzed a fairly comprehensive literature associated with <strong>the</strong> influence <strong>of</strong> human capital (between
<strong>the</strong> members <strong>of</strong> senior management) <strong>of</strong> <strong>the</strong> companies and <strong>the</strong> respective innovative capacity and
concluded that <strong>the</strong> cognitive resources (Skills) and values <strong>of</strong> <strong>the</strong> management team have a significant
influence on <strong>the</strong> company's strategic decisions; we found that <strong>the</strong> innovative attitude (part <strong>of</strong> it
centered on <strong>the</strong> manager attitude) has an important role on <strong>the</strong> product-process innovativeness.
The second contribution is to <strong>the</strong> innovation literature and concerns <strong>the</strong> several innovative capabilities
found in this study. First we saw that <strong>the</strong> Management innovativeness and <strong>the</strong> product-process
innovativeness are differentiated which consequently require different knowledge. Fur<strong>the</strong>rmore we
saw that <strong>the</strong> product-process innovativeness are coincident and refer to <strong>the</strong> same phenomenon. We
found that a new product innovation needs a new process, which justifies that <strong>the</strong> product process
innovativeness represents a same capacity. So, <strong>the</strong>re is a need to adjust <strong>the</strong> production process <strong>of</strong> a
product innovation. It means that <strong>the</strong>se two types <strong>of</strong> innovation are intrinsically related. To sum up,
<strong>the</strong> results <strong>of</strong> our study helps close <strong>the</strong> gap between what we know and what we need to know about
<strong>the</strong> effects <strong>of</strong> human capital on firm innovativeness and permits to support partly our H1. We didn’t
found a direct relation <strong>of</strong> human capital and management innovativeness.
A final integrative contribution refers to <strong>the</strong> identification <strong>of</strong> significant differences in <strong>the</strong> dimensions <strong>of</strong>
intellectual capital that influence <strong>the</strong> different innovative capacities. This contribution attempts to
answer a common criticism addressed to studies focusing on <strong>the</strong> innovativeness, referring to <strong>the</strong> lack
<strong>of</strong> analysis <strong>of</strong> <strong>the</strong> interrelationships between different variables within <strong>the</strong> organization (Ravichandran,
2000). Fur<strong>the</strong>r study should be done in two senses: to provide fur<strong>the</strong>r evidence <strong>of</strong> our conclusions
testing our model in different sectors or doing a multi-sector test. Even more, fur<strong>the</strong>r tests <strong>of</strong> our
model, concerning <strong>the</strong> liaisons not found such as <strong>the</strong> relation between human capital and
management innovation should be done. In <strong>the</strong> same line, following <strong>the</strong> proposal <strong>of</strong> Linzalone (2008)
more research should be done on <strong>the</strong> role that capital intellectual play in different stages <strong>of</strong> <strong>the</strong> new
products development process, as little is known about this relationship.
6. Annex: Questionnaire
Human Capital
Generally, employees are limited to perform tasks showing little motivation to change
Our employees have many skills to <strong>the</strong> activities performed
The company did not penalize innovation errors committed by employees
Our highly trained employees are specialized for <strong>the</strong> task or function <strong>the</strong>y perform in <strong>the</strong> company
Our employees are very talented
Our employees are considered <strong>the</strong> best in our industry by training
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Helena Santos-Rodrigues et al.
Whe<strong>the</strong>r individuals leave <strong>the</strong> company would have lost creativity problems
The innovative attitude <strong>of</strong> our company is <strong>the</strong> determinant <strong>of</strong> <strong>the</strong> satisfaction <strong>of</strong> our employees with
<strong>the</strong> company
Much <strong>of</strong> <strong>the</strong> value <strong>of</strong> our organization depends on <strong>the</strong> innovative attitude <strong>of</strong> our employees
Our directors are working to influence people to be committed voluntarily and apply <strong>the</strong>ir initiative for
innovation
The employees <strong>of</strong> our company contribute to creative solutions, new ways <strong>of</strong> doing things and work
performance
Innovation and try to change things is a basic principle <strong>of</strong> our company
Our directors like change
Our company facilitates <strong>the</strong> emergence <strong>of</strong> new ideas and development <strong>of</strong> <strong>the</strong> inventive
Our executives show great willingness to innovate
Structural Capital
Our employees trust <strong>the</strong> organization
Our partners rely on <strong>the</strong> company's functional directors
There is a high degree <strong>of</strong> trust between <strong>the</strong> people <strong>of</strong> our company
Our employees trust <strong>the</strong> people who make strategic decisions
Our company has a work environment that encourages <strong>the</strong> active participation <strong>of</strong> people in <strong>the</strong>
company's innovation
All employees are viewed as "peers"
Our employees are hired and trained to perform a specific task in a specific department.
I see our company as innovative, new experiments will and courage to take risks
Most business decisions must be approved by senior management
We managed to extract value from <strong>the</strong> innovation process
Consciously, unconsciously, <strong>the</strong> culture <strong>of</strong> our company is a reflection <strong>of</strong> <strong>the</strong> leader, or manager
Our employees make innovative suggestions
There are groups <strong>of</strong> improvements that facilitate business innovation
Our employees are open to reveal <strong>the</strong>ir true thoughts and ideas and innovative solutions through
formal and informal interactions with o<strong>the</strong>r members
Our employees enjoy participating in creative discussions
The suggestions made by employees are mostly implemented
We use detailed descriptions <strong>of</strong> <strong>the</strong> work (job descriptions), procedures and policies to guide <strong>the</strong>
actions <strong>of</strong> employees
In our company <strong>the</strong>re is innovation-oriented department (R & D, Quality, or o<strong>the</strong>r)
Our company has a set <strong>of</strong> processes and procedures focused on promoting learning and
innovation
Our company has a good collection system and implementation <strong>of</strong> new ideas
Relational Capital
Consciously, unconsciously, <strong>the</strong> culture <strong>of</strong> our company is a reflection <strong>of</strong> <strong>the</strong> leader, or manager
I see our company as innovative, new experiments will and courage to take risks
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Helena Santos-Rodrigues et al.
Our company has a work environment that encourages <strong>the</strong> active participation <strong>of</strong> people in <strong>the</strong>
company's innovation
There is a high degree <strong>of</strong> trust between <strong>the</strong> people <strong>of</strong> our company
All employees are viewed as "peers"
Our employees are open to reveal <strong>the</strong>ir true thoughts and ideas and innovative solutions through
formal and informal interactions with o<strong>the</strong>r members
Our employees enjoy participating in creative discussions
Our employees trust <strong>the</strong> people who make strategic decisions
Our partners rely on <strong>the</strong> company's functional directors
Our employees trust <strong>the</strong> organization
There are groups <strong>of</strong> improvements that facilitate business innovation
Our employees make innovative suggestions
The suggestions made by employees are mostly implemented
In our company <strong>the</strong>re is innovation-oriented department (R & D, Quality, or o<strong>the</strong>r)
We managed to extract value from <strong>the</strong> innovation process
Our company has a set <strong>of</strong> processes and procedures focused on promoting learning and
innovation
Our company has a good collection system and implementation <strong>of</strong> new ideas
We use detailed descriptions <strong>of</strong> <strong>the</strong> work (job descriptions), procedures and policies to guide <strong>the</strong>
actions <strong>of</strong> employees
Most business decisions must be approved by senior management
Our employees are hired and trained to perform a specific task in a specific department.
Innovativeness
Our company introduces many innovations in management or administration <strong>of</strong> significant importance
We introduce our company important management innovations that would improve <strong>the</strong> pr<strong>of</strong>its <strong>of</strong>
<strong>the</strong> enterprise
Our company introduced many innovations in <strong>the</strong> product market <strong>of</strong> significant importance
The importance <strong>of</strong> new products in total sales has increased substantially in recent years
Our company developed and introduced many innovations in <strong>the</strong> production process <strong>of</strong> significant
importance
Introduced process innovations were critical to reducing costs or o<strong>the</strong>r improvements
References
Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative
Science Quarterly, 45(3), pg. 425-455.
Andriessen, D. (2004). Making Sense <strong>of</strong> Intellectual Capital. Elsevier.
Bontis, N. (1998). Intellectual capital: an exploratory study that develops measures and models. Management
Decision, 36(2), 63-76.
Bontis, N., Dragonetti, N. C., Jacobsen, K., & Ross, G. (1999). The knowledge Toolbox: A Review <strong>of</strong> Tools
Available to Measure and Manage Intangible Resources. <strong>European</strong> Management Journal, 17(4), 391-402.
Bontis, N., & Fitz-enz, J. (2002). Intellectual capital ROI: A casual map <strong>of</strong> human capital antecedents and
consequents. Journal <strong>of</strong> Intellectual Capital, 3(3), 223-247.
Bontis, N., & Girardi, J. (2000). Teaching knowledge management and intellectual capital lessons: an empirical
examination <strong>of</strong> Tango simulation. Journal <strong>of</strong> Technology Management, 20(5/6/7/8), 545-555.
Cabrita, M. R., & Bontis, N. (2008). Intellectual capital and business performance in <strong>the</strong> Portuguese banking
industry. International Journal <strong>of</strong> Technology Management, 43(1-3), 212-237.
Carbone, P. P., Brandão, H. P., Leite, J. B. D., & Vilhena, R. M. P. (2005). Gestão por Competências e Gestão
do Conhecimento (1 ed.). Rio de Janeiro: FGV.
Costelo, A., & Osborne, J. (2005). Best Practices in Exploratory Factor Analysis: Four Recommendations for
Getting <strong>the</strong> Most From Your Analysis. Practical Assessment. Research & Evaluation, 10(7), 1-9
386

Helena Santos-Rodrigues et al.
Davenport, T. H., Prusak, L., & Wilson, H. J. (2003). Who´s bringing you hot ideas and are you responding?
Harvard Business School Press, 81(2), 58-64.
Edvinsson, L., & Malone, M. S. (1997). El Capital Intellectual: Cómo Identificar y calcular el valor de los recursos
intangibles de su empresa: Gestión 2000.
Edvinsson, L., & Sullivan, P. (1996). Developing a Model for Managing Intellectual Capital. <strong>European</strong>
Management Journal, 14(4), 356-364.
Govindarajan, V., & Trimble, C. (2005). Organizational DNA for Strategic Innovation. California Management
Review 47(3), 47-76
Grant, R. M. (1996). Toward a Knowledge-Based Theory <strong>of</strong> <strong>the</strong> Firm. Strategic Management Journal (1986-
1998), 17(Winter Special Issue), 109-122.
Hayton, J. (2005). Competing in <strong>the</strong> New Economy: The Effect <strong>of</strong> Intellectual Capital on Corporate
Entrepreneurship in High-Technology New Ventures. R&D Management, 35(2), 137-155.
Hii, J., & Neely, A. (2000). Innovative Capacity <strong>of</strong> Firms: on why some firms are more innovative than o<strong>the</strong>rs.
Paper presented at <strong>the</strong> 7th International Annual EurOMA <strong>Conference</strong> 2000- Ghent.
Huber, G., & Power, D. (1985). Retrospective reports <strong>of</strong> strategic-level managers: guidelines for increasing <strong>the</strong>ir
accuracy. Strategic Management Journal, 6(2), 171-180.
I.A.D.E. (2003). Modelo Intellectus: Medición y gestión del Capital Intelectual (1ª edición, Junio 2003 ed.).
Madrid: CIC.
Jardón, C., Verdugo, M., & Cal, M. (1997). Econometría estática aplicada. Santiago de Compostela: Tórculo.
Kane, A. A., Argote, L., & Levine, J. M. (2005). Knowledge transfer between groups via personnel rotation:
Effects <strong>of</strong> social identity and knowledge quality. Organizational Behavior and Human Decision Processes,
96(1), 56-71.
Khazanchi, S., Lewis, M. W., & Boyer, K. K. (2007). Innovation-supportive culture: <strong>the</strong> impact <strong>of</strong> organizational
values on process innovation. Journal <strong>of</strong> Operations Management, 25(4), 871-884.
Lev, B. (2001a). Intangibles (M. García-Ayuso, Trans. 2 ed.). Washington, DC: Brookings Institution.
Lev, B. (2001b). Intangibles: Medicion, Gestion e informacion (M. García-Ayuso, Trans. 2 ed.). Barcelona:
Ediciones Deusto.
Levinthal, D. A., & March, J. G. (1993). The myopia <strong>of</strong> learning. Strategic Management Journal, 14(8), 95-112.
Linzalone, R. (2008). Leveraging Knowledge Assets to Improve New Product Development Performances.
Measuring Business Excellence, 12(2), 38-50.
McGrath, R. G. (2001). Exploring learning, innovative capacity, and managerial oversight. Academy <strong>of</strong>
Management Journal, 44(1), 118-131.
Nunnally, J. (1978). Psychometric Theory (2 ed.). New York: McGraw-Hill.
OCDE/UE. (2005). Oslo Manual. Brussels: OCDE.
Peng, D. X., Schroeder, R. G., & Shah, R. (2008). Linking routines to operation capabilities: a new perspective.
Journal <strong>of</strong> Operations Management, 26(6), 730-748.
Pike, S., Roos, G., & Marr, B. (2005). Strategic Management <strong>of</strong> Intangible Assets and Value Drivers in R&D
Organizations. R&D Management, 35(2), 111-124.
Ravichandran, T. (2000). Redefining Organizational Innovation: Towards Theoretical Advancements. The Journal
<strong>of</strong> High Technology Management Research., 10(2), 243-274.
Roos, G., Pike, S., & Fernström, L. (2005). Managing Intellectual Capital in Practice. Elsevier.
Roos, G., & Roos, J. (1997). Measuring your Company’s Intellectual Performance. Long Range Planning, 30(3),
413-426.
Santos Rodrigues, H. (2008). Modelo de análisis del capital intelectual bajo la perspectiva de la incidencia en la
capacidad de innovación:. Aplicación al sector de automoción de la Eurorregión Galicia Norte de Portugal.
Vigo University (Spain), Vigo.
Spender, J.-C., & Marr, B. (2005). Knowledge-based perspective on Intellectual Capital. In B. Marr (Ed.),
Perspectives on intellectual capital (pp. 183-195). Oxford: Elsevier Butterworth-Heinemann publications.
Stewart, T. A. (1998a). Intellectual Capital: The New Wealth <strong>of</strong> Organizations (2ª ed.). New York: Doubleday.
Stewart, T. A. (1998b). Intellectual Capital: The New Wealth <strong>of</strong> Organizations (2ª ed.). New York: Doubleday.
Subramaniam, M., & Youndt, M. A. (2005). The influence <strong>of</strong> intellectual capital on <strong>the</strong> types <strong>of</strong> innovative
capabilities. Academy <strong>of</strong> Management Journal., 48(3), 450-463.
Sveiby, K.-E. (1997). The new organizational Wealth: Managing and Measuring Intangible Assets. San
Francisco: Berrett-Koehler.
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic
Management Journal (1986-1998), 18(7), 509-533.
Thornhill, S. (2006). Knowledge, Innovation and Firm Performance in High - and Low – Technology Regimes.
Journal <strong>of</strong> Business Venturing, 21, 687-703.
Torre, A., & Rallet, a. (2005). Proximity and location. Regional Studies, 39(1), 47-59.
Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: The role <strong>of</strong> intrafirm networks. Academy <strong>of</strong>
Management Journal, 41(4), 464-478.
Weterings, A., & Boschma, R. (2009). Does spatial proximity to costumers matter for innovative performance?
Evidence from <strong>the</strong> Dutch s<strong>of</strong>tware sector. Research Policy, 38, 746-755.
Youndt, M. A., Subramaniam, M., & Snell, S. A. (2004). Intellectual Capital Pr<strong>of</strong>iles: An Examination <strong>of</strong>
Investments and Returns. Journal <strong>of</strong> Management Studies, 41(2), 335-361.
387

Factors Influencing <strong>the</strong> Acquiring <strong>of</strong> Technological
Knowledge Among Technology Transfer Recipients – a
Perspective From a Radar Manufacturing Firm
Thanaletchumi Sathasivam, Zuraini Ismail and Ahmad Rahman Songip
University Technology Malaysia, Malaysia
thanalp@yahoo.com
zurainisma@citycampus.utm.my
ahmadrs@fkkksa.utm.my
Abstract: Technology transfer is becoming increasingly important for business and economic growth in
developing nations. The transfer and adoption <strong>of</strong> technology is essential from <strong>the</strong> perspective <strong>of</strong> <strong>the</strong> strength <strong>of</strong>
national economies in self-reliance and enhancing international competitiveness. Without proper knowledge
acquisition, transfer <strong>of</strong> technology cannot take place. The process <strong>of</strong> acquiring knowledge comprises learning to
understand, utilise and internalise <strong>the</strong> knowledge <strong>of</strong> <strong>the</strong> technology, and requires <strong>the</strong> organisation to choose or
adapt elements <strong>of</strong> <strong>the</strong> technology to local cultural conditions to integrate it with indigenous technologies. The
cultural context <strong>of</strong> <strong>the</strong> recipient can also affect <strong>the</strong> process <strong>of</strong> acquiring knowledge. In many cases, adopting <strong>the</strong>
technology may require changes to <strong>the</strong> organizational culture to support greater acceptance and use <strong>of</strong> <strong>the</strong>
technology among employees. The culture and social environment <strong>of</strong> <strong>the</strong> individual creates a schema for
organising knowledge and understanding reality. This paper has two objectives. Firstly, to investigate how
organisational culture affects readiness for technology transfer. Second,to identify elements <strong>of</strong> organisational
culture affecting readiness for technology transfer. A qualitative mode <strong>of</strong> data collection was used in this study.
Interviews and focus group discussions were conducted. The findings were used to identify <strong>the</strong> components and
to create <strong>the</strong> framework. Hypo<strong>the</strong>ses were formulated between <strong>the</strong> constructs <strong>of</strong> <strong>the</strong> framework to understand
better <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> technology transfer process. The implementation was tested using post-hoc
interviews.
Keywords: readiness, organisational culture, technological knowledge, absorption capacity, transfer <strong>of</strong>
technology, developing countries
1. Introduction
Technology transfer is crucial to developing nations and businesses. However, many organizations
experience failure in <strong>the</strong> technology transfer process. Researchers have identified many potential
causes for failure, such as insufficient technical support from <strong>the</strong> transferring entity, insufficient basic
knowledge among an organisation‟s employees to use <strong>the</strong> technology, and inadequate management
<strong>of</strong> change in <strong>the</strong> organisation (Cohen, 2004).Significant variability exists in <strong>the</strong> way organisations
approach <strong>the</strong> process, and <strong>the</strong> success rate, with no recognised or established standard for
approaching <strong>the</strong> technology transfer process (Cohen, 2004). Previous research has identified
organisational culture as an important factor influencing <strong>the</strong> outcome <strong>of</strong> technology transfer, with <strong>the</strong>
organisational culture affecting readiness (Cui, et al., 2006). The processes necessary to capture <strong>the</strong>
explicit and tacit knowledge necessary to adopt a transferred technology <strong>of</strong>ten require significant
change in employee behaviour.
Effective technology transfer requires <strong>the</strong> organisational culture to foster knowledge sharing
behaviour to facilitate <strong>the</strong> spread <strong>of</strong> tacit knowledge. Organisational factors such as highly
compartmentalised departments, lack <strong>of</strong> a team approach, and internal competition could prevent <strong>the</strong>
organisation from developing <strong>the</strong> cooperation necessary for adopting <strong>the</strong> new technology. In addition,
<strong>the</strong> new technology may represent a change that <strong>the</strong> employees perceive as threatening, which
induces resistance to adopting <strong>the</strong> technology. In this context, reference was made to recent research
investigating <strong>the</strong> technology transfer process in developing countries. It concluded that organisational
culture influences <strong>the</strong> interaction between <strong>the</strong> source and recipients <strong>of</strong> a new technology (Kasimin,
Ibrahim, & bin Yus<strong>of</strong>f, 2009). It also emphasised that in any processes based on human initiatives,
importance has to be placed on organisational culture.
Based on <strong>the</strong>se considerations, <strong>the</strong> aim <strong>of</strong> <strong>the</strong> study was to address <strong>the</strong> following two research
questions:
How does organisational culture affect readiness for technology transfer?
Which elements <strong>of</strong> organisational culture affect readiness for technology transfer?
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Thanaletchumi Sathasivam et al.
This paper is organised into six sections. This section introduces <strong>the</strong> study and provides <strong>the</strong> research
questions. Section Two portrays <strong>the</strong> literature and <strong>the</strong> subsequent section describes <strong>the</strong> research
methodology. Section Four describes <strong>the</strong> results and findings. Outcomes <strong>of</strong> <strong>the</strong> implementation are
discussed in Section Five. The paper concludes with a discussion on <strong>the</strong> way forward.
2. Literature review
This section firstly defines organizational culture followed by various previous researches that provide
perspectives to <strong>the</strong> research questions.
2.1 Organizational culture and technology transfer
In <strong>the</strong> specific context <strong>of</strong> technology transfer, Simonin (2004) defined organisational culture as „<strong>the</strong>
degree to which employees are encouraged to rethink <strong>the</strong> logic <strong>of</strong> current behaviors, to question
established routines and beliefs, and to challenge established wisdom.‟ H<strong>of</strong>stede (1991) suggested
that organisational culture is „<strong>the</strong> collective programming <strong>of</strong> <strong>the</strong> mind which distinguishes <strong>the</strong> members
<strong>of</strong> one organization from ano<strong>the</strong>r‟. Based on <strong>the</strong>se general definitions, organisational culture
establishes <strong>the</strong> standards for <strong>the</strong> behaviours expected <strong>of</strong> employees, with individuals exhibiting
variant behaviours marginalised or terminated by <strong>the</strong> organisation. National cultural factors do
influence organisational culture, and are particularly relevant in <strong>the</strong> context <strong>of</strong> international technology
transfer. Cross-cultural differences in values, beliefs, and norms produce significant differences in
management practices and <strong>the</strong> perceptions <strong>of</strong> employees <strong>of</strong> <strong>the</strong> organisational culture.
Investigations into technology transfer indicate that organizational culture can influence <strong>the</strong> transfer
process in areas such knowledge acquisition, sharing and transfer (Ishida, 2004). Many factors
influence organisational culture, which creates difficulties for identifying <strong>the</strong> components <strong>of</strong>
organisational culture critical for technology transfer. The rewards system, methods for selecting and
advancing employees, and <strong>the</strong> operational decisions by managers shape culture <strong>of</strong> an organisation
(Chandler, Keller, & Lyon, 2000). The structure <strong>of</strong> <strong>the</strong> organisation also has an influence on culture,
with vertical and compartmentalised structures fostering a mechanistic culture while horizontal and
matrix structures foster an entrepreneurial culture (Miller, Bierly, & Daly, 2007). Organisations can
also have a formal culture created by its policies and procedures and an informal culture developing
from <strong>the</strong> practices <strong>of</strong> its employees (Foss, 2005).
The model <strong>of</strong> organisational culture developed by Sonnentag (2002) indicates that <strong>the</strong> culture is
bifurcated into <strong>the</strong> perceptions <strong>of</strong> managers and <strong>the</strong> perceptions <strong>of</strong> employees. The perceptions <strong>of</strong>
managers are based on <strong>the</strong> formal elements <strong>of</strong> <strong>the</strong> organisational culture such as structure, policies,
and degree <strong>of</strong> management control. The perceptions <strong>of</strong> employees reflect <strong>the</strong> informal culture <strong>of</strong> <strong>the</strong>
organisation such as <strong>the</strong> networking relationships, <strong>the</strong> degree <strong>of</strong> commitment to <strong>the</strong> formal norms and
values, and <strong>the</strong> degree <strong>of</strong> independent decision-making perceived as acceptable. The greater <strong>the</strong>
alignment between <strong>the</strong> organisational culture and <strong>the</strong> processes associated with technology transfer,
<strong>the</strong> more likely <strong>the</strong> transfer will be effective (Simon & Lane, 2004).
2.2 Readiness in technology transfer
A necessary precondition to support <strong>the</strong> transfer <strong>of</strong> technology is <strong>the</strong> readiness <strong>of</strong> recipients to accept
<strong>the</strong> technology and <strong>the</strong> capacity to acquire <strong>the</strong> knowledge and skills necessary to use <strong>the</strong> technology
(Ouma-Onyango, 1997). This definition indicates that readiness can be decomposed into <strong>the</strong> two
dimensions <strong>of</strong> willingness and capacity, with both dimensions necessary for effective technology
transfer. Willingness is related to <strong>the</strong> state <strong>of</strong> mind <strong>of</strong> <strong>the</strong> organisation and its leadership about <strong>the</strong>
need and desirability <strong>of</strong> adopting <strong>the</strong> technology. Sufficient willingness is necessary among <strong>the</strong>
employees <strong>of</strong> <strong>the</strong> firm to motivate <strong>the</strong> effort necessary to adopt <strong>the</strong> technology and to overcome
socio-cultural impediments such as resistance to change. Capacity is related to <strong>the</strong> abilities <strong>of</strong> <strong>the</strong>
employees <strong>of</strong> <strong>the</strong> organisation to understand <strong>the</strong> technology, <strong>the</strong> fundamental principles underlying
<strong>the</strong> technology, and <strong>the</strong> way <strong>the</strong> technology can be used within current organisational operation.
Agmon and von Glinow (1991: 93) noted that many <strong>of</strong> <strong>the</strong> „problems <strong>of</strong> technology transfer are
encountered because <strong>the</strong> receiving organization is not able or ready or willing to absorb <strong>the</strong>
technology ei<strong>the</strong>r because <strong>of</strong> lack <strong>of</strong> knowledge or wrong incentives.‟ Having established <strong>the</strong>se
information and facts, we would be in position to establish answers to <strong>the</strong> research questions.
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2.3 Managing knowledge in technology transfer
Knowledge in an organisation is <strong>the</strong> combination <strong>of</strong> all information about policies, practices, data, and
experience and exposure <strong>of</strong> personnel that can be harnessed to achieve <strong>the</strong> objectives <strong>of</strong> <strong>the</strong>
organisation (Bhatt, 2002). Gopalakrishnan and Santoro (2004) distinguish between knowledge
transfer and technology transfer, suggesting that <strong>the</strong> variables involve different processes, although
knowledge transfer may be essential for technology transfer. Kallil, Claudio, & Seleim, (2006) also
claimed that managing knowledge and <strong>the</strong> transfer are <strong>the</strong> central elements in <strong>the</strong> technology transfer
process.
The knowledge management system used by <strong>the</strong> organisation is a critical construct in affecting
absorptive capacity because it controls <strong>the</strong> formal and informal routines related to <strong>the</strong> acquisition and
dissemination <strong>of</strong> knowledge (Bounfour, 2003; Kallil, Claudio, & Seleim, 2006). It involves <strong>the</strong> system
used for networking among employees and <strong>the</strong> transfer <strong>of</strong> information and knowledge (Daghfous,
2004). The level or type <strong>of</strong> technology in use in <strong>the</strong> organisation also affects capacity. Organisations
using technologies similar to <strong>the</strong> transferred technology will have greater capacity to absorb <strong>the</strong> new
technology (Kumar & Marg, 2003). As a result, <strong>the</strong> capacity dimension <strong>of</strong> readiness includes
education, training, experience, <strong>the</strong> knowledge management system, and <strong>the</strong> existing use <strong>of</strong>
technology in <strong>the</strong> organisation. The knowledge management system is composed <strong>of</strong> both formal and
informal components that can <strong>the</strong>oretically influence <strong>the</strong> technology transfer process.
The knowledge management system utilized in <strong>the</strong> organization can influence <strong>the</strong> capacity <strong>of</strong> <strong>the</strong>
organisation to acquire and use <strong>the</strong> information necessary to support <strong>the</strong> new technology (Oztemel
&Polat, 2007). Therefore a relationship also exists between <strong>the</strong> knowledge management system <strong>of</strong>
<strong>the</strong> organisation and readiness for technology transfer. The knowledge management system is a
significant factor in <strong>the</strong> ability <strong>of</strong> <strong>the</strong> organisation to disseminate both explicit and implicit knowledge to
<strong>the</strong> individuals requiring information. The capacity <strong>of</strong> <strong>the</strong> organisation in terms <strong>of</strong> its existing level <strong>of</strong>
knowledge and experience in turn influences <strong>the</strong> way it uses <strong>the</strong> knowledge management system
during <strong>the</strong> technology transfer process.
3. Methodology
In addressing <strong>the</strong> research question, interviews and focus group discussions were carried out to
determine <strong>the</strong> components for <strong>the</strong> framework. These participants were purposefully selected to
provide insights into <strong>the</strong> introduction <strong>of</strong> new technology that was intended to advance <strong>the</strong> existing
technologies within <strong>the</strong> firm. Upon implementing <strong>the</strong> findings <strong>the</strong> framework was tested using post hoc
interviews.
3.1 Qualitative data collection instruments
The data collection instruments in <strong>the</strong> qualitative phase <strong>of</strong> <strong>the</strong> study consisted <strong>of</strong> open ended
questions posed to <strong>the</strong> interviewees and focus group participants. The questions were intended to
obtain information about <strong>the</strong> perceptions and experiences <strong>of</strong> <strong>the</strong> study participants about <strong>the</strong>
technology transfer process. The questions were derived from <strong>the</strong> issues identified by previous
researchers investigating technology transfer. The development <strong>of</strong> <strong>the</strong> questions followed <strong>the</strong>
recommendations <strong>of</strong> Wengraf (2001) in which <strong>the</strong> questions should be based on <strong>the</strong>ory but should
use <strong>the</strong> language commonly used by <strong>the</strong> interviewees. Figure1 shows <strong>the</strong> process used for
developing <strong>the</strong> questions.
The general structure conformed to this pattern <strong>of</strong> relating <strong>the</strong> questions to <strong>the</strong> <strong>the</strong>oretical issues
underlying <strong>the</strong> research. Question 1 was a general question connected to <strong>the</strong> overall research
purpose and intended to establish <strong>the</strong> general direction <strong>of</strong> <strong>the</strong> participants. Questions 2, 3, and 4 were
related to <strong>the</strong> readiness construct. Questions 5, 6, 7, and 8 were related to organisational culture.
Questions 9, 10, and 11 were related to knowledge management. Questions 12 and 13 were related
to <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> technology transfer process.
3.2 Focus groups
Three focus group sessions were held with eight participants in each focus group in October and
December 2009. These participants came from across <strong>the</strong> organisation. The focus groups included
24 participants. The group included 10 Bachelor holders, nine Diploma holders, three Masters
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holders, one Certificate holder and two holders <strong>of</strong> o<strong>the</strong>r degrees. The average number <strong>of</strong> years in <strong>the</strong>
project was 6.4 years.
Figure 1: Process for developing <strong>the</strong> questions (adapted from Wengraf (2001, p. 157))
3.3 Interviews
The interview process followed <strong>the</strong> recommendations <strong>of</strong> Taylor and Bogdan (1998) concerning <strong>the</strong>
interactions between <strong>the</strong> interviewer and <strong>the</strong> interviewees. A total <strong>of</strong> eleven interviews were
conducted with members <strong>of</strong> <strong>the</strong> management staff in September 2009. These interviews were
conducted across nine different departments in <strong>the</strong> organisation. Individual interview participant
educational levels included seven Bachelor holders, three Master holders, and one Doctorate holder.
The average number <strong>of</strong> years on <strong>the</strong> project was 5 to 6 years. All participants except one were
between 30-39 years, with one being between 20 and 29 years.
4. Results and findings
Based on <strong>the</strong> approach explained in <strong>the</strong> previous section, <strong>the</strong> findings were analysed using iterative
<strong>the</strong>matic analysis (content analysis), with three levels <strong>of</strong> coding used (open coding, axial coding, and
narrative coding). The researcher performed three focus groups as well as 11 individual interviews in
order to identify <strong>the</strong> specific areas <strong>of</strong> concern for <strong>the</strong> study. The focus groups discussed a total <strong>of</strong> ten
questions, each <strong>of</strong> which was aligned with a specific construct that <strong>the</strong> researcher identified from
within <strong>the</strong> research. Interview respondents were presented with thirteen questions, also aligned to <strong>the</strong>
underlying constructs. This section provides a brief summary <strong>of</strong> <strong>the</strong> answers provided by each <strong>of</strong> <strong>the</strong>
groups.
4.1 Results from focus groups
The first question in <strong>the</strong> focus group discussed <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> technology transfer process.
Responses indicated that <strong>the</strong>re was room for improvement. The groups were consistent in identifying
technology transfer as being a full process from discussion to implementation. One group identified
that <strong>the</strong> company doing <strong>the</strong> transfer did not perform <strong>the</strong> technology transfer as expected. However,
<strong>the</strong> o<strong>the</strong>r two groups indicated that <strong>the</strong>re were failures on <strong>the</strong> part <strong>of</strong> <strong>the</strong> radar manufacturing
company in terms <strong>of</strong> learning and being able to implement <strong>the</strong> system. The groups were consistent in
not seeing a full achievement <strong>of</strong> <strong>the</strong> company‟s objectives.
One group indicated that “we need to overhaul <strong>the</strong> workflow, processes, procedures and policies to
accommodate <strong>the</strong> project”. Ano<strong>the</strong>r indicated that while <strong>the</strong> process was fine, it didn‟t meet <strong>the</strong> needs
<strong>of</strong> <strong>the</strong> environment and culture. The third stated that <strong>the</strong>re was some adjustment needed and that <strong>the</strong>
company continued to have adjustment needs for <strong>the</strong> project. Support staff <strong>of</strong> <strong>the</strong> technology transfer
was mixed, with some staff being highly supportive while o<strong>the</strong>rs were not.
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The problems encountered during <strong>the</strong> transition were reported at various levels across <strong>the</strong> groups.
The responses <strong>of</strong> <strong>the</strong> focus groups who indicated each <strong>of</strong> <strong>the</strong> problems that were identified during <strong>the</strong>
coding process for analysis purposes is shown in Table 1.
Table 1: Problems encountered during <strong>the</strong> technology transfer process (one <strong>of</strong> <strong>the</strong> questions)
The focus groups indicated that resolution <strong>of</strong> <strong>the</strong>se processes including providing instructions to
managers that had <strong>the</strong> skills and knowledge to provide support to operational staff, and hiring new
staff with <strong>the</strong> appropriate skills and knowledge. However, this was not accepted as a solution because
<strong>the</strong> new staff members were paid more than <strong>the</strong> older staff members and <strong>the</strong>y were hired at <strong>the</strong>
managerial level. This creates internal friction and resistance to <strong>the</strong>ir guidance. The focus groups
reported problems including <strong>the</strong> new employees not being listened to and <strong>the</strong>ir instructions being
ignored. There were comments that it was difficult to become integrated into <strong>the</strong> company, and <strong>the</strong>re
is need for intervention from high level managers. This reduced <strong>the</strong> effectiveness <strong>of</strong> this approach to
managing <strong>the</strong> difficulties involved in <strong>the</strong> technology transfer.
Internal communication methods identified included IT supported systems, including email, shared file
systems, and chat systems, as well as meetings. The only problem indicated was <strong>the</strong> inclusion <strong>of</strong>
newly hired managers and contractual employees in <strong>the</strong> communication systems. Communication
with <strong>the</strong> supplier <strong>of</strong> <strong>the</strong> technology was identified mainly as using meetings with management and
personal relationships between managers at <strong>the</strong> implementation level. However, one group did
indicate problems with information being held back, which <strong>the</strong>y indicated hurt <strong>the</strong> process. Existing
policies and procedures were seen both as benefits as well as hindrances. The existing policies were
helpful, but <strong>the</strong>y were intended for different kinds <strong>of</strong> projects, and also required more time than was
available for this project. The policies had to be shortened to accommodate this project, and
sometimes <strong>the</strong>y were too rigid for <strong>the</strong> needs <strong>of</strong> <strong>the</strong> project.
Knowledge sharing used IT facilities (emails, bulletin board, intranet, project management and
common file locations). It also involved meetings, including brainstorming, informal discussions, and
presentations. General consensus among <strong>the</strong> focus groups was that <strong>the</strong>se tools worked well. The
main approach to resolving problems without supplier involvement was to go to <strong>the</strong> manager <strong>of</strong>
operations or <strong>the</strong> project manager, and using project management techniques to track problems with
<strong>the</strong> implementation. Some escalation to <strong>the</strong> supplier was used, but it was not always met with a reply
in a timely fashion.
4.2 Results from interviews
The 11 interviews that were conducted included 13 different questions intended to identify <strong>the</strong>
individual experience and view <strong>of</strong> <strong>the</strong> process <strong>of</strong> technology transfer. These responses varied much
more widely than <strong>the</strong> focus group responses, due to <strong>the</strong> discussion process used to come to
conclusions within <strong>the</strong> focus group. Overall, <strong>the</strong> views <strong>of</strong> <strong>the</strong> participants were that <strong>the</strong> project was
challenging and exciting. However, <strong>the</strong> level <strong>of</strong> uncertainty in <strong>the</strong> project was clearly a stressor.
One participant remarked, “We felt like we had to actually turn <strong>the</strong> world around360 degrees, because
we had far too many uncertainties.” The respondents indicated that <strong>the</strong>re was a high level <strong>of</strong> reliance
on <strong>the</strong> technology provider, which was reflected at a much higher level than in <strong>the</strong> focus groups.
Challenges noted included organisational structure and culture, as well as technical barriers to
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implementation. One issue that was noted is that although management was supportive <strong>of</strong> <strong>the</strong> project,
<strong>the</strong> policies and procedures did not support <strong>the</strong> level <strong>of</strong> flexibility needed for <strong>the</strong> project.
There were a number <strong>of</strong> specific problems identified with <strong>the</strong> staff as well. These included problems
with compensation and salary scale, as well as problems <strong>of</strong> lack <strong>of</strong> employee morale and issues
about informing staff members. One commonality in this was that <strong>the</strong> relationship with <strong>the</strong> supplier <strong>of</strong>
<strong>the</strong> technology being implemented was considered to be routinely good. One respondent indicated
that it was “Diplomatically correct. Everything according to <strong>the</strong> books.” However, <strong>the</strong> understanding <strong>of</strong>
<strong>the</strong> technology was a significant problem identified by a number <strong>of</strong> responses. Overall, <strong>the</strong>re was a lot
<strong>of</strong> ambiguity about how <strong>the</strong> project went, and many individuals had very different ideas about what <strong>the</strong>
overall response to <strong>the</strong> technologies actually was.
5. Analysis using coding outcomes
Open coding and axial coding were both used in order to analyse <strong>the</strong> focus group and interview
outcomes and identify <strong>the</strong> appropriate constructs for examination in <strong>the</strong> quantitative research. Open
coding is <strong>the</strong> process <strong>of</strong> coding responses by identifying underlying concepts inherent in <strong>the</strong> response
(Flick, 2006). In order to perform open coding, <strong>the</strong> researcher first segmented <strong>the</strong> responses to focus
groups and interviews into words or phrases that identified concepts, in accordance with <strong>the</strong> structure
identified by Flick (2006). These responses were <strong>the</strong>n placed into a tabular format that allowed <strong>the</strong>
researcher to rapidly make connections between concepts expressed in sentences or individual
responses, as well as identifying <strong>the</strong> underlying concepts that <strong>the</strong> respondents expressed. The open
coding process would form <strong>the</strong> basis for <strong>the</strong> completion <strong>of</strong> <strong>the</strong> axial coding.
The second type <strong>of</strong> coding that was used was axial coding. While open coding is intended to identify
all concepts or constructs within a given response, axial coding is performed with a direct view to
answering <strong>the</strong> research question or research questions (Flick, 2006). During <strong>the</strong> process <strong>of</strong> axial
coding, <strong>the</strong> first step is selection <strong>of</strong> <strong>the</strong> most relevant codes or categories from those that were
previously identified (Flick, 2006). (In this research, <strong>the</strong> previous coding process was done via open
coding). Then, relationships between codes or categories are constructed using relationships within
<strong>the</strong> textual output to identify <strong>the</strong>se relationships. This allows for identification <strong>of</strong> subcategories, related
categories, and o<strong>the</strong>r relationships within <strong>the</strong> data that shed light on <strong>the</strong> relationships that were
explored in this research.
5.1 Open coding process
The open coding process was primarily conducted on <strong>the</strong> interviews, in which direct responses were
recorded. This was <strong>the</strong>n supported by <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> focus group participants during <strong>the</strong> axial
coding process. A sample <strong>of</strong> <strong>the</strong> coding process has been included for demonstration <strong>of</strong> <strong>the</strong> practice
as shown in Table 2. This coding process collapsed results from focus group questions and specific
interviews into one category in order to determine <strong>the</strong> overall outcomes <strong>of</strong> <strong>the</strong> process. The table
indicates <strong>the</strong> number <strong>of</strong> respondents that indicated <strong>the</strong> response pattern within <strong>the</strong> study. It should be
noted that response patterns were not explicitly based on exact wording, as <strong>the</strong> speech patterns and
verbosity <strong>of</strong> various respondents varied substantially. Instead, it was based on general meaning <strong>of</strong> a
given response. These results include all responses (and counts) for each interview. During <strong>the</strong> axial
coding process, responses that were not seen from at least two respondents will be eliminated. The
full output <strong>of</strong> this coding process is available in Appendix A (Open Coding Categories and Results).
These results demonstrate that <strong>the</strong>re was considerable overlap between <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> focus
groups and <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> interviews, although <strong>the</strong> interview respondents were considerably
more forthcoming regarding <strong>the</strong>ir criticisms <strong>of</strong> <strong>the</strong> project than in some <strong>of</strong> <strong>the</strong> focus groups. This could
be attributed to <strong>the</strong> use <strong>of</strong> informal interviews and <strong>the</strong> confidentiality <strong>of</strong> <strong>the</strong> interviews, which meant
that individuals would not face repercussions from being honest in <strong>the</strong>ir interviews. The open coding
process produced substantial evidence that would be used for <strong>the</strong> axial coding process, which is
described below.
5.2 Axial coding
The output <strong>of</strong> <strong>the</strong> open coding process was used as <strong>the</strong> input for <strong>the</strong> axial coding process. During this
process, <strong>the</strong> specific underlying constructs that were identified in <strong>the</strong> research questions and
hypo<strong>the</strong>ses were use as a focus for <strong>the</strong> coding process. Categories produced were <strong>the</strong>n collapsed
and <strong>the</strong> resulting constructs or concepts were used as <strong>the</strong> focus for identifying <strong>the</strong> appropriate
questions to be asked during <strong>the</strong> quantitative process. Table 3 identifies <strong>the</strong> correspondence <strong>of</strong> focus
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group and interview questions to specific constructs that were used within <strong>the</strong> research questions.The
original open coding categories that resulted from <strong>the</strong>se findings were collapsed into several subcategories
following <strong>the</strong> completion <strong>of</strong> <strong>the</strong> open coding. Some categories were collapsed into similar
meanings; for example, <strong>the</strong> categories “Challenging” and “Difficult” were collapsed into a single
response category. Any category that remained with only one response following this collapse
process was discarded. This resulted in a number <strong>of</strong> keyword-categories that were prevalent in <strong>the</strong>
focus group and interview responses. The axial coding outcomes are attached in Appendix B (Axial
Coding Results and Categories).
Table 2: Example <strong>of</strong> open coding (interview responses)
Table 3: Correspondence <strong>of</strong> focus group and interview questions to research constructs
5.3 Narrative coding
Following this axial coding process, <strong>the</strong> narrative coding process completed <strong>the</strong> qualitative portion <strong>of</strong>
<strong>the</strong> analysis. The narrative coding process focused on <strong>the</strong> areas identified in <strong>the</strong> axial coding process
above; creating questions that would bring to light more information regarding <strong>the</strong> identified areas <strong>of</strong>
concern or uncertainty by <strong>the</strong> respondents. These areas were as described above. The outcomes <strong>of</strong>
this coding process are concluded in a form <strong>of</strong> a model and it is described in <strong>the</strong> next section.
6. Proposed conceptual model
Based on <strong>the</strong> qualitative analysis conducted, a conceptual model depicting <strong>the</strong> factors influencing
technology transfer at organizational level is proposed in Figure 2
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Figure 2: Proposed conceptual model
Thanaletchumi Sathasivam et al.
The model is fur<strong>the</strong>r supported using <strong>the</strong> <strong>the</strong>oretical assumption that bivariate relationships exist
between <strong>the</strong> independent variables <strong>of</strong> readiness, organisational culture, and knowledge management,
and <strong>the</strong> dependent variable <strong>of</strong> effective transfer <strong>of</strong> technology. In each bivariate relationship, a change
in <strong>the</strong> value <strong>of</strong> any one independent variable can influence <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> transfer <strong>of</strong>
technology. Due to <strong>the</strong> complexity <strong>of</strong> <strong>the</strong> technology transfer process, <strong>the</strong> model incorporates
multivariate influences among <strong>the</strong> three major independent variables. The interrelationship <strong>of</strong> <strong>the</strong>
independent variables within <strong>the</strong> model represents a complex set <strong>of</strong> organisational processes
necessary for <strong>the</strong> effective transfer <strong>of</strong> technology. Organisational culture influences <strong>the</strong> processes
associated with knowledge management by establishing <strong>the</strong> values and norms related to knowledge
acquisition and dissemination. The relationship between knowledge management and <strong>the</strong>
effectiveness <strong>of</strong> technology transfer was also noted. Knowledge management is an independent
variable in <strong>the</strong> research, and is based on <strong>the</strong> <strong>the</strong>oretical assumption that knowledge transfer is <strong>the</strong>
central element in <strong>the</strong> technology transfer process (Kallil, Claudio, & Seleim, 2006). These
components <strong>of</strong> <strong>the</strong> knowledge management system are operationalised in <strong>the</strong> specific operating
environment. The following section describes <strong>the</strong> outcome <strong>of</strong> <strong>the</strong> implementation <strong>of</strong> <strong>the</strong> model in <strong>the</strong>
organization.
7. Outcome <strong>of</strong> <strong>the</strong> implementation using Post Hoc interviews
Practical implementation was conducted in <strong>the</strong> organization following <strong>the</strong> model that was supported
fur<strong>the</strong>r by previous research work. After twelve months <strong>of</strong> implementing <strong>the</strong>re were ten post-study
interviews conducted with members <strong>of</strong> <strong>the</strong> staff that were involved in <strong>the</strong> technology transfer project.
These interviews were intended to provide insight for what went on after <strong>the</strong> research ended, and to
analyse <strong>the</strong> “practical implementation” <strong>of</strong> <strong>the</strong> model to <strong>the</strong> organization. This was analyzed using
<strong>the</strong> same process <strong>of</strong> open coding, axial coding, and narrative coding that was performed for <strong>the</strong> main
qualitative results. Table 4 demonstrates <strong>the</strong> full characteristics <strong>of</strong> each <strong>of</strong> <strong>the</strong> respondents.
Table 4: Pr<strong>of</strong>iles <strong>of</strong> post-study interview respondents
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The results <strong>of</strong> <strong>the</strong> post-study questions were obtained from ten open-ended research questions that
focused on <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> technology transfer, ongoing technology transfer efforts, and <strong>the</strong> role
<strong>of</strong> <strong>the</strong> study itself in improving technology transfer. Particular issues included retrospective analysis <strong>of</strong>
problems that were identified during <strong>the</strong> study, as well as discussion <strong>of</strong> what changes have been
made at <strong>the</strong> radar manufacturing company in order to continue <strong>the</strong> technology absorption process.
These questions were intended to target <strong>the</strong> expertise <strong>of</strong> <strong>the</strong> respondents, as well as to determine
how <strong>the</strong> process <strong>of</strong> technology transfer continued following <strong>the</strong> completion <strong>of</strong> <strong>the</strong> study.
Post-interview results clearly indicated that respondents felt <strong>the</strong> technology transfer was effective in
some areas, with <strong>the</strong> effectiveness varying by <strong>the</strong> specific task. They highlighted <strong>the</strong> difficulties in <strong>the</strong>
strict timeline and <strong>the</strong> lack <strong>of</strong> effective planning, inability to manage risk, and gaps in <strong>the</strong> organization
which could reduce <strong>the</strong> effectiveness <strong>of</strong> technology transfer. Respondents did see an improvement in
<strong>the</strong> ability to use and understand <strong>the</strong> technology, indicating that <strong>the</strong> team has been working hard and
has been benefiting from increased exposure and experience as well as gaining access to improved
technical support. However, some technical support is required. Respondents clearly indicated that
<strong>the</strong>re was a learning curve associated with <strong>the</strong> process, which had not been attempted before at <strong>the</strong>
company, and that <strong>the</strong> process become easier as it went on. Respondents indicated substantial
changes in <strong>the</strong> organisational culture and structure in response to <strong>the</strong> challenges posed by this
technology transfer. This included <strong>the</strong> increased role <strong>of</strong> open discussion <strong>of</strong> problems, improving <strong>the</strong>
decision making process, changes to o<strong>the</strong>r policies and procedures in order to improve <strong>the</strong>ir flexibility
and applicability to <strong>the</strong> process, providing incentives to increase improvements, improvements to
knowledge management practices, and improved relationships with <strong>the</strong> electronics supplier, all <strong>of</strong>
which were seen as key in improving <strong>the</strong> ongoing process <strong>of</strong> technology transfer. One positive poststudy
development was <strong>the</strong> improvement <strong>of</strong> relationships between <strong>the</strong> radar manufacturing company
and its technology supplier. During <strong>the</strong> initial study, <strong>the</strong> relationship between <strong>the</strong> two firms was <strong>of</strong>ten
ambiguous, with respondents indicating that <strong>the</strong> technology supplier gave only <strong>the</strong> information and
support that was required by <strong>the</strong> contract (and which was largely considered to be inadequate).
However, <strong>the</strong> respondents to <strong>the</strong> post-study interview indicated that this had improved, and that <strong>the</strong>
company was now pursuing a closer relationship with <strong>the</strong> supplier as a means <strong>of</strong> improving its
integration in technology. Respondents also indicated that <strong>the</strong> company has taken a number <strong>of</strong> new
initiatives in order to improve <strong>the</strong> integration <strong>of</strong> technology and eventual effectiveness <strong>of</strong> technology
transfer. These methods have included engaging in skills-based hiring intended to support <strong>the</strong>
technology, sponsorship <strong>of</strong> existing staff to improve <strong>the</strong>ir skill level, closer relationships with suppliers,
external placement <strong>of</strong> staff at organisations that can provide improved competency, changes in
company structure and decision making practices, investment in knowledge resources and
development <strong>of</strong> a resource area for staff and a knowledge portal developed to support known
information.Overall, <strong>the</strong> results <strong>of</strong> <strong>the</strong> study were not considered surprising by respondents. In
particular, <strong>the</strong>y anticipated <strong>the</strong> difficulties with <strong>the</strong> technology transfer process based on <strong>the</strong>ir own
experience, and felt that <strong>the</strong> study accurately reflected <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> technology transfer
process. However, <strong>the</strong>y reiterated <strong>the</strong> fact that, as a first-time technology transfer process for <strong>the</strong>
radar manufacturing company, this was a learning experience and was not considered to be a
complete failure by <strong>the</strong> company.
8. Practical contribution to future technology transfer recipients
The research was focused on <strong>the</strong> practical environment and as such <strong>the</strong> majority <strong>of</strong> <strong>the</strong> insights that
were gained through <strong>the</strong> research were in fact practical. The practical contribution is reinforcement <strong>of</strong>
important characteristics including organisational culture and knowledge management in <strong>the</strong> effective
transfer <strong>of</strong> technology. The role <strong>of</strong> knowledge management appears to have been <strong>the</strong> most relevant
for <strong>the</strong> organisation during <strong>the</strong> integration <strong>of</strong> results and <strong>the</strong> aftermath <strong>of</strong> <strong>the</strong> technology transfer. The
organisation also exhibited a positive response to this knowledge. The post-study respondents
indicated that a number <strong>of</strong> positive changes to <strong>the</strong> knowledge management practices in <strong>the</strong>
organisation had taken place following <strong>the</strong> study completion and <strong>the</strong> initial technology transfer
process. These changes included <strong>the</strong> use <strong>of</strong> a closer relationship between <strong>the</strong> supplier and <strong>the</strong>
company, <strong>the</strong> hiring <strong>of</strong> individuals whose skills and knowledge could be used to maximize <strong>the</strong>
company‟s ability to use and understand <strong>the</strong> technology, and <strong>the</strong> beginning development <strong>of</strong> a formal
knowledge management system in order to provide <strong>the</strong> structures to build organisational capacity. A
significant pragmatic implication <strong>of</strong> this research is that technology transfer does not necessarily come
to a natural end point when <strong>the</strong> partner company releases <strong>the</strong> technology or tools to <strong>the</strong> target
company. Instead, it is an ongoing process, whose end may be at this point, but may also not be. This
finding has one major implication for practitioners <strong>of</strong> technology transfer - Do not impose artificial
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Thanaletchumi Sathasivam et al.
deadlines on success or failure <strong>of</strong> <strong>the</strong> technology transfer process. Although <strong>the</strong> hand<strong>of</strong>f point
between <strong>the</strong> providing company and <strong>the</strong> target company is important, both in terms <strong>of</strong> organisational
psychology and in terms <strong>of</strong> financial and competitive strategy planning, this does not mean that an
extended technology integration period spells disaster for <strong>the</strong> technology transfer process. Instead,
<strong>the</strong> organisation may need to undergo an ongoing period <strong>of</strong> adjustment that improves on its
organisational capacity and rectifies any problems that were found in <strong>the</strong> initial process <strong>of</strong>
organisational alignment. Practitioners can make use <strong>of</strong> this finding by integrating benchmarking <strong>of</strong>
<strong>the</strong>ir processes and critical reflection on <strong>the</strong> technology transfer process into <strong>the</strong> process itself.
Continual reassessment <strong>of</strong> <strong>the</strong> technology transfer process as it is ongoing will allow <strong>the</strong> organisation
to identify any improvements that can immediately be made. This will allow <strong>the</strong> technology transfer
process itself to be more successful. However, <strong>the</strong> technology fit within <strong>the</strong> organisation should
continue to be assessed even after <strong>the</strong> initial transfer. Without this ongoing process, <strong>the</strong> company that
does not immediately achieve success with a technology transfer may write <strong>of</strong>f this technology
prematurely, which will lead to wasted resources and capital due to premature abandonment <strong>of</strong> <strong>the</strong>
project. Of course, a project should not be continued indefinitely once it becomes clear than <strong>the</strong>
technology transfer process cannot recover, as this would involve a similarly irresponsible waste <strong>of</strong>
resources. However, practitioners may be reassured that technology transfer does not necessarily
halt at <strong>the</strong> completion <strong>of</strong> <strong>the</strong> license transfer from provider company to acquirer company, and <strong>the</strong>y
may consider whe<strong>the</strong>r ongoing improvements are appropriate in order to fur<strong>the</strong>r align <strong>the</strong> organisation
and <strong>the</strong> technology.
9. Conclusion
This study has successfully answered both <strong>the</strong> research questions. Firstly <strong>the</strong> qualitative approach
determined how organisational culture affects readiness for technology transfer. Secondly, it also
ga<strong>the</strong>red <strong>the</strong> elements <strong>of</strong> organisational culture affecting readiness for technology transfer. This study
has endeavoured to create a conceptual model with <strong>the</strong> factors as constructs and <strong>the</strong> relationship that
relates <strong>the</strong>m to each o<strong>the</strong>r. The model was practically implemented in <strong>the</strong> organization. Post hoc
interviews were conducted to fur<strong>the</strong>r understand <strong>the</strong> outcomes <strong>of</strong> <strong>the</strong> technology transfer and <strong>the</strong>
ongoing technology transfer efforts in <strong>the</strong> organization. The contribution will serve as a checklist for
<strong>the</strong> future technology transfer recipients.
10. Appendix A: Sample <strong>of</strong> open coding categories and responses
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Thanaletchumi Sathasivam et al.
11. Appendix B: Sample <strong>of</strong> axial coding outcomes and categories
References
Agmon, T. & von Glinow, M.A. (1991). Technology transfer in international business. New York: Oxford University
Press.
Bhatt, G.D. (2002). Management strategies for individual knowledge and organizational knowledge. Journal <strong>of</strong>
Knowledge Management, 6(1): 31-39.
Bounfour, A. (2003). The management <strong>of</strong> intangibles. London: Routledge.
Chandler, G., Keller, C. & Lyon, D. (2000). Unravelling <strong>the</strong> determinants <strong>of</strong> an innovation-supportive
organisational culture. Entrepreneurship: Theory and Practice, 25(1), 59-72.
Cohen, G. (2004). Technology transfer, strategic management in developing countries. Thousand Oaks CA:
Sage Publications.
Cui, A., Griffith, D., Cavusgil, S., & Dabic, M. (2006). The influence <strong>of</strong> market and cultural environmental factors
on technology transfer between foreign MNCs and local subsidiaries: A Croatian illustration. Journal <strong>of</strong>
World Business, 41(2), 100-111.
Daghfous, A. 2004. Absorptive capacity and <strong>the</strong> implementation <strong>of</strong> knowledge-intensive best practices. SAM
Advanced Management Journal, 69(2), 21-36.
398

Thanaletchumi Sathasivam et al.
Easterby-Smith, M., Snell, R., & Gherardi, S. (1998). Organization Learning: Diverging communities <strong>of</strong> practice?
Management learning, 29(3), 259 – 272.
Foss, S. (2005). Strategy, economic organisation and <strong>the</strong> knowledge economy. Oxford: Oxford University Press.
Gopalakrishnan, S. & Santoro, M. (2004). Distinguishing between knowledge transfer and technology transfer
activities: <strong>the</strong> role <strong>of</strong> key organisational factors. IEEE Transactions on Engineering Management, 51(1), 57-
69.
H<strong>of</strong>stede, G. (1991). Culture and organisations: S<strong>of</strong>tware <strong>of</strong> <strong>the</strong> mind. London: McGraw-Hill.
Ishida, S. (2004). Composite knowledge for high-tech corporations. In Benton, C. &
Richter, F. (Eds.) Meso-organizations and <strong>the</strong> creation <strong>of</strong> knowledge. (pp. 37-60). Westport CT: Praeger.
Kallil, O., Caudio, A., & Seliem, A. (2006). Knowledge management. SAM Advanced Management Journal, 71(3),
34-47.
Kasimin, H., Ibrahim, H., & bin Yus<strong>of</strong>f, M. (2009). Diagnosing an ongoing technology transfer process: An
approach based on ANT. International Journal <strong>of</strong> Networking and Virtual Organisations, 6(1), 47-63.
Kumar, N. & Marg, L. (2000). Foreign direct investment and technology capabilities in developing countries: A
review. Journal <strong>of</strong> Public Administration, 23, 1253-1278.
Leonardi, P. (2008). Indeterminacy and <strong>the</strong> discourse <strong>of</strong> inevitability in international technology management.
Academy <strong>of</strong> Management Review, 33(4), 975-984.
Miller, B., Bierly, P., & Daly, P. (2007). The knowledge strategy orientation scale. Journal <strong>of</strong> Managerial Issues,
19(3), 414-435.
Milutinovic, V. & Patricelli, F. (2002). E-business and e-challenges. Amsterdam: IOS Press.
Ouma-Onyango, R. (1997). Information resources and technology transfer management in developing countries.
London: Routledge.
Oztemel, E. & Polat, T. (2007). Technological readiness model for enterprises. In Pham,
D., Eldukhri, E. & Soroka, A. (Eds.) Intelligent production machines and systems. London: Elsevier.
Saint-Onge, H. (1996). “Tacit knowledge: The key to <strong>the</strong> strategic alignment <strong>of</strong> intellectual capital‟. Strategy and
Leadership, March/April 10-14.
Samli, A. (2002). In search <strong>of</strong> equitable, sustainable globalisation. Westport CT: Quorum Books.
Samli, A. (1985). Technology transfer: The general model. In Samli, A. (Ed.) Technology transfer: geographic,
economic, cultural and technical Dimensions (pp. 3-17). Westport CT: Quorum Books.
Schein, E.H. (1998). Three Culture <strong>of</strong> Management: The Key to Organizational Learning. Sloan Management
Review, (pp. 9-20)
Simon, F. & Lane, P. (2004). A model <strong>of</strong> cultural differences and international alliance performance. Journal <strong>of</strong>
International Business Studies, 35, 306-319.
Simonin, B. (2004). An empirical investigation <strong>of</strong> <strong>the</strong> process <strong>of</strong> knowledge transfer in international strategic
alliances. Journal <strong>of</strong> International Business Studies, 35(5), 407-431.
Sonnentag, S. (2002). Psychological management <strong>of</strong> individual performance. New York: John Wiley & Sons.
Sundbo, J. & Fuglsang, L. (2002). Innovation as strategic reflexivity. London: Routledge
Syed-Ikhsan, S. & Rowland, F. (2004). Benchmarking knowledge management in a public organisation in
Malaysia. Benchmarking: An International Journal,11(2), 238-266.
Taylor, S. & Bogdan, R. (1998). Introduction to qualitative research methods. New York: John Wiley.
Triandis, H. (1994). Culture and Social Behavior. San Francisco : McGraw Hill.
Trice H.M & Beyer J.M. (1993). The Cultural <strong>of</strong> Work Organization. Englewood Cliffs, NJ: Prentice Hall.Wengraf,
T. (2001). Qualitative research interviewing. London: Sage.
399

Enhancing IC Formation by Evoking Hidden Potentials –
<strong>the</strong> Case <strong>of</strong> Smart Textiles
Klaus Bruno Schebesch
Vasile Goldiş Western University, Arad, Romania
kbschebesch@uvvg.ro
Abstract: Traditional industries like textiles and clothing rely in general on conservative business models and use
new technology in ra<strong>the</strong>r restricted ways. Product design is fashion oriented and <strong>the</strong>refore predominantly “artistic”
in nature, distribution channels are directed towards outlets facilitating physical contact <strong>of</strong> clients with <strong>the</strong>
produce. New technology enters mainly via more mechanized production cycles for a given set <strong>of</strong> narrowly
defined final products. The formation <strong>of</strong> Intellectual Capital (IC) in such industries is a slow, a long lasting and a
fairly invisible process, which reflects itself much less in <strong>the</strong> final products (e.g. clo<strong>the</strong>s) than is <strong>the</strong> case in most
contemporary high tech industries. IC in today’s textiles sector is perhaps more evident from aspects <strong>of</strong> <strong>the</strong>
business process such as finding and maintaining <strong>the</strong> appropriate business partners. Sustaining low creativity
products means underutilization <strong>of</strong> both new product concepts and technological possibilities inherent to textiles
and clothing – at least for textiles perceived in a broader sense. This may be changed by enhancing IC formation
through a learning cycle which affects producers and consumers alike. A successful transition to more creativity
may be achieved by employing smart textiles and <strong>the</strong>ir associated products. Their effective utility may be
established by virtue <strong>of</strong> highly dynamic, participative design processes for new product concepts and by using
appropriate eCommerce features. Such features include well adapted recommender systems based on trust
creation and opinion formation. Finally, <strong>the</strong> properties <strong>of</strong> a stylized opinion formation process are displayed.
Trust-based opinion formation is regarded as part <strong>of</strong> a procedure for assessing <strong>the</strong> acceptance <strong>of</strong> many new or
parallel product concepts as <strong>the</strong>y derive from future uses <strong>of</strong> smart textiles.
Keywords: IC and learning, opinion and trust formation, smart textiles, recommendation
1. Introduction
The textiles and clothing industry which is dating back to ancient times may now be at <strong>the</strong> onset <strong>of</strong> a
revolution regarding technology and consumer behaviour. This pr<strong>of</strong>ound change may be generated
by an intensifying interdisciplinary research into new materials and new design concepts regarding
<strong>the</strong> use <strong>of</strong> textiles in a variety <strong>of</strong> new ways and using fabric with essentially new physical properties.
However, <strong>the</strong> applicability <strong>of</strong> such smart textiles is by no means restricted to human wearable
clothing. Many o<strong>the</strong>r final industrial and retail uses have been proposed, ranging from construction
and decoration, to automotive interiors. A large number <strong>of</strong> complementarities can be found, especially
with - but not restricted to - parts <strong>of</strong> computing and telecommunication. For instance, ubiquitous
computing is <strong>of</strong>ten related to <strong>the</strong> use <strong>of</strong> sensors, internet functions and o<strong>the</strong>r computing tasks in order
to meet a vast array <strong>of</strong> very immediate physiological, psychological and social needs <strong>of</strong> persons, and
which is <strong>of</strong>ten related to <strong>the</strong> use <strong>of</strong> textiles and derived products in different situations <strong>of</strong> everyday life.
Until recently, such applications would have been far too expensive to use in ubiquitous ways.
Given recent technological innovation and development, <strong>the</strong> key question now is whe<strong>the</strong>r (parts <strong>of</strong>)
<strong>the</strong> textiles sector will indeed undergo <strong>the</strong> awaited change. Will consumers accept and demand <strong>the</strong>
large scale use <strong>of</strong> smart textiles?
While it is very hard to make accountable forecasts which resolve <strong>the</strong>se questions, we propose that
affirmative outcomes can be achieved by IC formation and learning within <strong>the</strong> various communities <strong>of</strong>
producers and consumers which are increasingly interrelated. Fur<strong>the</strong>rmore, we argue in favour <strong>of</strong>
using adapted recommender systems with trust generation and also for learning <strong>of</strong> how to use
complementarities in products and technologies within highly collaborative eCommerce procedures.
In section 2 smart textiles and some <strong>of</strong> <strong>the</strong>ir related product concepts are introduced from an exploratory
point <strong>of</strong> view. Here <strong>the</strong> question appears <strong>of</strong> whe<strong>the</strong>r such concepts are indeed realizable,
especially if faced with low present consumer acceptance. Section 3 discusses generic opinion
formation processes which may determine production and buying decisions <strong>of</strong> social agents. Section
4 describes introducing new products like smart textiles by integrating consumer and producer into a
virtual learning organization which enhances IC formation. In section 5 a cascaded opinion formation
model which includes consumer and producer networks and which uses trust formation between
agents is proposed. The model is a part <strong>of</strong> a procedure which attempts to assess <strong>the</strong> acceptance <strong>of</strong>
new product concepts. Finally, section 6 presents some conclusions and an outlook.
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Klaus Bruno Schebesch
2. Smart textiles: New opportunities for old industries
From an exploratory <strong>the</strong> point <strong>of</strong> view which emphasizes artistic potential and technological fantasy
smart textiles seem to <strong>of</strong>fer a broad spectrum <strong>of</strong> new opportunities ranging from new product creation
all <strong>the</strong> way to salvaging declining industrial sectors. Judging by new design opportunities put forward
at specialized workshops (i.e. Baurley (2006)) and by <strong>the</strong> long list <strong>of</strong> potential applications <strong>of</strong> smart
textiles which in part coincide with <strong>the</strong> use <strong>of</strong> smart materials (i.e. Ohmatex (2007)), and in part with
new combinations <strong>of</strong> functionalities (Advanced Materials (2007)) <strong>of</strong> cloth related products, one still
awaits a sector take-<strong>of</strong>f. Although <strong>the</strong>re are signs <strong>of</strong> awareness <strong>of</strong> <strong>the</strong> opportunities (technical textiles
have a clear market position, i.e. Byrne, C. (2007)) actual market development <strong>of</strong> smart textiles is less
dramatic than many would expect.
Figure 1 lists some possible consumer trends (left hand side) in smart textiles derived products, which
are reflecting a strong elements <strong>of</strong> acceptance, which in turn are depending on personal networking.
For instance, <strong>the</strong> degree to which (body invasive) sensor implants will be accepted by a large customer
base in <strong>the</strong> future certainly depends on a crowding or imitation effect: consumer needs <strong>of</strong> <strong>the</strong>
future will be in strong relation to emerging social trends.
Figure 1: An example <strong>of</strong> an exploratory s<strong>of</strong>t forecast <strong>of</strong> consumer and technological trends reflecting
an optimistic to pragmatic view expressed at a 2006 London workshop on smart materials
(Baurley 2006, p32)
Possible technological trends (Figure 1, rhs) include different types <strong>of</strong> smart materials, and emerging
applications in clothing, which include ra<strong>the</strong>r dramatic examples as for instance “self cleaning” and
“self fitting clo<strong>the</strong>s”. These design examples are not meant to be exhaustive but are merely intended
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Klaus Bruno Schebesch
to portray <strong>the</strong> diversity and <strong>the</strong> rich potential for finding complementarities <strong>of</strong> many kinds as is <strong>the</strong> use
<strong>of</strong> internet services and <strong>the</strong> use power sources in <strong>the</strong> concept examples from figure 2.
Figure 2: Two examples <strong>of</strong> concepts presented at <strong>the</strong> workshop referred to in figure 1 concerning <strong>the</strong>
use <strong>of</strong> smart textiles and related concepts, left inset: ”adaptive, self fitting clothing according
to downloaded style instructions”. Right inset: “strength or power amplification in gloves”
Despite <strong>of</strong> <strong>the</strong> manifold opportunities <strong>of</strong> artistically and technologically induced designs for clothing
based on <strong>the</strong> use <strong>of</strong> smart textiles (view figures 1 and 2) <strong>the</strong>re remain questions <strong>of</strong> whe<strong>the</strong>r <strong>the</strong>se can
and if <strong>the</strong>y will translate into effective business opportunities and markets. At a societal level one
would expect important beneficial industrial transformations to be induced by <strong>the</strong> intellectual capital
(IC) resulting from building up such markets. At <strong>the</strong> conceptual level, one would <strong>the</strong>n be interested in
explaining a transition from a low pr<strong>of</strong>ile behaviour <strong>of</strong> buying traditional textiles to buying smart textiles
may take place and how this could be possibly be achieved by IC formation within a learning cycle
which affects producers and consumers alike. Effective utility <strong>of</strong> smart textiles may be established by
means <strong>of</strong> participative design processes for new product variants and by using appropriate
eCommerce features. Mechanisms for achieving this are described in <strong>the</strong> next two sections.
3. Opinion formation processes as a stylized model <strong>of</strong> product concept
selection?
Buying behaviour and ensuring <strong>the</strong> visibility <strong>of</strong> new consumer products like those based on smart
textiles, which are not covering self-explanatory basic needs <strong>of</strong> people, can be in part traced back to
opinion formation process within social networks. Opinion formation evolves alongside trust formation.
Trust between clients is an important ingredient for building recommender systems based on past
client scores (Schebesch et al. (2010)) effectively contributes to tilting buying behaviour.
For simplicity assume that <strong>the</strong> only observable may be network structure and whe<strong>the</strong>r <strong>the</strong> group <strong>of</strong>
people behind <strong>the</strong> network has reached a solution (a “consensus”). Then we can use a ra<strong>the</strong>r simple
dynamic opinion formation model, which can also be considered as a paradigm for modelling <strong>the</strong> formation
<strong>of</strong> conventions and <strong>of</strong> standards, by using a procedure <strong>of</strong> message exchange between agents
in social (client community, etc.) environments. Dynamic opinion formation can also be related to <strong>the</strong>
modeling <strong>of</strong> negotiation processes (Baronchelli et al. (2007)) and also to modelling <strong>the</strong> emergence <strong>of</strong>
“languages” in networks <strong>of</strong> humans. In <strong>the</strong> present context opinion formation is proposed to model <strong>the</strong>
emergence <strong>of</strong> sub-networks in client populations or extended virtual enterprises including producers,
which are composed <strong>of</strong> persons evolving similar opinions (e.g. to produce, to buy, see section 5). ()
Models for dynamic opinion formation use bounded confidence, which basically is a restriction to
mainly interact with culturally similar partners and <strong>the</strong>y may be stochastic versions <strong>of</strong> <strong>the</strong> so called
“naming game”, used to describe emergence <strong>of</strong> communication in networks. The full ma<strong>the</strong>matical
consequences <strong>of</strong> such models are not known as <strong>of</strong> today (Blondel et al. (2008)), but <strong>the</strong>re is insight by
means <strong>of</strong> numerical experiments: Besides <strong>the</strong> emergence <strong>of</strong> consensus, <strong>the</strong> dynamics typically
exhibit opinion polarization, i.e. convergence towards two or many opinions, and also phase transitions:
for some critical parameters abrupt changes occur in behavioural type, for instance <strong>the</strong> sudden
transition from consensus to polarization. The basic dynamic principle is well described by Krause’s
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Klaus Bruno Schebesch
consensus formation model (Krause (2000), Blondel et al. (2008)), which simply states: First assume
that n > 0 agents i = 1,...,
n are connected via a topology which is inducing a neighborhood. These
agents are evolving <strong>the</strong>ir respective opinion X ( i,
t)
> 0 over discrete time t = 0,
1,...,
T by updating
for every agent i = 1,...,
n <strong>the</strong> following (purely deterministic) difference equation:
X ( k,
t)
X ( i,
t + 1)
= ∑ , with random X (i,
0)
>0,
| { k(
i)}
|
{ k ( i)}
k (i)
| . |
where <strong>the</strong> index is running over <strong>the</strong> neigborhood <strong>of</strong> every agent i and where ” ” denotes <strong>the</strong>
number <strong>of</strong> respective neighbors. The index set { k(
i)}
is computed by finding all <strong>the</strong>
{ k :|| X ( k,
t)
X ( i,
t)
|| < w},
− for a given
w > 0.
Here || . || stands for a distance function, which simply measures <strong>the</strong> absolute difference between opinions
or opinion values <strong>of</strong> agents k and i.
By convention, <strong>the</strong> n starting opinions are sorted, i.e. with
X ( n,
0)
> X ( n − 1,
0)
> … > X ( 1,
0)
> 0 . Owing to <strong>the</strong> agent-dependent dynamic index set { k(
i)}
<strong>the</strong> dynamic process {X (.,t)}
is adaptable to every interconnection topology evolving in <strong>the</strong> agent’s
relational network. Adaptation is steered by setting w>0 for <strong>the</strong> size <strong>of</strong> <strong>the</strong> neighbourhood. Therefore,
<strong>the</strong> overall dynamical properties <strong>of</strong> opinion formation are more complicated <strong>the</strong>n perhaps guessed
from <strong>the</strong>ir equations.
In simulations performed by Blondel et al. (2008), large numbers <strong>of</strong> agents generically evolve into a
small number <strong>of</strong> different opinions and do not depend on initial opinion distribution. In figure 3 opinion
formation simultaneously evolves <strong>the</strong> interconnection network between agents. Dense networks tend
to produce less final opinions and <strong>the</strong>ir final connectivity matrices - as <strong>the</strong> one shown in figure 3 (C) -
tend to differ less from initial matrices - as shown in figure 3 (A) - when <strong>the</strong> process is randomly
perturbed (not shown). In practice <strong>of</strong> e.g. client networks, innovation networks, etc., one would expect
more loosely coupled networks (like <strong>the</strong> ones <strong>of</strong> figure 3) or multiple networks (see Ahn et al. (2009)).
(A) (B) (C)
Figure 3: Simulated opinion formation with 40 individuals representing 40 different starting opinions
for a small neighborhood using w=0.047, i.e. in a sparse social network: (A) network matrix
for t=1, (B) emergence <strong>of</strong> seven final opinions at t=10, and (C) network matrix for t=10
Ano<strong>the</strong>r type <strong>of</strong> dynamic opinion formation process is described in Baronchelli et al. (2007). This model
for negotiation dynamics can move from an absorbing or stable consensus state (one final
opinion) into a situation <strong>of</strong> (potentially) an unlimited number <strong>of</strong> final opinions. Here, agents are
endowed with a memory, by means <strong>of</strong> which <strong>the</strong>y can store an unspecified (potentially very large)
number <strong>of</strong> opinions. The resulting opinion formation process exhibits vastly different convergence
times and, somewhat surprisingly, also a sharp phase transition from consensus to non-echilibrium,
i.e. <strong>the</strong> coexistence <strong>of</strong> very many opinions in <strong>the</strong> agent network. Both opinion formation and implicit
trust formation will be used for illustrative purposes in <strong>the</strong> next two sections.
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4. Leaning and IC formation in an extended eCommerce environment
The buying behaviour following an opinion formation process as exemplified in <strong>the</strong> previous section
can distinguish at least between a low product creativity equilibrium (emerging opinions with a low
scale, say), and a high product creativity equilibrium (emerging opinions opposite on <strong>the</strong> scale).
We propose to advance <strong>the</strong> notion that <strong>the</strong> transition from low to high creative equilibrium in <strong>the</strong>
textiles sector is connected to IC formation grounded on <strong>the</strong> evolution <strong>of</strong> favourable opinions about
smart textiles within multiple user communities. Such consensus formation is based on successful
trust formation between community members. Trust formation stands for a very important sub-process
<strong>of</strong> social capital formation: Without trust both <strong>the</strong> efficiency and <strong>the</strong> predictive correctness <strong>of</strong> learning
using mechanisms <strong>of</strong> indirect democracy would be hard to explain (i.e. that <strong>of</strong> ballots to markets and
prediction markets, Rodriguez and Watkins (2007)).
IC may attract financial capital but is not doing so automatically. IC may be contrasted to financial
capital in being much more difficult to transfer. In a conceptual breakdown IC may be viewed as a
(collective) capacity <strong>of</strong> formulating and resolving complex classification problems. These problems
provide answers to focused what to do? questions in complicated and <strong>of</strong>ten dynamic environments.
IC may thus be related in a more formal way to co-evolutionary learning processes, which both
propose and solve classification problems using any mixture <strong>of</strong> supervised learning (using examples
or a teacher) and unsupervised learning (using a critic). Successful learning implies that clusterings <strong>of</strong>
entities (products, technologies, persons, markets, concepts, etc.) are
Mutually exclusive, indicating how to react next,
Semi-overlapping (vague, fuzzy), indicating what mixed solutions to apply or
Predicting correlated outputs or are multi-labeled, indicating i.e. what sequences <strong>of</strong> action to
follow,
and that <strong>the</strong>y can be found in reasonable time and at reasonable costs. The shapes <strong>of</strong> <strong>the</strong>se clusterings
are determined by <strong>the</strong> specific goals which co-evolve within <strong>the</strong> learning process. Hence, IC
should be well contrasted to Intellectual Repositories, which potentially supply answers to many more
problems, without however focusing on any temporary, contextual, commercial, etc., relevance.
Learning relevant things can assume a form <strong>of</strong> “learning by doing”, where <strong>the</strong> result (success) <strong>of</strong> learning
is a function <strong>of</strong> past action i.e. <strong>of</strong> production (or <strong>of</strong> consumption), which can give rise to power
law relationships between unit cost (or utility) and cumulated action. Learning can also be a function
<strong>of</strong> time passed since <strong>the</strong> initial production efforts, in <strong>the</strong> sense that learning effects cannot be concentrated
into arbitrarily short time spans. A similar argument holds true for forgetting and for unlearning
(on consumption in networks see Wu and Huberman (2007)). The contextual relevance is enforced by
learning within concrete societal environments:
Learning how to cooperate and how to overcome excessive rivalry,
Learning how to identify and use complementarities in order to stimulate <strong>the</strong> use <strong>of</strong> risky
innovations,
Learning how to classify and to predict with better information about <strong>the</strong> types <strong>of</strong> uncertainties
involved and
Learning how to run application specific scenario evolutions.
In more recent times, o<strong>the</strong>r important aspects <strong>of</strong> innovation processes such as innovation contests
and social innovation are increasingly considered. Two premises lead to <strong>the</strong> growing relevance <strong>of</strong> this
type <strong>of</strong> innovation procedures:
In certain product classes and markets it becomes increasingly difficult to "forecast by expert
opinion" what consumers really like.
Organizational setup and transaction costs decrease dramatically with <strong>the</strong> spread <strong>of</strong> <strong>the</strong> internet
and <strong>of</strong> different types <strong>of</strong> social forum subnets.
While in general such approaches are clearly useful for automated marketing and forecasting
procedures as described in Schebesch et al. (2010), <strong>the</strong>re is mounting evidence that <strong>the</strong>y can and
should be applied (with adaptations) for innovation processes too, as is outlined in Terwiesch and Xu
(2008). The results <strong>of</strong> an innovation contest may be a process or a product innovation (figure 4, lower
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Klaus Bruno Schebesch
rhs process components). The innovation contest requires designing and evaluating a competition for
new solutions <strong>of</strong> posted problems amongst a large number <strong>of</strong> participants originating from a larger
societal context. In order to make <strong>the</strong>se contests more efficient and more credible (i.e. to enhance
serious participation), such innovation contests have to be designed to encompass two or more
stages, with appropriate mechanisms for picking winners and for paying out prices for attractive or
promising solutions. The outcomes <strong>of</strong> such innovation contests may contain also additional information,
for instance with regard to acquaintance with and challenges caused by using sustainable
processes and products, i.e. information about <strong>the</strong> degree <strong>of</strong> empathy and goodwill present in a wider
population with regard to new product concepts, issues <strong>of</strong> sustainability and more.
A fur<strong>the</strong>r detail <strong>of</strong> figure 4 is <strong>the</strong> process item called knowledge platform. On knowledge and
innovation see Tödtling et al. (2009). While it would be certainly desirable to evolve such a knowledge
platform, <strong>the</strong>re is to this day no compelling procedure concerning <strong>the</strong> efficient collection <strong>of</strong> information
about all <strong>the</strong>se sub-processes <strong>of</strong> innovation and how this relates to IC.
Figure 4: Innovation processes: innovation contests and technological interrelatedness. A high resolution
postscript version can be obtained from <strong>the</strong> author
Figure 5 depicts <strong>the</strong> real-life feedback loops, which contribute to IC formation. The figure distinguishes
two contexts, namely markets and a background <strong>of</strong> social networks with agents which may - but in
general do not - belong to <strong>the</strong> markets. As innovation processes unfold, firms start a process <strong>of</strong>
(mutual) trust formation, which results in trust scores, i.e. determining to what extend should firm i
trust firm j. The evolution <strong>of</strong> trust scores is using information from <strong>the</strong> markets but also from <strong>the</strong>
background social networks <strong>of</strong> <strong>the</strong> firms. Trust scores are important in order to guide a behavioural
imitation or a technological adaptation process. High trust scores may be useful in branding and rebranding.
The eventually resulting reputation is an example <strong>of</strong> social capital, which contributes to a
more general assessment and valuation process indicated by <strong>the</strong> box Valuation systems <strong>of</strong> figure 5.
Both, <strong>the</strong> reputation mechanism and <strong>the</strong> evolving knowledge platform (see also figure 4) do not exert
an unconditional influence on market agents, and any possible effect may also be strongly delayed in
time. Finally, crowdsourcing by innovation contests, which also uses agents from outside <strong>the</strong> markets,
is also inherited from figure 4. Within <strong>the</strong> modelling boxes A-D we encounter opinion formation, which
may be used as template for behavioural or technological imitation as indicated e.g. in Martins and
Pereira (2008).
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Klaus Bruno Schebesch
We argue in favour <strong>of</strong> using adapted recommender systems with trust generation and also for
learning <strong>of</strong> how to use complementarities in products and technologies within highly collaborative
eCommerce procedures (Salakhutdinov et al. (2007), Abernethy et. al. (2009)). Trust formation and
recommender systems (Xiao and Benbasat (2007), Schebesch et al. (2010)) are explicit mechanisms,
which contribute to opinion formation in contexts like marketing and technology campaigns, in that
<strong>the</strong>y use more details about individuals. Recommender systems use matrices containing client and
product feature entries. A product is recommended to a client, if
The client is not aware <strong>of</strong> <strong>the</strong> product or did never buy / use <strong>the</strong> product,
There are scores from o<strong>the</strong>r clients concerning <strong>the</strong> very <strong>the</strong> product,
Meaningful recommendations stem from a cluster which contains <strong>the</strong> client, and
Only persons / organizations trustworthy to <strong>the</strong> client do participate in <strong>the</strong> recommendation.
Figure 5: Real-life feedback loops in social learning connected to aspects <strong>of</strong> innovation, branding,
and behavioural imitation, <strong>the</strong> boxes named by encircled letters A,B,C and D are are
modelling issues in <strong>the</strong>ir own right, a high resolution postscript version can be obtained
from <strong>the</strong> author
The cost <strong>of</strong> designing and operating a recommender system can be substantial. Finding good client
clusterings and empirically valid trust matrices can be expensive. Product score matrices may be
extremely sparse, indicating that most clients do not use most products. If one intends to recommend
new products based on smart textiles and if <strong>the</strong>se products did not produce as yet any scores from
clients, you may include wearing habits and electronic devices as auxiliary entries in order to start
with some surrogate data for <strong>the</strong> needed clusterization <strong>of</strong> clients. Such prelaunch forecasting <strong>of</strong>
products which are new to <strong>the</strong> market is a recurring topic in Marketing (Urban et al. (1996), Hoeffler
(2003), Natter et al. (2003)). Starting with new products based on smart textiles thus requires <strong>the</strong> use
<strong>of</strong> client similarities from o<strong>the</strong>r domains or markets and will have to rely more strongly on trust
between clients. Discovering <strong>the</strong> amount <strong>of</strong> trust new technologies and product designs are capable
to produce in a client population can be at least in principle enabled by means <strong>of</strong> providing incentives
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Klaus Bruno Schebesch
for clients to invest into prediction markets (by now a widely debated topic <strong>of</strong> experimental economics,
see Prediction Markets (2009)).
5. Trust-based cascaded opinion formation
A highly stylized but very robust producer-consumer opinion formation process is presented, which
mimics opinions with regard to a large list <strong>of</strong> options. As with future applications <strong>of</strong> smart textiles from
section 2, such options do not interrelate at early time steps. As time evolves, we assume that trust
increases between agents, albeit with different rates in different contexts. For simplicity, dynamic
effects <strong>of</strong> forgetting and unlearning are neglected here. As in section 3 we start out an opinion
formation process X ( i,
t)
> 0 over discrete time t = 0, 1,...,
T,
which we term opinion formation <strong>of</strong>
consumers. Next, we adjoin a second process Y ( i,
t)
> 0,
called opinion formation <strong>of</strong> producers,
which functions according to <strong>the</strong> same dynamic equations as process X . For simplicity we assume a
unidirectional dependence X ( Y ), which reflects a trust increase with those consumers which form
opinions in <strong>the</strong> vicinity <strong>of</strong> those evolved by <strong>the</strong> producers. The difference to <strong>the</strong> basic process described
in section 3 is how we determine <strong>the</strong> dynamic neigborhood <strong>of</strong> every agent. The index set
{ k( i)}
<strong>of</strong> every consumer i = 1,
2 X is now computed using a trust-based radius
(instead <strong>of</strong> constant radius w > 0 ), which partially depends on <strong>the</strong> match with <strong>the</strong> opinions evolved
by <strong>the</strong> producers j = 1,
2,...,
N and which evolves according to
N ,..., 0 ) , ( > t i W
Y
NY
XY∑
j = 1
( || X ( i,
t)
−Y
( j,
t)
|| < W )
W ( i,
t + 1)
= W ( i,
t)
+ W + W u
, with 1 >> W ( i,
0)
> 0,
X
with u(.) <strong>the</strong> unit function, which returns 1 if <strong>the</strong> argument is true and 0 o<strong>the</strong>rwise, and with <strong>the</strong>
parameters selected to be W X = 0.
5 and W XY = 0.
075.
The index set { h( j)} <strong>of</strong> every producer j is
updated by a trust-based radius V ( j,
t)
> 0,
which simply increases with time, namely
V ( j,
t + 1)
= V ( j,
t)
+ V , with 1 >> V ( j,
0)
> 0,
and with parameter V = 1.
5.
Y
If as assumed in <strong>the</strong> sequel, <strong>the</strong> starting opinions <strong>of</strong> <strong>the</strong> producers are a true
N N > )} 0 , ( { j Y
X
Y
{ X ( i,
0)},
subset <strong>of</strong> <strong>the</strong> starting opinions <strong>of</strong> <strong>the</strong> consumers reflecting more focused information <strong>of</strong> <strong>the</strong>
producers. Figure 6 depicts an example <strong>of</strong> a cascaded opinion formation process, where <strong>the</strong> out-
Figure 6: An opinion formation process with a starting number <strong>of</strong> opinions <strong>of</strong> producers N Y = 15
(some are place in close vicinity to o<strong>the</strong>rs) and a starting number N X = 50 <strong>of</strong> consumer
opinions, consumer opinions are converging towards “creative” solutions represented by
higher ranking opinions on <strong>the</strong> scale. Less creative solutions (9 on <strong>the</strong> producers side) are
abandoned
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Y

Klaus Bruno Schebesch
come <strong>of</strong> <strong>the</strong> consumer opinions (right plot) depends on <strong>the</strong> outcome <strong>of</strong> <strong>the</strong> faster opinion formation
process <strong>of</strong> <strong>the</strong> producers. Nine opinions converge to an opinion representing a product solution with
lower creativity and six to a high creativity solution (left plot). On <strong>the</strong> consumer side (rhs plot), all opinions
tend towards nearby located high creativity solutions.
Figure 7 depicts a process with <strong>the</strong> same consumer starting opinions and <strong>the</strong> same parameters for
both processes, but with more starting opinions on <strong>the</strong> producer side. Two converging producer
opinions occur with slightly less original opinions (11 out <strong>of</strong> 30, or 36%) now representing <strong>the</strong> more
creative solution. The consumers retain two distant extreme opinions (originating from 11 and 13
starting opinions, respectively), while a slight majority <strong>of</strong> different initial opinions tend towards opinions
representing medium creativity. In a distant future <strong>the</strong> opinions will eventually fuse into some intermediate
opinion value, somewhat below <strong>of</strong> that <strong>of</strong> <strong>the</strong> final opinion <strong>of</strong> <strong>the</strong> process from figure 6.
Figure 7: An opinion formation process with <strong>the</strong> same parameters as that <strong>of</strong> figure 6 except an increased
number <strong>of</strong> starting opinions <strong>of</strong> producers N = 30.
Generically, <strong>the</strong> qualitative properties <strong>of</strong> this cascaded opinion formation process are very stable with
regard to changes in <strong>the</strong> parameters and also with regard to smaller changes <strong>of</strong> initial opinion distribution
<strong>of</strong> both processes. There are, however, critical parameter ranges over which abrupt qualitative
changes occur, e.g. in <strong>the</strong> number and position <strong>of</strong> final agent opinions (not shown). Connecting such
trust-based opinion formation to design and recommender processes is ongoing research.
6. Conclusion and outlook
Smart textiles <strong>of</strong>fer many opportunities for reviving and reformulating <strong>the</strong> traditional industrial textile
sector. However, <strong>the</strong> diversity <strong>of</strong> potential applications <strong>of</strong> smart textiles and <strong>the</strong> uncertain outcome <strong>of</strong>
<strong>the</strong>se alternatives flattens <strong>the</strong> success probability distribution <strong>of</strong> pertinent investments considerably.
Buying behaviour regarding wearable clo<strong>the</strong>s incorporating smart textiles remains extremely uncertain
and, hence, different aspects <strong>of</strong> learning to cooperate, especially by means <strong>of</strong> discovering and
exploiting complementarities may be in order. A conceptual process formulation including recommender
systems, trust formation, innovation contests, crowdsourcing and prediction markets illustrates
this and highlights <strong>the</strong> learning loops which may lead to enhanced IC formation is displayed in section
4.
Learning is about avoiding mistakes, about acquiring <strong>the</strong> ability to forecast, about memorizing and
forgetting but also about a wide array <strong>of</strong> collective actions like reaching agreements, and about <strong>the</strong>
ability <strong>of</strong> conducting collaborative problem solving, as e.g. Biely et al. (2008) illustrate how to solve a
stylized generic co-evolving economic system, a solution <strong>of</strong> which is minimizing <strong>the</strong> costs <strong>of</strong> operating
a network <strong>of</strong> agents. Both improved network connectivity and agent activity can be learned, e.g. by
determining coalitions between agents via cost minima, see e.g. Schebesch and Someşan (2008).
Finally, a highly stylized but very robust producer-consumer opinion formation process is presented in
section 5. This process evolves opinions with regard to a large list <strong>of</strong> product options, which do not
interrelate at early times, as would be <strong>the</strong> case with <strong>the</strong> manifold smart textile designs. However, such
opinions adapt over time by increasing trust between agents.
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Klaus Bruno Schebesch
In future work, such cascaded opinion formation will be related to recommender-like systems, which
are able to identify hub-consumers from large client data bases or client networks in order to boost
opinion convergence and eventually sales. Their success relates in turn to successful IC formation, in
that producers and consumers collectively learn to prefer product concepts and products which
embody high levels <strong>of</strong> creativity.
References
Abernethy, J., Bach, F.R., Evgeniou, T. and Vert, J.-P. (2009) “A new approach to collaborative filtering:
Operation estimation with spectral regularization”. Journal <strong>of</strong> Machine Learning Research, Vol.10, pp803-
826
Advanced Materials (2007) “Smart and Interactive Textiles”, online at
http://www.bccresearch.com/report/AVM050B.html
Ahn, Y.-Y., Bargow, J., and Lehmann, S. (2009): Communities and Hierarchical Organization <strong>of</strong> Links in Complex
Networks, posted 18 March 2009, online at http://arXiv:0903.3178v1
Baronchelli, A., Dall’Asta, L., Barrat, A. and Loreto, V. (2007): ”Non-echilibrium phase transition in negotiaion
dynamics”, posted 23 July 2007, online at http://arXiv:0611.717v2
Baurley, S. (2006) “Design + Smart Materials Bazaar, 19th & 20th September 2006”, Central Saint Martins
College <strong>of</strong> Art and Design, Science Museum and Dana Centre, London, 61pp
Biely C., Hanel, R., and Thurner, S. (2008): „Socio-economical dynamics as a solvable system on co-evolving
networks”, posted 26 Sept 2008, Online at http://arXiv:0707.3085v3
Blondel, V.D., Hendrickx, J.M. and Tsitsiklis, J.N. (2008): ”On Krause’s consensus model with state-dependent
connectivity”, posted 13 July 2008, online at http://arXiv:0807.2028v1
Byrne, C. (2007) “Textiles and clothing - The scope <strong>of</strong> technical textiles”, at
http://smartextiles.co.uk/overview/application/textiles-clothing/
Hoeffler, S. (2003) “Measuring preferences for really new products”, Journal <strong>of</strong> Marketing Research,
40(November), 406-420
Krause, U. (2000) “A discrete nonlinear and non-autonomous model <strong>of</strong> consensus formation”. Communications in
Difference Equations, pp 227-236
Natter, M., and Mild, A. (2003) DELI: An interactive new product development tool for <strong>the</strong> analysis and evaluation
<strong>of</strong> market research data. Journal <strong>of</strong> Targeting, Measurement, and Analysis for Marketing, 12(1), pp43-52
Ohmatex (2007) White Paper on Smart Textiles, at http://www.docin.com/p-56702031.html
Prediction Markets (2009) at http://www.midasoracle.org/predictions/s<strong>of</strong>tware/
Salakhutdinov, R., Minh, A. and Hinton, G. (2007) “Restricted Boltzmann machines for collaborative filtering”. In
<strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 24 th International <strong>Conference</strong> on Machine Learning, pp791-295
Schebesch, K.B., Pop, N. Al., and Pelău, C. (2010) A New Paradigm in Contemporary Marketing – Computational
Marketing, Romanian Journal <strong>of</strong> Marketing Vol. 1, pp 36-74
Schebesch, K.B. and Someşan, C. (2008): “Activity internationalization and Innovation in SME: Searching Building
Blocks for Rating Models”, published by <strong>the</strong> ECEI 2008 <strong>Proceedings</strong>, 15-16 September, Winchester,
UK
Tödtling, F., Lehner, P. and Kaufmann, A. (2009): ”Do different types <strong>of</strong> innovation rely on specific kinds <strong>of</strong>
knowledge interaction?”, Technovation 29, pp59-71
Urban, G.L., Weinberg, B.D. and Hauser, G.R. (1996) “Prelaunch forecasting <strong>of</strong> really new products”. Journal <strong>of</strong>
Marketing Vol.60, pp47-60
Wu, F. and Huberman, B.A. (2007) “Novelty and collective attention”, PNAS Vol.105,45 pp17599-17603
Xiao, B., and Benbasat, I. (2007) “ eCommerce product recommendation agents: use, characteristics, and impact.
MIS Quarterly”, 31(1), pp137-209
409

In Search <strong>of</strong> key Factors for Ideal Research and Education
Projects
Karen Smits, Ilse van den Donker and Josephine Lappia
Hogeschool Rotterdam, The Ne<strong>the</strong>rlands
K.Smits@hro.nl
I.van.den.Donker@hro.nl
J.H.Lappia@hro.nl
Abstract: This paper investigates key factors for ideal research and education projects in <strong>the</strong> context <strong>of</strong> <strong>the</strong>
Rotterdam University <strong>of</strong> Applied Sciences. The project can be seen as knowledge productive activities. The
competitive importance <strong>of</strong> positive effects on knowledge processes such as knowledge creation, knowledge
exchange and pr<strong>of</strong>essional development is emphasized by many Western countries. For research centres within
Dutch universities <strong>of</strong> applied sciences it became recently necessary to report on <strong>the</strong>se knowledge processes
periodically to an external review committee. So it is important to investigate whe<strong>the</strong>r research and pr<strong>of</strong>essors,
who are familiar since 2002 within universities <strong>of</strong> applied science, indeed have a positive impact on pr<strong>of</strong>essional
development and curriculum innovation. This is <strong>the</strong> most important reason for funding by <strong>the</strong> national
government. Although policy considers <strong>the</strong> main concepts pr<strong>of</strong>essional development and curriculum innovation to
be interrelated, not many is written about <strong>the</strong> research questions which key factors have an impact on <strong>the</strong>m and
which conditions can ensure <strong>the</strong>m. So a qualitative exploratory research approach is chosen. Using a method <strong>of</strong>
inquiry by collecting narratives among sixteen lecturers involved in ideal research and eduction projects. The
interviews were audiotaped and transcribed. Transcripts were analysed by means <strong>of</strong> open coding using <strong>the</strong>
program Atlas ti. What was striking was that concepts were not unambiguous to <strong>the</strong> lecturers. Grounded in <strong>the</strong>ir
narratives three levels <strong>of</strong> pr<strong>of</strong>essional development and three levels <strong>of</strong> curriculum development appeared from
<strong>the</strong> data. The correlation <strong>of</strong> both concepts resulted in nine categories that perfectly fit <strong>the</strong> sixteen narritives.
Although <strong>the</strong> number <strong>of</strong> interviewees was not large, and <strong>the</strong>refore necessary to exercise care in drawing
conclusions, some interesting conclusions can be drawn. In <strong>the</strong> experiment category interviewees do not appear
to be able to exchange information on <strong>the</strong>ir experiment with o<strong>the</strong>rs. As soon as <strong>the</strong>y did succeed in sharing
information <strong>the</strong>y stated that <strong>the</strong>y contributed to <strong>the</strong> pr<strong>of</strong>essional development <strong>of</strong> o<strong>the</strong>r lecturers. The paper
reveals several key factors that play a role in research that have an impact on education projects. Also important
conditions are found that ensure knowledge processes to appear. The grounded model that was found gives an
idea how Intellectual Capital and IC dynamics interacts for lectures involved in ideal research projects.
Never<strong>the</strong>less research centres do not yet appear to occupy <strong>the</strong> position in education which <strong>the</strong>y ought to have.
Keywords: pr<strong>of</strong>essional development, curriculum innovation, universities <strong>of</strong> applied sciences, appreciative
inquiry, grounded <strong>the</strong>ory, IC dynamics
1. Importance <strong>of</strong> <strong>the</strong> research for pr<strong>of</strong>essional development and curriculum
innovation
In many Western countries, <strong>the</strong> competitive importance <strong>of</strong> positive effects on knowledge processes,
such as knowledge creation, knowledge exchange and pr<strong>of</strong>essional development, is emphasised.
This is certainly <strong>the</strong> case when it is possible to show that <strong>the</strong>se knowledge processes <strong>of</strong> a learning
organisation improve <strong>the</strong> primary process and product. Within Dutch universities <strong>of</strong> applied sciences,
it has been necessary since 2009 to report periodically and publicly to an external review committee
on <strong>the</strong>se knowledge processes, at least where this relates to <strong>the</strong> activities <strong>of</strong> research centres. It is
obligatory to report annually on several central key figures, such as: <strong>the</strong> number <strong>of</strong> pr<strong>of</strong>essors,
lecturers involved in research and support staff; and <strong>the</strong> number <strong>of</strong> FTE, expenditure on research and
supplementary income which research centres acquire from second and third-stream funding.
Pr<strong>of</strong>essors and research centres are phenomena which have characterised <strong>the</strong> universities <strong>of</strong> applied
sciences since 2002 and have increased rapidly since <strong>the</strong>n. The introduction <strong>of</strong> pr<strong>of</strong>essors and <strong>the</strong>
obligation which universities <strong>of</strong> applied sciences have to carry out applied research are considered to
be amongst <strong>the</strong> successful innovations in education <strong>of</strong> recent decades.
The impact <strong>of</strong> research and pr<strong>of</strong>essors on <strong>the</strong> education provided by universities <strong>of</strong> applied sciences
has been <strong>the</strong> most important reason for universities <strong>of</strong> applied sciences to appoint pr<strong>of</strong>essors and for
<strong>the</strong> Ministry <strong>of</strong> Education, Culture and Science to provide funding for this. It was thought that research
would raise education to a higher level and would equip students better as pr<strong>of</strong>essional practitioners
at <strong>the</strong> start <strong>of</strong> <strong>the</strong>ir careers. It is <strong>the</strong>refore a national objective that <strong>the</strong> research centres should make a
contribution to curriculum innovation within education and to <strong>the</strong> pr<strong>of</strong>essional development <strong>of</strong>
lecturers.
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Karen Smits et al.
The following characteristics <strong>of</strong> ideal research projects can be derived from <strong>the</strong> national objectives <strong>of</strong>
research centres:
Knowledge creation occurs on <strong>the</strong> instructions <strong>of</strong>, in close cooperation with, and by employers;
The results are exchanged (or even developed) with external stakeholders like employers, who
also make funds available for this;
Lecturers who are involved in research increase <strong>the</strong>ir pr<strong>of</strong>essional competence by carrying out
applied research;
The quality <strong>of</strong> bachelor's and master's education (e.i. primary process) receives a boost, as a
result <strong>of</strong> which students are better prepared as pr<strong>of</strong>essional practitioners at <strong>the</strong> start <strong>of</strong> <strong>the</strong>ir
careers.
From this definition can be derived that ideal research projects within <strong>the</strong> intellectual capital literature
can be classified as knowledge productive activities in <strong>the</strong> sense that <strong>the</strong> organization (universities <strong>of</strong>
applied sciences) create a workplace that enables knowledge production through learning (Stam,
2007). It seems that within ideal research projects in a certain way human capital, structural capital
and relational capital (Bontis, 2002) enhances eacho<strong>the</strong>r and are leading to innovation, whe<strong>the</strong>r it is
radical or incremental innovation.
However, up until now it has been unclear what key factors in <strong>the</strong> past ensured that knowledge
production is realised that has any impact both on pr<strong>of</strong>essional practice and education. It is also
unclear what factors inhibit <strong>the</strong> fur<strong>the</strong>r impact <strong>of</strong> research on pr<strong>of</strong>essional practice and education in
<strong>the</strong> opinion <strong>of</strong> lecturers involved in research. The issue which is central to this research is <strong>the</strong>refore
formulated in <strong>the</strong> following question: How can research centres be more successful in ensuring that
good research results in good education? In short, how can research centres realise ideal research
projects, such as those described above, quicker?
The two questions which are <strong>the</strong>refore central to this paper are:
What are <strong>the</strong> key factors which result in research having an impact on education (that is,
curriculum innovation) and pr<strong>of</strong>essional development?
What are important conditions that have to be met to ensure that <strong>the</strong>se processes occur?
2. Research centres at Rotterdam University <strong>of</strong> Applied Sciences
This research into key factors is taking place within <strong>the</strong> context <strong>of</strong> <strong>the</strong> Rotterdam University <strong>of</strong> Applied
Sciences. Pr<strong>of</strong>essors have been appointed by <strong>the</strong> university since 2002. At present, <strong>the</strong>re are forty
pr<strong>of</strong>essors active in 24 research programmes. Its research programmes are currently concentrated in
six research <strong>the</strong>mes <strong>of</strong> strategic importance to <strong>the</strong> Rotterdam municipal region. The number <strong>of</strong>
lecturers involved in research who participate in <strong>the</strong>se research programmes increased by 20% from
109 lecturers to 131 lecturers between 2008 and 2009. In total around 6% <strong>of</strong> all lecturers are actively
involved in research and eduction projects. Rotterdam University <strong>of</strong> Applied Sciences has <strong>the</strong>
ambition <strong>of</strong> doubling <strong>the</strong> number <strong>of</strong> lecturers and students who participate actively in <strong>the</strong>se strategic
research <strong>the</strong>mes by 2015.
Within <strong>the</strong> context <strong>of</strong> <strong>the</strong> Rotterdam University <strong>of</strong> Applied Sciences, <strong>the</strong>re are considerable differences
in <strong>the</strong> extent to which pr<strong>of</strong>essors and lecturers involved in research are successful in ensuring that
<strong>the</strong>ir research has an impact on <strong>the</strong> education <strong>of</strong>fered by <strong>the</strong> institute in which <strong>the</strong> research centre is
located. Research centres differ with regard to <strong>the</strong> duration <strong>of</strong> <strong>the</strong>ir activities. Some research centres
have been active for eight years. O<strong>the</strong>r research centres have only recently started <strong>the</strong>ir activities. It is
not known how <strong>the</strong> more successful research centres managed to interact successfully with issues
arising from pr<strong>of</strong>essional practice and <strong>the</strong> needs <strong>of</strong> education, and how such successful interaction
resulted in curriculum innovation and <strong>the</strong> pr<strong>of</strong>essional development <strong>of</strong> lecturers.
3. The search for success stories on ideal research and education projects
with an applied and positive approach to research
Research into <strong>the</strong> key factors which play a role in ensuring <strong>the</strong> successful impact <strong>of</strong> research on
education (that is, curriculum innovation) and pr<strong>of</strong>essional development is carried out on <strong>the</strong> basis <strong>of</strong>
<strong>the</strong> narratives <strong>of</strong> lecturers involved in research. It relates to situations in which curriculum innovation
and/or pr<strong>of</strong>essional development played a role and in which <strong>the</strong>y are satisfied with <strong>the</strong>ir own
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contribution, with that <strong>of</strong> <strong>the</strong>ir colleagues from <strong>the</strong> research centre who were involved, with that <strong>of</strong> <strong>the</strong>
institute and with that <strong>of</strong> <strong>the</strong> students. From <strong>the</strong>se narratives, <strong>the</strong> key factors are distilled which can be
reused by o<strong>the</strong>r members <strong>of</strong> <strong>the</strong> research centre. Since <strong>the</strong> research centres are still under
development and are being built, <strong>the</strong> aim is to develop a common language which will make it
possible to communicate about and report on <strong>the</strong>se knowledge processes. Once one is aware, as a
lecturer involved in research or as a university <strong>of</strong> applied sciences, <strong>of</strong> <strong>the</strong> factors which are important
for ensuring <strong>the</strong> succesful impact on education <strong>of</strong> research, this impact will presumably occur earlier
or be achieved more easily.
3.1 Research approach
The aim is to ensure that <strong>the</strong> list <strong>of</strong> key factors can be used in drawing up research plans for <strong>the</strong>
research centres. It is also possible that <strong>the</strong> research may detect patterns in <strong>the</strong> key factors. As such,
<strong>the</strong> research is an initial scan <strong>of</strong> <strong>the</strong> question <strong>of</strong> how key factors which play a role in curriculum
innovation and pr<strong>of</strong>essional development are interrelated. Since little has been written about this
research question in existing literature, a form <strong>of</strong> qualitative exploratory research was chosen. Using
<strong>the</strong> method <strong>of</strong> Grounded Theory (Strauss, 1994; Strauss & Corbin, 1997), <strong>the</strong> concepts to be
researched were considered broadly because it was not possible at <strong>the</strong> outset to conclude what
categories and factors within <strong>the</strong> research <strong>the</strong>mes would be relevant.
3.2 Interviewees
A group <strong>of</strong> approximately 75 lecturers structural involved in research, who participate in <strong>the</strong> research
<strong>of</strong> research centres, were asked whe<strong>the</strong>r <strong>the</strong>y would be willing to share <strong>the</strong>ir narratives with us.
Ultimately 16 lecturers involved in research participated in this on a voluntary basis. This group <strong>of</strong> 16
lecturers involved in research consisted <strong>of</strong> 11 women and five men in <strong>the</strong> age category ranging from
<strong>the</strong> mid-30s to <strong>the</strong> late 50s. Most <strong>of</strong> <strong>the</strong> participants had been employed by <strong>the</strong> university in lecturing
positions for a long time. Three employees had been employed for a shorter period (from several
months to several years, but less than three years). Although <strong>the</strong> lecturers involved in research who
participated came from numerous sectors, <strong>the</strong> social and medical sectors were overrepresented in <strong>the</strong>
research.
3.3 Method <strong>of</strong> inquiry and data collection
The lecturers involved in research interviewed each o<strong>the</strong>r using <strong>the</strong> Appreciative Inquiry interview
method. Appreciative Inquiry is an approach to <strong>the</strong> areas <strong>of</strong> both organisational analysis and
organisational learning which focuses on discovering, understanding and promoting innovation.
Appreciative Inquiry combines <strong>the</strong> search for knowledge and an intentional group activity, so that <strong>the</strong>
will <strong>of</strong> a group and <strong>the</strong> vision <strong>of</strong> <strong>the</strong> organisation become clear as one integrated whole. The art <strong>of</strong>
appreciation is <strong>the</strong> art <strong>of</strong> discovering those factors which give life to a group or an organisation. The
process includes holding interviews with a large percentage <strong>of</strong> those involved in order to analyse that
which is best from <strong>the</strong> past and in order to be able to visualise what might occur in <strong>the</strong> future. In its
most practical meaning, Appreciative Inquiry is a form <strong>of</strong> organisational research which attempts in a
very focused way to localise and explain what <strong>the</strong> living forces are which form <strong>the</strong> foundation <strong>of</strong> <strong>the</strong>
existence <strong>of</strong> an organisation (Cooperrider, Sorensen, Whitney & Yaeger, 2000: Cooperrider &
Withney, 1999). Wi<strong>the</strong>y, Trosten-Bloom and Rader (2010) recently published a book on Appreciative
Leadership, which describes how one can bring to <strong>the</strong> surface <strong>the</strong> best in people and organisations
after this phase <strong>of</strong> appreciative inquiry with <strong>the</strong> use <strong>of</strong> four o<strong>the</strong>r knowledge processes, and how one
can manage one's organisation actively and deliberately in order to achieve results.
3.4 Method <strong>of</strong> data analysis
The interviews had a duration <strong>of</strong> 45 minutes agreed beforehand and were recorded using audio
equipment. Transcripts were made from <strong>the</strong> audio recordings. The transcripts were <strong>the</strong>n analysed by
means <strong>of</strong> open coding using <strong>the</strong> program Atlas Ti. A summary was made <strong>of</strong> every narrative in which
<strong>the</strong> interviewees' narrative was constructed and <strong>the</strong> factors which had an effect were identified.
4. Results
On <strong>the</strong> basis <strong>of</strong> <strong>the</strong> <strong>the</strong>mes which were central to <strong>the</strong> narratives and on <strong>the</strong> basis <strong>of</strong> <strong>the</strong> literature
which assumed a correlation between <strong>the</strong> two research <strong>the</strong>mes, <strong>the</strong> narratives were analysed with
regard to both pr<strong>of</strong>essional development and curriculum innovation.
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What was striking first <strong>of</strong> all in <strong>the</strong> narratives was that <strong>the</strong> interviewees' opinions on <strong>the</strong> concepts <strong>of</strong>
pr<strong>of</strong>essional development and curriculum innovation were not unambiguous. The source which
inspired <strong>the</strong> interviewees to undertake pr<strong>of</strong>essional development appears to be intrinsic to some <strong>of</strong>
<strong>the</strong> respondents. O<strong>the</strong>rs stressed examples <strong>of</strong> <strong>the</strong> way in which <strong>the</strong>y had attempted to assist o<strong>the</strong>r
lecturers in <strong>the</strong>ir pr<strong>of</strong>essional development and were enthusiastic about this.
The variation which we discovered in relation to pr<strong>of</strong>essional development appears to relate to <strong>the</strong>
level <strong>of</strong> pr<strong>of</strong>essional development discussed. The following three levels <strong>of</strong> pr<strong>of</strong>essional development
emerged from <strong>the</strong> coding <strong>of</strong> <strong>the</strong> respondents' narratives:
One's own pr<strong>of</strong>essional development. By this we understand lecturers involved in research who
mentioned that <strong>the</strong>ir primary aim in carrying out research or a project was <strong>the</strong>ir own pr<strong>of</strong>essional
development.
Creating a basis <strong>of</strong> support amongst colleagues. By this we understand <strong>the</strong> lecturers involved in
research who undertook activities to draw <strong>the</strong> attention <strong>of</strong> <strong>the</strong>ir colleagues to (<strong>the</strong> results <strong>of</strong>) <strong>the</strong>ir
project.
Active participation in <strong>the</strong> pr<strong>of</strong>essional development <strong>of</strong> colleagues. We understand by this
lecturers involved in research who undertook activities with <strong>the</strong> explicit objective <strong>of</strong> involving <strong>the</strong>ir
colleagues in <strong>the</strong>ir project or to contribute, for instance, to <strong>the</strong> fur<strong>the</strong>r development <strong>of</strong> <strong>the</strong>ir
colleagues' research skills.
Of those interviewed, four interviewees appeared to have worked mainly on <strong>the</strong>ir own personal
development. In addition, four interviewees worked on obtaining support from colleagues. Eight
interviewees were also active in <strong>the</strong> pr<strong>of</strong>essional development <strong>of</strong> o<strong>the</strong>rs. Some interviewees who
were active at <strong>the</strong> first or second levels <strong>of</strong> pr<strong>of</strong>essional development also had <strong>the</strong> ambition <strong>of</strong> actively
contributing to <strong>the</strong> pr<strong>of</strong>essional development <strong>of</strong> o<strong>the</strong>rs.
4.2 Curriculum innovation
With regard to <strong>the</strong> <strong>the</strong>me <strong>of</strong> curriculum innovation, we also discovered that <strong>the</strong> variation in curriculum
innovation can be subdivided into three distinct levels:
The experiment. By this we understand lecturers who are involved in research and who are
involved in projects which do not constitute a permanent part <strong>of</strong> <strong>the</strong> <strong>of</strong>ficial curriculum. Most <strong>of</strong>
<strong>the</strong>se projects were initiated by <strong>the</strong> lecturer involved in <strong>the</strong> research.
Curriculum innovation which is not yet embedded. By this, we understand <strong>the</strong> results <strong>of</strong> projects
undertaken by lecturers involved in research which have resulted in innovation in (<strong>the</strong> contents <strong>of</strong>)
education, where <strong>the</strong> continuity <strong>of</strong> this new education depends on <strong>the</strong> lecturer involved in <strong>the</strong>
research or where <strong>the</strong> new education has not yet been implemented.
Embedded curriculum innovation. By this we understand new education which has been
implemented for several years in <strong>the</strong> curriculum and whose implementation does not depend
solely on <strong>the</strong> lecturer involved in <strong>the</strong> research who developed it.
Of <strong>the</strong> interviewees, five were primarily active at <strong>the</strong> level <strong>of</strong> <strong>the</strong> experiment. Five interviewees were
active at <strong>the</strong> level <strong>of</strong> curriculum innovation which was not yet embedded. Six interviewees were active
at <strong>the</strong> level <strong>of</strong> embedded curriculum innovation. In this case, time was also a factor which played a
role. As a result, this distribution may be entirely different in five years' time because <strong>the</strong> respondents
at <strong>the</strong> first two levels have <strong>the</strong> ambition <strong>of</strong> raising <strong>the</strong>ir activities to <strong>the</strong> next level.
4.3 Correlation between pr<strong>of</strong>essional development and curriculum innovation
Since three levels emerged from <strong>the</strong> coding in relation to both pr<strong>of</strong>essional development and
curriculum innovation and both <strong>the</strong>mes presumably bear some correlation to each o<strong>the</strong>r on <strong>the</strong> basis
<strong>of</strong> <strong>the</strong> literature, we have linked both research <strong>the</strong>mes, which has resulted in a table consisting <strong>of</strong> nine
categories (see Table 1). Only one category was left empty. Although <strong>the</strong> number <strong>of</strong> interviewees was
not large, and it is <strong>the</strong>refore necessary to exercise care in drawing conclusions, an interesting
conclusion can be drawn. In <strong>the</strong> experiment category, <strong>the</strong> interviewees do not appear to be able to
exchange information on <strong>the</strong>ir experiment with o<strong>the</strong>rs. As soon as <strong>the</strong>y did succeed in sharing
information, <strong>the</strong>y stated that <strong>the</strong>y had contributed to <strong>the</strong> pr<strong>of</strong>essional development <strong>of</strong> o<strong>the</strong>rs.
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Table 1: Correlation between pr<strong>of</strong>essional development and curriculum innovation has resulted in
nine categories <strong>of</strong> ideal research and education projects
Curriculum innovation
Pr<strong>of</strong>essional
development
His/her own pr<strong>of</strong>essional
development
Also ensures <strong>the</strong>
development <strong>of</strong> support
amongst colleagues
Actively contributes to
<strong>the</strong> pr<strong>of</strong>essional
development <strong>of</strong> o<strong>the</strong>rs
Experiment Is part <strong>of</strong> <strong>the</strong> curriculum
but not yet embedded
Case IV
Case XV
Case II
Case VI
Case XIII
Embedded in <strong>the</strong>
curriculum
Case III Case V
Case I
Case XIV
Case X
Case XII
Case VIII
Case IX
Case VII
Case XI
Case XVI
If we consider <strong>the</strong> present situation and <strong>the</strong> future scenario which <strong>the</strong> interviewees sketched in some
situations, we see that many <strong>of</strong> <strong>the</strong> lecturers involved in research who were interviewed were keen to
shift from <strong>the</strong> top-left box (his/her own pr<strong>of</strong>essional development in relation to experimental education)
to <strong>the</strong> bottom-right box (embedded curriculum innovation with <strong>the</strong> effect <strong>of</strong> contributing to <strong>the</strong>
pr<strong>of</strong>essional development <strong>of</strong> o<strong>the</strong>rs).
4.4 Key factors in pr<strong>of</strong>essional development and curriculum innovation
From <strong>the</strong> sixteen narratives, many factors emerged which may make a contribution to pr<strong>of</strong>essional
development or curriculum innovation. We can deduce from this that <strong>the</strong>re are several key concepts
which are referred to by interviewees as key factors.
For instance, choosing a socially relevant topic seems to be important, according to various
interviewees.
Multidisciplinary cooperation may also be regarded as a factor which results in pr<strong>of</strong>essional
development and curriculum innovation. The respondents frequently stated that by cooperating with
numerous disciplines <strong>the</strong>y developed <strong>the</strong>mselves, students became more motivated and learned
more, and better results were achieved in <strong>the</strong> projects.
In addition, an inspiring pr<strong>of</strong>essor was <strong>of</strong> considerable importance, particularly if <strong>the</strong> pr<strong>of</strong>essor
regarded <strong>the</strong> relationship with education as important and stimulated this.
A number <strong>of</strong> interviewees referred to a culture in which <strong>the</strong> results were not immediately
circumscribed as very important. Respondents stated that <strong>the</strong>y learnt a lot from projects which ran
aground. The characteristic <strong>of</strong> projects which acquired a fixed place in <strong>the</strong> curriculum was that <strong>the</strong>y
<strong>of</strong>ten did not appear at all promising at an earlier stage.
A striking feature is that most interviewees fulfil a so-called 'linking-pin' function between research and
education because <strong>the</strong>y were involved in both teaching and research. This appeared to be successful,
in particular, in those situations where <strong>the</strong> lecturer involved in research could involve students whom
he or she was teaching in his or her own applied research. A characteristic <strong>of</strong> all <strong>the</strong> interviewees was
that <strong>the</strong>y were intrinsically motivated to do research and held views with regard to <strong>the</strong> future <strong>of</strong>
pr<strong>of</strong>essional practice and <strong>the</strong> position <strong>of</strong> <strong>the</strong>ir discipline within this. In addition, <strong>the</strong>y had opinions <strong>of</strong>
<strong>the</strong>ir own on <strong>the</strong> way in which students should be involved in this and how <strong>the</strong>y should acquire <strong>the</strong>
attitude to research which <strong>the</strong> lecturer felt was necessary. They stated that <strong>the</strong>y wished to teach
students not to look for solutions too quickly or to apply tools, but first to take time to consider <strong>the</strong>
problem in its natural environment, in <strong>the</strong> field, with a critical but open attitude (thinking 'out-<strong>of</strong>-<strong>the</strong>box').
Many <strong>of</strong> <strong>the</strong> interviewees attempt to inspire students and colleagues by setting an example.
Having or acquiring a large business network also appears to be important. As a result, students can
be involved more easily in applied assignments and guest lectures can be organised which are
mutually inspiring.
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4.5 Important preconditions for pr<strong>of</strong>essional development and curriculum innovation
In addition to <strong>the</strong> above-mentioned factors, a number <strong>of</strong> preconditions also appeared to be important.
Both <strong>the</strong> lecturer involved in research and his or her colleagues whose pr<strong>of</strong>essional development is to
be advanced benefit considerably from funding, in terms <strong>of</strong> time and budget. This aspect, if present,
emerged as a positive factor and, if absent, was experienced as an obstacle. This was certainly <strong>the</strong>
case if <strong>the</strong> lack <strong>of</strong> time involved colleagues whose support was sought or who participated in
pr<strong>of</strong>essional development activities to which <strong>the</strong> lecturer involved in research had made an active
contribution.
In all <strong>the</strong> narratives, sharing knowledge was raised as an important precondition. Sharing knowledge
appears to have been regarded as important and does not yet seem to be self-evident. Several
projects relate exclusively to sharing knowledge. It appears from <strong>the</strong> narratives that not all <strong>the</strong>
methods used for sharing knowledge were equally effective. The method <strong>of</strong> sharing knowledge which
is chosen depends on <strong>the</strong> lecturer involved in research as a person. What are <strong>the</strong> primary inclinations
<strong>of</strong> this lecturer involved in research? What methods for sharing knowledge does he or she regard as
<strong>the</strong> most congenial? Any experience <strong>of</strong> knowledge sharing in <strong>the</strong> research centre may play a role in
this. More experienced research centres have largely overcome <strong>the</strong> obstacles to knowledge sharing,
while relatively new research centres are still encountering <strong>the</strong>se. It does not appear to be self-evident
that <strong>the</strong>se good practices are accessible to every research centre. The interviewees concluded that a
culture <strong>of</strong> compartmentalisation existed which obstructed horizontal knowledge sharing.
The methods <strong>of</strong> knowledge sharing which <strong>the</strong> interviewees describe vary from informal to formal and
from traditional to innovative. For instance, informal support for a project is spontaneously generated
by discussions with colleagues at <strong>the</strong> c<strong>of</strong>fee machine, traditional and formal knowledge is shared by
publishing booklets in which <strong>the</strong> results <strong>of</strong> <strong>the</strong> project are presented in a manner which is visually
attractive and innovative knowledge sharing takes place using digital tools in <strong>the</strong> form <strong>of</strong> a virtual
knowledge sharing platform developed for students, lecturers and pr<strong>of</strong>essional practitioners.
From <strong>the</strong> narratives it emerges that who <strong>the</strong> client is is important. Sometimes <strong>the</strong> lecturer involved in
research is his or her own client. Cases such as this usually involve experiments and it is not always
easy to ascertain <strong>the</strong> effect on <strong>the</strong> curriculum in <strong>the</strong> case <strong>of</strong> <strong>the</strong> lecturer in question who is involved in
<strong>the</strong> research. Where <strong>the</strong> client is an education client, <strong>the</strong> effect on both pr<strong>of</strong>essional development and
curriculum innovation is considerable. This may be <strong>the</strong> result, for instance, <strong>of</strong> involving numerous
lecturers who teach on <strong>the</strong> programme in <strong>the</strong> project, who <strong>the</strong>n jointly give form to <strong>the</strong> curriculum
innovation. Curriculum innovation in this case may be more extensive than if <strong>the</strong> lecturer is his or her
own client because <strong>the</strong> obstacle noted frequently, namely that education always has priority above
research activities plays less <strong>of</strong> a role. In <strong>the</strong> case <strong>of</strong> an external client, <strong>the</strong> topics naturally have
social relevance, but <strong>the</strong> linking-pin position <strong>of</strong> <strong>the</strong> lecturer involved in research determines whe<strong>the</strong>r
<strong>the</strong> project can also be used to <strong>the</strong> benefit <strong>of</strong> education. Often in <strong>the</strong> case <strong>of</strong> larger projects, <strong>the</strong>
organisational relationship to education is complex and is achieved only with difficulty.
5. Conclusions and discussion
The research centres do not yet appear to occupy <strong>the</strong> position in education which <strong>the</strong>y ought to have
in order to fulfull <strong>the</strong>ir promising role in enhancing knowledge productive activities such as ideal
research projects. Various characteristics <strong>of</strong> <strong>the</strong> education organisation as <strong>the</strong> dominant primary
process are at odds with <strong>the</strong> interests <strong>of</strong> research as <strong>the</strong> upcoming second process and <strong>the</strong>refore
obstruct <strong>the</strong> added value which research projects may have for education. This relates, for instance,
to aspects <strong>of</strong> scheduling, as a result <strong>of</strong> which it is difficult to cooperate with o<strong>the</strong>rs and to determine
moments for consultation; to <strong>the</strong> fact that education has priority, as a result <strong>of</strong> which it is not possible
to meet <strong>the</strong> demands on time made by research and firm agreements on products from <strong>the</strong> education
organisation based on this argument cannot be fulfilled; to <strong>the</strong> fact that <strong>the</strong> view that research is <strong>of</strong>
importance to education has not yet gained acceptance everywhere; and to <strong>the</strong> fact that <strong>the</strong> way
education is organised is so lacking in flexibility that it is difficult to schedule in <strong>the</strong> research activities
<strong>of</strong> students within <strong>the</strong> education organisation. In addition, it is difficult for a lecturer who is involved in
research and who integrates educational and research tasks to fit into <strong>the</strong> organisation because <strong>the</strong>
problem arises as to 'Who pays for what, and how should this be accounted for?' As a result, an
employee who plays an exemplary role is suddenly treated as an organisational 'pain in <strong>the</strong> neck' for
whom everything has to be arranged differently. One interviewee also stated that large new research
projects are sometimes treated by <strong>the</strong> service structure <strong>of</strong> <strong>the</strong> education organisation in this way and
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Karen Smits et al.
staff feel that <strong>the</strong>y are compelled to find <strong>the</strong>ir own solutions outside existing procedures in <strong>the</strong> areas
<strong>of</strong>, for instance, facility services and administration.
The importance <strong>of</strong> <strong>the</strong> grounded model based on <strong>the</strong> correlation between pr<strong>of</strong>essional development
and curriculum innovation is that <strong>the</strong> nine categories <strong>of</strong> ideal research and education projects that are
found reveal <strong>the</strong> way <strong>the</strong> different parts <strong>of</strong> Intellectual Capital and IC dynamics may interact. When
lecturers succeed in <strong>the</strong>ir own learning (enhancing human capital), <strong>the</strong>n <strong>the</strong>y report to need or to
establish relational capital to exchange in a succesfull way <strong>the</strong>ir findings to o<strong>the</strong>r lecturers. Fur<strong>the</strong>ron
<strong>the</strong>y report to need <strong>the</strong> support <strong>of</strong> <strong>the</strong>ir management to implement <strong>the</strong>ir innovative practice as a
structural part <strong>of</strong> <strong>the</strong> curriculum to add to <strong>the</strong> structural capital <strong>of</strong> <strong>the</strong> organization. The findings <strong>of</strong> this
research project and <strong>the</strong>se stories will be researched fur<strong>the</strong>ron. The <strong>the</strong>oretical approach <strong>of</strong>
Intellectual Capital and IC dynamics is a promising one as it help to explain and forcast <strong>the</strong> way
human capital via relational capital leads to structural capital.
References
Bontis, N. (2002). Managing organizational knowledge by diagnosing Intellectual Capital. Framing and advancing
<strong>the</strong> state <strong>of</strong> <strong>the</strong> field. In: Bontis, N. & Choo, C.W. (Eds.), The strategic management <strong>of</strong> Intellectual Capital
and organizational knowledge (pp. 621 – 624). Oxford, New York: Oxford University Press.
Cooperrider, D.L., Sorensen, P.F., Whitney, D. and Yaeger, T.F. (2000). Appreciative Inquiry: Rethinking human
organization toward a positive <strong>the</strong>ory <strong>of</strong> change. Stipes, Champaign, Illinois.
Cooperrider, D. and Withney, D. (1999). In: Dewulf, L. and Verheije, L. (2004). Appreciative Inquiry: how inquiry
and change can flow toge<strong>the</strong>r. An interview with David Cooperrider (Appreciative Inquiry: hoe onderzoeken
en veranderen samen kunnen vallen. Een interview met David Cooperrider). In: Education & Development
(Opleiding & Ontwikkeling), No. 11, pp 23-26.
Stam, C. (2007). Knowledge productivity: designing and testing a method to diagnose knowledge productiviy and
plan for enhancement, Enschede, Twente University
Strauss, A.I. (1994). Qualitative Analysis for Social Scientists, Cambridge University Press, Cambridge/New York
Strauss, A.I. and Corbin, J. (1997). Grounded Theory in Practice, Sage, Thousand Oaks
Withney, D.W.and Trosten-Bloom, A. and Rader, K. (2010). Appreciative Leadership, McGRaw Hill, New York.
416

Intellectual Capital and <strong>the</strong> Romanian Education System
Marta-Christina Suciu, Luciana Picioruş, Cosmin Imbrişcă, Alexandru Ghitiu
Bratescu and Foksha Vitaly
Academy <strong>of</strong> Economic Studies, Bucharest, Romania
suciuchristina@yahoo.com
lusianapiciorus@yahoo.co.uk
imbrisca_c@yahoo.com
alexghitiu@yahoo.com
vfoksha@yahoo.com
Abstract: ‘Intangible Economy’ is <strong>the</strong> reality <strong>of</strong> today business world and <strong>of</strong> educational systems fulfilling a key
role in a knowledge-based society. Also <strong>the</strong>y are considered in connection with <strong>the</strong> evolution <strong>of</strong> decision making
and resources allocation processes at institutional level. This is why <strong>the</strong> research focused on <strong>the</strong> relationship
between intellectual capital, knowledge and ‘intellectual assets’ versus economic education, by analyzing <strong>the</strong>
tremendous changes in <strong>the</strong> Romanian education system. Offering an interdisciplinary perspective, <strong>the</strong> paper
tackles controversial and at <strong>the</strong> hour issues: role <strong>of</strong> intellectual capital and mostly <strong>of</strong> human capital; education
and intellectual capital measurement models to be used bearing in mind <strong>the</strong> high degree <strong>of</strong> uncertainty in <strong>the</strong>
Romanian educational system. Therefore, <strong>the</strong> subject <strong>of</strong> this paper is two-folded: examining <strong>the</strong> current state <strong>of</strong>
intellectual capital as reflected by <strong>the</strong> education system and providing a valid instrument for determining <strong>the</strong> value
<strong>of</strong> it in <strong>the</strong> future. According to <strong>the</strong> complexity <strong>of</strong> <strong>the</strong> topic, a multi-method combination is used as research
included both primary and secondary data, both qualitative and quantitative depending on <strong>the</strong> sources so that to
visibly contour <strong>the</strong> system as an entity. The paper approaches <strong>the</strong> matter historically, from reasoning for <strong>the</strong>
modern <strong>European</strong> educational system foundation to <strong>the</strong> present Romanian educational background, and from
economic perspective, introducing intellectual capital and human capital also in <strong>the</strong> equation. Fur<strong>the</strong>r on, a close
look is given to <strong>the</strong> crisis looming over <strong>the</strong> education system, focusing on <strong>the</strong> socio-economic aspects
specifically: sources and directions <strong>of</strong> financing, perceptions and vagueness <strong>of</strong> future evolutions in <strong>the</strong> role <strong>of</strong>
education. The findings refer to success and failure factors on an attempt to identify a proper intellectual capital
measurement model that may be applied in reducing uncertainty and increase competitiveness <strong>of</strong> human capital,
considering <strong>the</strong> characteristics <strong>of</strong> <strong>the</strong> actual Romanian education system.
Keywords: intellectual capital, knowledge-based society, education, lifelong learning
1. Introduction
In this era <strong>of</strong> knowledge, intangible resources come first and Intellectual Capital is <strong>the</strong> key to
organizational success. This concept includes various resources grouped in three categories:
relational (customer loyalty, quality <strong>of</strong> supply contracts, network, and strength <strong>of</strong> stakeholder support
or regulatory imposts), organisational (structural appropriateness, organizational reputation, know-
how, tacit knowledge, quality <strong>of</strong> corporate governance) and human capital components.
The last component, human capital, is a vital part; it includes management experience and quality,
employees’ skills, dexterity (physical, psychological and intellectual) and judgement, as Adam Smith
structured it, <strong>the</strong>ir loyalty and personal reputation. Human capital is essential for companies which
derive <strong>the</strong>ir pr<strong>of</strong>its from knowledge and innovation, market value being above <strong>the</strong> financial statements’
figures. But can also be applied to national economies.
The second topic, more controversial, is <strong>the</strong> link between intellectual capital, investments in human
capital and education on one hand, and increase in productivity, on <strong>the</strong> o<strong>the</strong>r hand, with significant
consequences for economic growth <strong>of</strong> nations. This logical approach to human capital and education
interaction <strong>of</strong>fers arguments for explaining <strong>the</strong> differences in wages on a competitive labour market
(Cowen, R., Kazamias, A. 2009, pp. 634) such as <strong>the</strong> <strong>European</strong> market. Also, it was recognized that,
over <strong>the</strong> last 30 years, <strong>the</strong> EU 15 members incurred economic growth.
Percentages differ from nation to nation, but common findings were made: education expenditure as
percentage <strong>of</strong> GNP was relatively constant over <strong>the</strong> entire period for all Member States; an increase
in human resources investments, and an ascendant trend in <strong>the</strong> number <strong>of</strong> population ready to enrol
in tertiary education; <strong>the</strong> vocational training area, though not generous in providing data, enjoyed
greater participation (Wilson, R. A., Briscoe, G. 2004). However, <strong>the</strong> relationship is not fully
established, though empirical evidences tend to confirm it.
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Marta-Christina Suciu et al.
This paper, starting from specific literature review, aims at <strong>of</strong>fering a general perspective over <strong>the</strong>
current and past state <strong>of</strong> intellectual capital, namely human capital in Romania and in <strong>the</strong> Romanian
education system. The second objective is to provide a suitable intellectual capital measurement
model- presently <strong>the</strong> Romanian education system does not use such an instrument nor a specific
intellectual capital reporting system implemented at national level. It is our intention to demonstrate
<strong>the</strong> need for such a tool and its overall significance. The method used includes both qualitative and
quantitative data, acquired through <strong>the</strong>oretical research and collecting information using a
questionnaire specifically designed, so that it led to a relevant model for evaluating intellectual capital
and stressing <strong>the</strong> connection between investments in human capital, education and economic growth.
2. Paradigm <strong>of</strong> <strong>the</strong> <strong>European</strong> education system
2.1 Past and present
Education has always played an essential role for individuals in <strong>the</strong>ir pr<strong>of</strong>essional development,
students and adults who have already accumulated consistent knowledge. Therefore, Lifelong
Learning comes to support permanent pr<strong>of</strong>essional evolution along <strong>the</strong> entire lifespan, helping <strong>the</strong>m
to cope with dramatic changes that currently take place due to globalization, new values and
economical crisis that transform long-lasting cultural and social hierarchies. But concepts like crisis
and economic growth go hand in hand in <strong>the</strong> New Economy where knowledge and innovation come
first in <strong>the</strong> knowledge company. Humans have to adapt and so do educational systems from all
around <strong>the</strong> world. However, this structural revolution appears ra<strong>the</strong>r natural coming under <strong>the</strong>
influences <strong>of</strong> strong social disagreements, increasing role <strong>of</strong> voluntary activities and non-pr<strong>of</strong>it
organizations, permanent search <strong>of</strong> new values, all <strong>of</strong> <strong>the</strong>se as a reaction to economical phenomena.
At <strong>the</strong> same time, significant investment in human capital is required to be well trained and ready to
<strong>of</strong>fer skills, abilities according to <strong>the</strong> labour market demand.
In this context, Lifelong Learning came as an alternative to <strong>the</strong> traditional principles <strong>of</strong> education
(Jarvis 1991). But UNESCO expanded its acceptance shortly after using <strong>the</strong> concept for <strong>the</strong> first time,
in 1972, through a multidisciplinary study, analyzing <strong>the</strong> sociological, economical, philosophical as
well as historical implications. This is also because, though associated to technological advance,
social transformations and modern age, <strong>the</strong> specialty literature has operated with it long before its
<strong>of</strong>ficial acknowledgement. Therefore in 1929, Basil a Yeaxlee published a book anticipating <strong>the</strong>
human capital evolution, ascertaining permanent education as tailored to specific individual and social
needs, inseparable in order for it to be efficient. Important references can also be found in <strong>the</strong> Greek
paidea concept, Renaissance or Illuminism.
Consequently, Lifelong Learning is <strong>the</strong> foundation <strong>of</strong> <strong>the</strong> new educational system. Fur<strong>the</strong>r, it is a
paradigm, comprising a set <strong>of</strong> educational objectives, procedures required for <strong>the</strong>se goals to be
reached, and values as Turchenko affirmed in 1983.
Though <strong>of</strong>fering a universal perspective, Lifelong Education and educational systems differ according
to national educational policies and legislation, while <strong>the</strong> way <strong>of</strong> applying it is influenced by
educational practices already enforced. Still, a solid common base can be determined for all <strong>the</strong>
educational systems which exist in Europe. General education, pr<strong>of</strong>essional and vocational training,
and research in closely relation to productivity improvement, are priorities <strong>of</strong> a successful EU as it is
vital to keep up with <strong>the</strong> changes already mentioned before in a multicultural, multiethnic and
multilingual environment, abilities and skills to be at <strong>the</strong>ir highest level (Brock, C. and Tulasiewicz, W.
2000). Therefore, we can identify two elements <strong>of</strong> <strong>the</strong> <strong>European</strong> education system: a national one and
an <strong>European</strong> one. The first is represented by <strong>the</strong> compulsory school programs designed at national
level, comprising mo<strong>the</strong>r tongue, national history and geography, but even here <strong>European</strong> teaching
materials are used; national curricula are developed according to national values, using similar
methods.
But <strong>the</strong> <strong>European</strong> ingredient is represented by <strong>the</strong> <strong>European</strong> Union education itself and foreign
languages courses, all <strong>the</strong>se created in order to ensure, as <strong>the</strong> UK National Curriculum Council
Citizenship Group mentioned: ‘young people should be able to live and work in Europe in comfortably
but not uncritically’ (Brock, C. and Tulasiewicz, W. 2000 pp.17).
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2.2 Future challenges
Marta-Christina Suciu et al.
The <strong>European</strong> education system and national education systems are going to be confronted with
major transformations. Some are determined by <strong>the</strong> globalization phenomenon, <strong>the</strong>refore <strong>the</strong>y are
going to be difficult to predict as <strong>the</strong> causes are too complex to be exactly determined. However,
some <strong>of</strong> <strong>the</strong>m are worthy to be mentioned (Horner, W., Dobert, H., Korp, B. 2007).
First is <strong>the</strong> suzerainty <strong>of</strong> <strong>the</strong> education <strong>of</strong> national state and national specificity. An example is <strong>the</strong> one
<strong>of</strong> Switzerland and Germany (Bundeslaender), divided in administrative territorial units; <strong>the</strong>y have
<strong>the</strong>ir own sub-regional administrative, organization and evaluation structures as far as education is
concerned.
The second issue is related to <strong>the</strong> closer relationship developed nowadays between intercultural
socialization and education as a result <strong>of</strong> migration. Unfortunately, not many countries are ready to
deal with it. The consequences are mixed classes which function inefficiently and determine <strong>the</strong>
management to create ‘foreign classes’. Things become even more complicated: <strong>the</strong> beneficiaries are
in need <strong>of</strong> support in order to learn <strong>the</strong> language and <strong>the</strong> social norms, losing track <strong>of</strong> abilities and
skills formation.
Third, changes in <strong>European</strong> education systems will be severely influenced by <strong>the</strong> demographic crisis.
Two aspects that have to be considered: <strong>the</strong> ageing population and low fertility rates as <strong>the</strong>y translate
in a drop in school population and later on in a shortage <strong>of</strong> skilled labour force, posing an additional
burden on <strong>the</strong> economies. In <strong>the</strong> EU <strong>the</strong> impact <strong>of</strong> this crisis will strongly affect <strong>the</strong> national education
systems both in terms <strong>of</strong> structure and requirements.
The last issue is <strong>the</strong> ra<strong>the</strong>r uncertain future <strong>of</strong> <strong>the</strong> teaching pr<strong>of</strong>ession. The formation <strong>of</strong> teachers is in
need <strong>of</strong> improvements, requiring lifelong training and developing supplementary social skills (teachers
are in charge <strong>of</strong> communicating with students, <strong>the</strong>ir families and community).
Overall, <strong>the</strong>se future evolutions are much prejudiced by <strong>the</strong> perception <strong>of</strong> society as many <strong>of</strong> <strong>the</strong>
deficiencies <strong>of</strong> education systems are transferred to teachers without looking for <strong>the</strong> real cause <strong>of</strong> <strong>the</strong>
problems. The economic crisis made things worse, lowering wages and teachers in <strong>the</strong> social
hierarchy, thus causing a great number <strong>of</strong> <strong>the</strong>m retire early or reconsidering a second career.
3. Romanian education system
3.1 Historical background
In order for Romania to manage <strong>the</strong> integration in EU and to gain a strong competitive advantage in
<strong>the</strong> long run, and to sustain economic growth, a pr<strong>of</strong>ound reform <strong>of</strong> <strong>the</strong> education system was
necessary.
After <strong>the</strong> 1989 Revolution things transformed; <strong>the</strong> political regime was a democratic one, free access
to education was guaranteed by Constitution in 1991, <strong>the</strong>n <strong>the</strong> Education Law in 1995 and numerous
adjustments tried to ensure <strong>the</strong> correlation between economy, social realities and school. In 2003 <strong>the</strong>
new Law <strong>of</strong> Education entered intro force, aligning it to <strong>the</strong> <strong>European</strong> model.
The latest changes are imposed by <strong>the</strong> Bologna process, focusing on decentralisation <strong>of</strong> education
system, ensuring quality, especially for superior education, elaborating a national framework <strong>of</strong>
qualifications compatible with <strong>the</strong> <strong>European</strong> Qualifications Framework by <strong>the</strong> National Agency for
Qualification in Higher Education and Partnership with Economic and Social Environment in
collaboration with <strong>the</strong> higher education institutions- <strong>the</strong> National Qualifications Framework in
Romania, <strong>European</strong> transfer credit points, involvement <strong>of</strong> Romania in programmes which increase <strong>the</strong>
internationalization <strong>of</strong> higher education (Prepelita-Raileanu, B. 2010). Even more, ‘Economic
alphabetization’, as mentioned by <strong>the</strong> President <strong>of</strong> <strong>the</strong> National Council <strong>of</strong> Economic Education
(NCEE), Robert F. Duvall, ‘ is a vital skill, just as vital as reading literacy’ (Stern, G.H. 1998, pp.1).
‘Economic alphabetization’ contributes also to a better understanding <strong>of</strong> functional literacy.
In Romania, at secondary and upper-secondary level, <strong>the</strong> curriculum has a national compulsory
component, representing 90% <strong>of</strong> what children are thought, leaving less than 10% to school’s
decision. However, <strong>the</strong> structure is primarily focused on quality <strong>of</strong> educational services and integration
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<strong>of</strong> demand <strong>of</strong> <strong>the</strong> labour market. The economic education supply is strictly determined by <strong>the</strong>
decisions <strong>of</strong> central authorities, in dimension and distribution. The dimension is established according
to school population, eliminating competition, as <strong>the</strong> beneficiaries are selected based on <strong>the</strong> territory
criterion. Also, secondary and upper-secondary educations are financed by <strong>the</strong> state; <strong>the</strong>refore <strong>the</strong>
supply is inelastic with respect to price. The structure <strong>of</strong> <strong>the</strong> supply is homogenous, starting from 1
class/week in <strong>the</strong> 3 rd class up to 8 th class, but <strong>the</strong> number can increase through interdisciplinary
activities.
The demand <strong>of</strong> economic education is represented by pupils, especially high-school ones, and no
matter <strong>the</strong> specialization <strong>of</strong> <strong>the</strong> education institution, with an amplified demand in institutions where
beneficiaries selected optional courses in this field (Lăcătuş, M.L. 2008).
In post-secondary and tertiary education economic education is related to <strong>the</strong> specialization <strong>of</strong> <strong>the</strong>
studies. Never<strong>the</strong>less all those attending courses at this stage are required to have obtained a
baccalaureate diploma, certifying a minimum <strong>of</strong> knowledge.
3.2 Intellectual capital investments
The connection between investing in human capital and improvements <strong>of</strong> productivity is an essential
aspect <strong>of</strong> our study.
Initial research, mostly <strong>the</strong>oretical, define <strong>the</strong> relation between human capital and economic growth,
namely <strong>the</strong> GDP/capita evolution, <strong>the</strong> characteristics <strong>of</strong> <strong>the</strong> model, while <strong>the</strong> current trend focuses on
testing <strong>the</strong> assumptions using empirical data at large scale ( Sianesi and Van Reenen (2000) and
Temple (2000) studies; Wilson, R. A., Briscoe, G. 2004). The relation is valid as macroeconomic level,
e.g. Solow Growth Model. All models show that higher human capital and education investments
increase productivity, <strong>the</strong>refore economic growth. The two studies, Sianesi and Van Reenen, summed
up <strong>the</strong>ir findings: 1% augment in school conscription rate can determine a 1% to 3% increase in <strong>the</strong>
GDP/capita growth; one more year <strong>of</strong> secondary education points to over 1% boost in terms <strong>of</strong>
economic growth (Wilson, R. A., Briscoe, G. 2004).
In Romania, investments in human capital were influenced by <strong>the</strong> economic and political realities. If
<strong>the</strong> system was under centralized control during <strong>the</strong> Communist regime, after 1989 <strong>the</strong> economy was
liberalised and as <strong>the</strong> integration process began it changed.
Competition became fierce; human capital had to be perceived and evaluated through at least two
different lenses: quantity and quality. This is one <strong>of</strong> <strong>the</strong> explanations why Romania had occupied a
low position as indicated by <strong>the</strong> Human Development Index before <strong>the</strong> integration process started.
However, in <strong>the</strong> following years Romania had better results though far from <strong>the</strong> set standards.
According to <strong>of</strong>ficial statistical data, in 2005 only 1.6% <strong>of</strong> <strong>the</strong> adult population attended training
courses, far behind <strong>the</strong> <strong>European</strong> mean.
Currently, <strong>the</strong> strong economic crisis imposed severe measures with negative impact in <strong>the</strong> long run
as spending and investments in education and research were seized in 2009-2010, without
encouraging signals for next year. The solely positive aspect is related to <strong>the</strong> challenge mentioned in
<strong>the</strong> first chapter, <strong>the</strong> migration phenomenon. Romania may face a return on human capital previous
investment as many Romanians decide to return home because <strong>of</strong> high level <strong>of</strong> unemployment and
shrinkage <strong>of</strong> foreign labour markets. Therefore <strong>the</strong> national economy gains skills, competencies and
trained labour force, a great help in overcoming <strong>the</strong> crisis.
Everything has to be considered at macroeconomic level as it is a clear connection between growth
rates and human capital accumulation. Only strong investments in education are <strong>the</strong> way for <strong>the</strong>
economy to recover and to reach a sustainable economic growth.
4. Intellectual capital measurement
4.1 Choose <strong>the</strong> right instrument
The business world today needs new tools and coordinates to enrol in <strong>the</strong> New Economy. Different
than a traditional economy, <strong>the</strong> knowledge economy raises many problems in establishing <strong>the</strong>
measurement unit while considering transactions with services, experiences or ideas.
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Marta-Christina Suciu et al.
Also, ever since <strong>the</strong> first items <strong>of</strong> <strong>the</strong> new language were created, <strong>the</strong> interest for possible
measurement and valuation ways increased considerable, so to conform <strong>the</strong> old principle <strong>of</strong> ‘what can
be measured, can be managed’.
Measuring Intellectual Capital for an organization is not an easy task. The main issue is that it deals
with intangible assets which can be measured at cost, at market, <strong>the</strong>ir contribution to cash flows or
o<strong>the</strong>r numerous possibilities <strong>of</strong> reporting <strong>the</strong>m. There are up to over 30 available measurement types.
In fact, probably <strong>the</strong> adequate way for an organization to measure its intangibles is by evaluating <strong>the</strong>ir
market value. But this poses <strong>the</strong> problem <strong>of</strong> a reactive approach that may leave <strong>the</strong> organization
lagging behind <strong>the</strong> competition.
Therefore a measurement model must be chosen according to several criteria (Choo, C. and Bontis,
N. 2002):
Auditable and consistent information (observers cannot interfere with <strong>the</strong> data, while information
sources should not be biased, following very strictly <strong>the</strong> evaluation system requirements, whe<strong>the</strong>r
it is a qualitative or quantitative measurement);
Not to impose a large measurement cost (keep in mind <strong>the</strong> purpose <strong>of</strong> <strong>the</strong> analysis, to improve
<strong>the</strong> company, not hinder it, and avoiding losing control over <strong>the</strong> collection and management <strong>of</strong> <strong>the</strong>
data base used);
Helping strategic and tactical management (<strong>the</strong> results must be useful);
Generate information for shareholders and investors (Intellectual Capital and Human Capital
reports for specific purposes);
Future, past and present.
Depending on <strong>the</strong>se criteria and exact needs an organization may choose from a palette <strong>of</strong> evaluation
models, to focus on financial valuation, value assessment or measurement.
However, when dealing with <strong>the</strong> evaluation <strong>of</strong> <strong>the</strong> educational system and its relationship with
intellectual capital, <strong>the</strong>re have to be solved at least three issues:
Limited financial flows (it is a special market: in Romania <strong>the</strong>re are a few private schools, <strong>the</strong>
overwhelming majority is formed by public schools);
Pr<strong>of</strong>itability cannot be a purpose; <strong>the</strong> objective must be to create a system that educates children
not one that gains money (in Romania <strong>the</strong> secondary and upper-secondary level is financed by
<strong>the</strong> state, also post-university and tertiary level, only for <strong>the</strong> best qualified beneficiaries);
It cannot be evaluated immediately but it must be observe how, after graduating from school or
o<strong>the</strong>r courses, trainings, etc., individuals develop pr<strong>of</strong>essionally (two-dimension framework <strong>of</strong> an
evaluation model must include <strong>the</strong>n and now for relevance).
Therefore it is difficult and <strong>of</strong> little importance to measure <strong>the</strong> financial aspects <strong>of</strong> <strong>the</strong> system, although
<strong>the</strong>y cannot be ignored, but instead must focus on its ability to create value for society. This can be
done by evaluating <strong>the</strong> system by measuring statistical elements such as school abandonment rate,
rate <strong>of</strong> literacy, international results, but also how <strong>the</strong> individual develops.
4.2 The intellectual capital empirical study
4.2.1 Sample and data collection
The chosen research tool was a questionnaire specially designed, according to two objectives:
determining <strong>the</strong> current state <strong>of</strong> intellectual capital and ga<strong>the</strong>ring information for a valid intellectual
capital evaluation model, taking into consideration <strong>the</strong> characteristics <strong>of</strong> <strong>the</strong> Romanian education
system. Measurement items were adapted from specific literature where possible, while new items
were developed according to <strong>the</strong> defined goals.
The questionnaire was firstly tested and revised accordingly. The testing was carried out in November
2010 and <strong>the</strong> retrieval rate was 80%. This was performed for electronic questionnaires and on
material support.
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Marta-Christina Suciu et al.
The questionnaire was divided into three sections: human capital, organizational capital and network
capital, and an introductory part for defining concepts which might have posed problems to <strong>the</strong>
respondents.
The respondents were randomly selected, representing a diverse sample with 25% men and 75%
women, with ages ranging between 20 and 60 years old.
4.2.2 Data analysis and results
The interpretation started from <strong>the</strong> data ga<strong>the</strong>red, oriented towards:
Correlation and percentage relation between <strong>the</strong> initial educational background and secondary or
tertiary studies;
Variation in motivation in attending supplementary courses and trainings;
Correlation and percentage relation between education system and development <strong>of</strong> <strong>the</strong> individual;
Correlation and percentage relation between innovative individuals and <strong>the</strong>ir educational
background;
The results indicate that, overall, people tend to follow <strong>the</strong> same pr<strong>of</strong>essional path from start to finish
thus almost 50% <strong>of</strong> people who graduated from a high school specialized in ma<strong>the</strong>matics, physics or
chemistry went on to a technical university. This remains true for <strong>the</strong> o<strong>the</strong>r types <strong>of</strong> educational
backgrounds as it can be observed in <strong>the</strong> graph demonstrating <strong>the</strong> correlation in Figure 1.
While <strong>the</strong>re is this correlation between high school and secondary/ tertiary education <strong>the</strong>re was not
found a consistent link between studies and <strong>the</strong> decision to pursue fur<strong>the</strong>r education after graduating.
On <strong>the</strong> o<strong>the</strong>r hand, what it is unexpected is that <strong>the</strong> majority claimed to have attended such
complementary courses.
Vocational Specialization
Tehnological
Specialization
Philology Specializaiton
Ma<strong>the</strong>matics
Specialization
Educational background
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Technical Humanist Law
Secondary / tertiary education
Figure 1: Correlation between initial educational background and tertiary education
However, <strong>the</strong> data shows a strong difference in motivation for attending courses. Therefore most
people with an economic or humanist background cite pr<strong>of</strong>essional reasons, namely 23% and 44% <strong>of</strong>
<strong>the</strong> respondents, while those with a technical background chose due to personal reasons, 47%, and
only 17% <strong>of</strong> those citing personal reasons are <strong>of</strong> a philology background and 17% <strong>of</strong> an economics
one. It should be pointed out here that <strong>the</strong> results may be partially skewed due to <strong>the</strong> personal
perception thus even though <strong>the</strong> result is an improvement for some <strong>the</strong>y might consider <strong>the</strong> course a
necessity for <strong>the</strong> job whereas o<strong>the</strong>rs might see it as an opportunity to enrich personal knowledge. The
number <strong>of</strong> respondents citing both personal and pr<strong>of</strong>essional reasons is under 3%.
While most <strong>of</strong> <strong>the</strong>m say that <strong>the</strong>ir employer provides <strong>the</strong>m with training and courses, about 48% <strong>of</strong>
those who claimed to have taken part at training, paid it <strong>the</strong>mselves. Therefore <strong>the</strong> conclusion is that
most employees are in fact content, not happy, and those that are not content are likely agents <strong>of</strong>
change.
422

Who paid for
Third parties
Employer
Myself
16%
14,28%
28,20%
Marta-Christina Suciu et al.
68%
71,52%
64,10%
16%
14,20%
7,70%
0% 20% 40% 60% 80% 100% 120%
Type <strong>of</strong> interest
Personal interest Pr<strong>of</strong>essional interest Both
Figure 2: Motivation for attending courses and financial support distribution
For most <strong>of</strong> <strong>the</strong> respondents <strong>the</strong> education system played an important role in <strong>the</strong>ir personal and
pr<strong>of</strong>essional development. On a scale <strong>of</strong> 1 to 5, 5 being <strong>the</strong> highest, <strong>the</strong> average result was 4.37 with
a mode <strong>of</strong> 5 and a standard deviation <strong>of</strong> only 0.87.
After a more thorough analysis it was determined that individuals have found a mentor in <strong>the</strong>ir activity,
and this has pushed <strong>the</strong> overall average to 4.08. However, <strong>the</strong> correlation between <strong>the</strong>ir opinion <strong>of</strong> <strong>the</strong>
importance <strong>of</strong> a mentor and <strong>the</strong> impact <strong>of</strong> <strong>the</strong> education system is only 0.38 whereas <strong>the</strong> correlation
between <strong>the</strong> importance <strong>of</strong> <strong>the</strong> system and <strong>of</strong> teachers is 0.54. This indicates that while for those that
had a mentor <strong>the</strong>ir education made a difference, <strong>the</strong>re is a lack <strong>of</strong> teachers and specialised
pr<strong>of</strong>essionals in mentoring.
Concerning <strong>the</strong>ir propensity to bringing improvements in <strong>the</strong> organization <strong>the</strong> results reveal a fairly
surprising conclusion. Of all <strong>the</strong> respondents, 90% claim to have brought something new, however,
considering what <strong>the</strong>y claim and <strong>the</strong> nature <strong>of</strong> <strong>the</strong>ir job, only about 30% were deemed to have actually
made an improvement. What is unexpected is that, <strong>of</strong> those who innovated something, 40% were <strong>of</strong> a
technical background, 33% <strong>of</strong> and economic background and only 22% <strong>of</strong> a philology specialization.
This is important because one <strong>of</strong> <strong>the</strong> initial assumptions was that people with philological educational
background are being more inclined to innovation and change. This has been disproved by <strong>the</strong> data.
It should also be pointed out that even though <strong>the</strong>y had a technical background <strong>the</strong>ir current job is
quite creative.
The relational capital is well managed in terms <strong>of</strong> information collection and management, more than
80% <strong>of</strong> <strong>the</strong> respondents appreciating <strong>the</strong> effort <strong>of</strong> <strong>the</strong> organization on a scale from 1 to 5, where 5 is
<strong>the</strong> highest, with an average <strong>of</strong> 3.7.
5. Measurement instrument and conclusions
In <strong>the</strong> Romanian educational system <strong>the</strong>re are frequent transformations, different standards in
different branches <strong>the</strong>refore making difficult its objective evaluation. According to <strong>the</strong> results, technical
specializations certify better trained future employees, ready to bring innovative ideas for <strong>the</strong> benefit
<strong>of</strong> <strong>the</strong>ir employers. Therefore, <strong>the</strong>y already have <strong>the</strong> necessary skills to manage different types <strong>of</strong>
jobs, adapting easier to changes.
Evaluating <strong>the</strong> references from <strong>the</strong> specific literature and <strong>the</strong> empirical study we carried out, <strong>the</strong>
evaluation model for intellectual capital to be applied in reducing uncertainty and increase
competitiveness <strong>of</strong> human capital, considering <strong>the</strong> characteristics <strong>of</strong> <strong>the</strong> Romanian education system,
should consider <strong>the</strong> arguments for an educational policy based on rate <strong>of</strong> return analysis.
423

Marta-Christina Suciu et al.
This treats expenses with human capital as an investment that boosts productivity and generates
future monetary/non-monetary outflows, and a connection to economic growth analysis.
The instrument to be used should be a questionnaire aimed at present and future beneficiaries <strong>of</strong> <strong>the</strong>
education system in Romania. It has to focus and develop through additional questions, tackling
several issues:
School involvement in <strong>the</strong> beneficiaries’ pr<strong>of</strong>essional and personal development route;
Periodical assessment <strong>of</strong> education system (Human, Organizational and Relational Capital);
Celerity <strong>of</strong> finding a job;
Level <strong>of</strong> training and knowledge in relation to what <strong>the</strong> labour market/ <strong>the</strong> job description.
It should be applied after graduating from every phase <strong>of</strong> education and <strong>the</strong>n, after graduation, every
1-5 years. In time <strong>the</strong> sample may incur variations in size, according to <strong>the</strong> criteria mentioned
previously in <strong>the</strong> paper: avoiding large measurement costs, having an appropriate evaluation system
nationally implemented, with well determined requirements for qualitative/quantitative measurements.
The most important objective <strong>of</strong> <strong>the</strong> questionnaire is to determine what changes need to be made so
that <strong>the</strong> education system can help train competent individuals. With literacy levels approaching an all
time high <strong>the</strong> next issue to be tackled is <strong>the</strong> differentiation between a functional literate and a person
with a proper education. The requirements are shifting and it is highly unlikely that it can be predicted
what will be considered necessary ten to twenty years after a child will have started his education.
Thus it is vital that a series <strong>of</strong> core competencies are determined so that, no matter which track is
chosen, certain abilities are common to all. In this manner discrepancies should be removed with
time. The major difficulty is <strong>the</strong> though in 2007 and 2008 <strong>the</strong> Romanian budgetary effort towards
investments in education increased to 5.2% and 6% <strong>of</strong> GDP, starting 2009 <strong>the</strong> economic crisis has
contracted it again to.
Ano<strong>the</strong>r goal is to provide valuable information to managers and to o<strong>the</strong>r stakeholders (direct
beneficiaries, social and business community, etc.). Periodical reports on intellectual capital
evaluation could be valuable, bringing additional investments at institutional level and getting
everyone in <strong>the</strong> community involved at different levels.
This will prove vital especially after <strong>the</strong> decentralization <strong>of</strong> <strong>the</strong> education system in Romania as
proposed by <strong>the</strong> Education Law which is about to be enforced in 2011, but also it means additional
percentages to <strong>the</strong> economic growth <strong>of</strong> Romania, if <strong>the</strong> negative impact <strong>of</strong> <strong>the</strong> budgetary reduction
from April 2009 can be <strong>of</strong>fset by a long term national strategy. General progress was however
incurred by Romania according to OECD, both in terms <strong>of</strong> HDI annual ranking and in increase in <strong>the</strong>
percentage <strong>of</strong> graduates from secondary and tertiary education, <strong>of</strong> over 50% <strong>of</strong> <strong>the</strong> total number <strong>of</strong>
graduates in 2008.
It would appear that an individual, who can be expected to bring improvements in a company, as
revealed by <strong>the</strong> data, is someone who has studied formal disciplines such as ma<strong>the</strong>matics or physics,
which require him to structure information in a practical way. This is more noticeable when <strong>the</strong> person
is employed in a field that is not a continuation <strong>of</strong> prior studies.
Extrapolating from <strong>the</strong>se elements, though not sufficient when ascertaining <strong>the</strong> ability <strong>of</strong> individuals to
improve on something in an organization, still are necessary:
1. The interests and training must go beyond what is job requirement, allowing making use <strong>of</strong> his
knowledge and apply it elsewhere;
2. Having a systematic approach to a complex problem, so that to identify <strong>the</strong> key issues and
work on <strong>the</strong>m first instead <strong>of</strong> trying to improve everything at once.
It should be pointed out that certain biases are present. Firstly, results refer strictly to <strong>the</strong> Romanian
education system and as such <strong>the</strong>y are likely to be different elsewhere. They do not take into account
extreme cases like a high degree <strong>of</strong> training and specialization or if a certain talent is required.
The final conclusion <strong>of</strong> our paper is that education systems have to train people as to be able to thrive
in <strong>the</strong> knowledge-based economy and society. It is becoming obvious that knowing <strong>the</strong> correct answer
can be irrelevant in today’s world, but more important is to know <strong>the</strong> correct question and <strong>the</strong>
424

Marta-Christina Suciu et al.
necessary steps to answering it. In o<strong>the</strong>r words, <strong>the</strong> aim is to educate an individual in <strong>the</strong> spirit <strong>of</strong>
asking questions and not just answering <strong>the</strong>m.
Acknowledgments
This paper is a result <strong>of</strong> <strong>the</strong> projects: Parteneriate 92116 (project financed by CNCSIS /UEFISCSU),
DOCCENT and POSDRU/6/1.5/S/11 „Doctoral Program and PhD Students in <strong>the</strong> education research
and innovation triangle”. The second and third projects are co-funded by <strong>the</strong> <strong>European</strong> Social Fund
through <strong>the</strong> Sectorial Operational Programme for Human Resources Development 2007-2013,
coordinated by <strong>the</strong> Bucharest Academy <strong>of</strong> Economic Studies.
References
Brock, C. and Tulasiewicz, W. (2000) Education in a Single Europe, Routledge, London, pp. 15-17
Choo, C. and Bontis, N. (2002) The Strategic Management <strong>of</strong> Intellectual Capital and Organizational Knowledge,
Oxford University Press, New York
Cowen, R., Kazamias, A. (2009), International Handbook <strong>of</strong> Comparative Education, vol. 2, Springer, New York,
pp. 634- 635
Horner, W., Dobert, H., von Kopp, B. And Mitter, W. (2007) The education systems <strong>of</strong> Europe, Springer,
Dordrecht, Norway, pp. 852-854
Jarvis, P. (1991) Twentieth Century Thinkers in Adult Education, Routledge, London, pp. 38
Lăcătuş, M.L. (2008) Pre-university Education and Economic Education, PhD Graduation Thesis, PhD
Supervisor: Marta Christina Suciu, Academy <strong>of</strong> Economic Studies, Bucharest, pp. 38-46
Prepelita-Raileanu, Branduşa, “The Decentralization Strategy <strong>of</strong> Romanian Higher Education and <strong>the</strong>
Implementation <strong>of</strong> Quality Management System”, [online], <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 7 th WSEAS International
<strong>Conference</strong> on Latest Trends on Engineering Education (EDUCATION ‘10), ISSN: 1792-426X, ISBN: 978-
960-474-202-8, Corfu Island, Greece, July 22-24, 2010, pp. 116-118, http://www.wseas.us/elibrary/conferences/2008/crete/education/education66.pdf
Stern. G. .H. (December 1998) ‘’Do We Know Enough about Economics? ‘’, [online], Federal Reserve Bank <strong>of</strong>
Minneapolis, pp. 1, http://www.minneapolisfed.org/publications_papers/pub_display.cfm?id=3578
Swing, E. and Schriewer, J. (2000) Problems and prospects in <strong>European</strong> education, Greenwood Publishing
Group, U.S.A., pp. 1-2
Wilson, R. A., Briscoe, G. (2004) ‘’The impact <strong>of</strong> human capital on economic growth: a review’’, [online], in Descy,
P.; Tessaring, M. (eds) ‘’Impact <strong>of</strong> education and training Third report on vocational training research in
Europe: background report’’, Luxembourg: Office for Official Publications <strong>of</strong> <strong>the</strong> <strong>European</strong> Communities,
(Cedefop Reference series, 54), pp. 31-32
425

Information and Communication Technology in Bilingual
Societies in Finland
Jukka Surakka 1 , Pertti Saariluoma 2 , Pertti Jokivuori 2 , Marjo Silvennoinen 2 ,
Helena Suvinen 2 , and M T Hyyppä 3
1
Arcada-University <strong>of</strong> Applied Sciences, Finland
2
Jyväskylä University, Finland
3
National Institute for Health and Welfare, Finland
jukka.surakka@arcada.fi
Abstract: Background. Information and communication technology (ICT) have a great simultaneous influence
on society. ICT reflects human behavior and life style. The rapid development <strong>of</strong> ICT has various consequences
in human behavior that are constantly changing. It allows people to communicate quite freely but has also a
reverse side, causing people to become dependent on it. This is a new form <strong>of</strong> addiction, an addiction to be
constantly updated. Ano<strong>the</strong>r serious side effect is that through <strong>the</strong> internet, it is possible to spread false and
harmful information about o<strong>the</strong>r people. The relationship between humans and technology has been studied and
observed from <strong>the</strong> technological point <strong>of</strong> view; but during recent years, <strong>the</strong> relationship between human behavior
and technology has increasingly been observed from <strong>the</strong> angle dealing with human values and goals. It has been
demonstrated that <strong>the</strong> Swedish-speaking minority in Finland has certain socio-cultural habits that differ from <strong>the</strong>
Finnish-speaking majority’s way <strong>of</strong> life and culture. For example, Swedish speakers own more social capital and,
<strong>the</strong>refore, <strong>the</strong>y are probably healthier and live significantly longer. These differences in social capital and health
may be related with communication. Hence, it is interesting to study <strong>the</strong> ICT behavior in and between <strong>the</strong>se
language groups. Intellectual capital is perceived to be <strong>the</strong> principal source <strong>of</strong> value for society and companies
operating in <strong>the</strong> ICT sector. Fur<strong>the</strong>r, it is important to investigate this issue as one <strong>of</strong> <strong>the</strong> major source <strong>of</strong>
competitive advantage in society and firms. We focus specifically on <strong>the</strong> possibilities this ICT behavior research
<strong>of</strong>fers, acknowledging that <strong>the</strong>re has been relatively little discourse on intellectual capital in this sector. Research
about intellectual capital and ICT user behavior is needed for understanding <strong>the</strong> possibilities <strong>of</strong> utilizing ICT in
intellectual capital context. Methods. In this study, we surveyed a total <strong>of</strong> 2 211 randomly chosen subjects, <strong>of</strong>
which 50% were Finnish-speakers and 50% were Swedish speakers. The survey was carried out in four bilingual
municipalities in Finland. The survey included 14 questions about ICT and its usage: <strong>the</strong> anonymity <strong>of</strong> <strong>the</strong>
internet; <strong>the</strong> ease or difficulty to communicate via internet vs. face-to-face; purposes for which subjects use <strong>the</strong>
internet, etc. Results. Factor analysis revealed that both Finnish- and Swedish-speaking subjects valued <strong>the</strong>
intimacy <strong>of</strong> <strong>the</strong> internet since it makes <strong>the</strong> communication easier than face-to-face meetings. In general, <strong>the</strong>y
perceived that <strong>the</strong> internet communication makes <strong>the</strong>m more aggressive than communicating face-to-face. This
phenomenon was more pronounced among Finnish-speaking subjects. Fur<strong>the</strong>rmore, Swedish speakers tended
to use <strong>the</strong> internet more as a communication forum for hobbies and leisure activities, while Finnish speakers
used it more as a tool.Also, Swedish speakers valued face-to-face communication more than Finnish speakers.
Conclusions. It seems that Finnish-speaking subjects value <strong>the</strong> anonymity <strong>of</strong> <strong>the</strong> internet, and <strong>the</strong>y do not need
to meet people physically face-to-face. One can argue that Finnish speakers favor virtual social communication,
so called “social media”, instead <strong>of</strong> personal contacts. Swedish speakers seem to use <strong>the</strong> internet as a tool to
arrange face-to-face meetings and to reach personal contacts. Perhaps, Swedish speakers are socially better
prepared to meet people face-to-face. In previous studies on social capital, personal communication, meeting
people, get toge<strong>the</strong>r and being socially active have characterized Swedish speaking Finns. Human competencies
and relationships are <strong>the</strong> most important elements contributing to stabile intellectual capital base, and <strong>the</strong>refore it
is relevant and necessary to study ICT user behavior. Our findings in ICT user behavior suggest that investment
in people and studying different culture’s ICT behavior are important factors in intellectual capital context,
particularly in <strong>the</strong> current context <strong>of</strong> rapid technological development.
Keywords: bilingual societies, communication, ICT, intellectual capital, social capital, user behavior
1. Introduction
Intellectual capital is perceived to be <strong>the</strong> principal source <strong>of</strong> value for society and companies
operating in <strong>the</strong> ICT sector. Human competencies and relationships are <strong>the</strong> most important elements
contributing to a stabile intellectual capital base, accounting for more than 55% <strong>of</strong> intellectual capital
(O’Regan et al 2001). By participating in different lifestyles, humans create certain rules and models
to be followed. They are visualized in mind and followed when needed. By those models, humans
build up <strong>the</strong> order and meaning for life. The lifestyle is not always a voluntary choice; we are <strong>of</strong>ten
driven to a certain lifestyle. Lifestyles become step-by-step a part <strong>of</strong> our mind structure and determine
which things are important and in which way. We develop different technologies for various purposes,
but <strong>the</strong>y all have one thing in common: <strong>the</strong>y are aimed to ease our daily life and to help us reach our
goals. Technologies are always aimed for certain purposes, and <strong>the</strong>ir usefulness must be evaluated
from that point <strong>of</strong> view. Different lifestyles contribute to several human actions, and technology is
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Jukka Surakka et al.
naturally involved in <strong>the</strong>se actions. From <strong>the</strong> users' psychological points <strong>of</strong> view, it is important to see
human technology interaction from a wide (visual) angle. The human-technology interaction does not
only mean feasibility or competence to use technologies or emotional experience. The position <strong>of</strong>
technology in human life (Leikas and Saariluoma 2008, Leikas 2009, Saariluoma and Leikas 2010)
must also be taken into consideration. This means that we need a much deeper understanding <strong>of</strong> <strong>the</strong>
human mind and life than is needed for feasibility and competence. In technology planning, it is
nowadays essential to analyze lifestyles, because such analyses can reveal what type <strong>of</strong> technologies
we need.
Interface psychology has its specific perspective on human-technology interaction. It focuses on
users, and on <strong>the</strong> psychological preconditions <strong>of</strong> <strong>the</strong>ir behaviors and actions. This means that
interface psychology may question <strong>the</strong> role <strong>of</strong> some psychological construct in <strong>the</strong> human-technology
interaction, ra<strong>the</strong>r than directly studying <strong>the</strong> usefulness <strong>of</strong> <strong>the</strong> devices. Social and cross-cultural
psychology can reply to some <strong>of</strong> <strong>the</strong> new challenges produced by <strong>the</strong> complicated human-technology
interactions in ICT.
By trust, we generally refer to <strong>the</strong> fact that somebody believes something to be guaranteed. The
social importance <strong>of</strong> trust is central in our attempts to predict how o<strong>the</strong>r people will behave. As Rotter
(1967) defines it “A generalized expectancy held by an individual that <strong>the</strong> word <strong>of</strong> ano<strong>the</strong>r…can be
relied on.” Trust is also important in <strong>the</strong> mo<strong>the</strong>r-infant relation. This means that trust is a family
resemblance concept, i.e., it is like rope which has no single common characteristic which would
connect all those things we call trust, but <strong>the</strong>y are not totally unrelated ei<strong>the</strong>r (Wittgenstein 1958). As
Katz and Golbeck (2006) declares trust “as a prioritization tool for default logic”. This is especially
clear with promises. Often trust is <strong>the</strong> guarantee that people will not cause you harm. In <strong>the</strong> extremely
public and anonymous internet, it is a special problem whe<strong>the</strong>r people can really trust that behind <strong>the</strong>
faceless machine, everything works so that <strong>the</strong>y shall not be harmed by <strong>the</strong> information <strong>the</strong>y directly
or indirectly give <strong>of</strong> <strong>the</strong>mselves.
It is natural to think that culture contributes strongly to <strong>the</strong> idea <strong>of</strong> trust. The sense <strong>of</strong> trust differs
across cultures from West to East (Yoki, Maddux, Brewer, and Takemura, 2005). Cultural differences
in trust are more understandable if <strong>the</strong>re is a question about two different nations. But what about
differences in trustfulness between cultures inside a small country? Can people with <strong>the</strong> same ancient
history, same political system and same residency have a different sense <strong>of</strong> trust?
In this study, we are interested in <strong>the</strong> role <strong>of</strong> culture on internet behavior and on trustfulness in two
different language groups. We compare Finnish-speaking Finns and Swedish-speaking Finns.
Swedish speakers are a particularly interesting subculture having <strong>the</strong> four major criteria for ethnicity:
self-identification <strong>of</strong> ethnicity, language, social culture and ancestry (Mc Rae 1997). This minority
(5,3% <strong>of</strong> <strong>the</strong> total population) lives in <strong>the</strong> Western and Sou<strong>the</strong>rn provinces <strong>of</strong> Finland, intermingles
with <strong>the</strong> Finnish-speaking majority and is quite similar to Finnish-speaking communities in socioeconomic
status, education and health services. Swedish speakers have significantly better self-rated
health (Hyyppä and Mäki, 2001a, Nyqvist and Martelin, 2007, Nyqvist et al., 2008) and a longer
disability-free life expectancy (Hyyppä and Mäki, 2001a) than <strong>the</strong> Finnish speakers. There have been
established significant disparities in <strong>the</strong> annual suicide rates, violent and accidental death rates and
cardiovascular mortality, as well as in survival (Hyyppä and Mäki 2001a, Koskinen and Martelin, 2003,
Hyyppä 2010). In <strong>the</strong>se reports, <strong>the</strong> common denominator is <strong>the</strong> inadequacy <strong>of</strong> <strong>the</strong> conventional
health-risk factors to explain <strong>the</strong> significant inequality in health between <strong>the</strong> language groups (Hyyppä
2010). The Swedish-speaking minority also has more social trust and less social mistrust than <strong>the</strong>
Finnish-speaking majority in Finland (Surakka et al 2009, Hyyppä 2010). Social trust was positively
related to <strong>the</strong> frequency <strong>of</strong> visiting friends, church attendance and visiting <strong>the</strong> public library. These
associations were independent <strong>of</strong> language group and o<strong>the</strong>r factors.
To get an idea how social trust in internet use differs between <strong>the</strong> two population groups, we decided
to measure ICT-trust and to investigate <strong>the</strong> possible culture-related factors in a large and
representative population study. The main aim is to find out what kind <strong>of</strong> factors explain differences
between <strong>the</strong> ethnic groups and cultures. Fur<strong>the</strong>r, we discuss <strong>the</strong> meaning and consequences <strong>of</strong> ICT
behavior in creating intellectual capital value.
2. Methods
Participants
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Jukka Surakka et al.
The participants were n=2211 people who were living in a Swedish-speaking area on <strong>the</strong> coast <strong>of</strong>
Finland. The area consists <strong>of</strong> four different municipalities (Loviisa: 7,400 inhabitants, 58% Finnish
speakers, 39% Swedish speakers; Porvoo: 48,000 inhabitants, 64% Finnish speakers, 33% Swedish
speakers; Mustasaari: 18,000 inhabitants, 29% Finnish speakers, 71% Swedish speakers; and
Pietarsaari: 19,800 inhabitants, 42% Finnish speakers, 55% Swedish speakers). The majority <strong>of</strong> <strong>the</strong>
participants were female (57 %) and <strong>the</strong> rest were male (43 %). Half <strong>of</strong> <strong>the</strong> respondents were using
mainly Finnish (49 %) and <strong>the</strong> o<strong>the</strong>r half mainly Swedish (51 %) during <strong>the</strong>ir daily activities. The age
<strong>of</strong> <strong>the</strong> participants ranged from 20 to 76 (M = 51.67, SD = 13.93).
Questionnaire
The survey included several questions about social participation and activities during job and leisure
time, as well as, about communication on <strong>the</strong> internet. We formulated a structured questionnaire to
get measurable numerical data suitable for a quantitative analysis and to make comparisons
regarding specific questions. For an efficient way to reach people, we chose to use a postal
questionnaire. It included a total <strong>of</strong> 132 questions about ICT activities, social, citizen and political
activities, self-rated health, work, physical activity, sleep behavior, leisure activities and health-related
behaviors. Also, questions about age, income, education, and medication were asked. The
questionnaire was made and presented in participants’ own mo<strong>the</strong>r tongue. The results were
statistically analyzed by actor analysis, two-way anova and binary regression analysis.
3. Results
For surveying <strong>the</strong> time spent in different activities, <strong>the</strong> amount <strong>of</strong> internet use, (Finnish speakers'
mean use 7.37h/week and Swedish speakers' mean use 7.13 h/week). Finnish speakers (mean 7.57
h/day) slept slightly more than Swedish speakers (mean 7.48 h/day), but Finnish speakers suffered
from insomnia more than Swedish speakers (p=0.01), and Finnish speakers also felt that <strong>the</strong>y were
more tired than <strong>the</strong>ir colleagues at work than Swedish speakers did (p=0.04). There were differences
between groups in intimacy but not in anonymity <strong>of</strong> <strong>the</strong> internet (Table 1).
Table 1: Use <strong>of</strong> internet, duration <strong>of</strong> sleep, tiredness, frequency <strong>of</strong> insomnia, intimacy and anonymity
Question
Use <strong>of</strong>
internet?
Duration <strong>of</strong>
Alternatives Swedish speakers
N=930
N=930
sleep?
Are you more
tired than your
work
colleagues? %
Are you
suffering from
insomnia %
It is easier to
reveal inner
intimate
feelings
through <strong>the</strong>
internet
mean±
Anonymity
makes <strong>the</strong>
internet a
pleasant
discussion
forum
mean±
Finnish speakers
N=957
N=957
PP value*
h/week 7.13±9.6 7.37±8.9 0.62
h/day 7.48±1.10 7.57±1.28 0.08
No 65.3 58.6
I cannot say 27.8 32
Yes 6.9 9.3
Never 29.9 24.1
Sometimes 63.2 65.3
Often 5.9 8.8
Always
Scale 1 - 4
1=I definitely disagree
1.0 1.9
2=I disagree
3=I agree
4=I definitely agree
2.1±0.8
2.4±0.7
Scale 1 - 4
1=I definitely disagree
2=I disagree
3=I agree
4=I definitely agree
2.98±0.65
428
3.01±0.65
0.04
0.01
0.0001
0.18

P value * Level <strong>of</strong> significance is set at p

Jukka Surakka et al.
people. Communication in <strong>the</strong> internet does not need personal contacts, and fur<strong>the</strong>r, one does not
need to know one's communication partner. Virtual communication is easy and requires no
responsibility.
In contrast to Swedish speakers, Finnish speakers value <strong>the</strong> anonymity <strong>of</strong> internet relationships.
Finnish speakers seem to get along without personal face-to-face contacts. The internet <strong>of</strong>fers virtual
relationships without physical meetings, and one is even able to express negative inner feelings to <strong>the</strong>
communication partner. For Swedish speakers, <strong>the</strong> internet is more a tool and a forum for real
meetings with people. They organize <strong>the</strong>ir leisure and hobby activities and familiarize <strong>the</strong>mselves with
new people via <strong>the</strong> internet. Such a use <strong>of</strong> <strong>the</strong> internet means a positive social media that may create
social networks and streng<strong>the</strong>n social capital. Based on our research, 30% <strong>of</strong> Swedish speakers used
<strong>the</strong> internet to promote <strong>the</strong>ir hobbies, while only 21% <strong>of</strong> <strong>the</strong> Finnish-speaking participants used it for
this purpose. If people have hobbies, <strong>the</strong>y probably know each o<strong>the</strong>r well, and <strong>the</strong> internet is used to
transmit information about hobbies between friends and neighbors.
The present study also examined people’s reciprocal trust in <strong>the</strong> internet. Our aim was to compare
social reciprocal trust between two different cultures, i.e., between <strong>the</strong> Finnish-speaking majority and
<strong>the</strong> Swedish-speaking minority in Finland. The trust was evaluated by measuring intimacy in <strong>the</strong>
internet communication and by comparing face-to-face and online communications. We found that
Finnish-speaking Finns valued more intimacy in <strong>the</strong> internet than Swedish-speaking Finns. In o<strong>the</strong>r
words, <strong>the</strong> intimacy which <strong>the</strong> internet can <strong>of</strong>fer is more significant to <strong>the</strong> Finnish-speaking internet
users compared with <strong>the</strong> minority Swedish speakers. The discrepancy is interesting because <strong>the</strong>se
two cultures live intermingled with each o<strong>the</strong>rs in <strong>the</strong> same regions.
One explanation for our results might be that <strong>the</strong> total number <strong>of</strong> connected (not isolated)
associational memberships correlates with trust (Paxton, 2007). Indeed, <strong>the</strong> Swedish-speaking
minority does have richer social contacts than <strong>the</strong> Finnish-speaking majority. According to <strong>the</strong> results
<strong>of</strong> Hyyppä and Mäki (2001b, 2003), Finnish-Swedish people are more active in civic and social
activities. Also, <strong>the</strong>y have more mutual trust (Surakka et al., 2009, Hyyppä, 2010). Because <strong>of</strong> <strong>the</strong>ir
community spirit, <strong>the</strong> Swedish-speaking people do not need intimacy in <strong>the</strong>ir internet use for selfexpression.
Intimacy in <strong>the</strong> internet may not <strong>of</strong>fer a surplus for Swedish speakers as it <strong>of</strong>fers for
Finnish speakers. Our previous studies have shown that in Finland, <strong>the</strong> Swedish-speaking minority
owns more social capital than <strong>the</strong> Finnish-speaking majority (Hyyppä and Mäki, 2000b, 2003, Nyqvist
et al, 2008, Hyyppä, 2010). The present new observation <strong>of</strong> <strong>the</strong> language group differences in internet
behavior seems to be a consequence <strong>of</strong> differences in <strong>the</strong> amount <strong>of</strong> social capital.
It can also be speculated that Swedish speakers have higher self-confidence and, <strong>the</strong>refore, <strong>the</strong>y are
better prepared meeting o<strong>the</strong>r people face-to-face. They are most likely more accustomed to personal
contacts and meetings due to <strong>the</strong>ir traditional culture and lifestyle. Consequently, <strong>the</strong>y do not need
virtual communication through <strong>the</strong> internet to express negative feelings; or, it is also possible that <strong>the</strong>y
do not have as many negative feelings as Finnish speakers seem to have.
As well as ICT user behavior is associated with social capital, it is also associated with intellectual
capital context. In spite <strong>of</strong> <strong>the</strong> perception that ICT and ICT user behavior is such a critical source <strong>of</strong>
value, <strong>the</strong>re has not been comprehensive attempts to explicitly evaluate or discuss <strong>the</strong> intellectual
capital component <strong>of</strong> it. However, human competencies, relationships and trust are <strong>the</strong> most
important elements contributing to a stabile intellectual capital base; <strong>the</strong>refore it is <strong>of</strong> outmost
importance to increase <strong>the</strong> understanding <strong>of</strong> ICT user behavior. ICT behavior is strongly associated
with human capital, e.g.: innovation capacity, creativity, know-how, learning capacity, and with
structural capital, e.g.: general use <strong>of</strong> information technologies, organizational learning capacity.
Relational capital is also involved with ICT user behavior, e.g.: contacts and links with o<strong>the</strong>r people,
partners and customers. On <strong>the</strong> whole, our findings in ICT behavior suggest that investment in people
and studying different culture’s ICT behavior are important factors in intellectual capital context,
particularly in <strong>the</strong> current context <strong>of</strong> rapid technological development.
Acknowledgements
This study was supported by a grant from <strong>the</strong> Swedish Cultural Foundation in Finland.
References
Hyyppä, M.T. (2010). Healthy Ties. Social Capital, Population Health and Survival. New York: Springer.
430

Jukka Surakka et al.
Hyyppä, M.T.and Mäki, J., (2001 a). Why do Swedish-speaking Finns have longer active life? An area for social
capital research. Health Promotion International, 16, 55–64.
Hyyppä, M. T. and Mäki, J.(2001 b). Individual level relationships between social captial and self-rated health in
bilingual community. Preventive medicine, 32, 148-155.
Hyyppä, M. T.and Mäki, J. (2003). Social participation and health in a community rich in stock <strong>of</strong> social capital.
Health Education Research, 18(6), 770–779.
Katz, Y. and Golbeck, J. (2006). Social network-based trust in prioritized default logic. <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong>
Twenty-First National <strong>Conference</strong> onArtificial Intelligence (AAAI-06).
Koskinen, S.and Martelin, T., (2003). Why is mortality low among <strong>the</strong> Swedish-speaking minority in Finland?
Yearbook <strong>of</strong> Population Research in Finland 39, pp.51–31.
Leikas, J. (2009). Life-based design: Fom <strong>of</strong> life as a foundation for ICT-design for older adults. Jyväskylä studies
in computing 105. Jyväskylä: University <strong>of</strong> Jyväskylä Press.
Leikas, J. and Saariluoma, P. (2008). Worth and mental contents in designing for aging citizens' form <strong>of</strong> life.
Gerontehcnology, 7, 305-318.
McRae, K.D., (1997). Conflict and compromise in multilingual societies. Volume 3. Finland. Waterloo (Ont.),
Wilfrid Laurier University Press.
Nyqvist, F. and Martelin, T., (2007). Skillnader i självskattad hälsa mellan svensk- och finskspråkiga in Finland.
[In Swedish with an English summary][Differences in self-reported health <strong>of</strong> Swedish- and Finnish-speakers
in Finland]. Sosiaalilääketieteellinen aikakauslehti. Journal <strong>of</strong> Social Medicine 44, 78–86.
Nyqvist, F., Finnäs, F., Jakobsson, G., Koskinen, S., (2008). The effect <strong>of</strong> social capital on health: The case <strong>of</strong>
two language groups in Finland. Health & Place 14, 347–360.
O’Regan P, Kennedy T, O’Donnell D, Bontis N, Cleary P. Exploring Intellectual Capital Practice in <strong>the</strong> Irish ICT
sector. Report CIMA, Chartered Institute <strong>of</strong> Management Accountants, November 2003
Paxton, P., (2007). Not all association memberships increase trust. A model <strong>of</strong> generalized trust in thirty-one
countries. Social Forces, 86(1), pp. 47-76.
Rotter, J., (1967). A New Scale for <strong>the</strong> Measurement <strong>of</strong> Interpersonal trust. Journal <strong>of</strong> Personality and Social
Psychology, 35, (4), pp. 651-666.
Saariluoma, P. & Leikas, J. (2010). Life-Based Design – an approach to design for life. Global Journal <strong>of</strong>
Management and Business Research, 10, 27-34.
Surakka, J., Hyyppä M.T, Jokivuori, P., Saariluoma, P. (2009) Social trust in Bilingual Communities in Finland.
<strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> <strong>European</strong> <strong>Conference</strong> on Intellectual Capital. Haarlem, The Ne<strong>the</strong>rlands 28-29.4.2009
pp.452-457. Academic Publishing Limited Reading, UK, http://academic-conferences.org/2-proceedingshtm.
Wittgenstein, L. (1958). Philosophical investigations. Oxford: Basil Blackwell.
Yuki, M., Maddux, W.W., Brewer, M.B., Takemura, K. (2005). Cross-cultural differences in relationship- and
group-based trust. Personality and Social Psychology Bulletin, 31, 48-62.
431

Personal Knowledge Management (PKM) and Personal
Employability Management (PEM) – Concepts Based on
Competences
Marzena Świgoń
University <strong>of</strong> Warmia and Mazury, Olsztyn, Poland
marzena.swigon@uwm.edu.pl
Abstract: The purpose <strong>of</strong> this paper is to highlight a common basis <strong>of</strong> two concepts: Personal Knowledge
Management (PKM) and employability. PKM is an interdisciplinary concept, connected with management
science, information science, information technology etc. The basis <strong>of</strong> this concept is individual’s competences
and skill development, which are needed to knowledge and information management. Employability is related to
human resource management and concerns <strong>the</strong> extent to which people possess <strong>the</strong> skills and o<strong>the</strong>r attributes to
find and stay in work <strong>of</strong> <strong>the</strong> kind <strong>the</strong>y want. In this paper both concepts are brief characterised, including <strong>the</strong>ir
definitions, development and current models. Through a review <strong>of</strong> relevant literature <strong>the</strong> paper discusses
relations between PKM and employability. The paper finds that <strong>the</strong> common basis <strong>of</strong> both concepts are
competences and skills <strong>of</strong> individuals among o<strong>the</strong>rs: social, technological, communication and learning. That is
why definitions, typologies and kinds <strong>of</strong> competences and skills are presented. The paper suggests that <strong>the</strong>re is
<strong>the</strong> strong link between PKM and self-perceived employability, here called Personal Employability Management
(PEM). PEM could be defined as a kind <strong>of</strong> self-perceived and self-management skills and competences. Because
<strong>of</strong> <strong>the</strong> changes in public employment policy, accelerating changes in economics and <strong>the</strong> competition <strong>of</strong> workforce
in global labour markets, <strong>the</strong> idea <strong>of</strong> Personal Employability Management seems powerful. The fact is,
employability <strong>of</strong> today’s knowledge workers is not stable. The hypo<strong>the</strong>sis <strong>of</strong> this paper is that PKM might be a
support for self-perceived employability. If individuals will develop PKM skills and competences, <strong>the</strong>y will be able
to manage <strong>the</strong>ir own carrier more successful. Fur<strong>the</strong>rmore, both concepts are important not just at individual
level. They are <strong>of</strong> benefit to organizations, as well. Organizations use personal knowledge <strong>of</strong> employees (a part
<strong>of</strong> intellectual capital) to building knowledge repositories, which are <strong>the</strong> most important competitive advantage
resource. Employers benefit by employment <strong>of</strong> competent people, people with PKM skills.
Keywords: employability, personal knowledge management, competences, skills
1. Introduction
The knowledge economy, globalisation, turbulent environments (economic, political etc.), changing
organisational structures have an unquestionable influence on individuals, <strong>the</strong>ir attitudes, views and
careers. Today individuals are responsible for managing <strong>the</strong>ir own careers. They are encouraged to
embrace career self-management ra<strong>the</strong>r than relying on <strong>the</strong> organisation for career planning and job
security (Clarke 2008). Traditional careers, linked to organization, have disappeared. Contemporary
careers, e.g. protean career (Hall 1996), boundary less, are personalized, based on knowledge and
lifelong learning.
Personal Knowledge Management (PKM) is a relatively new concept, created around 10 years ago
(Avery et al. 2001), connected with management science (knowledge management and intellectual
capital), information science and information technology. The basis <strong>of</strong> this concept is skill
development, i.e. information skills, personal, social, cognitive which are needed to management <strong>of</strong>
knowledge in all spheres <strong>of</strong> human life. The concept <strong>of</strong> employability has a longer tradition than PKM,
stems from a half <strong>of</strong> <strong>the</strong> 20th century and is related to human resource management (Van der Heijde
and Van der Heijden 2006). It concerns <strong>the</strong> extent to which people possess <strong>the</strong> skills and o<strong>the</strong>r
attributes to find and stay in work <strong>of</strong> <strong>the</strong> kind <strong>the</strong>y want. The fact is, employability <strong>of</strong> today’s
knowledge workers is not stable. The literature indicates that nowadays in changing career contexts
employability has to be managed (Clarke 2008). It seems that knowledge management on personal
level might be a support for employability, in o<strong>the</strong>r words PKM enhances employability. The aim <strong>of</strong>
this paper is to highlight <strong>the</strong> common points <strong>of</strong> both concepts, because hi<strong>the</strong>rto, apart from <strong>the</strong> single
mention (Truch 2001), <strong>the</strong>y are not reflected in <strong>the</strong> literature. Around 10 years ago Truch (2001: 102)
suggested that managing personal knowledge as a basic competence could be “<strong>the</strong> key to tomorrow’s
employability”. This paper suggests that <strong>the</strong>re is <strong>the</strong> strong link between PKM and self-perceived
employability, here called Personal Employability Management (PEM). PEM could be defined as a
kind <strong>of</strong> self-perceived and self-management skills and competences, which are related to <strong>the</strong> work
context. Because <strong>of</strong> <strong>the</strong> changes in public employment policy, accelerating changes in economics and
<strong>the</strong> competition <strong>of</strong> workforce in global labour markets, <strong>the</strong> idea <strong>of</strong> Personal Employability
Management seems powerful.
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Marzena Świgoń
The paper is organized as follows: first some <strong>of</strong> <strong>the</strong> definitions <strong>of</strong> terms: knowledge, skills and
competences are cited. Second, <strong>the</strong> selective literature review in scope to both concepts are
described. Next, <strong>the</strong> relations between <strong>the</strong>m are pointed out. Finally some practical and future
research implications are suggested. The relationship between PKM and PEM remain <strong>the</strong>oretical.
Fur<strong>the</strong>r research to test <strong>the</strong> models <strong>of</strong> PKM and PEM is planned and will be reported on at a later
date.
2. Definition <strong>of</strong> terms, types <strong>of</strong> competences
The terms: knowledge, skills and competences (KSC) - occurring in a variety <strong>of</strong> PKM and
employability descriptions – do not have universal definitions. Never<strong>the</strong>less, in this paper some
examples <strong>of</strong> definitions are cited.
According to The <strong>European</strong> Parliament and <strong>the</strong> Council <strong>of</strong> <strong>the</strong> <strong>European</strong> Union <strong>European</strong> Union
(2008, Annex I, 2) „knowledge means <strong>the</strong> outcome <strong>of</strong> <strong>the</strong> assimilation <strong>of</strong> information through learning.
Knowledge is <strong>the</strong> body <strong>of</strong> facts, principles, <strong>the</strong>ories and practices that is related to a field <strong>of</strong> work or
study. In <strong>the</strong> context <strong>of</strong> <strong>the</strong> <strong>European</strong> Qualifications Framework, knowledge is described as <strong>the</strong>oretical
and/or factual.” Knowledge involves <strong>the</strong> mental processes <strong>of</strong> comprehension, understanding and
learning. It is embodied in humans as <strong>the</strong> capacity to understand, explain, learn etc.
The terms competence and skills are <strong>of</strong>ten, in practice, used simultaneously. It is worth underlining
that skills concern <strong>the</strong> execution <strong>of</strong> single tasks, while competence deals with execution <strong>of</strong> several
different tasks in one domain. The research in scope <strong>of</strong> ontologies for skills and competences towards
an international standard classification are under way (Markowitsch and Plaimauer 2009). The
<strong>European</strong> Commission is developing a <strong>European</strong> Skills, Competences and Occupations taxonomy
(ESCO), which will related to <strong>the</strong> labour market and education sector and will be available in all EU
languages.
According to The <strong>European</strong> Union (2008, Annex I, 2) “skills means <strong>the</strong> ability to apply knowledge and
use know-how to complete tasks and solve problems. In <strong>the</strong> context <strong>of</strong> <strong>the</strong> <strong>European</strong> Qualifications
Framework, skills are described as cognitive (involving <strong>the</strong> use <strong>of</strong> logical, intuitive and creative
thinking) or practical (involving manual dexterity and <strong>the</strong> use <strong>of</strong> methods, materials, tools and
instruments); competence means <strong>the</strong> proven ability to use knowledge, skills and personal, social
and/or methodological abilities, in work or study situations and in pr<strong>of</strong>essional and personal
development. In <strong>the</strong> context <strong>of</strong> <strong>the</strong> <strong>European</strong> Qualifications Framework, competence is described in
terms <strong>of</strong> responsibility and autonomy.” Although <strong>the</strong>se definitions are “vague, partly contradictory”
(Markowitsch and Plaimauer 2009) <strong>the</strong>y show <strong>the</strong> hierarchy <strong>of</strong> terms. In abovementioned definitions
competence is an overriding term for skills and for knowledge.
Fur<strong>the</strong>rmore, competence could be an overriding term for o<strong>the</strong>r terms too, e.g. behaviours. According
to Boyatzis “a competency is defined as a capability or ability. It is a set <strong>of</strong> related but different sets <strong>of</strong>
behaviour organized around an underlying construct called ‘intent’. The behaviours are alternate
manifestations <strong>of</strong> <strong>the</strong> intent, as appropriate in various situations or times [...] The threshold clusters <strong>of</strong>
competencies are: expertise and experience; knowledge (i.e. declarative, procedural, functional and
metacognitive) and an assortment <strong>of</strong> basic cognitive competencies, such as memory and deductive
reasoning” (2008: 6; 2009).
It is worth noting that <strong>the</strong>re has been debate about <strong>the</strong> difference between competency (American
approach) and competence (British approach). According to Winterton (2009) competency
(competencies in <strong>the</strong> plural) is most <strong>of</strong>ten used to denote characteristics <strong>of</strong> an individual that are
associated with superior performance in a job. Similarly competence (competences in <strong>the</strong> plural) is
most <strong>of</strong>ten used to describe what a person needs to know and be able to do in order to undertake <strong>the</strong>
tasks associated with a particular occupation. In this sense, prevalent in <strong>the</strong> UK, competence is
assessed in terms <strong>of</strong> a person’s ability to demonstrate performance to <strong>the</strong> standards required <strong>of</strong>
employment in a work context. Sometimes <strong>the</strong> American approach is described as an “input”
(attributes <strong>of</strong> an individual) and <strong>the</strong> British approach as an “output” (demands <strong>of</strong> <strong>the</strong> job). Moreover,
<strong>the</strong> terms competence and competency are frequently used interchangeably or <strong>the</strong> more
comprehensive approaches to competence that include job activities as well as individual
characteristics are proposed (Winterton 2009: 684). For example A<strong>the</strong>y and Orth (1999: 216) define
“competency” as “a set <strong>of</strong> observable performance dimensions, including individual knowledge, skills,
attitudes, and behaviours, as well as collective team, process, and organizational capabilities, that [...]
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provide <strong>the</strong> organization with sustainable competitive advantage”. In this paper this comprehensive
approach has been assumed, because <strong>of</strong>ten it is difficult to distinguish between worker-oriented
characteristic and job-oriented characteristic. Occupational features and person characteristics are
both a kind <strong>of</strong> mix <strong>of</strong> knowledge, skills, abilities, attitudes and behaviours.
The term ‘competence’ (single, without fur<strong>the</strong>r adjective) is problematic, because it is most commonly
used as an umbrella term for demonstrating requisite knowledge and skills as well as appropriate
behaviour in a work context. According to <strong>the</strong> unified typology <strong>of</strong> KSC (Winterton and Stringfellow
2005), <strong>the</strong>re are four dimensions <strong>of</strong> competences: cognitive competence (knowledge and
understanding), functional competence (skills), social competence (attitudes and behaviours) and
meta-competence. Meta-competence is ra<strong>the</strong>r different from <strong>the</strong> first three dimensions since it is
concerned with facilitating <strong>the</strong> acquisition <strong>of</strong> <strong>the</strong> o<strong>the</strong>r substantive competences. The term “metacompetence”
was used as <strong>the</strong> apex <strong>of</strong> <strong>the</strong>se three dimensions in graphical holistic competence model
(Winterton 2009: 691). For comparison, in “TENCompetence Project” (2008), Information Society
Technologies (IST) project founded by <strong>the</strong> <strong>European</strong> Commission, a different distinction between
variery <strong>of</strong> competences classes has been adopted, namely: 1) cognitive competence (knowledge); 2)
functional competence (skills or competencies); 3) personal competence (e.g. intelligence, flexibility);
4) ethical competence (attitudes); 5) trans-/metacompetences (e.g. communication skills).
Similarly, <strong>the</strong>re is no universal typology <strong>of</strong> so called “basic skills”. They can be grouped into three
categories (Winterton and Stringfellow 2005): 1) behavioural and personal skills (e.g. flexibility, self
learning, motivation and commitment, decision making); 2) cross section and basic work and technical
skills (e.g. quality awareness, entrepreneurship, work and project organisation); 3) s<strong>of</strong>t and method
skills (e.g. communication and moderation, languages and culture, collaboration, creative, information
handling, documentation and presentation). According to <strong>the</strong> authors this typology could be reconciled
with <strong>the</strong> abovementioned unified typology <strong>of</strong> KSC since all <strong>of</strong> <strong>the</strong> behavioural and personal skills
would appear as social competences; cross section and technical skills are mostly functional
competences (with some cognitive); s<strong>of</strong>t and method skills are a combination <strong>of</strong> functional and social
(and meta-) competences.
For <strong>the</strong> purpose <strong>of</strong> this paper – to compare two concepts: PKM and employability – it is important to
highlight that in <strong>the</strong> first concept (PKM) all terms (KSC) have a broader meaning <strong>the</strong>n in <strong>the</strong> second,
which is related to a work context only. Personal Knowledge Management could be useful not only at
work, but in a private life as well. The PKM is more universal concept, connected with effective
problem solving in all spheres <strong>of</strong> activity.
3. Personal Knowledge Management
PKM is a conceptual framework, blending technology, personal skills, processes and methodology,
PKM is <strong>of</strong>ten viewed as shifting <strong>the</strong> responsibility for personal learning, growth, and knowledge
sharing from <strong>the</strong> corporate to individual level (Jefferson 2006). It is defined as a set <strong>of</strong> skills and
attitudes that lead to more effective cognition, communication, collaboration, creativity, problem
solving, lifelong learning, social networking, leadership and <strong>the</strong> like (Pauleen 2009). PKM aspires to
foster <strong>the</strong> development and utilization <strong>of</strong> personal knowledge and competencies (Pircher 2010).
The term Personal Knowledge Management has been used for <strong>the</strong> first time in 1998 as <strong>the</strong> name for
a set <strong>of</strong> workshops for MBA students at UCLA Anderson School <strong>of</strong> Management, and <strong>the</strong>n in Tabor
School <strong>of</strong> Business at Millikin University. The goal <strong>of</strong> <strong>the</strong>se workshops was to learn how to cope with
information overload using technology. Workshop topics included among o<strong>the</strong>rs: skills <strong>of</strong> information
categorizing and classifications (introduced by S. R. Ranganathan, H. E. Bliss, M. Dewey, Ch. A.
Cutter), which stem from Library and Information Science (LIS); and information organizing and
management due to information technology. The authors <strong>of</strong> PKM workshops stressed that appropriate
information storing enables <strong>the</strong> transformation <strong>of</strong> information into personal knowledge (Frand and
Hixon 1998; Avery et al. 2001; Frand and Lippincott 2002). There were seven information skills
initially identified: 1) retrieving information – ga<strong>the</strong>ring from print and electronic sources, through
experimentation and oral inquiry, as well as a wide range <strong>of</strong> discipline-specific techniques; 2)
evaluating information – selecting, determining quality and relevance <strong>of</strong> pieces <strong>of</strong> information; 3)
organizing information – making <strong>the</strong> connections to link pieces <strong>of</strong> information, skills <strong>of</strong> syn<strong>the</strong>sis and
analysis; 4) collaborating around information – listening, showing respect for <strong>the</strong> understanding <strong>of</strong>
o<strong>the</strong>r’ ideas, building win/win relationships and resolving conflicts; 5) analyzing information –
extracting meaning out <strong>of</strong> date; 6) presenting information – understanding <strong>of</strong> audience, rhetoric skills;
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Marzena Świgoń
and 7) securing information – developing and implementing practices that help to assure <strong>the</strong>
confidentiality, integrity and actual existence <strong>of</strong> information (Avery et al. 2001, see also Świgoń 2009).
From <strong>the</strong> beginning <strong>of</strong> this concept <strong>the</strong> question is, what <strong>the</strong> adjective “personal” in PKM means.
According to Avery et al. (2001), “personal” knowledge is not a private knowledge intended to be
learned and kept within <strong>the</strong> individual. They assumed that <strong>the</strong> individual person using PKM’s seven
skills “is central to <strong>the</strong> collective process <strong>of</strong> managing knowledge in groups, in organizations and in
society” (Avery et al. 2001). “Personal” is connected with self-awareness <strong>of</strong> one’s own abilities and
expertise within a public sphere <strong>of</strong> action.
More recently, <strong>the</strong> important contribution into this problem has been made. Namely, <strong>the</strong>re were three
categories <strong>of</strong> PKM identified. According to Zhang (2009) PKM consists <strong>of</strong>: 1) (PK)M, which denotes
<strong>the</strong> management <strong>of</strong> personal knowledge; 2) P(KM), which represents <strong>the</strong> knowledge management
from a personal perspective and 3) (PKM) - <strong>the</strong> intersection <strong>of</strong> <strong>the</strong>m both, which represents <strong>the</strong>
management <strong>of</strong> personal knowledge from an individual’s perspective. The author emphasized that in
<strong>the</strong> categories <strong>of</strong> PKM, P(KM) does not necessarily have to deal with personal knowledge and can
describe an individual’s management <strong>of</strong> organisational knowledge for achieving personal objectives.
In o<strong>the</strong>r words, <strong>the</strong> term “personal knowledge” in <strong>the</strong> PKM concept has a very broad meaning. The
personal knowledge <strong>of</strong> individual knowledge worker consists <strong>of</strong> his subjective, private knowledge
(regarding private and pr<strong>of</strong>essional life) and universal, objective knowledge (public, community,
organizational). Zhang (2009) mentioned two interconnected strategies: personalising organisational
knowledge and “organisationalising” personal knowledge. During <strong>the</strong>se cyclic processes <strong>the</strong> personal
knowledge <strong>of</strong> individuals is transformed into <strong>the</strong> organisational knowledge and <strong>the</strong>n individualised to
become <strong>the</strong> personal knowledge <strong>of</strong> o<strong>the</strong>r individuals.
Lately <strong>the</strong> new model PKM 2.0 was proposed (Cheong Tsui 2010) which consists <strong>of</strong> four components:
Personal Information Management (PIM), Personal Knowledge Internalization (PKI), Personal
Wisdom Creation (PWC) and Inter-Personal Knowledge Transferring (IKT). In <strong>the</strong> light <strong>of</strong> this and
o<strong>the</strong>r PKM models (Świgoń 2010) <strong>the</strong> most important issue are skills and competences <strong>of</strong> individuals.
4. Employability and PEM
The literature <strong>of</strong> this subject can be divided into three areas <strong>of</strong> work: 1) employability <strong>of</strong> <strong>the</strong> workforce,
2) employability as human resource strategy and 3) employability <strong>of</strong> individuals (Rothwell, Jewell and
Hardie 2009). First perspective on employability at a national workforce level is related to government
policy or national-level “skills” agendas. It is stemmed from concerns about <strong>the</strong> changing nature <strong>of</strong>
work and employment at <strong>the</strong> end <strong>of</strong> <strong>the</strong> 20 th century. Second perspective on employability within
human resource management (HRM) and <strong>the</strong> psychology <strong>of</strong> work and careers is related to <strong>the</strong> notion
<strong>of</strong> employability as <strong>the</strong> ability <strong>of</strong> individuals to retain or get jobs. This notion is based on skills and
personal flexibility acquired through employment. Third perspective, most popular in UK, is connected
with <strong>the</strong> ability <strong>of</strong> <strong>the</strong> university sector to provide graduates with <strong>the</strong> skills employers need
(“employability skills”).
In <strong>the</strong> second and <strong>the</strong> third perspective, <strong>the</strong> closest to this paper, employability is defined as “<strong>the</strong>
ability to keep <strong>the</strong> job one has or to get <strong>the</strong> job one desires” (Rothwell and Arnold 2007: 25). At an
individual level employability can be defined “in terms <strong>of</strong> skills and abilities, attitudes and behaviours,
as a current state, a process or a future outcome, and individual characteristic made up <strong>of</strong> <strong>the</strong> sum <strong>of</strong>
an individual’s job related skills, or as a reflection <strong>of</strong> <strong>the</strong> individual’s position within <strong>the</strong> labour market”
(Clarke 2008: 262).
This specific type <strong>of</strong> employability – self-perceived employability <strong>of</strong> individuals - is strongly connected
with <strong>the</strong> PKM concept. For <strong>the</strong> purpose <strong>of</strong> this paper <strong>the</strong> term Personal Employability Management
(PEM) has been introduced. PEM could be defined as a kind <strong>of</strong> self-perceived and self-management
skills and competences in a work context.
Employability is a critical requirement for enabling competitive advantage and career success at <strong>the</strong>
individual level. It is <strong>of</strong>ten considered only as an individual’s responsibility, like in <strong>the</strong> above mentioned
definitions. On <strong>the</strong> o<strong>the</strong>r hand, it is known that employability is as dependent on context as on <strong>the</strong>
individual. In o<strong>the</strong>r words it is determined by factors within <strong>the</strong> control <strong>of</strong> <strong>the</strong> individual but also by
factors that are outside <strong>of</strong> his/her control (Clarke 2008). To <strong>the</strong>se last factors belong: individual
characteristics (age, gender, marital status, ethnicity, health) and labour market characteristics
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(number and type <strong>of</strong> available jobs). Although PEM does not include factors that are outside <strong>of</strong>
individual control, it is obvious that <strong>the</strong>se factors influence on individual ability to employability
management.
The notion <strong>of</strong> employability as <strong>the</strong> ability <strong>of</strong> individuals to retain or get jobs is connected with <strong>the</strong>
competence-based approach. According to Van der Heijde and Van der Heijden (2006: 453)
employability is defined as “<strong>the</strong> continuous fulfilling, acquiring or creating <strong>of</strong> work through <strong>the</strong> optimal
use <strong>of</strong> competences”. In this approach to employability five dimensions are pointed out: 1)
occupational expertise; 2) anticipation and optimization; 2) personal flexibility; 4) corporate sense; and
5) balance. The first dimension <strong>of</strong> employability consists <strong>of</strong> pr<strong>of</strong>essional knowledge and skills.
Occupational expertise constitutes a substantial element <strong>of</strong> employability and is seen as a significant
human capital factor for <strong>the</strong> vitality <strong>of</strong> organizations. The second and third dimensions concern
adapting to changes (“adaptability”) and developments at various levels (job, career). Anticipation and
optimization concern preparing for future work changes. Personal flexibility relates to adaptability to all
kinds <strong>of</strong> changes in <strong>the</strong> internal and external labour market. Corporate sense is an employee’s ability
to participation and performance in different workgroups, such as working teams, <strong>the</strong> occupational
community and o<strong>the</strong>r networks. Balance is defined as compromising between opposing employers’
interests as well as one’s own work and private employee’s interests and between employers’ and
employees’ interests. Van der Heijde and Van der Heijden (2006) presented a reliable and valid
instrument for measuring employability, based on <strong>the</strong> five-dimensional conceptualization <strong>of</strong>
employability.
Recently o<strong>the</strong>r authors reported on <strong>the</strong> development <strong>of</strong> an employability scales. Rothwell and Arnold
(2007) reported on <strong>the</strong> development and validation <strong>of</strong> a self-report measure <strong>of</strong> individuals’ perceived
employability. The scale consisted <strong>of</strong> items which were intended collectively to reflect employability
within and outside <strong>the</strong> person’s current organisation. The authors concluded that self-perceived
employability can usefully be thought <strong>of</strong> as ei<strong>the</strong>r a unitary construct, or one with two related
components – internal and external employability.
Moreover, <strong>the</strong> scale for examining <strong>the</strong> expectations and self-perceptions <strong>of</strong> employability was tested
among students (Rothwell, Herbert, Rothwell, 2008; Rothwell, Jewell, Hardie, 2009). This is
connected with <strong>the</strong> third abovementioned perspective on employability. Student self-perceived
employability scale consisted <strong>of</strong> statements regarding 4 elements: student’s perception <strong>of</strong> university,
field <strong>of</strong> study, self-belief and <strong>the</strong> state <strong>of</strong> <strong>the</strong> external labour market. Ano<strong>the</strong>r model <strong>of</strong> self-perceived
employability regarding graduates was developed by Pool and Sewell (2007). The essential
components <strong>of</strong> this model were: career development learning, experience, degree (subject,
knowledge and skills), generic skills and emotional intelligence. Providing students with opportunities
to develop all <strong>the</strong>se elements will result in development <strong>of</strong> self-efficacy, self-confidence and selfesteem,
<strong>the</strong> links to employability, and - in <strong>the</strong> light <strong>of</strong> this paper - to PEM.
5. Skills and competences – a common point <strong>of</strong> PKM and employability
In this section <strong>the</strong>re are compared skills and competences <strong>of</strong> both concepts.
To <strong>the</strong> skills connected with employability (Mallough, Kleiner, 2001: 118-119) belong: management
skills (decision making, problem solving, trouble shooting, conceptualising, analysing, planning, coordinating,
delegating), computer and o<strong>the</strong>r technical skills (ability to utilise computers as an
analytical, decision-making and processing tool, programming), communications skills (speaking,
mediating, negotiation, speaking foreign languages, listening skills), organisational skills (ability to set
goals and utilise time management and resources to achieve those goals, ability to set priorities and
follow through o responsibilities), specific skills (job specific skills: selling, assembly, financial, writing,
budgeting etc.), general (attention to detail, reliability, courtesy, quality <strong>of</strong> work, co-operation),
psychological (self-motivation, initiative, positive attitude, tolerance etc.), interaction and networking
(participation in social clubs, community work or recreational activities), educational and vocational
training (specialised training, level <strong>of</strong> degrees, prestige <strong>of</strong> <strong>the</strong> school), skills gained from <strong>the</strong>
educational process (applied ma<strong>the</strong>matics, locating information, teamwork, research, applied
technology), interviewing and resume skills (self-confident, objectives, job-related interests,
experience etc.).
In <strong>the</strong> aforementioned initial PKM publication (Avery et. al 2001) <strong>the</strong> set <strong>of</strong> seven information skills
was outlined. The similar skills, but connected with “information and ideas”, were described by Barth
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(2004); <strong>the</strong>re were: 1) accessing (question formation, search techniques, research strategies, inquiry);
2) evaluating (source identification, qualification and cultivation, validation, judgment, intuition); 3)
organizing (email filtering, discard, outlining, networking); 4) analyzing (analytical techniques, testing
hypo<strong>the</strong>sis); 5) collaborating (emotional intelligence, facilitation, relationship management,
leadership); 6) conveying (written and spoken word, unspoken) and 7) securing (self-discipline, threat
awareness). Wright (2005) suggested that PKM involves a combination <strong>of</strong> four kinds <strong>of</strong> competences:
1) cognitive (experimentation, prototyping, modelling); 2) information (accessing, organizing,
structuring, presenting); 3) social (collaborating, communicating); and 4) learning and development
competences (problem definition, analytical skills). The author emphasised <strong>the</strong> role <strong>of</strong> individual,
social and organizational context in applying <strong>of</strong> competences. Individual enablers include motivation,
risk, innovation; social are related to trust, support <strong>of</strong> community <strong>of</strong> practice; and organizational
enablers include flexibility, autonomy, supportive leadership and trust as well. In <strong>the</strong> PKM literature
<strong>the</strong>re is a lot <strong>of</strong> o<strong>the</strong>r typologies <strong>of</strong> skills and competences (Świgoń 2010).
From <strong>the</strong>se selected descriptions <strong>of</strong> skills and competences one can point out that a lot <strong>of</strong> <strong>the</strong>m are
common for both concepts. In o<strong>the</strong>r words, skills and competences are <strong>the</strong> main convergence <strong>of</strong> PKM
and PEM. However, <strong>the</strong> problem is that <strong>the</strong> authors used different, not unified terms and typologies.
This issue must be undertaken by specialists at <strong>European</strong> or international level. For <strong>the</strong> purpose <strong>of</strong>
this paper, in order to show <strong>the</strong> common “skills and competences” (using this phrase is safer) <strong>of</strong> both
concepts, <strong>the</strong> following typology, based on all aforementioned examples, is proposed:
1. Personal skills and competences: self-knowledge (<strong>of</strong> strong and weak points),
pr<strong>of</strong>essional/occupational knowledge, expertise, writing, reading, foreign languages; motivation
and commitment, active attitude, problem solving, decision making, creativity, analysis, learning
and self-development, reflecting etc.
2. Interpersonal skills and competences: knowledge about macro/world and micro/local
environment; listening, talking, communicating, conveying; teamwork, collaborating creating <strong>of</strong>
relationships, socializing, coordinating etc.
3. Information and Technological skills and competences: knowledge about information sources;
information retrieving, storing, sending, presenting, distributing, securing, evaluating, organizing
etc.
It is worth repeating, that skills and competences in <strong>the</strong> PKM have a broader application <strong>the</strong>n in <strong>the</strong>
PEM, because <strong>the</strong>y could be utilised not only in <strong>the</strong> job/career management context, for example as a
support <strong>of</strong> employability, but in <strong>the</strong> private life too.
6. In conclusion
PKM and employability were, hi<strong>the</strong>rto, <strong>the</strong> subject <strong>of</strong> <strong>the</strong> separate studies. However, <strong>the</strong>y are strongly
connected, especially due to emphasizing <strong>the</strong> impact <strong>of</strong> abovementioned skills and competences on
individual’s effectiveness. In today’s information society and turbulent environments all citizens have
to be engaged in lifelong learning and self-development. Personal Knowledge Management as a
concept based on wide range <strong>of</strong> individuals skills and competences undoubtedly can be a support <strong>of</strong>
employability. Skills and competences are <strong>the</strong> crucial factors leading to success in self management
including knowledge management, career management and employability management. Although
both concepts are focused on individuals, <strong>the</strong>y involve benefits for whole organizations, firms and
enterprises. Recently Cheong and Tsui (2010) in an exploratory empirical study proved that <strong>the</strong> roles
<strong>of</strong> PKM are positively correlated to <strong>the</strong> values <strong>of</strong> PKM for individuals and organizations. It was also
found that <strong>the</strong> values <strong>of</strong> PKM for individuals are correlated to <strong>the</strong> values <strong>of</strong> PKM for <strong>the</strong> organization.
The more effective employee’s work is <strong>the</strong> more improved <strong>the</strong> organizational productivity can be.
Individuals use organizational knowledge to augment <strong>the</strong>ir own personal knowledge, which can be
used in or outside <strong>the</strong>ir home organization. On <strong>the</strong> o<strong>the</strong>r hand, organizations use personal knowledge
<strong>of</strong> employees (a part <strong>of</strong> intellectual capital) to building knowledge repositories, which are <strong>the</strong> most
important competitive advantage resource. Employers benefit by employment <strong>of</strong> competent and
qualified people, people with PKM skills and competences. Talent management is <strong>the</strong> biggest
challenge for today’s employers.
In <strong>the</strong> future research <strong>the</strong> empirical studies in <strong>the</strong> scope <strong>of</strong> PKM and PEM seem necessary. We don’t
know how individuals manage <strong>the</strong>ir own personal knowledge and employability. Which <strong>of</strong> <strong>the</strong>se skills
and competences could be managed at an individual level and which involve supporting from outside,
o<strong>the</strong>r people, groups and organizations? We need research in a scope <strong>of</strong> scales/instruments for
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measure self-perceived skills and competences regarding PKM and PEM. The authors own empirical
studies in this subject are under way.
References
A<strong>the</strong>y, T.R. and Orth, M.S. (1999) “Emerging competency methods for <strong>the</strong> future”, Human Resource
Management, Vol 38, pp 215–226.
Avery, S., Brooks R., Brown J., Dorsey P. and O’Conner M. (2001) “Personal Knowledge Management:
framework for integration and partnerships”, Paper presented at <strong>the</strong> ASCUE 2001 <strong>Conference</strong> <strong>Proceedings</strong>,
North Myrtle Beach, SC, June, [on-line], http://fits.depauw.edu/ascue/<strong>Proceedings</strong>/2001/avery.html .
Barth, S., (2004) “Self-organization: taking a personal approach to KM”, [on-line],
http://www.knowledgeboard.com/download/3285/pkm-chapter-stevebarth.pdf .
Boyatzis, R. E. (2008) “Competencies in <strong>the</strong> 21 st century”, Journal <strong>of</strong> Management Development, Vol 27 No. 1,
pp 5-12.
Cheong, R.K.F. and Tsui, E. (2010) “The roles and values <strong>of</strong> personal knowledge management: an exploratory
study”, VINE: The Journal <strong>of</strong> Information and Knowledge Management Systems, Vol 40, No. 2, pp 204-227.
Clarke, M., (2008) “Understanding and managing employability in changing career contexts”, Journal <strong>of</strong>
<strong>European</strong> Industrial Training, Vol 32 No. 4, pp 258-284.
The <strong>European</strong> Parliament and <strong>the</strong> Council <strong>of</strong> <strong>the</strong> <strong>European</strong> Union (2008) „Recommendation 2008 <strong>of</strong> on <strong>the</strong>
establishment <strong>of</strong> <strong>the</strong> <strong>European</strong> Qualifications Framework for lifelong learning”, [on-line],
http://ec.europa.eu/education/policies/educ/eqf/rec08_en.pdf .
Frand, J. and Hixon, C. (1998) “Personal Knowledge Management: Who, What, Why, When, Where, How?”, [online],
http://www.anderson.ucla.edu/faculty/jason.frand/researcher/speeches/educom98pkm/ .
Frand J. and Lippincott, A. (2002) “Personal Knowledge Management: a strategy for controlling information
overload”, [on-line], http://www.anderson.ucla.edu/faculty/jason.frand/researcher/articles/info_overload.html.
Hall, D.T. (1996) “Protean careers <strong>of</strong> <strong>the</strong> 21 st century”, Academy <strong>of</strong> Management Executive, Vol X, No. 4, pp 8-
16.
Jefferson, T.L. (2006) “Taking it personally: personal knowledge management”, VINE, Vol 36 No. 1, pp 35-37.
Mallough, S. and Kleiner, B. (2001) “How to determine employability and wage earning capacity”, Management
Research News, Vol 24 No. ¾, pp 118-122.
Markowitsch, J. and Plaimauer, C. (2009). Descriptors for competence: towards an international standard
classification for skills and competences. Journal <strong>of</strong> <strong>European</strong> Industrial Training, Vol 33 No. 8/9, pp 817-
837.
Pauleen, D. (2009) “Personal knowledge management: putting <strong>the</strong> “person” back into <strong>the</strong> knowledge equation”,
Online Information Review, Vol 33 No. 2, pp 221-224.
Pircher, R. (2010) “Targeting <strong>the</strong> Blind Spot: Personal Knowledge Management as an Enabler for Knowledge
Creation and Application”, [on-line], http://2010.personalknowledge.org/home
Pool, L.D. and Sewell, P. (2007) “The key to employability: developing a practical model <strong>of</strong> graduate
employability”, Education + Training, Vol 49, No. 4, pp 277-289.
Rothwell, A. and Arnold, J. (2007) “Self-perceived employability: development and validation <strong>of</strong> a scale”,
Personnel Review, Vol 36 No. 1, pp 23-41.
Rothwell, A., Hervert, I. and Rothwell, F. (2008) “Self-perceived employability: construction and initial validation <strong>of</strong>
a scale for university students”, Journal <strong>of</strong> Vocational Behavior, Vol 73, pp 1-12.
Rothwell, A., Jewell, S. and Hardie, M. (2009) “Self-perceived employability: investigating <strong>the</strong> responses <strong>of</strong> postgraduate
students”, Journal <strong>of</strong> Vocational Behavior, Vol 75, pp 152-161.
Świgoń, M. (2009) “Personal knowledge management (indywidualne zarządzanie wiedzą)”, Paper read at Xth
International Forum for Scientific and Technical Information, Zakopane, Poland, September, [on-line],
http://www.ptin.org.pl/konferencje/10forum/repozytorium/Swigon.pdf .
Świgoń, M. (2010) “Personal Knowledge Management - a set <strong>of</strong> skills and methods” In: History - Archive studies
– Information Science: methodological issues. Ed. by K. Narojczyk, M. Świgoń, M. Wolny. Wydawnictwo
Uniwersytetu Warmińsko-Mazurskiego, Olsztyn, pp 207-213.
TENcompetence project (2008) Information Society Technologies (IST) project founded by <strong>the</strong> <strong>European</strong>
Commission, [on-line], http://tencompetence-project.bolton.ac.uk/node/96/index.html .
Truch, E. (2001) “Managing personal knowledge: <strong>the</strong> key to tomorrow’s employability”, Journal <strong>of</strong> Change
Management, Vol 2 No. 2, pp 102-105.
Van der Heijde, C.M. and Van der Heijden, B.I.J.M. (2006) “A competence-based and multidimensional
operationalization and measurement <strong>of</strong> employability”, Human Resource Management, Vol 45 No. 3., pp
449-476.
Winterton, J. and Stringfellow, E. (2005) “Typology <strong>of</strong> knowledge, skills and competences: clarification <strong>of</strong> <strong>the</strong>
concept and prototype”, [on-line],
http://www.ecotec.com/europeaninventory/publications/method/CEDEFOP_typology.pdf
Winterton, J. (2009) “Competence across Europe: highest common factor or lowest common denominator?”,
Journal <strong>of</strong> <strong>European</strong> Industrial Training, Vol 33 No. 8/9, pp 681-700.
Wright, K. (2005) “Personal knowledge management: supporting individual knowledge worker performance”,
Knowledge Management Research & Practice, Vol 3, pp 156-165.
Zhang, Z. (2009) “Personalising organizational knowledge and organisationalising personal knowledge”, Online
Information Review, Vol 33 No. 2, pp 237-256.
438

World Atlas <strong>of</strong> Intellectual Capital: Concept and
Methodology
Eduardo Tomé
Universidade Lusíada de Famalicão, Portugal
eduardo.tome@clix.pt
Abstract: This paper presents <strong>the</strong> <strong>the</strong>oretical base <strong>of</strong> a future World Atlas on Intellectual Capital (IC). The Atlas
is to be made in an economic perspective. Its first edition, due hopefully in 2012, will describe <strong>the</strong> situation
regarding IC in <strong>the</strong> 60 major world economies. The Atlas will analyse IC through twelve relevant economic
perspectives: demand, supply, equilibrium, price, quantity, market forces, role <strong>of</strong> <strong>the</strong> State, investment, stock,
need, international flows and returns. We believe that <strong>the</strong> Atlas could be important for economic policy analysis
and management, and <strong>the</strong>refore, for <strong>the</strong> wellbeing <strong>of</strong> <strong>the</strong> world population. In order to make <strong>the</strong> Atlas, many
crucial conceptual questions must be addressed. In this paper we outline <strong>the</strong> major ones that we have
encountered until now.
Keywords: intellectual capital, economics, market, public policy, asset, countries
1. Introduction
Intellectual Capital (IC) is a very complex concept. Its appearance in <strong>the</strong> world <strong>of</strong> economics was
mainly due to problems related to accountancy and business value. In <strong>the</strong> early nineties <strong>of</strong> <strong>the</strong> 20 th
century it became obvious that it was important to understand <strong>the</strong> difference between <strong>the</strong> book value
(BV) and <strong>the</strong> market value (MV) <strong>of</strong> companies. The book value was explained by <strong>the</strong> tangible assets
(TA) <strong>of</strong> companies, but to explain <strong>the</strong> market value it was necessary to consider <strong>the</strong> intangible assets
(IA). Consequently, a myriad <strong>of</strong> <strong>the</strong>oretical analysis and case studies were made to account both <strong>the</strong>
value <strong>of</strong> <strong>the</strong> IAs and <strong>the</strong>ir returns. In addition, and in order to find <strong>the</strong> difference between <strong>the</strong> priority
and <strong>the</strong> need <strong>of</strong> IAs, <strong>the</strong> audit <strong>of</strong> IAs became a decisive management topic. All those studies became
more and more important as it was apparent worldwide that in <strong>the</strong> 21 st century intangible assets would
to be a fundamental cause, if not <strong>the</strong> fundamental cause, <strong>of</strong> <strong>the</strong> companies’ competitiveness.
The notion <strong>of</strong> IC was also somehow applied to countries and regions. Some studies have tried to
extend <strong>the</strong> analysis that had been made to companies, by applying <strong>the</strong> same models in relation to
economic spaces. Examples <strong>of</strong> those studies are very well known. Therefore, until now, <strong>the</strong> analysis
<strong>of</strong> IC at a national and regional level has been essentially done by merely trying to account for <strong>the</strong>
stock <strong>of</strong> <strong>the</strong> IC/IA and for <strong>the</strong> return <strong>of</strong> those assets. A very interesting application <strong>of</strong> this way <strong>of</strong>
reasoning has been done by <strong>the</strong> World Bank with <strong>the</strong> Knowledge Economy Indicator (KEI) (World
Bank, 2011).
This situation may be considered as very obvious from a management or accountancy point <strong>of</strong> view,
but we find that it is much less understandable from a policy maker point <strong>of</strong> view. Therefore, here we
try to analyse <strong>the</strong> question <strong>of</strong> how to study IC and IA from a policy maker point <strong>of</strong> view. We think that
<strong>the</strong> analysis should be made in four steps. In step one <strong>the</strong> variables that constitute <strong>the</strong> basic setting <strong>of</strong>
any market, namely: demand, supply, price, quantity and equilibrium, should be defined for IC.
Secondly <strong>the</strong> nature <strong>of</strong> <strong>the</strong> major players in that market (private, public and non-pr<strong>of</strong>itable private)
should be analysed; in particular, <strong>the</strong> way <strong>the</strong> public sector interferes in <strong>the</strong> market <strong>of</strong> IC in every
country (ruling, funding or providing) should be <strong>the</strong> object <strong>of</strong> a close examination. Thirdly, as we
accept that IC is a national asset, we think that it is important to consider <strong>the</strong> notions <strong>of</strong> investment,
stock, return and need. Finally, we think that in a globalized world it is very important to analyse <strong>the</strong>
international flows <strong>of</strong> IC; those flows have (obviously) many consequences in <strong>the</strong> market, relevant
agents and asset.
We believe that if we could have available data on all those variables, for a given country, we could
be able to suggest a public policy on IC for that country. And we think that by having a depiction <strong>of</strong> <strong>the</strong>
situation on IC worldwide we could pr<strong>of</strong>it <strong>of</strong> a good guide for orientating <strong>the</strong> world economy. In
consequence we aim to make, in <strong>the</strong> near future, a “World Atlas on Intellectual Capital”.
In this paper we begin by defining <strong>the</strong> concept <strong>of</strong> IC (2.1); <strong>the</strong>n we describe <strong>the</strong> traditional way <strong>of</strong>
analysing IC (2.2) and we present a new and complementary way <strong>of</strong> analysing IC (2.3). In section 3
we briefly describe <strong>the</strong> four perspectives that we will use in <strong>the</strong> Atlas (3.1) and we explain in detail
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Eduardo Tomé
what we consider to be <strong>the</strong> meaning <strong>of</strong> each variable that will be included in <strong>the</strong> Atlas (3.2). Section 4
contains brief conclusions (41) and some suggestions to fur<strong>the</strong>r research (4.2).
2. Concept and methodology
2.1 Intellectual capital
The concept <strong>of</strong> IC is one that can only be defined by default, or proxys. Some main, very basic and
generally accepted ideas about IC, are <strong>the</strong> following:
IC is a sum <strong>of</strong> Human, Organizational and Social commodities (Edvinsson and Malone, 1997;
Bonfour and Edvinsson, 2005).
IC includes a variety <strong>of</strong> goods and services like education, training, experience, competences,
skills, health, R&D, patents, brands and organizational routines. These goods or services all have
two basic characteristics: <strong>the</strong>y are intangible and <strong>the</strong>y somehow relate to intelligence.
IC is possessed by individuals, companies, organizations, regions and countries.
IC may be divided in Human (i.e. education, training) and Non Human (R&D goods, patents).
Regarding <strong>the</strong> Atlas construction, it should be noted that <strong>the</strong> IC is by itself a sum <strong>of</strong> different types <strong>of</strong>
goods <strong>of</strong> services, means that <strong>the</strong> analysis <strong>of</strong> IC can be done ei<strong>the</strong>r in a
“macroeconomic/aggregative” way or in a “microeconomic/disaggregative” way. In consequence:
In <strong>the</strong> first type <strong>of</strong> analysis we would consider a single market for IC per country, and one situation
for each one <strong>of</strong> <strong>the</strong> 12 relevant variables we mentioned in <strong>the</strong> introduction;
in <strong>the</strong> second type <strong>of</strong> analysis we would consider as many submarkets as <strong>the</strong> many divisions on
<strong>the</strong> concept <strong>of</strong> IC that we would use.
The division <strong>of</strong> IC in smaller subsections would give realism to <strong>the</strong> study, but it would also require
much more data. And, it should not be forgotten, that “macroeconomic/aggregative” analysis, if it is
possible to perform, would be very useful because it would give an unique vision to <strong>the</strong> markets.
2.2 The traditional way <strong>of</strong> studying IC: Accountability and management
The “traditional way” <strong>of</strong> analysing IC is summed in column 2 <strong>of</strong> <strong>the</strong> following Table 1. This perspective
is company based, asset related and short term oriented. The fields that relate to that analysis are
management and accountancy. The basic question is to define <strong>the</strong> relation between MV and BV, and
in consequence, it is important to define IA as an asset and also <strong>the</strong> returns <strong>of</strong> this asset. This
perspective has been applied to companies and organizations, and, residually, to regions and
countries. In this point <strong>of</strong> view, <strong>the</strong> IC is considered to be a part <strong>of</strong> <strong>the</strong> investment, as in any private
business. Therefore, managers and company stakeholders should be interested in IC studies; <strong>the</strong>
labour force could also be interested because <strong>the</strong> IC has consequences to <strong>the</strong> labour market.
2.3 The method <strong>of</strong> analyzing IC to be used in <strong>the</strong> Atlas: Economics and public policy
In order to make <strong>the</strong> Atlas, <strong>the</strong> traditional analysis must be considerably changed. In our perspective,
<strong>the</strong> IC is viewed as a commodity for which <strong>the</strong> national market must be defined. This new perspective
is summarized in <strong>the</strong> third row <strong>of</strong> <strong>the</strong> Table .
We consider <strong>the</strong> IC market defined by 12 variables, namely: demand, supply, equilibrium, price,
quantity, market forces, <strong>the</strong> State, need, investment, stock, flow and return. The meaning <strong>of</strong> each one
<strong>of</strong> those variables is addressed in <strong>the</strong> next subsection (3.2).
It is essential to understand that <strong>the</strong> Atlas represents an extension <strong>of</strong> <strong>the</strong> analysis concerning IC from
<strong>the</strong> management and accountancy perspective to <strong>the</strong> economic perspective. We are interested in
examining <strong>the</strong> variables that define <strong>the</strong> market, and not only in analysing <strong>the</strong> IC as an asset.
Accordingly, we want to find <strong>the</strong> complex societal and long term returns <strong>of</strong> IC and not only <strong>the</strong> short
term returns <strong>of</strong> IC for companies. We want to focus <strong>the</strong> analysis in <strong>the</strong> national perspective and
market perspective <strong>of</strong> IC and not only in <strong>the</strong> company perspective. Fur<strong>the</strong>rmore, we are interested in
supporting <strong>the</strong> possible public policies on <strong>the</strong> IC market and not only in analysing IC from a private
perspective. Therefore, we believe that <strong>the</strong> Atlas would not only interest companies; instead, policy
makers, voters, students, teachers, unions, and any member <strong>of</strong> <strong>the</strong> civil society, with an interest in IC,
may find <strong>the</strong> Atlas useful.
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Table 1: Two complementary methodologies to study IC
Traditional Studies Proposed
Methodology
Basic perspective Accountancy and Management Economics
Basic question Market Value minus Book Value Market <strong>of</strong> IC
Variables Assets Demand, Supply, Price, Quantity,
Equilibrium, Market forces, Role <strong>of</strong>
<strong>the</strong> State, Investment, Stock, Flow,
Needs
Outcomes analysed Revenues (short run) Returns (economic and non
economic, short and long run)
Dominant perspective Company and organization based.
Residually regions and countries
Management perspective Private business
National and market based
Public policy
Investment perspective Company Investment Societal investment
Economic agents that might be
interested
2.4 Complementarity or antagonism?
Managers and stakeholders
Also: own labour force
Policy makers
Also: voters, job-seekers, students,
civil society
We must emphasize that <strong>the</strong> two methodologies here defined are complementary one to ano<strong>the</strong>r. In
fact, we consider that our methodology enlarges <strong>the</strong> traditional one because it not only takes in
account <strong>the</strong> asset/return question, but goes far beyond it. Even more important, we are not interested
in company based and pr<strong>of</strong>it oriented studies, but in micro or macroeconomic and public policy
oriented studies. However, we would be in <strong>the</strong> first row <strong>of</strong> those who defend and confirm <strong>the</strong>
importance and <strong>the</strong> validity <strong>of</strong> <strong>the</strong> “traditional” way <strong>of</strong> thinking about IC. We just believe that it was too
limited and that it should be complemented.
3. The Atlas <strong>of</strong> intellectual capital: A <strong>the</strong>oretical introduction
In this section, are described <strong>the</strong> <strong>the</strong>oretical foundations <strong>of</strong> <strong>the</strong> Atlas. First (3.1) <strong>the</strong> four perspectives
used are briefly discussed: market perspective (3.1.1), agent perspective (3.1.2), asset perspective
(3.1.3) and global perspective (3.1.4). Second (3.2), <strong>the</strong> meaning <strong>of</strong> <strong>the</strong> twelve different variables that
should compose <strong>the</strong> Atlas for each country is explained: demand, supply, price, quantity, equilibrium,
main market forces, role <strong>of</strong> <strong>the</strong> State, investment, stock, return, need and international flows. All <strong>the</strong>
analysis can be made in <strong>the</strong> aggregate and disaggregate perspectives as defined in 2.1.
3.1 The four perspectives used in <strong>the</strong> Atlas
3.1.1 Market perspective: demand, supply, price, quantity, equilibrium.
We use a very basic definition <strong>of</strong> market. We assume that <strong>the</strong>re is a demand (defined by <strong>the</strong>
economic agents that want <strong>the</strong> good) and a supply (constituted by <strong>the</strong> economic agents that produce
<strong>the</strong> good) for IC. Supply and demand are explained in terms <strong>of</strong> quantity, and made at different prices,
generating equilibrium or disequilibrium. The demand is explained by some kind <strong>of</strong> utility and <strong>the</strong>
supply by some kind <strong>of</strong> return.
3.1.2 Agent perspective: main market forces and role <strong>of</strong> <strong>the</strong> State
Given <strong>the</strong> definition <strong>of</strong> market we use, and <strong>the</strong> rationale for demand and supply that we accept (see
3.1.1, <strong>the</strong> market could be explained by private actions) and includes only private agents, namely
private consumers seeking utility and private companies seeking pr<strong>of</strong>its. However <strong>the</strong> participation <strong>of</strong>
<strong>the</strong> public bodies and <strong>of</strong> <strong>the</strong> “third sector” is frequent. Public intervention is explained by market
failures and equity concerns. In particular, <strong>the</strong> public sector may legislate, fund or produce policies on
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IC. The intervention <strong>of</strong> <strong>the</strong> “third sector” is explained by <strong>the</strong> failures <strong>of</strong> both <strong>the</strong> private and <strong>the</strong> public
sectors.
3.1.3 Asset perspective: investment, stock, return and need.
Accordingly to our own definition <strong>of</strong> IC, we will study a mix <strong>of</strong> capital goods or services. Therefore, we
consider that <strong>the</strong> purchase will be made in <strong>the</strong> present moment, but <strong>the</strong> return will be felt in <strong>the</strong> future,
presumably long time afterwards. That purchase should be considered as an investment and it would
accrue to <strong>the</strong> existing stock value <strong>of</strong> IC. Fur<strong>the</strong>rmore, given that IC is capital, we assume that its
depreciation should be measured. Given that IC relates to organizations, <strong>the</strong> depreciation should not
only be physical but also social (unlearning and degeneration <strong>of</strong> competences and skills). Finally, we
assume that, <strong>the</strong> need for IC should be defined as <strong>the</strong> difference between <strong>the</strong> actual level <strong>of</strong> IC <strong>of</strong> an
agent and <strong>of</strong> those <strong>of</strong> world leaders in <strong>the</strong> field.
3.1.4 Global perspective: international flows
One <strong>of</strong> <strong>the</strong> basic features <strong>of</strong> IC is its relationship with globalization. The IC market <strong>of</strong> a given country
is balanced by inflows from o<strong>the</strong>r countries and by outflows to o<strong>the</strong>r countries. The migration <strong>of</strong> IC is
explained by basic models <strong>of</strong> attraction and repulsion, as it happens with <strong>the</strong> movements <strong>of</strong> labour or
<strong>the</strong> movements <strong>of</strong> companies.
It is interesting to note that this fourth perspective has an impact in <strong>the</strong> o<strong>the</strong>r three perspectives,
namely:
The inflows increase <strong>the</strong> supply and <strong>the</strong> outflows decrease <strong>the</strong> demand <strong>of</strong> IC.
The inflows add to <strong>the</strong> main market forces and should be welcomed by <strong>the</strong> State; <strong>the</strong> outflows
decrease <strong>the</strong> main market forces and should be considered as a problem to <strong>the</strong> State.
The private forces may feel threatened by <strong>the</strong> inflows, even if <strong>the</strong>y may use <strong>the</strong>m for <strong>the</strong>ir own
pr<strong>of</strong>it. The private forces should be worried about <strong>the</strong> outflows <strong>of</strong> IC, even if <strong>the</strong>y could contribute
to that flow by migrating <strong>the</strong>mselves, with good reason.
The inflows increase <strong>the</strong> stock <strong>of</strong> IC and <strong>the</strong> outflows decrease <strong>the</strong> stock <strong>of</strong> IC.
3.2 The meaning <strong>of</strong> <strong>the</strong> variables that compose <strong>the</strong> Atlas
The major problem we face in order to make <strong>the</strong> Atlas is that IC can be only measured by
approximation. As stated in 1.1, <strong>the</strong> concept <strong>of</strong> IC is in itself so diverse that we may use one
aggregate perspective or a very large number <strong>of</strong> disaggregate perspectives.
3.2.1 Supply
Each one <strong>of</strong> <strong>the</strong> set <strong>of</strong> commodities defined in 2.1 as IC is currently <strong>of</strong>fered by <strong>the</strong> society. In this
context, <strong>the</strong> three more important questions to ask are <strong>the</strong> following: 1) Who <strong>of</strong>fers <strong>the</strong>se
commodities? 2) How can that <strong>of</strong>fer be measured? and 3) What do we mean when we say that a
country has a high level <strong>of</strong> supply <strong>of</strong> IC? Here are our current answers to <strong>the</strong>se three questions:
First, as a process, <strong>the</strong> supply <strong>of</strong> Intellectual Capital is defined by <strong>the</strong> actions made by <strong>the</strong>
National systems <strong>of</strong> Welfare State. A Welfare State (WS) is a set <strong>of</strong> policies organized to solve
social problems in <strong>the</strong> public good (Esping Andersen, 1990). To provide IC is one <strong>of</strong> <strong>the</strong>se
problems. Indeed, IAs tends to exist in societies which develop some very elaborate types <strong>of</strong>
social infrastructures. Those social infrastructures relate to Education, Health, R&D and Basic
Infrastructures. They are only provided if <strong>the</strong> society has a Welfare State. They generate internally
<strong>the</strong> intangible assets that will be used by companies and organizations. Several types <strong>of</strong> Welfare
State exist: Social Democratic, Conservative, Liberal, Latin and Socialist (Deacon, 2000; Esping
Andersen, 1990; Ferrara et al., 2000). In each type <strong>of</strong> Welfare State, different forms <strong>of</strong> Welfare
Mixes exist, defining different balances between <strong>the</strong> market major players (3.2.6). In a Liberal
Welfare State <strong>the</strong> private sector is dominant; in a Socialist Welfare State <strong>the</strong> public sector is
almost exclusive. In a previous study we found that Social Policies are <strong>the</strong> hidden face <strong>of</strong> <strong>the</strong> IC,
because in practice <strong>the</strong> best WSs are those that generate more IC (Tomé, 2008).
Second, <strong>the</strong> supply <strong>of</strong> IC can be defined by variables as <strong>the</strong> absolute levels <strong>of</strong> schooling
enrolment, and in particular at <strong>the</strong> highest levels, by <strong>the</strong> volume <strong>of</strong> training (formal and informal),
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<strong>the</strong> numbers <strong>of</strong> doctors or hospitals, <strong>the</strong> numbers <strong>of</strong> computers, net users, telephones and
Televisions, <strong>the</strong> numbers <strong>of</strong> patents and brands and <strong>the</strong> numbers <strong>of</strong> Researchers in R&D.
Third, <strong>the</strong> ultimate result <strong>of</strong> all <strong>the</strong> supply <strong>of</strong> IC is <strong>the</strong> “Knowledge Worker” (KW),
A KW being someone who uses intensively IC. When we consider that a country that has a large
supply <strong>of</strong> IC, we mean that its workforce is healthy and educated, and that its organizations are
known as world leaders. The reverse happens in countries that lack <strong>the</strong> supply <strong>of</strong> IC.
It should be noted that <strong>the</strong>re is a difference between being an intensive producer <strong>of</strong> IC and a large
producer <strong>of</strong> IC. In fact, a negative relation seems to exist between intensity and quantity. IC
seems to be better and more intensively produced in small countries like <strong>the</strong> Nordic. This is
probably explained by <strong>the</strong> decreasing returns to scale which defines <strong>the</strong> provision <strong>of</strong> quality
services.
3.2.2 Demand
The same questions that were addressed in relation to <strong>the</strong> Supply <strong>of</strong> IC, should be put forward in
relation with <strong>the</strong> demand <strong>of</strong> IC.
First, IC is demanded by <strong>the</strong> individuals and organizations <strong>of</strong> a given country. The demand for IC
depends <strong>of</strong> <strong>the</strong> activity <strong>of</strong> organizations and <strong>of</strong> <strong>the</strong> welfare <strong>of</strong> individuals. This means that <strong>the</strong>
demand for IC should represent more <strong>the</strong> Business side and it should act as a counterpart <strong>of</strong> IC
Supply, which, as we just saw, is centred in <strong>the</strong> Welfare State. However, <strong>the</strong> distinction is
somehow unclear), because one organization may supply and demand IC at <strong>the</strong> same time. As
we will see in <strong>the</strong> next section, we believe that <strong>the</strong> supply and <strong>the</strong> demand <strong>of</strong> IC are very closely
related;
Second, <strong>the</strong> demand must be measured using <strong>the</strong> same scale as <strong>the</strong> supply, in order to permit
market comparison;
Third, <strong>the</strong> demand for IC should be measured by <strong>the</strong> level and number <strong>of</strong> Knowledge workers that
<strong>the</strong> economy <strong>of</strong> a given country wants to employ in a given year. When we say that a country has
a large demand for IC, we mean that <strong>the</strong> people and organizations that work in that country desire
intensively each one <strong>of</strong> <strong>the</strong> partial constituents <strong>of</strong> <strong>the</strong> IC notion, as defined in 2.1. When we say
that <strong>the</strong> country has a small demand <strong>of</strong> IC we mean <strong>the</strong> opposite.
3.2.3 Price
By price <strong>of</strong> IC we mean <strong>the</strong> amount <strong>of</strong> funds that a member <strong>of</strong> <strong>the</strong> public (someone who demands <strong>the</strong>
good or service) needs to obtain one unit <strong>of</strong> <strong>the</strong> good. This amount <strong>of</strong> funds may be spent by <strong>the</strong>
private consumer, but may also be awarded by <strong>the</strong> public sector or even by a third sector
organization.
In economic terms and when <strong>the</strong>re is equilibrium, <strong>the</strong> price should be equal to <strong>the</strong> amount <strong>of</strong> funds
that <strong>the</strong> providers <strong>of</strong> <strong>the</strong> good or service want to obtain from each unit <strong>of</strong> IC. In consequence:
If <strong>the</strong> IC is considered in a macroeconomic perspective we may say that in some countries <strong>the</strong> IC
is expensive in comparison with o<strong>the</strong>r countries, measured in dollars or in Power Purchase
Parities (PPP);
However if <strong>the</strong> IC is considered in a microeconomic perspective, we find different prices in each
country, for each type <strong>of</strong> IC constituent;
Finally, we must be aware that <strong>the</strong> current prices in a country may be very low (e.g. Bangladesh),
and due to inefficiency or inexistence <strong>of</strong> supply, <strong>the</strong> possible price for <strong>the</strong> IC constituent in that
market can be socially unbearable.
3.2.4 Quantity
By quantity we mean <strong>the</strong> amount <strong>of</strong> IC sold and purchased in <strong>the</strong> market. Again, it can be assumed
that <strong>the</strong>re is a macroeconomic quantity <strong>of</strong> IC for <strong>the</strong> IC as a whole, or several microeconomic
quantities for each one <strong>of</strong> <strong>the</strong> constituents <strong>of</strong> <strong>the</strong> IC. The microeconomic analysis would deepen and
diversify <strong>the</strong> first macro impression.
Given <strong>the</strong> relationship between price and demand or price and supply, it should be possible, for each
country, to define a Demand curve and a Supply curve. Thus:
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In <strong>the</strong> demand curve, more price would correspond to less quantity demanded;
In <strong>the</strong> supply curve, more price would signify more quantity <strong>of</strong>fered.
3.2.5 Equilibrium and disequilibrium in <strong>the</strong> IC market
In order to be able to identify an equilibrium or disequilibrium, <strong>the</strong> supply and <strong>the</strong> demand in <strong>the</strong> IC
market have to be measured in <strong>the</strong> same unity. As with any o<strong>the</strong>r good or service, when <strong>the</strong> demand
and supply are at equal levels an equilibrium exists in <strong>the</strong> IC market. Equilibriums in IC markets have
been studied in a macroeconomic way (Ashton and Green, 1996). In <strong>the</strong>ory and in practice at least
three different levels <strong>of</strong> equilibrium exist in <strong>the</strong> national markets <strong>of</strong> IC: high level, medium level and
low level.
In <strong>the</strong> equilibrium <strong>of</strong> high level <strong>the</strong>re is a virtuous cycle <strong>of</strong> investment in IC. Investments are made
by organizations (demanding IC) because <strong>the</strong>y expect Knowledge workers to be available. In
return, people and <strong>the</strong> Welfare States invest (and <strong>the</strong>refore supply) in IC because <strong>the</strong>y expect that
<strong>the</strong> investment will guarantee a future job and a prosperous social life. This type <strong>of</strong> equilibrium is
characteristic <strong>of</strong> developed economies which, significantly, are those that have <strong>the</strong> most important
and developed form <strong>of</strong> Welfare States;
In <strong>the</strong> equilibrium <strong>of</strong> low level <strong>the</strong>re is a vicious cycle regarding <strong>the</strong> investment in IC. Investments
(and demand) by organizations in IC are small because <strong>the</strong>y do not expect Knowledge workers to
exist in <strong>the</strong> economy. At <strong>the</strong> same time, individuals and <strong>the</strong> Welfare State tend to invest little in IC
because <strong>the</strong>y do not perceive <strong>the</strong> investment as worthy. This type <strong>of</strong> situation is characteristic <strong>of</strong>
countries with low income and low Human Development Indicator (HDI) figures, which are also
<strong>the</strong> ones that have <strong>the</strong> weakest form <strong>of</strong> Welfare States, if any; in fact, in many <strong>of</strong> those countries it
may be assumed that only a “Welfare Society” exists, in which <strong>the</strong> public and <strong>the</strong> Non-
Governmental Organizations (NGOs) find ways <strong>of</strong> satisfying <strong>the</strong> basic social needs <strong>of</strong> welfare, but
not even a Welfare State;
A third type <strong>of</strong> equilibrium exists, particularly in emerging countries. In those countries <strong>the</strong> supply
<strong>of</strong> IC tends to be increasing rapidly, in order to match <strong>the</strong> growing in <strong>the</strong> demand for IC, that
results from <strong>the</strong> strong process <strong>of</strong> economic development. This third type <strong>of</strong> equilibrium is related
to a weak form <strong>of</strong> Welfare States, named a “Quasi-Welfare State”, in which <strong>the</strong> different market
forces try to begin to cope, providing <strong>the</strong> social goods demanded, among which is IC.
It may also happen that <strong>the</strong> IC market is not balanced.
An unbalance may occur in one any sub-market <strong>of</strong> IC, as defined in 2.1;
In high equilibriums, in particular in times <strong>of</strong> expansion, <strong>the</strong> demand tends to be higher than <strong>the</strong>
supply and some countries tend to attract <strong>the</strong> IC from o<strong>the</strong>rs less developed; this happened in <strong>the</strong>
USA and Western Europe in <strong>the</strong> sixties <strong>of</strong> <strong>the</strong> 20 th century;
In low equilibriums, <strong>the</strong> demand tends to be smaller than <strong>the</strong> supply and <strong>the</strong> few IC assets tend to
flee to more advanced countries; a country may generate Knowledge workers that are not used
by <strong>the</strong> economic structure. That situation happened after <strong>the</strong> fall <strong>of</strong> <strong>the</strong> Berlin Wall in <strong>the</strong> Eastern
<strong>European</strong> economies, and is happening now with <strong>the</strong> young graduates from <strong>the</strong> Sou<strong>the</strong>rn
countries <strong>of</strong> <strong>the</strong> Eurozone.
The difference between a developed country (high equilibrium), an emergent country (middle
equilibrium) and a developing country (low equilibrium) would be that <strong>the</strong> demand and supply curves
would relate to more quantities in <strong>the</strong> developed countries than in <strong>the</strong> emerging or developing
countries. In relation to <strong>the</strong> price, <strong>the</strong> issue is more complex. Due to supply problems, a commodity <strong>of</strong>
IC nature may be more expensive in a poor country than in a rich one. Anyway, <strong>the</strong> cross point
between demand and supply curves would be higher (at least in quantity grounds) in a developed
country, than in an emerging country or in a developing country.
3.2.6 Market forces
The supply and <strong>the</strong> demand <strong>of</strong> IC are made by a different set <strong>of</strong> economic agents. Namely:
IC is provided by companies, <strong>the</strong> public sector or <strong>the</strong> third sector organizations; <strong>the</strong> way <strong>the</strong>se
agents interact and relate defines <strong>the</strong> “Welfare mix” (WM) in <strong>the</strong> provision <strong>of</strong> IC; we are refereeing
here to schools, hospitals, training centers, internet organizations, when producing IC (see 3.2.1);
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IC is demanded by individuals, and also by <strong>the</strong> three types <strong>of</strong> sectors (public, private and non
pr<strong>of</strong>itable private) previously mentioned, as a way <strong>of</strong> satisfying <strong>the</strong>ir needs; we are refereeing
here to <strong>the</strong> cells <strong>of</strong> <strong>the</strong> economic tissue, being <strong>the</strong>m ei<strong>the</strong>r individuals or organizations, when
consuming IC.
Three important points must be made:
The difference between developed, developing and emerging countries is that in <strong>the</strong> first <strong>the</strong> WM
is very developed, in <strong>the</strong> second is almost inexistent and in <strong>the</strong> third is only taking shape (see
3.2.1 and 3.2.5);
In developed countries a great difference exists in <strong>the</strong> way <strong>the</strong> WM is organized, generating
different types <strong>of</strong> Welfare States (WSs) (see 3.2.1);
Even if <strong>the</strong> demand and <strong>the</strong> supply are made by <strong>the</strong> three sectors that constitute <strong>the</strong> WS (public
private and non pr<strong>of</strong>itable private), as an activity and it is very different to supply IC or to demand
IC
3.2.7 The role <strong>of</strong> <strong>the</strong> State
IC has important societal consequences, and IC is surely a matter <strong>of</strong> social policy. The public
intervention in <strong>the</strong> IC market may be explained by market failures or by equity matters. The public
intervention may be made by rulings, funding or provision. Social programs linked to IC are usually
evaluated by <strong>the</strong>ir direct results, ei<strong>the</strong>r in physical (persons supported) or in financial (money spent)
terms. Impact studies can define <strong>the</strong> economic consequences <strong>of</strong> <strong>the</strong> operations (Tomé, 2005).
The scope and extension <strong>of</strong> <strong>the</strong> public intervention in <strong>the</strong> IC market depends <strong>of</strong> two factors:
In <strong>the</strong> developed countries it depends on <strong>the</strong> type <strong>of</strong> WS or WM; a Liberal form <strong>of</strong> WS has much
less public intervention that a Social Democratic or a Socialist form <strong>of</strong> WS;
In <strong>the</strong> world, as a whole, it <strong>the</strong> depends on <strong>the</strong> existence or <strong>the</strong> absence <strong>of</strong> <strong>the</strong> WMs; countries in
which no WS exists or in which only a quasi WS exists, have comparatively less public
intervention in <strong>the</strong> IC market than <strong>the</strong> countries having high levels <strong>of</strong> WS.
3.2.8 Need
The need <strong>of</strong> Intellectual Capital is measured by <strong>the</strong> gap between <strong>the</strong> level <strong>of</strong> IC that exists in <strong>the</strong>
society and level that should exist in order to <strong>the</strong> country to be one <strong>of</strong> <strong>the</strong> top Knowledge Based
Economies (KBE)s in <strong>the</strong> world. This means that <strong>the</strong>re is a fundamental difference between need and
demand. A simple example that may illustrate such difference is <strong>the</strong> following: in a developing country
<strong>the</strong> demand for IC may be small, because companies and organizations do not want to hire KWs, in
spite <strong>of</strong> <strong>the</strong>ir great need, because <strong>the</strong> level <strong>of</strong> IC would have to increase immensely if <strong>the</strong> country
would become developed and world leader. The need <strong>of</strong> IC may be measured ei<strong>the</strong>r in terms <strong>of</strong>
supply or in terms <strong>of</strong> demand or in terms <strong>of</strong> equilibrium.
3.2.9 Investment
The investment in IC is defined by <strong>the</strong> expenses made by <strong>the</strong> society to increase <strong>the</strong> levels <strong>of</strong> IC. It
may be defined in terms IC as a whole, or for every one <strong>of</strong> its constituents, and it was defined in 2.1
(education, training, health, basic infrastructures, R&D, brands, etc). In some way, <strong>the</strong> investment in
IC is very much related with <strong>the</strong> supply <strong>of</strong> IC, as <strong>the</strong> production <strong>of</strong> any good is related with <strong>the</strong>
previous investment in <strong>the</strong> production function. However, <strong>the</strong> investment in IC is different from <strong>the</strong>
supply <strong>of</strong> IC. The investment is accounted by <strong>the</strong> money spent, but on <strong>the</strong> contrary, <strong>the</strong> supply is
measured by <strong>the</strong> level <strong>of</strong> social structures that ultimately enable <strong>the</strong> existence <strong>of</strong> KWs. Those social
structures are made available in consequence <strong>of</strong> <strong>the</strong> expenditures, but are not equal to those
expenditures. A high investment may generate a high supply, but not necessarily. A high investment
may generate a small supply, if <strong>the</strong> money is not well spent. The supply is <strong>the</strong> first and more basic
outcome <strong>of</strong> <strong>the</strong> investment.
3.2.10 Stock
For each country, in every year, it should be possible to define <strong>the</strong> stock <strong>of</strong> IC. That stock represents
<strong>the</strong> number <strong>of</strong> available items in <strong>the</strong> country for each one <strong>of</strong> <strong>the</strong> parts from which IC is made <strong>of</strong>. That
stock may be defined in Human (workers) and in Non Human (patents, science) terms. It is important
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Eduardo Tomé
to stress that <strong>the</strong> stock <strong>of</strong> IC <strong>of</strong> a country is different from <strong>the</strong> demand, <strong>the</strong> supply and <strong>the</strong> investment)
and it is also different from <strong>the</strong> need <strong>of</strong> IC. For instance, in a developing country, <strong>the</strong> stock may be low
(non existence <strong>of</strong> qualified people or patents), <strong>the</strong> supply may also be low (low level <strong>of</strong> national
production being made), <strong>the</strong> investment may be small (few expenses on IC being done), <strong>the</strong> demand
may also be small (few companies and organizations wanting to come to <strong>the</strong> country), but <strong>the</strong> need
may be very high (because in order to develop <strong>the</strong> country a very significant increase in IC would be
required). The stock <strong>of</strong> IC is increased by <strong>the</strong> investment and by inflows <strong>of</strong> IC, and decreased by <strong>the</strong>
degeneration <strong>of</strong> knowledge and skills, and by <strong>the</strong> outflows <strong>of</strong> IC.
3.2.11 Flows
Significant flows <strong>of</strong> IC are transferred from a country and to ano<strong>the</strong>r. Such flows may be linked to
Human and Non Human IC. Human IC flows are physically represented by <strong>the</strong> migration <strong>of</strong>
Knowledge workers from a given country to ano<strong>the</strong>r. The various types <strong>of</strong> Non Human IC (patents,
brands, etc.) may also be considered as flows <strong>of</strong> IC. Those flows are economically very important,
because <strong>the</strong>y balance <strong>the</strong> market <strong>of</strong> IC in given a country. When excess demand or not enough
supply exists in a country, IC workers should come from abroad. In practice <strong>the</strong>se movements occur
when a country, like <strong>the</strong> USA, receives highly qualified engineers from India. When <strong>the</strong>re is an excess
in supply and not enough demand, IC workers have a tendency to go abroad. This second type <strong>of</strong>
movements occurs when countries, like Ukraine, export highly qualified people to Western Europe
because <strong>the</strong>ir own economy cannot manage to employ <strong>the</strong>m. When intellectual property is lacking in
a country it may be imported from abroad; when Intellectual Property is <strong>of</strong> good quality it may be
exported to <strong>the</strong> outside world.
3.2.12 Returns
Returns from IC are benefits that are socially perceived. They may include increases in wages or
employment rates, for workers, and in productivity, product quality and exports for firms. At a national
level, <strong>the</strong> IC has an impact in <strong>the</strong> level <strong>of</strong> average income; <strong>the</strong> quality <strong>of</strong> living and happiness may
also be regarded as a consequence <strong>of</strong> <strong>the</strong> IC. Calculations on <strong>the</strong> impact <strong>of</strong> <strong>the</strong> various parts in IC in
<strong>the</strong> different economies have already been done. It would be important in <strong>the</strong> Atlas to put <strong>the</strong>m
toge<strong>the</strong>r in a list and to make some useful comparisons.
4. Concluding remarks
4.1 Conclusions
We hope to have explained <strong>the</strong> <strong>the</strong>oretical basis, <strong>the</strong> methodology and <strong>the</strong> usefulness <strong>of</strong> an World
Atlas <strong>of</strong> Intellectual Capital. This paper is <strong>the</strong> first step in a long road in which we hope to continue.
4.2 Suggestions to fur<strong>the</strong>r studies
We plan report our fur<strong>the</strong>r studies in a book, first concerning 60 countries, and <strong>the</strong>n to make o<strong>the</strong>r
editions including as many o<strong>the</strong>r countries as possible. It will be a large team effort. We hope to
deliver <strong>the</strong> first edition (delete <strong>the</strong> space) in 2012. Suggestions and inputs on this matter are
thankfully) welcomed.
References
Ashton D., Green F (1996) Education, Training and <strong>the</strong> Global Economy Edward Elgar; Cambridge UK; pp 100-4.
Bonfour, A.; Edvinsson L (eds) (2005) Intellectual Capital for Communities Butterworth-Heinemann. Elsevier.
Oxford. UK.
Deacon B. (2000) “Eastern <strong>European</strong> welfare states: <strong>the</strong> impact <strong>of</strong> <strong>the</strong> politics <strong>of</strong> globalization” Journal <strong>of</strong> Social
<strong>European</strong> Policy, Vol. 10 No.2, pp. 146-61.
Edvinsson, L.; Malone, M. (1997) Intellectual Capital. Harper Business
Esping Andersen G. (1990) The Three Worlds <strong>of</strong> Welfare Capitalism. Princeton. Princeton University Press.
Ferrera, M; Hemerijck, A.; Rhodes, M; (2000) The Future <strong>of</strong> Social Europe. Recasting Work and Welfare in <strong>the</strong>
New Economy. Celta Editora. Oeiras (Portugal)
Tomé E. (2005) “Evaluation Methods in Social Policy” Boletín Informativo de Trabajo Social (Bits), Revista Digital
– Escola Universitaria de Trabajo Social de Cuenca – Universidade de Castilla la Mancha - numero 8,
Setembro 2005-
Tomé E. (2008) (“The Hidden Face <strong>of</strong> Intellectual Capital: Social Policies” Journal <strong>of</strong> Intellectual Capital, Vol.) 9,
issue 3, pp. 499-518.
World Bank (2011) KEI and KI Indexes: KAM 2009. http://info.worldbank.org/etools/kam2/KAM_page5.asp-
446

Relational Capital Management <strong>of</strong> new Ventures Through
Virtual Embeddedness and Social Media
Eleni Magdalini Vasileiadou 1 , Magdalena Missler-Behr 1 and Sebastian Ullrich 2
1
Brandenburg University <strong>of</strong> Technology, Cottbus, Germany
2
SRH Hochschule, Berlin, Germany
vasileia@tu-cottbus.de
magdalena.missler-behr@tu-cottbus.de
ullrich@asperado.de
Abstract: New forms <strong>of</strong> data storage and transfer as well as <strong>the</strong> new methods to communicate, collaborate and
exchange knowledge at diminishing transaction costs over <strong>the</strong> world-wide-web have revolutionised networking,
knowledge creation and innovation processes in <strong>the</strong> Web 2.0 era. Virtual embeddedness signifies <strong>the</strong> possibility
to draw upon pay-per-use computing resources and a variety <strong>of</strong> customised web services and applications. The
facilitated utilisation <strong>of</strong> S<strong>of</strong>tware-as-a-Service and in particular social media (SM) applications enables effective
networking on platforms and in virtual communities in social as well as in business terms. Such networking
processes lead to <strong>the</strong> accumulation <strong>of</strong> social, relational and intellectual capital, as <strong>the</strong>y facilitate information and
knowledge exchange, integration and creation. As information and knowledge sharing, collaboration and
socialising take virtual dimensions, opportunities and threats arise for enterprises regarding relational capital
management (RCM) as well as knowledge and value creation. Most new ventures are keen on utilising SM for
internal and external communication and collaboration purposes. Through networking in <strong>the</strong> web, building up
virtual relationships and exchanging virtual knowledge through forums, blogs and online communities, RCM can
be accomplished efficiently and effectively, provided that <strong>the</strong> targeted customers, partners and potential
shareholders are keen on going online and utilising SM as well. In this context, <strong>the</strong> question arises: how can new
ventures improve <strong>the</strong>ir RCM through <strong>the</strong> utilisation <strong>of</strong> innovative information and communication technologies
(ICT) and SM? To answer this question, ventures have to grasp <strong>the</strong> potential <strong>of</strong> web technologies and SM and
assess <strong>the</strong>ir appropriability to achieve relationship-specific goals. They need to be aware <strong>of</strong> SM risks in order to
exploit chances and avert threats that arise through SM use. After an analysis <strong>of</strong> <strong>the</strong> properties <strong>of</strong> social and
relational capital and <strong>of</strong> <strong>the</strong> different forms <strong>of</strong> embeddedness <strong>of</strong> organisations, <strong>the</strong> utilisation <strong>of</strong> SM for RCM
purposes, <strong>the</strong> implementation <strong>of</strong> a SM strategy and <strong>the</strong> example <strong>of</strong> a German e-commerce venture that took
advantage <strong>of</strong> web technologies to build up and manage relational capital in virtual and physical dimensions are
discussed. The paper also tries to visualise how virtual embeddedness and SM influence knowledge, value and
reputation creation and <strong>the</strong> social and relational capital <strong>of</strong> organisations by means <strong>of</strong> a conceptual model.
Keywords: social capital, relational capital, Web 2.0, social media, new ventures
1. Introduction
Entrepreneurs draw upon <strong>the</strong> value <strong>of</strong> <strong>the</strong>ir social and relational capital lying within embedded
network ties, such as goodwill, reputation and trust, to access tangible and intangible resources,
exchange information and knowledge and create value (Shane and Cable, 2002; Packalen, 2007;
Zhang et al, 2008; Hormiga, Batista-Canino and Sánchez-Medina, 2010). While most research papers
concentrate on <strong>the</strong> positive effects <strong>of</strong> physical embeddedness on new ventures, Morse, Fowler and
Lawrence (2007) explain how virtual embeddedness can help to overcome <strong>the</strong> liabilities <strong>of</strong> newness
(Stinchcombe, 1965), which reflect <strong>the</strong> new ventures’ lack <strong>of</strong> resources and capacities. To overcome
<strong>the</strong>se liabilities, mostly consisting <strong>of</strong> <strong>the</strong> lack <strong>of</strong> social and financial capital, new ventures have to
develop organisational systems (e.g. roles and procedures), reputation and trustworthiness and to
build up <strong>the</strong>ir relational capital through target-oriented activities.
In <strong>the</strong> following sections, overviews and definitions <strong>of</strong> social and relational capital, physical and virtual
embeddedness, innovative Web 2.0 technologies and social media (SM) illustrate <strong>the</strong>ir benefits and
risks for (not only new) ventures. Finally, after <strong>the</strong> discussion <strong>of</strong> <strong>the</strong> utilisation <strong>of</strong> SM by Elbenwald
GmbH, a German young venture that used <strong>the</strong> advantages <strong>of</strong> <strong>the</strong> web to accumulate relational and
financial capital, a conceptual model about <strong>the</strong> impact <strong>of</strong> virtual embeddedness on <strong>the</strong> creation <strong>of</strong>
intellectual and relational capital is drawn as a conclusion <strong>of</strong> literature review and made observations.
2. Social capital and relational capital
The term “social capital” (SC) stands for a very broad, amazingly elastic concept, credited with
heterogeneous <strong>the</strong>oretical backgrounds by social, political, business and organisational sciences
(Adler and Kwon, 2002: 17; Woolcock, 1998). SC consists <strong>of</strong> a social structure and cultural context
that shapes and influences social and economic actions <strong>of</strong> embedded actors through <strong>the</strong>
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development <strong>of</strong> expectations and norms (Coleman, 1988; Putnam, 1995). SC comprises opportunities
and obligations, reciprocity norms, privileged access or exclusion from information and financial
credit, as well as social status, image, reputation and trust. SC is embodied in relations <strong>of</strong> actors and
<strong>the</strong>ir networks (figure 1), formed by ties (figure 2) and nodes (figure 1). The conflicted term “capital”
can be viewed as metaphor and mechanism (Tamaschke, 2003: 250) as <strong>the</strong> high degree <strong>of</strong>
intangibility and appropriability <strong>of</strong> social relationships implicates that <strong>the</strong>y can be purposefully utilised
to obtain future benefits. SC influences <strong>the</strong> success <strong>of</strong> actors that can draw upon <strong>the</strong>ir relationships to
reach <strong>the</strong>ir goals. But SC cannot be exclusively owned or measured and can easily be destroyed, as
it lies in <strong>the</strong> space between acting entities, in network ties as well as in <strong>the</strong> structural holes between
<strong>the</strong>m (Burt, 1992).
Figure 1: Types, properties, benefits and risks <strong>of</strong> networks
Different approaches to define SC have focused on <strong>the</strong> substance, sources and effects <strong>of</strong> social
capital for individual as well as collective authors: <strong>the</strong> substance is ‘<strong>the</strong> goodwill that is engendered by
<strong>the</strong> fabric <strong>of</strong> social relations that can be mobilized to facilitate action’ (Adler and Kwon, 2002: 17); <strong>the</strong>
sources reside in <strong>the</strong> social structure. Opportunities, motivations and abilities that lead to social and
economic transactions and to <strong>the</strong> enactment <strong>of</strong> private or communal goals are developed in that
structure. Solidarity, information and influence made available through social relations result to both
positive and negative effects, as SC encompasses benefits and risks (Adler and Kwon, 2002). The
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Eleni Magdalini Vasileiadou et al.
development <strong>of</strong> SC, taking place as a by-product <strong>of</strong> communication and o<strong>the</strong>r exchange activities,
requires a focus (or focal actor) around which joint activities are organised (Nohria, 1992).
Taking an enterprise as a focus, <strong>the</strong> concept <strong>of</strong> SC can be transposed in <strong>the</strong> relational capital (RC)
domain <strong>of</strong> intellectual capital (IC). There are interrelations between SC and IC <strong>of</strong> an organisation.
Facets <strong>of</strong> SC, such as relationships and <strong>the</strong> norms <strong>of</strong> reciprocity that arise from <strong>the</strong>m constitute
intangible assets. ‘Claim[s] to future benefits that [do] not have a physical <strong>of</strong> financial embodiment’
(Lev, 2001: 5) are embodied in both SC and IC. SC contributes to <strong>the</strong> creation <strong>of</strong> human capital (HC)
(Coleman 1988) and IC (Nahapiet and Ghoshal, 1998), while <strong>the</strong> accumulation <strong>of</strong> SC and IC is based
on HC, which comprises social and pr<strong>of</strong>essional skills and competences <strong>of</strong> an organisation’s
members. McElroy (2002: 32) proposed to integrate SC in <strong>the</strong> concept <strong>of</strong> IC as an IC domain <strong>of</strong> an
organisation, but his model was not adopted. As <strong>the</strong> umbrella term SC implicates public good qualities
and a broader cultural context, <strong>the</strong> term “relational capital” (RC) prevailed in contemporary IC
research as a successor <strong>of</strong> “customer capital” (Edvinsson and Malone, 1997) to describe <strong>the</strong> SC <strong>of</strong>
organisations. RC, as established in <strong>the</strong> course <strong>of</strong> <strong>European</strong> Union projects, terms <strong>the</strong> third, most
intangible domain <strong>of</strong> IC besides <strong>the</strong> domains <strong>of</strong> human and structural capital. These three domains
represent ‘<strong>the</strong> intelligence found in human beings, organisational routines and network relationships,
respectively’ (Bontis, 1999: 440) and include intangible resources and activities that represent
knowledge stocks and flows (Pike, Rylander and Roos, 2002: 658). Through <strong>the</strong> flows <strong>of</strong> knowledge
enabled through relations, IC factors influence each o<strong>the</strong>r and <strong>the</strong> knowledge, value and success <strong>of</strong>
<strong>the</strong> organisation (Vasileiadou and Missler-Behr, 2010: 600).
RC stands for <strong>the</strong> external structure family <strong>of</strong> intangible assets, comprising stocks and flows <strong>of</strong>
relationships to stakeholders, communities and <strong>the</strong> public, <strong>the</strong> firm reputation (image) that can change
over time and <strong>the</strong> value <strong>of</strong> relationships that can also partly be translated into legal property such as
trademarks and brand names (Sveiby, 2001: 346). Firms are embedded in <strong>the</strong>ir environment and
maintain a set <strong>of</strong> relationships with o<strong>the</strong>r embedded agents, on which <strong>the</strong>y partly depend to create
value from <strong>the</strong>ir business idea, succeed, grow and survive. Not only ra<strong>the</strong>r strong relationships to
customers, suppliers, shareholders and allies but also weaker ones to agents located fur<strong>the</strong>r from <strong>the</strong>
closer competitive environment such as government agencies and trade unions as well as to certain
community groups and <strong>the</strong> mass media are <strong>of</strong> interest (De Castro, Sáez and López, 2004: 578). The
latter relationships also lead to assuming social responsibility and <strong>the</strong>refore obtaining social
legitimisation <strong>of</strong> <strong>the</strong> firm’s activities and <strong>the</strong>refore influence <strong>the</strong> corporate reputation and image
significantly.
3. Forms <strong>of</strong> physical and virtual embeddedness
Embeddedness describes <strong>the</strong> constellation, structure and quality <strong>of</strong> focal actors’ ties (Granovetter,
1973; Zukin and Di Maggio, 1990). Its structural, relational and cognitive dimensions (figure 3)
embody <strong>the</strong> respective dimensions <strong>of</strong> SC and RC <strong>of</strong> organisations, as interpreted in <strong>the</strong> context <strong>of</strong> IC
research. Structural embeddedness describes <strong>the</strong> morphology <strong>of</strong> networks configured by <strong>the</strong>
presence or absence <strong>of</strong> ties. It stands for <strong>the</strong> overall connection pattern that describes who and how
can be reached and serves as an appropriate organisation for <strong>the</strong> development <strong>of</strong> SC and RC (figure
3; Granovetter, 1973; Burt, 1992). Relational embeddedness stands for <strong>the</strong> qualities <strong>of</strong> relationships
developed through interactions, such as trust, norms, obligations and expectations. Such qualities
define <strong>the</strong> strength <strong>of</strong> inter-actor ties and influence <strong>the</strong> focal actor’s behaviour (figure 3; Nahapiet and
Ghoshal, 1998). Relational embeddedness also embodies aspects <strong>of</strong> cognitive, cultural and political
embeddedness (hierarchic distribution <strong>of</strong> power and resources). The cognitive embeddedness (figure
3) comprises symbols and frameworks as well as shared understandings, codes, languages and
narratives (Cicourel, 1973) and is also analysed in terms <strong>of</strong> cultural embeddedness (Zukin and Di
Maggio, 1990).
The ‘contextualization <strong>of</strong> economic activity in on-going patterns <strong>of</strong> social relations’ (Dacin, Ventresca
and Beal, 1999: 319) refers to both <strong>the</strong> traditional physical embeddedness <strong>of</strong> actors in a social
structure supported by “face-to-face” interaction and to <strong>the</strong> virtual embeddedness <strong>of</strong> actors consisting
<strong>of</strong> virtually embedded ties, sustained by means <strong>of</strong> electronic ICT (figure 1 and figure 4; Morse, Fowler
and Lawrence, 2007: 142).
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Eleni Magdalini Vasileiadou et al.
Figure 2: Types, properties, benefits and risks <strong>of</strong> ties
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Eleni Magdalini Vasileiadou et al.
Figure 3: The dimensions <strong>of</strong> structural, relational and cognitive embeddedness (based on Nahapiet
and Ghoshal, 1998)
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Eleni Magdalini Vasileiadou et al.
Figure 4: Virtual embeddedness (based on Morse, Fowler and Lawrence, 2007)
4. Relational capital management through virtual embeddedness, Web 2.0 and
social media
Nowadays, <strong>the</strong> optimisation <strong>of</strong> virtual embeddedness (VE) constitutes one key factor <strong>of</strong> successful
relationship management (RM). Relationship and knowledge management have been transformed
through <strong>the</strong> internet and new rich-content media based on user interaction and peer-to-peer content
creation. The intensity and rich content <strong>of</strong> relationships based on electronic linkages increase through
<strong>the</strong> boost <strong>of</strong> user interaction triggered by <strong>the</strong> utilisation <strong>of</strong> web technologies outlined by <strong>the</strong> umbrella
term “Web 2.0” (figure 5), which encompasses <strong>the</strong> concept <strong>of</strong> <strong>the</strong> web as a platform for user
participation, cost-effective scalability and usability and harnessing <strong>of</strong> collective intelligence (O’Reilly,
2005). Social media (SM) enable communication, collaboration and formation <strong>of</strong> virtual communities
through computer-mediated communication in digital environments and thus help to build, renew and
maintain RC through virtually embedded ties. Web 2.0 users can establish a variety <strong>of</strong> virtual
connections at low or no cost and easily build (virtual) structural embeddedness, as <strong>the</strong>y can easily
identify and assess potential virtual connections and decide if <strong>the</strong>y should expect benefits from an
ongoing connection and interaction. The identification and assessment <strong>of</strong> potential connections and
relationships is facilitated through <strong>the</strong> dissemination <strong>of</strong> widespread information about actors and <strong>the</strong>ir
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Eleni Magdalini Vasileiadou et al.
(<strong>of</strong>ten blended) online and <strong>of</strong>fline identities which influence <strong>the</strong> web’s social processes. Social tools
help to construct rich online identities as pr<strong>of</strong>iles that consist <strong>of</strong> self-declared, action-based and thirdparty
information, while identity sharing indicates a certain amount <strong>of</strong> trust in web security and online
goodwill (Nabeth, 2009).
Enterprise 2.0 constitutes <strong>the</strong> value proposition for virtually embedded organisations to use ‘emergent
social s<strong>of</strong>tware platforms within companies, or between companies and <strong>the</strong>ir partners and customers’
(McAfee 2006) to generate content, support decision-making and build communities. As shown in
figure 5, SM applications and Web 2.0 technologies embody opportunities that can be brought in <strong>the</strong>
context <strong>of</strong> Enterprise 2.0 to achieve mass internal content creation or external collaborative
contributions, to build large-scale communities, to broadcast solution sourcing, to harness information
markets and to implement participatory viral marketing campaigns (Chui, Miller and Roberts, 2009).
Web 2.0 facets can be categorised in multiple groups according to <strong>the</strong>ir chief objectives, as divergent
disciplinary backgrounds lead to a multiplexity <strong>of</strong> Web 2.0 applications and technologies, reflecting
different perspectives on <strong>the</strong> intelligent web and its dynamic design. Marketing and branding
approaches, open innovation, outsourcing and collaboration concepts <strong>of</strong> <strong>the</strong> market-oriented view are
supported by service and deployment models <strong>of</strong> Cloud Computing, comprehensive approaches <strong>of</strong>
Extensible Markup Language (XML) descriptions and o<strong>the</strong>r standard web technologies. Innovative
technologies facilitate rich content and rich user experience and transform websites into dynamic web
applications. The accessible resource base <strong>of</strong> a huge amount <strong>of</strong> meta-data derived from usergenerated
content enables process- and data-mining by means <strong>of</strong> web-based s<strong>of</strong>tware with extremely
shortened release cycles, such as online marketing tools and e-commerce s<strong>of</strong>tware. Fur<strong>the</strong>rmore,
technological innovations like mobile interfaces with fully-covered online access and mobile service
marketplaces lead to ubiquitous computing environments (Baechle, 2008). In <strong>the</strong> “attention economy”
that drives Web 2.0 and its myriads <strong>of</strong> interconnected contributors (Brzozowski et al, 2009)
bookmarking services and Really Simple Syndication (RSS) feeds enable to keep <strong>the</strong> attention astute
on topics <strong>of</strong> interest. SM enable self-publishing to attract attention, be it <strong>the</strong> attention <strong>of</strong> a wider public
(e.g. by blogging) or <strong>of</strong> a circle <strong>of</strong> friends (e.g. by facebook-posting). SM increase customers’
engagement with products through <strong>of</strong>fering feedback opportunities. Users enjoy sharing experiences,
opinions and ideas with like-minded consumers in an open community. Thereby, enterprise reputation
is built up through “word-<strong>of</strong>-mouth” and “like” suggestions resulting to viral marketing (Boyd-Myers,
2010).
The participation in web discussion groups is triggered by <strong>the</strong> expectation <strong>of</strong> social benefits derived
from a sense <strong>of</strong> community. Important incentives are <strong>the</strong> response, feedback and acknowledgement
<strong>of</strong> o<strong>the</strong>rs. Reputation attached to identities and assessed through reviews and aggregated ratings
leads to <strong>the</strong> fostering <strong>of</strong> trust among strangers (Resnick et al, 2000). Moderation and feedback
mechanisms enable <strong>the</strong> establishment <strong>of</strong> norms and standards <strong>of</strong> web interaction, whereby good
behaviour according to <strong>the</strong> so-called “netiquette” and valued contributions improve <strong>the</strong> reputation,
trust and SC <strong>of</strong> <strong>the</strong> contributors. Concerning <strong>the</strong> evaluation <strong>of</strong> contributions, <strong>the</strong> assessment <strong>of</strong> quality
is problematic. While <strong>the</strong> view count <strong>of</strong> <strong>the</strong> amount <strong>of</strong> clicks on a contribution hints at its relevance to
<strong>the</strong> virtual community, attention is better measured by feedback, opinions, comments and tags, which
also inspire fur<strong>the</strong>r participation (Brzozowski et al, 2009). But what works for <strong>the</strong> public web may
break down when it comes to sharing knowledge insights e.g. in enterprise blogs and wikis. If <strong>the</strong>
effort to share knowledge is not recognised and accredited by <strong>the</strong> management, <strong>the</strong> employees’
motivation diminishes.
Therefore, in order to achieve an effective utilisation <strong>of</strong> SM for enterprise purposes ("Enterprise 2.0",
also analysed in figure 5), motivation to participate and awareness <strong>of</strong> <strong>the</strong> usability <strong>of</strong> SM have to be
fostered through managerial support, feedback and participation (figure 6). Enabling structures can
easily be created based on <strong>the</strong> Enterprise 2.0 drivers <strong>of</strong> participative content generation. Internal
platforms <strong>of</strong>fer good opportunities for effective in-house project management and mass internal
collaborative content creation in enterprise wikis, blogs or podcasts (McAfee, 2006). External online
platforms build a basis for collaboration with suppliers and business partners, social networking,
customer communication and collaboration in terms <strong>of</strong> after-sales feedback, co-creation, open
innovation and viral marketing. SM can also be used for broad public oriented publishing and
crowdsourcing. Through establishing a SM policy, guidelines and standards about how <strong>the</strong> employees
should use SM to avoid information leaks and any danger <strong>of</strong> defamation can be set up (see also IBM,
2010). A SM implementation strategy also aims at harnessing <strong>the</strong> user-generated power <strong>of</strong> online
communities to manage relationships and reputation online (figure 6). To achieve effective and
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Eleni Magdalini Vasileiadou et al.
efficient RM through SM, <strong>the</strong> effects <strong>of</strong> its utilisation should be monitored and evaluated. As shown in
figure 6, this is possible through <strong>the</strong> visualisation <strong>of</strong> structures, data mining <strong>of</strong> relationship contents
and netnography <strong>of</strong> online community participants.
Figure 5: Objectives and utilisation opportunities <strong>of</strong> Web 2.0 technologies and social media (based on
Chui, Miller and Roberts, 2009 and Dawson, 2009)
Although SM can contribute to a venture’s customer and revenue growth, its utilisation can turn out to
be more demanding, costly and time-consuming than expected and involves not only opportunities
but also threats. Certain negative effects <strong>of</strong> SM like <strong>the</strong> addiction to certain forms <strong>of</strong> rich content
virtual interactive communication, <strong>the</strong> ‘illusion <strong>of</strong> <strong>the</strong> real, intimate knowledge <strong>of</strong> true connections’
(Connor, 2010), <strong>the</strong> cultivation <strong>of</strong> ‘fragmented and shallower cultures’ (Connor, 2010) and <strong>the</strong> loss <strong>of</strong>
realistic self-perception can be regarded as social costs. SM can foster thin virtual relationships which
lack stability, credibility and commitment and thus lead to a deterioration <strong>of</strong> a company’s RC in case
<strong>of</strong> excessive misuse. Extensive and inefficient employee use and mismanagement <strong>of</strong> electronic
communications can even scaffold unrealistic customer expectations. In most cases, blown-up
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Eleni Magdalini Vasileiadou et al.
promises remain unfulfilled and result to dissatisfied customers and partners, bad reputation and loss
<strong>of</strong> relational and financial capital. As many risks are inherent in SM use, a SM strategy must consider,
assess and manage not only benefits but also risks concerning reputation, security, governance and
assurance issues, such as data <strong>the</strong>ft or leakage, lack <strong>of</strong> content control, liability for libel, privacy
violations and brand defamation (ISACA, 2010).
Despite <strong>the</strong> risks and costs associated to its utilisation, ventures discover and realise <strong>the</strong> potential <strong>of</strong>
SM tools for brand recognition, customer satisfaction, open innovation and human resource
management purposes. According to recent studies, SM use constitutes <strong>the</strong> rule ra<strong>the</strong>r than <strong>the</strong>
exception and ‘has even begun to impact brand recognition and enterprise revenue’ (ISACA, 2010: 4).
An efficient SM implementation leading to RC development and financial success is demonstrated in
<strong>the</strong> following best practice case study about Elbenwald.
Figure 6: Social media implementation strategy (based on Dawson, 2009 and Kane et al, 2009)
5. A touch <strong>of</strong> fantasy and magic through e-commerce – <strong>the</strong> case study <strong>of</strong>
Elbenwald
The name Elbenwald, meaning “Elves’ Forest” in German, was inspired by J.R.R. Tolkien’s tales, just
like <strong>the</strong> business idea <strong>of</strong> <strong>the</strong> online-shop that bears it, founded in <strong>the</strong> year 2000 by three highlymotivated
young entrepreneurs who met in <strong>the</strong> course <strong>of</strong> <strong>the</strong>ir studies. They decided to carry out <strong>the</strong>
establishment <strong>of</strong> an e-commerce venture as an experiment and adventure to distribute “Lord <strong>of</strong> <strong>the</strong>
Rings” - related articles online and to create value for <strong>the</strong> Middle-earth fans who would <strong>the</strong>n get better
access to a wider variety <strong>of</strong> <strong>the</strong>ir favourite articles. Rich content communication and interaction with
and between <strong>the</strong>ir customers is, was and will remain <strong>the</strong> first priority <strong>of</strong> Elbenwald, as <strong>the</strong>y are mostly
interested in <strong>of</strong>fering fantasy-related desiderata. To initialise <strong>the</strong>ir SM strategy, <strong>the</strong>y immediately
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Eleni Magdalini Vasileiadou et al.
enriched <strong>the</strong>ir initial web presence (website and web-based sales) with <strong>the</strong> establishment <strong>of</strong> a forum
for an online community. Elbenwald try to satisfy <strong>the</strong>ir customers’ wishes and communicate <strong>the</strong>m to
<strong>the</strong>ir suppliers, thus <strong>of</strong>fering <strong>the</strong> latter decision support concerning product development. Elbenwald
foster trust through reputational endorsements <strong>of</strong> products such as feedback, ratings and comments
and <strong>the</strong>y lay great importance on <strong>the</strong>ir reputation, which <strong>the</strong>y also demonstrate online by an <strong>of</strong>ficial
“trusted shop” certificate. To create up-to-date dynamic web content, Elbenwald use microblogging
(Twitter), podcasting (YouTube) and RSS feeds.
Figure 7: Chronological development <strong>of</strong> <strong>the</strong> e-commerce venture Elbenwald
To add more fantasy context and content to <strong>the</strong>ir scalable online presence, Elbenwald integrated <strong>the</strong>
Harry Potter’s Hogwarts’ magic dimension in <strong>the</strong>ir flexible portfolio. The integration and online
distribution <strong>of</strong> fur<strong>the</strong>r articles related to o<strong>the</strong>r successful fantasy films, TV series and games led to a
six-fold turnover growth (2001–2004). Elbenwald’s success demonstrates <strong>the</strong> geniality <strong>of</strong> <strong>the</strong> business
idea to bring more fantasy and magic into <strong>the</strong> real world. The financial success implicated by a
sustainable revenue growth is verified by <strong>the</strong> positive development <strong>of</strong> operative cash flow and return
on investment. The venture started <strong>of</strong>f with as little debt capital as possible. Elbenwald’s growth was
based on a growing demand in a market that <strong>the</strong>y enlarged through a broader portfolio <strong>of</strong> products. In
2005, <strong>the</strong> Elbenwald management team organised an “Elbenwald Medieval Convention” in order to
enable <strong>the</strong> virtual community to meet in <strong>the</strong> real world and <strong>the</strong>reby intensify <strong>the</strong> ra<strong>the</strong>r weak virtual
ties through face-to-face interaction and shared “live” experiences. In 2009, Elbenwald started to co-
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Eleni Magdalini Vasileiadou et al.
create personalised items through printing and stamping film motifs on articles. In 2010, <strong>the</strong>y went live
in Berlin through <strong>the</strong> establishment <strong>of</strong> a “real” store in <strong>the</strong> Shopping Mall Alexa in Berlin (figure 7).
6. Discussion <strong>of</strong> a conceptual model <strong>of</strong> RCM through virtual embeddedness
and social media
The conceptual model <strong>of</strong> RCM through social media in a virtually embedded organisation (figure 8;
based on Nahapiet and Ghoshal, 1998) can be exemplified by <strong>the</strong> case study <strong>of</strong> Elbenwald. Through
<strong>the</strong>ir motivation, ability and opportunity to take advantage <strong>of</strong> <strong>the</strong> web’s ubiquity, accessibility and
usability, <strong>the</strong> founders <strong>of</strong> Elbenwald draw upon <strong>the</strong>ir structural, relational and cognitive
embeddedness to implement <strong>the</strong>ir SM strategy in order to achieve added value for <strong>the</strong>ir customers
and to manage and increase <strong>the</strong>ir RC. Their structural embeddedness is visualised by <strong>the</strong>ir forum and
social networking site, <strong>the</strong>ir relational embeddedness is reflected in <strong>the</strong> commitment <strong>of</strong> <strong>the</strong>ir
community’s fans and <strong>the</strong>ir cognitive embeddedness can be found within <strong>the</strong> shared narratives <strong>of</strong>
Tolkien’s Middle-earth and o<strong>the</strong>r magic stories.
Figure 8: Relational capital management through virtual embeddedness in Web 2.0 (based on
Nahapiet and Ghoshal, 1998)
A certain structural embeddedness in <strong>the</strong> Web 2.0 community, relational embeddedness in form <strong>of</strong>
transparency, reputational endorsements as substitutes <strong>of</strong> trust and “netiquette” standards as well as
a shared symbolic reality in terms <strong>of</strong> cognitive embeddedness constitute prerequisites for <strong>the</strong>
empowerment to utilise social media in <strong>the</strong> Web 2.0 environment. As shown in <strong>the</strong> model <strong>of</strong> figure 8,
<strong>the</strong> utilisation <strong>of</strong> social media is enabled by means <strong>of</strong> human capital factors (motivation, opportunity
and ability). Communication and collaboration activities aim at <strong>the</strong> creation <strong>of</strong> IC (knowledge,
innovation, image and reputation). The basic human need <strong>of</strong> expression constitutes <strong>the</strong> main intrinsic
motivation to contribute to social networking sites and build up relational capital (RC) online. Fur<strong>the</strong>r
human incentives as well as structural capital elements providing usability and ubiquity <strong>of</strong> computing
environments also enable and facilitate <strong>the</strong> utilisation <strong>of</strong> social media. The desired outcomes <strong>of</strong> <strong>the</strong>
information and knowledge sharing, collaborative and social networking activities do not only create
IC but also RC, as <strong>the</strong>y improve <strong>the</strong> overall embeddedness properties <strong>of</strong> an organisation, especially
concerning <strong>the</strong> dimension <strong>of</strong> trust. Also <strong>the</strong> activities <strong>of</strong> generating and sharing content and social
networking in online communities (structural elements) lead to <strong>the</strong> development <strong>of</strong> shared norms and
standards (relational elements) and a shared symbolic reality (cognitive element), ensuring fur<strong>the</strong>r
motivation and empowerment for online contribution and co-creation. For new ventures, online RCM
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Eleni Magdalini Vasileiadou et al.
through user interaction and participation leads to <strong>the</strong> accumulation <strong>of</strong> reputation which fosters
legitimisation and trustworthiness (figure 8; Morse, Fowler and Lawrence, 2007).
7. Conclusion
In <strong>the</strong> Web 2.0 environment, relationships are virtually embedded and managed with <strong>the</strong> help <strong>of</strong> ICT
and especially SM and RM s<strong>of</strong>tware. As <strong>the</strong> evolution <strong>of</strong> <strong>the</strong> “social” web to a service platform for
participation and user interaction leads to new opportunities and threats for virtually embedded actors,
it is very importance to achieve a high level <strong>of</strong> VE in <strong>the</strong> appropriate constellation. New opportunities
to build social, relational and intellectual capital online through exploiting virtual embeddedness (VE)
and social media are mostly utilised by new ventures. They can use <strong>the</strong> web to present <strong>the</strong>ir business
idea, build up <strong>the</strong>ir image and reputation and legitimate <strong>the</strong>ir existence, to <strong>of</strong>fer products and services
online and interact with <strong>the</strong>ir customers in terms <strong>of</strong> web-based open innovation. As proposed by
Morse, Fowler and Lawrence (2007), <strong>the</strong> degree <strong>of</strong> a new venture’s VE helps a new venture to
overcome its liabilities <strong>of</strong> newness (Stinchcombe, 1965) and increases its likelihood <strong>of</strong> survival.
Of course, <strong>the</strong> RC <strong>of</strong> an organisation is not only embodied in VE elements but in physical ties as well,
which are not taken into consideration in <strong>the</strong> conceptual model <strong>of</strong> this paper for simplicity reasons.
The RC <strong>of</strong> most firms consists <strong>of</strong> a variety <strong>of</strong> both physical and virtual ties which both contribute to <strong>the</strong>
quality <strong>of</strong> relationships and define <strong>the</strong> constellation, range and accessibility <strong>of</strong> an actor’s overall
connections. Therefore, an effective RM implicates <strong>the</strong> implementation <strong>of</strong> a combination <strong>of</strong> physical
and virtual embeddedness that is appropriate for <strong>the</strong> specific environmental conditions as well as for
<strong>the</strong> venture’s value proposition and industrial sector (Morse, Fowler and Lawrence, 2007: 153). The
management and evaluation <strong>of</strong> both virtual and physical ties is a challenge that can be facilitated by a
target-oriented adoption and utilisation <strong>of</strong> Web 2.0 technologies and SM tools. But <strong>the</strong> benefits <strong>of</strong> <strong>the</strong>ir
utilisation should not be overestimated in social or economic terms: virtual face-to-screen-to-face
interaction can facilitate but not substitute “real” face-to-face communication and <strong>the</strong> potential to
achieve competitive advantage in <strong>the</strong> ICT sector diminishes with a growing number <strong>of</strong> dot-com
ventures based on quite similar business models. A new venture will not be successful just because
<strong>of</strong> using or <strong>of</strong>fering SM and Web 2.0. But it will probably become much more successful through an
efficient use <strong>of</strong> SM and Web 2.0 and less or not successful at all through refraining from using <strong>the</strong>
advantages <strong>of</strong> VE. Therefore, <strong>the</strong> main focus <strong>of</strong> implications for fur<strong>the</strong>r research should lie in <strong>the</strong>
evaluation <strong>of</strong> risks and benefits concerning SM and Web 2.0 utilisation and <strong>the</strong> potential for creation
<strong>of</strong> relational and intellectual capital and open innovation.
References
Adler, P.S. and Kwon, S.W. (2002) "Social Capital: Prospects for a New Concept", Academy <strong>of</strong> Management
Review, Vol. 7, No. 1, pp. 17-40.
Ahuja, G. (2000) "Collaboration networks, structural holes, and innovation: A longitudinal study", Administrative
Science Quarterly, Vol. 45, No. 3, pp. 425-455.
Baechle, M. (2008) “Ökonomische Perspektiven des Web 2.0 – Open Innovation, Social Commerce und
Enterprise 2.0”, Wirtschaftsinformatik, Vol. 50, No. 2, pp. 129-132.
Boissevain, J. (1974) Friends <strong>of</strong> Friends, Networks, Manipulators and Coalitions, Basil Blackwell, Oxford.
Bontis, N. (1999) “Managing Organizational Knowledge by Diagnosing Intellectual Capital – Framing and
Advancing <strong>the</strong> State <strong>of</strong> <strong>the</strong> Field”, International Journal <strong>of</strong> Technology Management, Vol. 18, No. 5-8, pp.
433-462.
Bourdieu, P. (1986) "The forms <strong>of</strong> capital", in: Richardson, J.G. (ed.), Handbook <strong>of</strong> Theory and Research for <strong>the</strong>
Sociology <strong>of</strong> Education, Greenwood, New York.
Boyd-Myers, C. (2010) "New Media: Your Social Media Strategy in 60 Seconds", TNW Social Media Blog,
[online], 17 Dec, http://<strong>the</strong>nextweb.com/socialmedia/2010/12/17/new-media-your-social-media-strategy-in-
60-seconds/ [5 Jan 2011].
Brzozowski, M.J., Sandholm, T. and Hogg, T. (2009) "Effects <strong>of</strong> feedback and peer pressure on contributions to
enterprise social media", <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> ACM 2009 International <strong>Conference</strong> on Supporting Group
Work - GROUP '09, Sanibel Island, Florida, USA, ACM Press, pp. 61-70.
Burt, R.S. (1992) Structural Holes, Harvard University Press, Cambridge, Massachusetts.
Burt, R.S. (2000) "The network structure <strong>of</strong> social capital", Research In Organizational Behavior, Vol. 22, pp. 345-
423.
Chui, M., Miller, A. and Roberts, R.P. (2009) “Six ways to make Web 2.0 work”, McKinsey Quarterly, [electronic],
02/2009, [online], https://www.mckinseyquarterly.com/PDFDownload.aspx?ar=2294 [5 Jan 2011]
Cicourel, A.V. (1973) Cognitive Psychology, Penguin Books, Harmondsworth, England.
Cohen, W.M. and Levinthal, D.A. (1990) "Absorptive Capacity: A new perspective on learning and innovation",
Administrative Science Quarterly, Vol. 35, No. 1, pp. 128-152.
458

Eleni Magdalini Vasileiadou et al.
Coleman, J.S. (1988) "Social capital in <strong>the</strong> creation <strong>of</strong> human capital", American Journal <strong>of</strong> Sociology, Vol. 94,
Supplement: Organizations and Institutions: Sociological and Economic Approaches to <strong>the</strong> Analysis <strong>of</strong>
Social Structure, pp. S95-S120.
Connor, A. (2010): "The Social Cost <strong>of</strong> Social Media", Flamingo Asia Pacific Blog, [online], 14 Apr,
http://www.flamingo-singapore.com/2010/04/<strong>the</strong>-social-cost-<strong>of</strong>-social-media/ [7 Feb 2011].
Dacin, M.T., Ventresca, M.J. and Beal, B.D. (1999) “The embeddedness <strong>of</strong> organizations: Dialogue and
directions”, Journal <strong>of</strong> Management, Vol. 25, No. 3, pp. 317-356.
Dawson, R. (2009) Implementing Enterprise 2.0 - A practical guide to creating business value inside
organizations with web technologies, Advanced Human Technologies.
De Castro, G.M., Sáez, P.L. and López, J.E.N. (2004) "The role <strong>of</strong> corporate reputation in developing relational
capital", Journal <strong>of</strong> Intellectual Capital, Vol. 5, No. 4, pp. 575-585.
Edvinsson, L. and Malone, S. (1997) Intellectual Capital – Realizing Your Company’s True Value By Finding It’s
Hidden Brainpower, HarperCollins, New York.
Fowler, S.F., Lawrence, T.B. and Morse, E.A. (2004) "Virtually embedded ties", Journal <strong>of</strong> Management, Vol. 30,
No. 5, pp. 647–666.
Granovetter, M.S. (1973) "The Strength <strong>of</strong> Weak Ties", American Journal <strong>of</strong> Sociology, Vol. 78, No. 6, pp. 1360-
1380.
Hormiga, E., Batista-Canino, R.M. and Sánchez-Medina, A. (2010) "The role <strong>of</strong> intellectual capital in <strong>the</strong> success
<strong>of</strong> new ventures", International Entrepreneurship and Management Journal [electronic], 03/2010, pp. 1-22,
[online], http://www.springerlink.com/content/m84k33215567v165/fulltext.pdf [5 Jan 2010].
IBM (2010) "IBM Social Computing Guidelines - Blogs, wikis, social networks, virtual worlds and social media",
IBMers’ Blogs, [online], http://www.ibm.com/blogs/zz/en/guidelines.html [05 Jan 2011].
ISACA (2010) Social Media: Business Benefits and Security, Governance and Assurance Perspectives, [online],
http://www.isaca.org/Knowledge-Center/Research/Documents/Social-Media-Wh-Paper-26-May10-
Research.pdf [07 Feb 2011].
Kane, G., Fichman, R., Gallaugher, J. and Glaser, J. (2009) "Community Relations 2.0", Harvard Business
Review, Vol. 87, No. 11, pp. 45-50.
Lengrand, L. and Chatrie, I. (1999) Business Networks and <strong>the</strong> Knowledge-Driven Economy: An empirical Study
Carried out in Europe and Canada, Office for Official Publications <strong>of</strong> <strong>the</strong> <strong>European</strong> Communities,
Luxembourg, [online],
http://www.insme.org/documents/Industrial%20aspects%20<strong>of</strong>%20<strong>the</strong>%20information%20society.pdf [05
Jan 2011].
Lev, B. (2001) Intangibles – Management, Measurement and Reporting, Brookings Institution Press, Washington,
District <strong>of</strong> Columbia.
McAfee, A. (2006) "Enterprise 2.0 – The Dawn <strong>of</strong> Emergent Collaboration", MIT Sloan Management Review, Vol.
47, No. 3, pp. 21-28.
McElroy, M.W. (2002) "Social innovation capital", Journal <strong>of</strong> Intellectual Capital, Vol. 3, No. 1, pp. 30-39.
Morse, E.A., Fowler, S.W. and Lawrence, T.B. (2007) "The Impact <strong>of</strong> Virtual Embeddedness on New Venture
Survival: Overcoming <strong>the</strong> Liabilities <strong>of</strong> Newness", Entrepreneurship Theory and Practice, Vol. 31, No. 2, pp.
139-159.
Nabeth, Thierry (2009), "Social web and identity: a likely encounter", IDIS, Vol. 2, pp. 1-5.
Nahapiet, J. and Ghoshal, S. (1998) "Social Capital, Intellectual Capital, and <strong>the</strong> Organizational Advantage",
Academy <strong>of</strong> Management Review, Vol. 23, No. 2, pp. 242-266.
Nohria, N. (1992) “Is a network perspective a useful way <strong>of</strong> studying organizations?”, in: Nohria, N. and Eccles,
R.G. (ed.), Networks and organizations: Structure, form, and action, Harvard Business School Press,
Boston, Massachusetts, pp. 1-22
O’Reilly, T. (2005) "What is Web 2.0 – Design Patterns and Business Models for <strong>the</strong> Next Generation <strong>of</strong>
S<strong>of</strong>tware", Web 2.0 Archives, [online], http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-isweb-20.html
[05 Jan 2011].
Packalen, K.A. (2007) "Complementing Capital: The Role <strong>of</strong> Status, Demographic Features, and Social Capital in
Founding Teams' Abilities to Obtain Resources", Entrepreneurship Theory and Practice, Vol. 31, No. 6, pp.
873-891.
Pike, S., Rylander, A. and Roos, G. (2002): “Intellectual Capital Management and Disclosure”, in Choo, W.C. and
Bontis, N. (ed.) The strategic management <strong>of</strong> intellectual capital and organizational knowledge, Oxford
University Press, New York, pp. 657-671.
Putnam, R. (1995) "Bowling Alone: America's Declining Social Capital", Journal <strong>of</strong> Democracy, Vol. 6, No. 1, pp.
65-78.
Putnam, R. (2000) Bowling Alone - The Collapse and Revival <strong>of</strong> American Community, Simon & Schuster, New
York.
Resnick, P., Zeckhauser, R., Friedman, E. and Kuwabara, K. (2000) "Reputation Systems: Facilitating Trust in
Internet Interactions", Communications <strong>of</strong> <strong>the</strong> ACM [electronic], Vol. 43, No. 12, pp. 1-7, [online]:
http://presnick.people.si.umich.edu/papers/cacm00/reputations.pdf [05 Jan 2011].
Shane, S. and Cable, D. (2002) "Network Ties, Reputation, and <strong>the</strong> Financing <strong>of</strong> New Ventures", Management
Science, Vol. 48, No. 3, pp. 364-381
Stinchcombe, A.L. (1965) "Organizations and social structure", in March, J.G. (ed.) Handbook <strong>of</strong> Organizations,
Rand-McNally, Chicago, Illinois, pp. 153-193.
459

Eleni Magdalini Vasileiadou et al.
Sveiby, K.E. (2001) "A knowledge based <strong>the</strong>ory <strong>of</strong> <strong>the</strong> firm to guide strategy formulation", Journal <strong>of</strong> Intellectual
Capital, Vol. 2, No. 4, pp. 344-358.
Tamaschke, L. (2003) "The role <strong>of</strong> social capital in regional technological innovation: seeing both <strong>the</strong> wood and
<strong>the</strong> trees", in: Huysman, M., Wenger, E. and Wulf, V. (ed.) Communities and Technologies. Kluwer B.V.,
Deventer, <strong>the</strong> Ne<strong>the</strong>rlands, pp. 241-264.
Uzzi, B. (1997) "Social structure and competition in interfirm networks: The paradox <strong>of</strong> embeddedness",
Administrative Science Quarterly, Vol. 42, No. 1, pp. 35-67.
Van Grove, J. (2009) "3 Great Social Media Policies to Steal From", American Express Open Forum Articles,
[online], 25 Sept, http://www.openforum.com/idea-hub/topics/technology/article/3-great-social-mediapolicies-to-steal-from-jennifer-van-grove-1
[05 Jan 2011].
Vasileiadou, E. M. and Missler-Behr, M. (2010) "Relevance and Importance <strong>of</strong> Intellectual Capital Reporting for
New Technology-Based Ventures", <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 2nd ECIC <strong>Conference</strong>, March 29-30, Lissabon,
Portugal, pp. 600-611.
Von Hippel, E. (1994) "’Sticky Information’ and <strong>the</strong> Locus <strong>of</strong> Problem Solving: Implications for Innovation",
Management Science, Vol. 40, No. 4, pp. 429-439.
Woolcock, M. (1998) "Social capital and economic development: Toward a <strong>the</strong>oretical syn<strong>the</strong>sis and policy
framework", Theory and Society, Vol. 27, No. 2, pp. 151-208.
Zhang, J., Souitaris, V., Soh, P. and Wong, P. (2008) “A Contingent Model <strong>of</strong> Network Utilization in Early
Financing <strong>of</strong> Technology Ventures”, Entrepreneurship Theory and Practice, Vol. 32, No. 4, pp. 593-613.
Zukin, S. and Di Maggio, P. (1990) "Introduction", in Zukin, S. and DiMaggio, P. (ed.) Structures <strong>of</strong> Capital: The
Social Organization <strong>of</strong> <strong>the</strong> Economy, Cambridge University Press, New York, pp. 1-36.
460

ICBS Intellectual Capital Benchmarking System: A
Practical Methodology for Successful Strategy Formulation
in <strong>the</strong> Knowledge Economy
José María Viedma Marti
Politechnic University <strong>of</strong> Catalonia, Barcelona, Spain
icms.viedma@telefonica.net
Abstract: The advent <strong>of</strong> <strong>the</strong> knowledge economy fundamentally changes <strong>the</strong> way to create wealth. According to
<strong>the</strong> new strategic management <strong>the</strong>oretical foundations -Resource Based View, Dynamic Capabilities and
Knowledge Based View- key strategic knowledge or Intellectual capital has become <strong>the</strong> fundamental driver <strong>of</strong>
wealth creation. In this new context close review <strong>of</strong> business excellence literature concludes that business
excellence has always been due, and still is, to good strategy formulation and superior strategy implementation.
In order to achieve business excellence substantial efforts have been made to improve <strong>the</strong> process <strong>of</strong> strategy
implementation. Never<strong>the</strong>less, fewer efforts have been made in <strong>the</strong> process <strong>of</strong> strategy formulation where SWOT
analysis still is <strong>the</strong> most well known existing framework. After an introduction in section 1, section 2 deals with
new strategic management <strong>the</strong>ory developments that <strong>the</strong> knowledge economy context requires. Finally in section
3 <strong>the</strong> paper describes ICBS as <strong>the</strong> result <strong>of</strong> a practical research based on <strong>the</strong> extended or improved SWOT
analysis. ICBS (Intellectual Capital Benchmarking System) is both, a new management method and a new
management tool that allows companies to perform a competitiveness strategy check-up <strong>of</strong> <strong>the</strong>ir business
models. For that purpose ICBS benchmarks <strong>the</strong>ir core innovation and operations intellectual capital against <strong>the</strong>
world class competitors in <strong>the</strong>ir sector. It is a framework build around <strong>the</strong> key factors and criteria that determine
competitiveness in innovation and operations in <strong>the</strong> context <strong>of</strong> global markets. The research has been conduced
following <strong>the</strong> design sciences approach and <strong>the</strong> system has been piloted in more than fifty <strong>European</strong> enterprises.
Keywords: strategy formulation, core competencies, core capabilities, intellectual capital, benchmarking,
competitive intelligence, strategic management
1. Introduction
The advent <strong>of</strong> <strong>the</strong> knowledge economy fundamentally changes <strong>the</strong> way to create wealth. According to
<strong>the</strong> new strategic management <strong>the</strong>oretical foundations (Resource Based View, Dynamic Capabilities
and Knowledge Based View) key strategic knowledge or Intellectual capital has become <strong>the</strong>
fundamental driver <strong>of</strong> wealth creation. In this new context close review <strong>of</strong> business excellence
literature concludes that business excellence has always been due, and still is, to good strategy
formulation and superior strategy implementation.
In order to achieve business excellence substantial efforts have been made to improve <strong>the</strong> process <strong>of</strong>
strategy implementation and some <strong>of</strong> <strong>the</strong>m have produced relevant frameworks and methodologies
such as Balanced Scorecard and InCaS (Intellectual Capital Statement. Made in Europe). Less effort
has been made in <strong>the</strong> process <strong>of</strong> strategy formulation and in practice <strong>the</strong> SWOT analysis still is <strong>the</strong>
most well known existing framework.
Never<strong>the</strong>less in a world, where customer preferences are volatile and <strong>the</strong> identity <strong>of</strong> customers and
<strong>the</strong> technologies for serving <strong>the</strong>m are changing, a market-focused strategy may not provide <strong>the</strong>
stability and constancy <strong>of</strong> direction needed as a foundation for long term strategy. When <strong>the</strong> external
environment is in a state <strong>of</strong> flux, <strong>the</strong> firm itself, in terms <strong>of</strong> its bundle <strong>of</strong> resources and capabilities,
may be a much more stable basis on which to define its identity. Hence, a definition <strong>of</strong> <strong>the</strong> firm in
terms <strong>of</strong> what it is capable <strong>of</strong> doing may <strong>of</strong>fer a more durable basis for strategy than a definition based
upon <strong>the</strong> needs <strong>the</strong> business seeks to satisfy. (Mahoney 1992, DenHond 1996, Peteraf 1993, Stalk
1992) Consequently, <strong>the</strong> SWOT analysis methodology can‘t cope with <strong>the</strong> new external environment
requirements and a kind <strong>of</strong> improved or extended SWOT analysis is needed.
ICBS is <strong>the</strong> output <strong>of</strong> a practical research on extended or improved SWOT analysis.
ICBS (Intellectual Capital Benchmarking System) is both, a new management method and a new
management tool that allows companies to perform a competitiveness strategy check-up <strong>of</strong> <strong>the</strong>ir
business models. For that purpose ICBS benchmarks <strong>the</strong>ir core innovation and operations intellectual
capital against <strong>the</strong> world class competitors in <strong>the</strong>ir sector. It is a framework build around <strong>the</strong> key
factors and criteria that determine competitiveness in innovation and operations in <strong>the</strong> context <strong>of</strong>
global markets. The factors considered in innovation are: emerging needs, project objectives, new
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products and services, new processes, new core capabilities, new pr<strong>of</strong>essional core capabilities,
innovation infrastructure, and financial results. The factors considered in operations are: business unit
objectives, products and services, processes, core competencies, pr<strong>of</strong>essional core competencies,
operations infrastructure, and financial results. ICBS identifies <strong>the</strong> specific innovation and operations
factors and criteria which are relevant in a given business sector.
ICBS valuates <strong>the</strong> competitiveness <strong>of</strong> <strong>the</strong> existing business models and <strong>the</strong> viability <strong>of</strong> <strong>the</strong> future
oriented innovation projects. In <strong>the</strong> evaluation <strong>the</strong> system relies on benchmarking and competitive
intelligence techniques. The research has been conduced following <strong>the</strong> design sciences approach
and <strong>the</strong> system has been piloted in more than fifty <strong>European</strong> enterprises.
2. Theoretical background
The fundamental question in <strong>the</strong> field <strong>of</strong> strategic management is why some firms perform better than
o<strong>the</strong>rs and how those firms achieve and sustain competitive advantage. The answer to <strong>the</strong>se
questions may be interpreted in <strong>the</strong> light <strong>of</strong> two distinct paradigms: <strong>the</strong> resource-based paradigm and
<strong>the</strong> activity-based paradigm. We propose a <strong>the</strong>oretical approach that seeks to integrate those
paradigms. In developing <strong>the</strong>se ideas, our work presents a new perspective on <strong>the</strong> strategy
formulation process in <strong>the</strong> context <strong>of</strong> <strong>the</strong> knowledge economy.
The resource based view
In accordance with Grant (1998), a key common ingredient in all business success stories is <strong>the</strong>
presence <strong>of</strong> a soundly formulated and effectively implemented strategy. Grant (1998) has stated that
<strong>the</strong> starting point for <strong>the</strong> formulation <strong>of</strong> strategy must be some statement <strong>of</strong> <strong>the</strong> firm‘s identity and
purpose. This generally takes <strong>the</strong> form <strong>of</strong> a mission statement that answers <strong>the</strong> question: ‗What is our
business?‘. Traditionally, firms have defined <strong>the</strong>ir business in terms <strong>of</strong> <strong>the</strong> market <strong>the</strong>y serve by
asking: ‗Who are our customers?‘ and ‗Which <strong>of</strong> <strong>the</strong>ir needs are we seeking to serve?‘ Never<strong>the</strong>less,
in a volatile world in which <strong>the</strong> identity <strong>of</strong> customers, <strong>the</strong>ir preferences, and <strong>the</strong> technologies for
serving <strong>the</strong>m are all changing, a market-focused strategy might not provide <strong>the</strong> stability and
constancy <strong>of</strong> direction required as a foundation for long-term strategy. When <strong>the</strong> external environment
is in state <strong>of</strong> flux, <strong>the</strong> firm itself, in terms <strong>of</strong> its bundle <strong>of</strong> resources and capabilities, might be a much
more stable basis upon which to define a sense <strong>of</strong> identity. Hence, a definition <strong>of</strong> <strong>the</strong> firm in terms <strong>of</strong>
what it is capable <strong>of</strong> doing might <strong>of</strong>fer a more durable strategic basis than a definition based upon <strong>the</strong>
needs which <strong>the</strong> business seeks to satisfy (Quinn, 1992).
The above discussion points to <strong>the</strong> fundamental role <strong>of</strong> resources, capabilities and competencies in
strategy formulation for entrepreneurial success in an environment <strong>of</strong> rapid change in technology and
in <strong>the</strong> needs <strong>of</strong> customers and industry. A problem <strong>of</strong> nomenclature hampering <strong>the</strong> development <strong>of</strong>
<strong>the</strong> resource-based view has been <strong>the</strong> variety <strong>of</strong> labels used to describe <strong>the</strong> firm‘s resource set.
Resources are inputs into <strong>the</strong> production process and <strong>the</strong>y can be tangible or intangible (Itami, 1987).
Capabilities may be understood as <strong>the</strong> way resources, talents and processes are combined and used
(Teece et al., 1997). The term ―competencies‖ appears frequently in <strong>the</strong> literature preceded by <strong>the</strong>
adjectives, core and distinctive. Sometimes is interchangeably used with <strong>the</strong> term capability which, in
turn, is also frequently preceded by <strong>the</strong> adjective core. Although <strong>the</strong>re are subtle differences in focus
and interpretation, all have a common approach to strategic management.
Tangible resources are concrete, tractable, and easy to identify and evaluate. They include <strong>the</strong>
financial and physical assets that are identified and valued in a firm‘s financial statements, such as
capital, factories, machines, raw materials and land. Intangible resources are generally more difficult
to measure, evaluate, and transfer. They include skills, knowledge, relationships, motivation, culture,
technology, and competencies. Lev (2001) states that ―intangibles are frequently embedded in
physical assets (e.g. knowledge contained in technology) and in labour (e.g. tacit knowledge), leading
to considerable interactions between tangible and intangible assets in <strong>the</strong> creation <strong>of</strong> value‖.
Resources are not usually productive in isolation. They become productive in collaboration in <strong>the</strong>
context <strong>of</strong> a team dedicated to a specific purpose. Ano<strong>the</strong>r important element <strong>of</strong> <strong>the</strong> resource-based
view is that not all resources are <strong>of</strong> equal importance or possess <strong>the</strong> potential to be a source <strong>of</strong>
sustainable competitive advantage. Alternative classifications <strong>of</strong> barriers to resource duplication
abound in <strong>the</strong> organizational literature. For example, Barney (1991) proposes that advantage-creating
resources must meet four conditions, namely, value, rareness, inimitability and non-substitutability,
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José María Viedma Marti
while Grant (1991) argues that levels <strong>of</strong> durability, transparency, transferability and replicability are
important determinants. Fur<strong>the</strong>r, Reed and DeFillippi (1990) suggest three sources <strong>of</strong> ambiguity and
advantage, mostly, tacitness, complexity and specificity. In short, resources are likely to be inimitable
or imperfectly imitable where <strong>the</strong>ir relationship with <strong>the</strong> advantage is poorly understood.
Capabilities have been proved more difficult to define and are <strong>of</strong>ten described as invisible assets
(Itami, 1987). Essentially, capabilities comprise <strong>the</strong> skills <strong>of</strong> individuals or groups as well as <strong>the</strong>
organizational routines and interactions through which all <strong>the</strong> firm‘s resources are coordinated (Grant,
1991). Ra<strong>the</strong>r than single discrete skills and technologies, capabilities are bundles <strong>of</strong> constituent skills
and technologies (Tovstiga and Birchall, 2002) that create disproportionate value for <strong>the</strong> customer,
differentiate its owner from competitors, and allow entrance to new markets (Hamel and Prahalad,
1994). A more dynamic perspective is introduced by Teece et al., (1997:516) focusing on how some
organizations first develop firm-specific competencies and how <strong>the</strong>y renew competencies to respond
to shifts in <strong>the</strong> business environment. The authors define dynamic capabilities as ―<strong>the</strong> firm‘s ability to
integrate, build, and reconfigure internal and external competencies to address rapidly changing
environment‖.
All <strong>of</strong> <strong>the</strong> above mentioned tangible and intangible resources represent a basis for <strong>the</strong> creation <strong>of</strong>
economic value, but competencies, in particular, have received special attention in <strong>the</strong> recent strategy
literature as being potential source <strong>of</strong> sustained competitive advantage. Competencies are <strong>the</strong> means
by which a firm deploys resources in a characteristic manner in order to compete (Haanes, 2000).
Thus, pr<strong>of</strong>essional competencies integrate pr<strong>of</strong>essional skills and knowledge, and organizational
competencies include a firm‘s knowledge, routines, and culture. Some authors, especially Prahalad
and Hamel (1990:81), have distinguished particular competencies, which <strong>the</strong>y call ―core
competencies‖, as being fundamental to <strong>the</strong> firm‘s performance and strategy. ―Core competencies‖,
according to <strong>the</strong>se authors, are those that make a disproportionate contribution to ultimate customer
value, or to <strong>the</strong> efficiency with which that value is delivered. Core competencies thus provide a basis
for entering new markets.
The authors put <strong>the</strong> cumulative development <strong>of</strong> specific competencies at <strong>the</strong> centre <strong>of</strong> <strong>the</strong> agenda <strong>of</strong>
corporate strategy because ―<strong>the</strong> real sources <strong>of</strong> advantage are to be found in management‘s ability to
consolidate corporate-wide technologies and production skills into competencies that empower
individual businesses to adapt quickly to changing opportunities‖. Hence, <strong>the</strong> sustainable competitive
advantage <strong>of</strong> firms resides not in <strong>the</strong>ir products, but in <strong>the</strong>ir core competencies. Fur<strong>the</strong>rmore, those
core competencies feed into more than one product, which, in turn, feed into more than one business
unit. As mentioned by Tidd (2005:6) ―core competencies are <strong>the</strong> roots <strong>of</strong> products and services, which
suggest that <strong>the</strong> most appropriate level <strong>of</strong> analysis and investment is nei<strong>the</strong>r <strong>the</strong> product nor <strong>the</strong>
market, but <strong>the</strong> core competencies‖.
Adopting a slightly different perspective, <strong>the</strong> present paper uses <strong>the</strong> term ―core competencies‖ to refer
to a unique bundle <strong>of</strong> intangible assets that are <strong>the</strong> basis <strong>of</strong> <strong>the</strong> definite, sustainable, competitive
advantages (Andriessen, 2001). In adopting this perspective, <strong>the</strong> present study uses <strong>the</strong> terms ―core
competencies‖ and ―core capabilities‖ interchangeably and also considers <strong>the</strong> term ―intellectual
capital‖ to be an equivalent expression. This approach is in agreement with Sullivan (2000) who
defined intellectual capital as knowledge that can be converted into pr<strong>of</strong>its or knowledge that
produces value. Figure 1 summarizes <strong>the</strong> above discussion on resources and capabilities, and Figure
2 shows <strong>the</strong> major intangible assets within a core competence (Andriessen, 2001).
The activity-based view
The activity-based view has mainly been concerned with seeing firms as value chains that create
value by transforming a set <strong>of</strong> inputs into more refined output (Porter 1985, 1996). Never<strong>the</strong>less, to be
more specific, we need to consider how value is created in <strong>the</strong> internal business process value chain.
The business process value chain can be divided into major processes: (i) <strong>the</strong> innovation process;
and (ii) <strong>the</strong> operation process.
The innovation process is made up <strong>of</strong> product design and product development, whereas <strong>the</strong>
operations process is made up <strong>of</strong> manufacturing, marketing, and post-sale service. Figure 3 illustrates
<strong>the</strong> business process value chain.
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Sustainable
competitive
advantage
Tangible
- Financial
- Physical
Figure 1: Resources and capabilities <strong>of</strong> a firm
Processes
- Leadership & Control
- Communication
- Management Information
José María Viedma Marti
Strategy
Core competencies =
Core capabilities =
intellectual capital
Resources
Intangible
Best in class
“competitors”
core competencies
Organisational Human Relational
- Technology - Knowledge - Customer
- Knowledge - Skills - Suppliers
- Reputation - Motivation - Stakeholders
- Culture - Communication - Competitors
abilities - O<strong>the</strong>r partners
Endowments
- Installed base <strong>of</strong> customers
- Brand & image
- Network <strong>of</strong> suppliers
- Network <strong>of</strong> talent
- Ownership <strong>of</strong> standards
Skills & Tacit Knowledge
- Know-how
- Talent
- Competencies
Unique bundle <strong>of</strong>
intangible assets
(=core
competence)
Technology & Explicit Knowledge
- Patents
- Manuals
- Procedures
Collective Values & Norms
- e.g. Client focus,
Reliability, Quality
Figure 2: A core competence as a unique bundle <strong>of</strong> intangible assets (source: Andriessen (2001))
Customer
need
Identified
Adapted
innovation operations
Design Develop Make Market Service
Customer
need
Satisfied
Figure 3: Business process value chain (source adapted from Kaplan and Norton (1996))
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José María Viedma Marti
The traditional perspective has focused on <strong>the</strong> operations process. According to <strong>the</strong> short-term view,
value creation begins with <strong>the</strong> receipt <strong>of</strong> an order from an existing customer for an existing product or
service, and ends with <strong>the</strong> delivery <strong>of</strong> <strong>the</strong> product to <strong>the</strong> customer (Kaplan and Norton, 1996). In this
case, value is created through operations core competencies.
However, viewed from <strong>the</strong> perspective <strong>of</strong> <strong>the</strong> innovation process, value creation is a long-term
process which, for many companies, is a more powerful driver <strong>of</strong> future financial performance than <strong>the</strong>
short-term operations process. This view requires an organisation to create entirely new products and
services that will meet <strong>the</strong> emerging needs <strong>of</strong> current and future customers. For many companies,
<strong>the</strong>ir ability to manage successfully a multi-year product-development process, or to develop a
capability to reach entirely new categories <strong>of</strong> customers, can be more critical for future economic
success than managing existing operations efficiently, consistently, and responsively. Value is thus
created through innovation core capabilities. Specifically, innovation value chain is about to translate
competencies into new processes, products and services, and learning from successful and
unsuccessful projects, use this experience to improve existing competencies and, where necessary,
develop new competencies (Tidd, 2005).
In summary, building core competencies is not done in a vacuum, but is done in <strong>the</strong> business process
value chain in which resources are deployed in a characteristic manner in order to compete. The
resource-based view and <strong>the</strong> activity-based view are <strong>the</strong>refore complementary. Taken toge<strong>the</strong>r, <strong>the</strong>y
explain <strong>the</strong> process <strong>of</strong> creating value and securing a sustainable competitive advantage.
3. Building an intellectual capital strategic management methodology and
information system
In all success stories <strong>the</strong>re is always a soundly formulated and effectively implemented strategy, and
<strong>the</strong> framework <strong>of</strong> Strengths, Weaknesses, Opportunities, and Threats (SWOT) remains <strong>the</strong> most
common approach to analysing business strategy. One <strong>of</strong> <strong>the</strong> main challenges for <strong>the</strong> knowledge and
information economy <strong>of</strong> today is how to use SWOT analysis efficiently and effectively in <strong>the</strong> present
context. The framework considers strategy to be a link between <strong>the</strong> firm and its industry environment,
and distinguishes between two features <strong>of</strong> a firm‘s internal environment (its strengths and
weaknesses) and two features <strong>of</strong> its external environment (opportunities and threats). However, does
this correspond to current reality? A modern firm can be said to embody three sets <strong>of</strong> key
characteristics (its goals and values; its resources and capabilities; and its organisational structure
and systems), and <strong>the</strong> external environment can be said to be comprised <strong>of</strong> its relationships with
three groups (its customers; its competitors; and its suppliers).
This paper seeks to use SWOT analysis in an efficient and effective way to achieve success in <strong>the</strong>
new context in which <strong>the</strong> main features are: (i) <strong>the</strong> importance <strong>of</strong> knowledge as <strong>the</strong> main source <strong>of</strong>
sustainable competitive advantage; and (ii) world-wide hyper-competition. The challenge is to move
SWOT analysis away from <strong>the</strong> generalities <strong>of</strong> ‗strengths‘, ‗weaknesses‘, ‗opportunities‘, and ‗threats‘
to more concrete factors and characteristics appropriate to <strong>the</strong> new reality.
As previously noted, in today‘s knowledge economy <strong>the</strong> resource-based view and <strong>the</strong> activity-based
view are <strong>the</strong> fundamental cornerstones that determine company competitiveness. The resourcebased
view (Barney, 1991, 1999; Grant 1991, 1998; Teece , D. J., Pisano G. and Shuen A. 1997)
stresses that, in turbulent times and in times <strong>of</strong> rapid change in technology and in customer and
industry needs, sustainable competitive advantages are mainly due to <strong>the</strong> intangible resources <strong>of</strong> a
company or, more specifically, to core competencies (which are, in practice, equivalent to core
knowledge). But resources per se do not create value, and because <strong>the</strong> resource-based view focuses
only on what <strong>the</strong> firm has, this view does not, in isolation, adequately explain how to deploy scarce
resources to create superior value. To that end, <strong>the</strong> activity-based view (Porter 1980, 1985, 1996) is a
necessary complementary perspective which focuses on what <strong>the</strong> firm does, and takes into account
that value creation results from <strong>the</strong> activities to which <strong>the</strong> resources are applied. If core knowledge is
<strong>the</strong> key strategic asset, improving existing core knowledge and building new core knowledge are
fundamental tasks. Building and improving core knowledge require organisational learning
capabilities, including <strong>the</strong> appropriate learning structures and information systems. World-wide
industry hyper-competition has ensured that strategic competitive benchmarking has become an
essential learning tool. This valuable knowledge can be obtained only from systematic and frequent
comparison with <strong>the</strong> world-class processes and core competencies <strong>of</strong> competitors in <strong>the</strong> same
business segments. In fact, companies and organisations are now competing on <strong>the</strong> basis <strong>of</strong> core
465

José María Viedma Marti
knowledge and core competencies. Opportunities and threats come mainly from competitors who
<strong>of</strong>fer <strong>the</strong> best in <strong>the</strong> same industry segment.
As a result <strong>of</strong> <strong>the</strong> above discussion, <strong>the</strong> SWOT analysis framework moves from that shown in Figure 4
to that shown in Figure 5. In effect, <strong>the</strong>re is a change from simple SWOT analysis to an extended
SWOT Analysis
SWOT analysis.
The Firm
1. Goals and Values
2. Resources and Capabilities
3. Structure and Systems
Source: Robert M. Grant 1998.
Figure 4: SWOT analysis
The Firm
1. Goals and Values
2. Resources and
capabilities
• Core activities
• Core competencies
• Core knowledge
3. Structure and systems
• Strategic
Benchmarking and
competitive intelligence
structure and systems
Figure 5: Extended SWOT analysis
Strategy
Extended SWOT Analysis
Benchmarking
Benchmarking
Strategy
Benchmarking
The Industry
Environment
• Competitors
• Customers
• Suppliers
The world class industry
segment competitors
1. Goals and Values
2. Resources and
capabilities
• Core activities
• Core competencies
• Core knowledge
3. Structure and systems
The extended SWOT analysis gives us <strong>the</strong> main factors to consider when seeking strategies that
leading to entrepreneurial excellence. The main factors <strong>of</strong> <strong>the</strong> extended SWOT analysis also
determine <strong>the</strong> information system required to measure and manage those factors. In o<strong>the</strong>r words, <strong>the</strong>
main factors produce <strong>the</strong> strategic benchmarking <strong>of</strong> intellectual capital system (ICBS) that we have
defined as a practical methodology for successful strategy formulation in <strong>the</strong> knowledge economy.
Never<strong>the</strong>less, as previously noted, strategy formulation in dynamic environments, even those mainly
based on core capabilities, has different features when dealing with <strong>the</strong> innovation process than when
dealing with <strong>the</strong> operations process. Core capabilities can be very different in <strong>the</strong> two processes.
The innovation process points to new products and services through <strong>the</strong> innovation value chain in
which innovation capabilities are basic and fundamental. ICBS has a specific system for <strong>the</strong>
innovation process—<strong>the</strong> innovation intellectual capital benchmarking system (IICBS).
The operations process, which produces ordinary products and services through <strong>the</strong> systematic and
repetitive operations value chain, also requires core competencies and core capabilities to be
competitive. However, <strong>the</strong>se competencies and capabilities will probably be <strong>of</strong> a different nature from
<strong>the</strong> ones mentioned above in <strong>the</strong> discussion <strong>of</strong> <strong>the</strong> innovation process. ICBS also has a specific
process for <strong>the</strong> operations value chain—<strong>the</strong> operations intellectual capital benchmarking system
(OICBS). Figure 6 illustrates <strong>the</strong> business process broken down into its two constituent parts, and <strong>the</strong>
specific methodologies and information systems that correspond to each <strong>of</strong> <strong>the</strong> constituent parts.
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Customer
need
identified
IICBS
Innovation Intellectual
Capital Benchmarking
System
José María Viedma Marti
INNOVATION OPERATIONS
Design
Core activities
Develop
Core competencies
Innovation core
knowledge
Figure 6: Business process value chain
Make
Market
Core activities
Core competencies
Operations core
knowledge
OICBS
Service
Operations Intellectual
Capital Benchmarking
System
Customer
need
satisfied
In summary, <strong>the</strong> general model <strong>of</strong> <strong>the</strong> ICBS can be divided into two partial models. The first, <strong>the</strong>
IICBS, refers to innovation core activities and core knowledge, whereas <strong>the</strong> second, <strong>the</strong> OICBS,
refers to operations core activities and core knowledge.
The two models have a similar structure and <strong>the</strong>y work in a similar way, but <strong>the</strong>re is a fundamental
difference. The IICBS model refers to <strong>the</strong> core activities and core knowledge <strong>of</strong> <strong>the</strong> different projects
that make up <strong>the</strong> innovation process. In contrast, <strong>the</strong> OICBS model refers to <strong>the</strong> core activities and
core knowledge <strong>of</strong> <strong>the</strong> different business units that make up <strong>the</strong> operations process.
This paper describes only <strong>the</strong> IICBS. However, <strong>the</strong> structure and function <strong>of</strong> <strong>the</strong> OICBS can be easily
deduced, because <strong>the</strong> systems are very similar and work in an analogous fashion.
3.1 (IICBS) Innovation Intellectual Capital Benchmarking System general framework
Using <strong>the</strong> metaphor <strong>of</strong> a tree, we can consider <strong>the</strong> company that performs innovation activities as a
new tree in which <strong>the</strong> visible part (that is to say, <strong>the</strong> trunk, <strong>the</strong> branches, and <strong>the</strong> fruits) corresponds to
<strong>the</strong> tangible assets <strong>of</strong> <strong>the</strong> innovative company (see Figure 7). The invisible part <strong>of</strong> <strong>the</strong> tree (that is to
say, <strong>the</strong> roots <strong>of</strong> <strong>the</strong> tree below ground) corresponds to <strong>the</strong> intangible assets <strong>of</strong> <strong>the</strong> innovative
company. The two parts—tangible and intangible—are inseparable. The roots <strong>of</strong> <strong>the</strong> tree send <strong>the</strong>
sap through <strong>the</strong> trunk and <strong>the</strong> branches to <strong>the</strong> fruits. In a similar way, knowledge and its aggregates—
competencies, capabilities, and intellectual capital—make up <strong>the</strong> innovation sap that flows from <strong>the</strong>
roots to <strong>the</strong> new processes, and thus to <strong>the</strong> new products and services.
Continuing with <strong>the</strong> tree metaphor, each company project unit can be assimilated to a specific tree,
and <strong>the</strong> whole company has as many trees as it has project units. Each <strong>of</strong> <strong>the</strong>se trees is fed with <strong>the</strong>
knowledge <strong>of</strong> its roots. Fur<strong>the</strong>rmore <strong>the</strong> company has at its disposal a common intangible innovation
infrastructure that is shared by all <strong>the</strong> project units. This infrastructure corresponds to <strong>the</strong> fertile soil in
which all <strong>the</strong> company trees are planted. This fertile soil nourishes <strong>the</strong> roots (core knowledge) <strong>of</strong> each
individual innovation company tree. See Figure 8.
The IICBS methodology draws inspiration from <strong>the</strong> tree metaphor. The flowchart <strong>of</strong> Figure 9 is a
summary representation <strong>of</strong> <strong>the</strong> IICBS working scheme. The flowchart shows that, within each
company innovation tree (project unit), an analysis can be made, successively, on <strong>the</strong> fruits (new
products and services), <strong>the</strong> branches (new processes), and <strong>the</strong> roots (new core competencies and
467

José María Viedma Marti
pr<strong>of</strong>essional core competencies). For this purpose, ad hoc personalised questionnaires can be used.
In addition, <strong>the</strong> overall soil fertility (innovation infrastructure) can be analysed.
New Service A’
New Product A
New Product A”
PRESENT
(Value Extraction)
KNOWLEDGE
New Process A
New Process A
COMPETENCI ES
New Service B
New New Process Process BB
TANGI TANGI BLE BLE
RESOURCES
RESOURCES
New New Process Process BB
New Product B’
I NTANGI BLE RESOURCES
CAPABI LI TI ES
HUMAN
CAPI TAL
New New Process Process CC
New New Process Process CC
New Process C
I NTELLECTUAL
CAPI TAL
STRUCTURAL
CAPI TAL
RELATI ONAL
CAPI TAL
New Service C
NEW KNOWLEDGE NEW KNOWLEDGE NEW KNOWLEDGE NEW KNOWLEDGE NEW KNOWLEDGE NEW KNOWLEDGE
NEW KNOWLEDGE NEW KNOWLEDGE NEW KNOWLEDGE NEW KNOWLEDGE
Figure 7: Innovation tree
Company
Innovation
PU PU1..............PU 1..............PU2.............PU 2.............PU3...........…PU 3...........…PU n
New Product C’
New Service C”
© Intellectual Capital Management Systems
ICK ICK1............ 1............ ICK ICK2............ICK 2............ICK3..........…ICK 3..........…ICK n
PU=Project Unit
ICK=Innovation Core Knowledge
I nnovation I nfrastructure
1. I nnovation and Strategy
2. Technology standard
3. R+D integration
4. R+D organisation
Figure 8: Company Innovation Infrastructure
5. I nnovation resource allocation
6. Technology information systems
7. Technology management systems
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José María Viedma Marti
Company A
Customer
emerging
needs
Company B
Project 1
Objectives
New Products
and Services
New Processes
New core
capabilities
New pr<strong>of</strong>essional
Core capabilities
Innovation
Infrastructure
Flowchart 1
Benchmarking
GAP
Benchmarking
GAP
Benchmarking
GAP
Benchmarking
GAP
Benchmarking
GAP
Benchmarking
GAP
Figure 9: Innovation Intellectual Capital Benchmarking System
Project (h)
Objectives
New Products
and Services (h)
New Processes
(h)
New core
Capabilities (h)
New pr<strong>of</strong>essional
Core capabilities (h)
Innovation (h) = Homologous
Infrastructure
In analysing each particular tree (that is, each individual project unit), we use <strong>the</strong> innovation value
chain as an analysis tool. See Figure 10.
New
pr<strong>of</strong>essional
core capabilities
Project capabilities
Financial
Results
New
core
capabilities
Project
Value Chain
Competitive advantages core project activities
Competitive advantages outsourcing activities
Competitive advantages alliance activities
Figure 10: Innovation value chain as an analysis tool
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Emerging
customer
needs
New products
and services
Competitive
Segment
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José María Viedma Marti
All <strong>of</strong> <strong>the</strong> above-mentioned analyses have <strong>the</strong> ultimate purpose <strong>of</strong> discovering, in each <strong>of</strong> <strong>the</strong>
flowchart steps or phases, <strong>the</strong> new core knowledge and new core technologies that are <strong>the</strong> prime
reason for sustainable competitive advantages.
In <strong>the</strong> same way <strong>the</strong> methodology makes it possible to compare each specific tree (project unit) with
<strong>the</strong> homologous tree <strong>of</strong> <strong>the</strong> best <strong>of</strong> <strong>the</strong> competition, thus facilitating <strong>the</strong> benchmarking <strong>of</strong> fruits (new
products and services), branches (new processes), roots (new core competencies and pr<strong>of</strong>essional
core competencies), and soil fertility (innovation infrastructure). The benchmarking process is shown
in Figures 10 and 11. In both figures <strong>the</strong> benchmarking gap gives <strong>the</strong> necessary information for taking
appropriate corrective action and for learning from past errors.
New Core
capabilities
Our Company Best in class
Results
New Core
competencies
Customer
emerging
needs
Figure 11: The process <strong>of</strong> benchmarking in IICBS
Competitive
business
segment
Customer
emerging
needs
Results
New Core
competencies
New Core
capabilities
Apart from using <strong>the</strong> tree metaphor, <strong>the</strong>re is an alternative explanation <strong>of</strong> <strong>the</strong> IICBS methodology and
framework. The IICBS framework can also be articulated in terms <strong>of</strong> <strong>the</strong> eight competitiveness factors
The that are included in <strong>the</strong> following The eight figure eight factors 12: factors framework
Company
innovation
infrastructure
6
New pr<strong>of</strong>essional
core capabilities
Financial
results
Figure 12: The eight-factor framework
7
8
5
New core
capabilities
Factors
1
Emerging
needs
4
New processes
2
Project
Objetives
3
New Products
and services
The eight factor framework that we have already noted is in fact a flexible framework that allows <strong>the</strong>
core capabilities or intellectual capital identification and evaluation within each particular factor. By <strong>the</strong>
same token <strong>the</strong> different components <strong>of</strong> intellectual capital (human capital, structural capital and
relational capital) can be assessed and appraised.
The eight factor framework explains how sustainable competitive advantages are achieved in <strong>the</strong> new
products and new services that come out <strong>of</strong> <strong>the</strong> processes and operations. Briefly, <strong>the</strong>y can be
achieved in <strong>the</strong> following way:
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Companies if <strong>the</strong>y want to successfully compete in <strong>the</strong> future <strong>the</strong>y need to innovate in a systematic
way. The way to innovate is through projects that have <strong>the</strong> clear objective <strong>of</strong> satisfying customer
emerging needs. Customer needs satisfaction is accomplished through <strong>the</strong> project‘s new products
and services. Never<strong>the</strong>less competitive products and services are not easily achieved; a lot <strong>of</strong> work is
needed in order to gradually establish competitive advantages in <strong>the</strong> different core activities <strong>of</strong> <strong>the</strong>
value chain process. Core competencies and core capabilities in <strong>the</strong> core project activities <strong>of</strong> <strong>the</strong>
value chain produce new products and services with competitive advantages and high knowledge or
intellectual content. In addition <strong>the</strong> company innovation infrastructure or in o<strong>the</strong>r words <strong>the</strong> company
R+D department gives <strong>the</strong> necessary support to <strong>the</strong> whole process.
Finally <strong>the</strong> acquisitions <strong>of</strong> core capabilities and <strong>the</strong> accomplishment <strong>of</strong> all those competitive
advantages is only possible by means <strong>of</strong> <strong>the</strong> actions <strong>of</strong> <strong>the</strong> different project leaders that decide on and
carry out objectives and strategies, and who shape business culture with <strong>the</strong>ir ways and methods.
3.2 IICBS Innovation Intellectual Capital balance-sheets
The processing <strong>of</strong> questionnaires corresponding to each <strong>of</strong> <strong>the</strong> company competitiveness factors
provides us with <strong>the</strong> innovation capabilities results and balance sheets. These results and balance
sheets can be obtained for <strong>the</strong> project as a whole or for each competitiveness factor. Some examples
<strong>of</strong> balances and results are given below: (Figures 13, 14, and 15).
ICBS
M & L. Project Fast new fashion products production
NEW PRODUCTS
NEW PROCESSES
NEW CORE CAPABILITIES
NEW PROFESSIONAL CORE CAPABILITIES
COMPANY INNOVATION INFRASTRUCTURE
FINANCIAL RESULTS
QUICK PRODUCTION CYCLE
DESIGN TEAM
SUPPLY CHAIN
OUTLETS
FASHION CREATIVITY
INFORMATION, TECHNOLOGY, SYSTEMS
Innovation Intellectual Capital Global Assesssment
COMPETITOR
CONSOLIDATED RESULTS
KSF KEY SUCESS FACTORS
Figure 13: Innovation Intellectual Capital Global assessment
3.3 Implications for managers
Consolidated
Reliability
Index
Senior managers effectively integrate <strong>the</strong> ICBS into <strong>the</strong> overall business strategy in a similar way <strong>the</strong>y
integrate o<strong>the</strong>r strategy-focused models. Never<strong>the</strong>less, in <strong>the</strong> particular case <strong>of</strong> <strong>the</strong> ICBS two new
functions have to be performed: business intelligence and competitive benchmarking.
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ICBS
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José María Viedma Marti
INNOVATION INTELLECTUAL CAPITAL BALANCE SHEET
Project
Competitor
Zara
ASSETS LIABILITIES
1.- NEW PRODUCTS 1.- NEW PRODUCTS
1.2 Price/Quality relationship 2,1 1.1 Design -1,2
1.7 Conformance 1,7 1.3 Embodied services -1,3
1.8 Garment selection 0,8 1.4 New trends adaptation -2,1
1.5 Fabric quality -1,5
1.6 Fashion -0,9
2.- NEW PROCESSES 2.- NEW PROCESSES
2.1 Customer needs identification 1,0 2.2 Discovering emerging needs -4,0
2.5 Design CAD 2,2 2.3 Selecting merket segment -3,8
2.6 Manufacturing CAM 1,4 2.4 Creativity -3,0
2.7 supply chain architecture -2,5
2.8 Process architecture -3,2
2.9 Logistics -3,1
3.- NEW CORE CAPABILITIES 3.- NEW CORE CAPABILITIES
3.2 Supply chain architecture 1,0 3.1 FASHION CREATION -2,0
3.3 Design for manufacturability DFM -2,2
3.4 Supply chain design -1,9
3.5 Three-D.concurrent engineering -3,0
3.6 Quick development and production -2,3
5.- INNOVATION INFRASTRUCTURE 5.- INNOVATION INFRASTRUCTURE
5.2 R+D integration 2,0 5.1 Innovation and strategy -1,0
5.3 Technology standerd -3,0
5.4 R+D organisation -4,1
5.5 Innovation resource allocation -4,0
5.6 Technology information systems -4,0
5.7 Technology management systems -3,9
INNOVATION INTELLECTUAL CAPITAL BALANCE SHEET
M & L. Project Fast new fashion products
Competitor
production
Zara
ASSETS LIABILITIES
1.- NEW PRODUCTS 1.- NEW PRODUCTS
1.2 Price/Quality relationship 2,1 1.1 Design -1,2
1.7 Conformance 1,7 1.3 Embodied services -1,3
1.8 Garment selection 0,8 1.4 New trens adaptation -2,1
1.5 Fabric quality -1,5
1.6 Fashion -0,9
2.- NEW PROCESSES 2.- NEW PROCESSES
2.1 Customer needs identification 1,0 2.2 Discovering emerging needs -4,0
2.5 Design CAD 2,2 2.3 Selecting merket segment -3,8
2.6 Manufacturing CAM 1,4 2.4 Creativity -3,0
2.7 supply chain architecture -2,5
2.8 Process architecture -3,2
2.9 Logistics -3,1
3.- NEW CORE CAPABILITIES 3.- NEW CORE CAPABILITIES
3.2 Supply chain architecture 1,0 3.1 FASHION CREATION -2,0
3.3 Design for manufacturability DFM -2,2
3.4 Supply chain design -1,9
3.5 Three-D.concurrent engineering -3,0
KNOWLEDGE AND 3.6 SKILLS Quick development ON and production -2,3
- Gorments
-2,0
5.- INNOVATION INFRASTRUCTURE - Weaving 5.- INNOVATION INFRASTRUCTURE -1,0
5.2 R+D integration - Dyeing 2,0 5.1 Innovation and strategy -1,9 -1,0
- Printing
5.3 Technology standerd -2,1 -3,0
- Finishing
5.4 R+D organisation -3,0 -4,1
- Fashion trends 5.5 Innovation resource allocation -1,2 -4,0
- Best designers 5.6 Techgnology information systems -3,1 -4,0
- Dress making 5.7 Technology management systems -2,3 -3,9
- Prototypes and models
-1,7
- Creativity
-3,1
Figures 14 and 15: Innovation Intellectual Capital balance-sheets
472
Consolidated
Reliability
Index
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Consolidated
Reliability
Index
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José María Viedma Marti
The main benefits from using ICBS are <strong>the</strong> following:
Learning from one‘s betters to surpass one‘s own competitive position.
Identifying <strong>the</strong> specific competitiveness factors that are relevant I a given business activity.
Through <strong>the</strong> ICBS factors framework, enabling <strong>the</strong> identification, auditing and benchmarking <strong>of</strong>
<strong>the</strong> core competencies or core knowledge that are <strong>the</strong> main sources <strong>of</strong> long term sustainable
competitive advantages.
When using ICBS in an orderly systematic and repetitive way we obtain competencies statements
that complete financial balance sheets and lead companies to leverage core knowledge.
Selecting in a systematic and organised way <strong>the</strong> necessary information for evaluating relevant
factors, core knowledge, core competencies and key intellectual capital.
Identifying <strong>the</strong> key areas in which in-depth benchmarking can be carried out in <strong>the</strong> future.
Promoting organizational learning through assessment teams, benchmarking teams, and strategic
teams
Introducing a common language for company managers when dealing with intellectual capital
Facilitating <strong>the</strong> work <strong>of</strong> <strong>the</strong> benchmarking and competitive intelligence team.
4. Conclusions
In <strong>the</strong> knowledge economy, soundly formulated and effectively implemented strategies are still <strong>the</strong>
main drivers <strong>of</strong> company success, and SWOT analysis is still <strong>the</strong> most common approach for
analysing business strategy. However, in <strong>the</strong> new context, classical SWOT analysis does not provide
suitable guidance for building an effective strategic management methodology and information
system. An extended SWOT analysis which takes into consideration <strong>the</strong> two main streams <strong>of</strong> modern
strategic thought—<strong>the</strong> resource-based view and <strong>the</strong> activity-based view—is a more reliable
foundation. ICBS draws inspiration from <strong>the</strong> extended SWOT analysis and builds a strategic
management methodology and information system in which intellectual capital is <strong>the</strong> key issue.
References
Andriessen, D. (2001). Weightless Wealth. Paper for <strong>the</strong> 4 th world Congress on <strong>the</strong> Management <strong>of</strong> Intellectual
Capital. Mc Master University. Hamilton, Ontario, Canada.
Barney, J.B. (1991). ―Firm resources and sustained competitive advantage‖. Journal <strong>of</strong> Management, Vol. 17,
No.1, pp 99-120.
Barney, J. (1999). How a Firm’s Capabilities Affect Boundary Decisions. Sloan Management Review. Spring pp
137–145.
Den Hond, F.(1996) ―Capabilities Perspective on <strong>the</strong> Firm‖ Chapter 3 p.p. 49-74. In search <strong>of</strong> a useful <strong>the</strong>ory <strong>of</strong>
environmental strategy, PhD.Thesis. Amsterdam Vrije Universiteit.
Grant, R.M. (1991). The resource-based <strong>the</strong>ory <strong>of</strong> competitive advantage: Implications for strategy formulation.
California Management Review, 33, Spring, 114-35.
Grant, R.M. (1998). Contemporary strategy analysis. Oxford: Blackwell Publishers Ltd. Oxford, UK.
Haanes, K. (2000). Linking Intangible Resources and Competition. <strong>European</strong> Management Journal, 18, 1, 52-62.
Hamel, G. and Prahalad, C.K. (1994). Competing for <strong>the</strong> future. Boston, MA: Harvard Business School Press.
InCaS Project. http://www.incas-europe.org/index-en.htm
Itami, H. And Roehl, T.(1987). Mobilizing Invisible Assets. Cambridge, MA: Harvard University Press.
Kaplan, R.S. and Norton, D.P. (1996). Using <strong>the</strong> balanced scorecard as a strategic management system.
Harvard Business Review, 74, 1, 75-85.
Lev, B. (2001). Intangibles: Management, measurement, and reporting. Brookings Institution Press.
Mahoney, J. and Pandian, JR. (1992) ―The resource-Based view within <strong>the</strong> conversation <strong>of</strong> strategic
management‖. Strategic Management Journal Vol. 13 pp 363-380
Peteraf, M. A. ―The cornerstones <strong>of</strong> competitive advantage‖ Strategic Management Journal Vol. 14 (1993) pp
179-191
Porter, M.E. (1980). Competitive Strategy. Free Press. New York.
Porter, M.E. (1985). Competitive Advantage. New York: Free Press.
Porter, M.E. (1996). What is strategy? Harvard Business Review, 7, 6, 61-78.
Prahalad, C.K. and Hamel, G. (1990). The core competence <strong>of</strong> <strong>the</strong> corporation. Harvard Business Review,
May/June, 68, 79-91.
Quinn, J. B. (1992). Intelligent Enterprise. New York: The Free Press.
Reed, R. and DeFillippi, R.J. (1990). Causal ambiguity, barriers to imitation and sustainable competitive
advantage. Academy <strong>of</strong> Management Review, 15, January, 88-102.
Stalk G., Evans P. and Shulman, L.E. ―Competing on capabilities: The new rules <strong>of</strong> corporate strategy‖ Harvard
Business Review March-April 1992 pp 57-69.
473

José María Viedma Marti
Sullivan, H.P. (2000). Value-Driven Intellectual Capital. New York: John Wiley&Sons, Inc, 3-18.
Teece, D.J., Pisano, G. and Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic
Management Journal, 18, 7, 509-33.
Tidd, J. (2005). From knowledge management to strategic competence: Measuring technological, market and
organizational innovation. London: Imperial College Press.
Torvstiga, G. and Birchall, D.W. (2002). Strategic knowledge, sourcing, integration, and assimilation: A
capabilities-portfolio perspective. In Bontis, N. (Ed.) World congress on intellectual capital readings, 104-18.
Viedma, J.M. (2002). Innovation capability – Benchmarking System (ICBS). In Bontis, N. (Ed.), World Congress
on Intellectual Capital Readings. Boston, MA: Butterworth-Heinemann, 243-65.
474

A Critical Review <strong>of</strong> Business Performance Models and
Frameworks and Their Application to Sales Organisations
Angelos Vouldis 1,2 and Angelica Kokkinaki 2
1
Cyprus Import Corporation Ltd, Cyprus
2
University <strong>of</strong> Nicosia, Cyprus
vouldis.a@unic.ac.cy
avouldis@cic.com.cy
kokkinaki.a@unic.ac.cy
Abstract: In view <strong>of</strong> <strong>the</strong> recent developments <strong>of</strong> <strong>the</strong> global economy, <strong>the</strong> organisations have placed in high
priority <strong>the</strong> development <strong>of</strong> efficient, yet cost-effective management processes. Within this orientation, efficient
and cost-effective monitoring and measurement <strong>of</strong> performance in marketing and sales has also received
increased attention. This paper reviews <strong>the</strong> literature regarding existing frameworks and models that have been
proposed so far in relation to performance measurement. It aims to raise awareness and understanding <strong>of</strong> some
<strong>of</strong> <strong>the</strong> most popular performance improvement models and frameworks available to organizations. It sheds light
on <strong>the</strong> common problems people face into why managing performance can be so difficult and why some <strong>of</strong> <strong>the</strong>
best attempts at improvement can fail. Most organisations still do not have appropriate methods for measurement
business performance. The paper draws on both academic literature and organisational practice to support <strong>the</strong>
selection <strong>of</strong> <strong>the</strong> appropriate model or framework that works best for measuring business performance <strong>of</strong> an
organisation. It is involved a critical review <strong>of</strong> <strong>the</strong> background, scope, key strengths, issues in implementation for
every important particular performance management model. The criteria for selecting <strong>the</strong> appropriate model or
framework focus on <strong>the</strong> align daily work to <strong>the</strong> organisation’s strategic objectives, provide a structured approach
to strategic management, establish winning performance indicators, support internal and external communication,
sustain customer satisfaction at all times and finally identify strengths and areas for improvement. Frameworks
and models to be covered will include <strong>the</strong> Balanced Scorecard, <strong>European</strong> Foundation for Quality Management
(EFQM) Excellence Model®, ISO 9001:2000, Six Sigma, Performance Prism and Tableau de Bord (France). A
key <strong>the</strong>me that will run throughout this review will be <strong>the</strong> fact that each <strong>of</strong> <strong>the</strong>se measurement frameworks <strong>of</strong>fers
a partial view <strong>of</strong> business performance. Based on <strong>the</strong> literature review <strong>the</strong> paper suggests a framework for
comparing <strong>the</strong>se alternative approaches which fulfils <strong>the</strong> identified lacks and strengths focus on <strong>the</strong>ir application
to sales organizations.
Keywords: performance measurement, performance management, sales organisation, literature review,
business performance models, business performance frameworks
1. Introduction
This paper reviews <strong>the</strong> literature regarding existing frameworks and models that have been proposed
so far in relation to performance measurement. The research is based on data has been collected
through a literature review to create a solid <strong>the</strong>oretical basis for <strong>the</strong> different models and frameworks
for managing performance. Findings from this research study will be considered supporting people to
decide on <strong>the</strong> approach or balance <strong>of</strong> approaches that would best suit <strong>the</strong>ir organisation and
circumstances. The paper is structured as follows. The research findings <strong>of</strong> <strong>the</strong> critical literature
review are summarise in a framework for comparing <strong>the</strong>se alternative approaches which fulfils <strong>the</strong>
identified lacks and strengths focus on <strong>the</strong>ir application to sales organisations. Finally, in <strong>the</strong> last
section, conclusions for future research are provided.
1.1 Models and frameworks for performance measurement
It is interesting to conduct a literature review regarding existing frameworks and models that have
been proposed so far in relation to performance measurement. Keegan et al. (1989) outline three
distinct steps for <strong>the</strong> for performance measurement system design. ‘Defining <strong>the</strong> strategic objectives
<strong>of</strong> <strong>the</strong> firm and how <strong>the</strong>y can be translated into divisional goals and individual management actions;
deciding what to measure; instilling <strong>the</strong> performance measurement system into management thinking,
possibly through <strong>the</strong> budgeting process.’
The more widely used models and frameworks for performance measurement have been reviewed
below in alphabetical order.
475

2. Balanced scorecard framework
Angelos Vouldis and Angelica Kokkinaki
A method widely utilised in various organisational settings is <strong>the</strong> Balanced Scorecard (BSC) approach
(Kaplan & Norton, 1992). Introduced by Robert S. Kaplan and David P. Norton in 1992, balanced
scorecards have found widespread adoption in Fortune 1000 companies. Rohm & Halbach (2005)
state that ‘building and implementing a scorecard system is more about changing hearts and minds
and sustaining new directions, than it is about selecting performance measures and buying Balanced
Scorecard s<strong>of</strong>tware.’
The Balanced Scorecard is a holistic model that can be used at various levels across <strong>the</strong>
organisation, service, team or group. It aims to enable organisations to manage strategy by linking
corporate objectives, initiatives, measures and targets at all levels in <strong>the</strong> organisation. It is <strong>of</strong>ten
viewed as an attempt to translate strategy in to action and it proposes measuring enterprise
performance under four different perspectives, as shown in Figure 1.
Figure 1: Balanced scorecard perspectives (from Kaplan & Norton, 1992)
The Financial Perspective links <strong>the</strong> financial objectives to <strong>the</strong> corporate strategy <strong>of</strong> an organisation.
The Customer Perspective examines aspects related to customers’ perceptions.The Innovation and
Learning Perspective on <strong>the</strong> Balanced Scorecard expands objectives and measures related to
organisational learning and growth with respect to employees, systems and organisational alignment.
The Internal Business Perspective focuses on all actions and key processes necessary for delivering
<strong>the</strong> value expected by <strong>the</strong> customers in a productive and efficient way and in doing so to prioritize
research, design and development processes and examine important operations process measures
as cost, quality, time, and performance characteristics.
Originally <strong>the</strong> Balanced Scorecard prompted users to identify an equal number <strong>of</strong> measures in each <strong>of</strong>
four perspectives. This demonstrated <strong>the</strong> need to balance financial and non-financial measures;
internal and external measures; leading and lagging measures; and short and long-term measures.
Researchers realised that having balance in <strong>the</strong> number <strong>of</strong> measures is no longer considered strictly
necessary after different implementations and researches development. Schneiderman (2006) argues
that balance is actually harmful and that ‘good scorecards will be unbalanced’.
Rohm & Halbach (2005) suggest a ‘Nine Steps To Success balanced scorecard’ 'framework as
shown in Figure 2 for building and implementing a Balanced Scorecard approach.
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Angelos Vouldis and Angelica Kokkinaki
Figure 2: The balanced scorecard institute’s 9 step framework (from Rohm & Halbach, 2005)
Step one is an Assessment <strong>of</strong> <strong>the</strong> organisation’s foundations, its core beliefs, market opportunities,
competition, financial position, short and long-term goals, and an understanding <strong>of</strong> what satisfies
customers. Step two is <strong>the</strong> development <strong>of</strong> overall Business Strategy. Step three is a decomposition
<strong>of</strong> business strategy into smaller components, called Objectives. In step four, a Strategic Map <strong>of</strong> <strong>the</strong>
organisation’s overall business strategy is created. In Step five, Performance Measures are
developed to track both strategic and operational progress. In step six, new Initiatives are identified
that need to be funded and implemented to ensure that our strategies are successful. Step seven
involves automating <strong>the</strong> Balanced Scorecard system, and consists <strong>of</strong> analysing s<strong>of</strong>tware options and
user requirements to make <strong>the</strong> most cost-effective s<strong>of</strong>tware choice for today and to meet enterprise
performance information requirements in <strong>the</strong> future. Step eight involves cascading <strong>the</strong> corporate
scorecard throughout <strong>the</strong> organization to business and support units, and ultimately to teams and
individuals.
Blokdijk (2008) states some <strong>of</strong> <strong>the</strong> following main reasons that balanced scorecard may fail.
Leadership from <strong>the</strong> management <strong>of</strong> <strong>the</strong> organisation is essential. Management with <strong>the</strong>ir commitment
and participation <strong>of</strong> <strong>the</strong> development <strong>of</strong> this business approach will motivate employees to <strong>the</strong>ir daily
tasks and will eventually lead to business success. Communication is ano<strong>the</strong>r important reason
required at every level <strong>of</strong> an organisation. Training and communication required as <strong>the</strong>
implementation <strong>of</strong> <strong>the</strong> balanced scorecard approach likely to mean huge changes in an organisation.
Timing is crucial for <strong>the</strong> development <strong>of</strong> any business operation. A strategic and timing plan needs to
visualise <strong>the</strong> sequence and order <strong>of</strong> activities or events that need to happen to create <strong>the</strong> desired
future state.
3. <strong>European</strong> Foundation for Quality Management (EFQM) Excellence Model®
The <strong>European</strong> Foundation for Quality Management Model (EFQM) is widely recognized as a
comprehensive organisational development and improvement framework used for evaluating
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Angelos Vouldis and Angelica Kokkinaki
strengths and areas for improvement across <strong>the</strong> organisation’s activities. Self-assessment is
considered as one <strong>of</strong> <strong>the</strong> most interesting topics for both researchers and companies implementing
<strong>the</strong> EFQM model (Black & Crumley, 1997). Undertaking a self-assessment process against <strong>the</strong> EFQM
Excellence Model provides an objective, systemic measure <strong>of</strong> an organisation’s strengths and areas
<strong>of</strong> improvement, and gives rise to <strong>the</strong> establishment and implementation <strong>of</strong> action plans, integrated in
business planning (Porter & Tanner, 1996).
The model is divided into two areas, five ‘enablers’ and four ‘results’ with a specific criterion weights
for each element if an organisation wants to achieve ‘Excellence’ as shown figure 3.
Figure 3: The EFQM Excellence Model 2010 (Gemoets, 2010)
The rationale for <strong>the</strong> implementation <strong>of</strong> <strong>the</strong> model is summarised in Jackson (2001) where it is
suggested that ‘<strong>the</strong>re is no one best way <strong>of</strong> implementing <strong>the</strong> EFQM excellence model into all
organisations.’ Questionnaires based upon <strong>the</strong> Model and workshop approach can be used across
<strong>the</strong> organisation on how <strong>the</strong> nine criteria are being met.
One <strong>of</strong> <strong>the</strong> major limitations <strong>of</strong> <strong>the</strong> EFQM model is that <strong>the</strong>re is a lack <strong>of</strong> guidelines for identifying
problems that result from organisational weaknesses (Rusjan, 2005). Svensson & Klefsjo (2006) warn
that, if <strong>the</strong> organisation has not reached <strong>the</strong> necessary maturity level, it is probably a waste <strong>of</strong>
resources to start a comprehensive self-assessment project. Hides et al. (2004) report that <strong>the</strong> longterm
nature <strong>of</strong> <strong>the</strong> EFQM Excellence Model makes it unsuitable for “quick fixes” whilst Karapetrovic &
Willborn (2001) link <strong>the</strong> choice <strong>of</strong> <strong>the</strong> self-assessment approach to <strong>the</strong> level <strong>of</strong> maturity <strong>of</strong> an
organization and <strong>the</strong> intensity <strong>of</strong> effort invested in <strong>the</strong> self-assessment. Li & Yang (2003) state that
although <strong>the</strong> current scoring system <strong>of</strong> <strong>the</strong> EFQM model has been widely accepted by both
academics and practitioners as a sound approach for self-assessment, certain writers are in
agreement that organisations have encountered problems applying <strong>the</strong> model because <strong>the</strong> scoring
criteria are too generally defined.
4. ISO 9001:2000
The literature reviewed indicated that Quality has focused to extend to all parts <strong>of</strong> <strong>the</strong> business.
Quality must be an integral part <strong>of</strong> <strong>the</strong> way <strong>the</strong> business is managed and requires very strong, crossfunctional
leadership at <strong>the</strong> highest levels in <strong>the</strong> company (Cobb, 2003). The technique to involve all
parts <strong>of</strong> <strong>the</strong> business is <strong>the</strong> Total Quality Management (TQM). An international tool for implementing
<strong>the</strong> TQM is <strong>the</strong> ISO. Organisations can use ISO as a model in designing <strong>the</strong>ir management systems
(Hoyle, 2005). ISO 9000 is a family <strong>of</strong> standards for <strong>the</strong> development <strong>of</strong> good management practices
via <strong>the</strong> development <strong>of</strong> consistently good quality products. It has four basic steps: Say what you do.
Do what you say. Record what is done. Improve, based on <strong>the</strong> results. (Delnista, 1999). An average
time to implement <strong>the</strong> quality management system ISO 9000 series is reported at between 12 to 16
months (Brown et al., 1998). Once a quality system is in place and established <strong>the</strong> organisation can
seek independent assessment by an internationally recognised accreditation body.
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Angelos Vouldis and Angelica Kokkinaki
ISO 9001 series enhances customer satisfaction by meeting customer requirements with a processbased
quality management system as illustrates figure 4. One <strong>of</strong> <strong>the</strong> most important sections <strong>of</strong> this
quality management system is <strong>the</strong> measurement, analysis and improvement. It demands continuous
improvement and <strong>the</strong> establishment <strong>of</strong> measurable goals. Schlickman (2003) states ‘ISO 9001:2000
requirements are designed to create continual improvement.’
Figure 4: Model <strong>of</strong> process-based quality management (from Grimes, 2003)
As Tricker & Lucas (2005) documented ‘ISO 9001:2000 is flexible enough to fit any sort <strong>of</strong>
organisation’. This flexibility is connected with <strong>the</strong> loop <strong>of</strong> <strong>the</strong> continual improvement. Careful selection
<strong>of</strong> measures and proper collection <strong>of</strong> data provide a basis for continual process improvement (West &
Cianfrani, 2004).
Feng et al. (2007) concluded from <strong>the</strong>ir research that ISO 9000 series has a positive and significant
effect on operational performance, but a positive weak effect on business performance. It emphasises
on <strong>the</strong> measurement and monitoring <strong>of</strong> several key performance indicators. There are many barriers
in <strong>the</strong> implementation processes <strong>of</strong> ISO 9000 standards. According to Quazi & Padibjo (1998) <strong>the</strong>
following main issues are important:
Lack <strong>of</strong> top management support and commitment;
Employee resistance change;
Lack <strong>of</strong> understanding <strong>of</strong> ISO 9000 system;
Constraints on resources (manpower, time, finance);
Lack <strong>of</strong> training and education <strong>of</strong> employees;
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Unclear benefits <strong>of</strong> obtaining certification.
Angelos Vouldis and Angelica Kokkinaki
Some researchers query on <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong> ISO 9000 series quality management system.
Terziovski et al. (2003) found that ISO 9000 certification did not have a significantly positive
relationship with organisational performance. Yeung et al. (2003) revealed that senior executives’
incorrect understanding <strong>of</strong> ISO 9000 and attitudes to <strong>the</strong> international standards are <strong>the</strong> main cause
<strong>of</strong> <strong>the</strong> ineffectiveness <strong>of</strong> ISO 9000 implementation. Brown & Wiele (1998) found that lack <strong>of</strong>
commitment from employees and managers is <strong>the</strong> most frequently mentioned problem faced by Small
to Medium Enterprises (SMEs) in implementing ISO certification.
5. The Performance Prism
The Performance Prism is a measurement framework designed to assist performance measurement.
It was developed by <strong>the</strong> Centre for Business Performance at Cranfield School <strong>of</strong> Management, in
conjunction with Accenture company. It developed from <strong>the</strong> Balanced Scorecard, as a second
generation <strong>of</strong> performance measurement framework which considers <strong>the</strong> wants and needs <strong>of</strong> all <strong>the</strong>
organisation's stakeholders. Neely et.al (2001) described <strong>the</strong> Performance Prism consists <strong>of</strong> five
interrelated facets as shown figure 5.
Figure 5: The five facets <strong>of</strong> <strong>the</strong> Performance Prism (from Neely et.al, 2001)
At <strong>the</strong> first facet comparing with <strong>the</strong> balanced scorecard view <strong>of</strong> stakeholders are included additionally
to customers and stakeholders <strong>the</strong> employees, suppliers, alliance partners or intermediaries, <strong>the</strong> local
community. The second facet concentrates on Strategies. It explored <strong>the</strong> issue <strong>of</strong> what strategies
should be put in place to ensure <strong>the</strong> wants and needs <strong>of</strong> <strong>the</strong> stakeholders are satisfied. The fourth
facet <strong>of</strong> <strong>the</strong> Performance Prism, <strong>the</strong> Capabilities facet are <strong>the</strong> combination <strong>of</strong> people, practices,
technology and infrastructure that toge<strong>the</strong>r enable execution <strong>of</strong> <strong>the</strong> organisation's business
processes.
The fifth and final facet <strong>of</strong> <strong>the</strong> Performance Prism is <strong>the</strong> Stakeholder Contribution facet. This facet
organisation has been entering into a relationship with <strong>the</strong>ir stakeholders which should involve <strong>the</strong>
stakeholders contributing to <strong>the</strong> organisation.
The model is used a set <strong>of</strong> performance measures that help deliver <strong>the</strong> wants and needs <strong>of</strong> both <strong>the</strong>
organisation and its key stakeholders using strategy maps identifying <strong>the</strong> objectives and drivers <strong>of</strong>
performance that are inherent in <strong>the</strong> organisation’s strategy. The maps are usually developed in
cross-functional management workshops. The performance prism enables a balanced picture <strong>of</strong> <strong>the</strong>
business to be provided, significantly highlighting external and internal measures, as well as enabling
financial and non-financial measures and measures <strong>of</strong> efficiency and effectiveness (Neely, 2002). It
drills down from strategies to processes and to capabilities; <strong>the</strong> performance prism achieves a
comprehensiveness and wide-angle view that o<strong>the</strong>r business performance measurement frameworks
lack (Adams & Neely, 2000). However, as Medori & Steeple (2000) state that it is provided little
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Angelos Vouldis and Angelica Kokkinaki
guidance on how <strong>the</strong> appropriate measures can be identified, introduced and ultimately used to
manage <strong>the</strong> business. Fur<strong>the</strong>rmore Performance Prism was recently developed with little experience
<strong>of</strong> using it in different organisations.
6. Six Sigma
Six Sigma can be considered as a recent quality improvement initiative that has gained popularity and
acceptance in many industries across <strong>the</strong> globe (Jiju et.al, 2005). Six Sigma is named after <strong>the</strong>
process that has six standard deviations on each side <strong>of</strong> specification window (Chen et al., 2007).
Wyper & Harrison (2000) interpreted Six Sigma as a useful management philosophy and problemsolving
methodology that is a direct extension <strong>of</strong> Total Quality Management (TQM).
It is a disciplined methodology with statistical focus for process improvement in <strong>the</strong> area <strong>of</strong> customer
satisfaction, reducing errors and defects, reducing cycle time. The basic principles <strong>of</strong> <strong>the</strong> six-sigma
approach, which is ultimately a managerial decision-making tool, include:
Aligning key business processes and customer requirements with <strong>the</strong> organization’s strategic
goals;
Identifying corporate sponsors to champion projects, supporting <strong>the</strong> team, obtaining necessary
resources, and helping organizational members to overcome <strong>the</strong> resistance to change;
Instituting a standard measurement system to be used throughout <strong>the</strong> organisation;
Identifying appropriate metrics that focus on business results and accountability;
Providing extensive six-sigma and project management training;
Deploying appropriately trained teams to improve quality and pr<strong>of</strong>itability while reducing time and
waste;
Setting stretch improvement goals (Evans & Lindsay, 2005)
Six Sigma still has its limitations. News keeps cropping up about <strong>the</strong> efficacy <strong>of</strong> <strong>the</strong> Six Sigma
business strategy from its critics, as a management fad – a fashion that sweeps <strong>the</strong> world with great
excitement for a brief period <strong>of</strong> time, usually less than a year, and <strong>the</strong>n disappears (Swinney, 2005).
7. Tableau de Bord (France)
Tableau de Bord was developed by process engineers in order to improve <strong>the</strong> internal processes and
control <strong>the</strong> performance (Epstein & Manazoni, 1998). The Tableau de Bord, meaning “dashboard” or
“instrument panel”, has been an important management control tool used in French enterprises for
more than 40 years and is believed to have similar attributes with balance scorecard with <strong>the</strong>
exception that <strong>the</strong> latter is developed as a strategic tool. Although <strong>the</strong> majority <strong>of</strong> <strong>the</strong> large companies
in France were using it, due to <strong>the</strong> limited availability <strong>of</strong> translated literature it had a minimal overseas
diffusion (Bontis et al., 1999).
The development <strong>of</strong> <strong>the</strong> Tableau de Bord involves translating <strong>the</strong> vision and mission into a set <strong>of</strong>
objectives, from which each unit identifies its Key Success Factors which are translated into series <strong>of</strong>
quantitative Key Performance Indicators (Kanji, 2002). Fur<strong>the</strong>rmore, it emphasises to financial
measures that <strong>of</strong>ten are focus internally inside <strong>the</strong> organisation ra<strong>the</strong>r than externally from customers.
As defined from <strong>the</strong> translation by De Guerny et al., (1990) a Tableau de Bord has <strong>the</strong> following
primary characteristics:
‘It is simple and can <strong>the</strong>refore be ‘installed’ relatively quickly;
It concentrates on only a few key items <strong>of</strong> information, which focus on <strong>the</strong> specific area <strong>of</strong>
responsibility and issue at hand (that is, only <strong>the</strong> truly decision-relevant information), and does not
attempt to provide answers to all possible questions;
It primarily provides information about <strong>the</strong> status <strong>of</strong> processes in <strong>the</strong> operational areas (such as
Sales or Production), and about <strong>the</strong> purely financial aspects that are regarded as <strong>the</strong> results <strong>of</strong>
<strong>the</strong>se operational activities;
It makes <strong>the</strong> information quickly available according to <strong>the</strong> specific demand <strong>of</strong> a decision maker
and also outside <strong>the</strong> frequency and periodicity <strong>of</strong> accounting.’
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8. Selecting <strong>the</strong> appropriate model or framework for measuring business
performance for a sales organisation
The objective <strong>of</strong> <strong>the</strong> selecting <strong>the</strong> appropriate model framework will enable <strong>the</strong> sales organisation
quickly and effectively selecting metrics that support sales objectives, strategy and goals. The
selected framework or model will support to:
Expand a deeper understanding <strong>of</strong> <strong>the</strong> factors <strong>of</strong> sales productivity
Develop a common understanding for monitoring and improving performance
Recognise sales performance from a variety <strong>of</strong> perspectives
As Neely et al. (2003) analysed to gain real value from measuring business performance need to
address <strong>the</strong> challenges <strong>of</strong> <strong>the</strong> third generation approaches, namely:
Models or frameworks must reflect <strong>the</strong> static and dynamic realities <strong>of</strong> organisations but at <strong>the</strong>
same time not lose appropriateness as a managerial tool;
We must move from data to information and must provide rigorous information especially for <strong>the</strong>
intangible value drivers in organisations;
The models must be practical and aligned with o<strong>the</strong>r organisational processes in order to allow
actions to be taken;
And most fundamentally <strong>of</strong> all, we must seek increasingly robust ways <strong>of</strong> demonstrating <strong>the</strong> cash
flow implications <strong>of</strong> <strong>the</strong> non-financial and intangible organisational value drivers.
Performance measurement framework must have practical value, <strong>the</strong> process <strong>of</strong> populating <strong>the</strong>
framework has to be understood in detailed. Neely et.al (2000) finalised, as shown figure 6, into four
interlinked <strong>the</strong>mes <strong>of</strong> measurement system design, implementation, use and ongoing management,
and <strong>the</strong> people, processes, infrastructure and culture issues associated with <strong>the</strong>m.
Figure 6: Measuring business performance: emerging research <strong>the</strong>mes (from Neely et.al, 2000)
The starting point for any selection process has to be <strong>the</strong> recognition that <strong>the</strong> different models and
frameworks for measuring business performance each have different strengths and weaknesses. The
criteria for selecting <strong>the</strong> appropriate model or framework focus on <strong>the</strong> align daily work to <strong>the</strong>
organisation’s strategic objectives, provide a structured approach to strategic management, establish
winning performance indicators, support internal and external communication, sustain customer
satisfaction at all times and finally identify strengths and areas for improvement
A framework to support <strong>the</strong> selection <strong>of</strong> <strong>the</strong> appropriate model or framework has been developed
based on existing literature and <strong>the</strong> functions and elements <strong>of</strong> a sales organisation. The following
assessment criteria were used asking specific questions for every different model or framework:
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Angelos Vouldis and Angelica Kokkinaki
Scope: What is <strong>the</strong> aiming to change and improve? What outcome are <strong>the</strong> organisation looking
for? Does <strong>the</strong> improvement need to be holistic covering all <strong>the</strong> organisations activities or designed
for a specific task, service or area <strong>of</strong> activity?
Time: What is <strong>the</strong> timescale for <strong>the</strong> change?
Resources: What resources are available or are needed?
Staff involvement: To what extent do you want to involve staff in <strong>the</strong> changes?
Flexibility: Does <strong>the</strong> performance measurement system remains integrated, efficient and effective
at all times?
Organisations need to undertake research to decide on <strong>the</strong> approach or balance <strong>of</strong> approaches that
would best suit <strong>the</strong>ir organisation and circumstances. It is unlikely that a single approach would
address all <strong>the</strong>ir needs maybe will be needed to extent it to fulfil <strong>the</strong> most important criteria <strong>of</strong> efficient
and cost-effective monitoring and measurement <strong>of</strong> business performance.
Addressing <strong>the</strong>se criteria for every different model or framework as present in Table 1 allows
organisations to develop <strong>the</strong>ir awareness and understanding <strong>of</strong> selecting <strong>the</strong> appropriate model <strong>of</strong>
framework for measuring business performance in an organisation.
Table 1: Selecting an appropriate model or tool for measuring business performance
Performance
Models
Balanced
Scorecard
Framework
<strong>European</strong>
Foundation for
Quality
Management
(EFQM)
Excellence
Model®
ISO 9001:2000
Performance
Prism
Six Sigma
Tableau de
Bord
Scope Time Resources
Holistic model
that can be
used at
various levels
across <strong>the</strong>
organisation.
Holistic self
assessment
model
Tool for
implementing
<strong>the</strong> TQM
Focus to
analyse
stakeholders
needs
Statistical
focus for
process
improvement
Translating
<strong>the</strong> vision and
mission into a
set <strong>of</strong>
objectives
Four to six
months to
implementation
depending on
level <strong>of</strong>
measurement
in place
Approximately
six weeks
Implementation
six to nine
months
Up to approx.
six months
it will normally
take three to
nine months
It is simple and
can <strong>the</strong>refore
be ‘installed’
relatively
quickly.
Low resource
investment –
<strong>of</strong>ten just
facilitation
costs and
staff time.
Essential
external
expert
support
Internal
expert is
essential.
External
auditor
organisation
is vital to be
used.
Several
management
workshops
are
necessary
Consultancy
requirement
Low resource
investment
483
Staff
involvement
Inclusive if
scorecards are
cascaded and
widely deployed
Fully inclusive.
Workshops
approach can
be used across
<strong>the</strong> organisation
Inclusive <strong>of</strong> staff
in <strong>the</strong> areas <strong>of</strong>
activity being
improved.
Considers <strong>the</strong>
wants and
needs <strong>of</strong> all <strong>the</strong>
organisation's
stakeholders.
Focuses on
making
improvements
in <strong>the</strong> area <strong>of</strong>
customer
satisfaction
Support
management to
share
responsibilities
Flexibility
It integrates
different classes <strong>of</strong>
organisational
performance –
financial and nonfinancial,
internal
and external.
Long-term nature <strong>of</strong>
<strong>the</strong> EFQM link
flexibility to <strong>the</strong> level
<strong>of</strong> maturity
Connected with <strong>the</strong>
loop <strong>of</strong> <strong>the</strong>
continual
improvement.
It achieves a
comprehensiveness
and wide-angle
view
Dynamic
operational
capabilities with
consultancy support
It primarily provides
information about
<strong>the</strong> operational
areas less about
<strong>the</strong> purely financial
aspects

9. Discussion and conclusions
Angelos Vouldis and Angelica Kokkinaki
This report reviews <strong>the</strong> extensive literature relating to organisational performance management and
presents a suggested framework to evaluate <strong>the</strong> most suitable model or framework for a sales
organisation. As shown from this literature analysis <strong>the</strong>re is no single model or process for developing
performance objectives and measures, nor is <strong>the</strong>re a process that will guarantee good results. It has
been attempted to syn<strong>the</strong>size this models and frameworks with <strong>the</strong> aim to produce <strong>the</strong> most suitable
conceptual framework for <strong>the</strong> size, kind, and available resources. Additional it must be taken in
consideration also <strong>the</strong> culture and <strong>the</strong> existing tools that are already have been used by <strong>the</strong>
organisation for measuring and manage business performance.
However <strong>the</strong>re are clear arguments which are provided from <strong>the</strong>se models and frameworks. These
can be summarised as:
Performance management should be integrated and involved all <strong>the</strong> key stakeholders across <strong>the</strong>
organisation. It should mirror <strong>the</strong> objectives linking with <strong>the</strong> strategies <strong>of</strong> <strong>the</strong> organisation to <strong>the</strong>
execution <strong>of</strong> activities which will enable <strong>the</strong>ir achievement.
Processes and tools should be considered to extract and communicate insights ra<strong>the</strong>r than
performance data. With meetings and trainings can be created a learning and improvement
performance culture reinforce each o<strong>the</strong>r on a sustainable basis.
The measurement systems to develop successfully <strong>the</strong>re are key capabilities and responsibilities
that an organisation must have in place. An effectively measurement system must be evaluate
with <strong>the</strong> time, effort and finally with implementation and running costs.
It clears that for measurements systems to evolve effectively <strong>the</strong>re are key resources which must
have in place. Fur<strong>the</strong>rmore as de Waal, A. (2002) state that performance is an outcome <strong>of</strong> both
organisational and human activities. It is important <strong>the</strong> selected performance management system to
engage an appropriate culture to <strong>the</strong> organisation’s employees and should reflect <strong>the</strong> requirements <strong>of</strong>
all <strong>of</strong> <strong>the</strong> key stakeholders <strong>of</strong> <strong>the</strong> organisation and not just reflect a limited set.
Additional, a performance measurement system should be a dynamic system and must include
information from <strong>the</strong> wider environment. It is recognized by <strong>the</strong> above literature review that <strong>the</strong>
external and internal environment <strong>of</strong> an organisation is constantly changing.
Although recommendations and conceptual frameworks for performance measurement system design
have been systematically defined, few are <strong>the</strong> contributions on how to transform <strong>the</strong>m to a
development process. Therefore <strong>the</strong>re is still a need to expand a step-by-step method for
implementing a comprehensive, integrated performance measurement system.
References
Adams, C. and Neely, A. (2000). “The Performance Prism to Boost M&A Success”, Measuring Business
Excellence, Vol. 4, No. 3, pp 19-23.
Black, A. & Crumley, C. (1997). “Self-assessment: what’s in it for us?”, Total Quality Management, Vol. 8, No. 2,
pp. 96-109.
Blokdijk, G (2008). Balanced Scorecard 100 Success Secrets, 100 Most Asked Questions on Approach,
Development, Management, Measures, Performance and Strategy. USA: Lulu.com. pp. 18-35.
Bontis, N., & Dragonetti, N., &Jacobsen, K. & Roos, G. (1999). “The knowledge toolbox: a review <strong>of</strong> <strong>the</strong> tools
available to measure and manage intangible resources”, <strong>European</strong> Management Journal,Vol. 17 No. 4, pp.
391-402.
Brown, A. & Wiele, A. (1998). “Smaller enterprises’ experience with ISO 9000”, International Journal <strong>of</strong> Quality &
Reliability Management, Vol. 15 No. 3, pp. 273-285.
Chen, S., Hsu, H. and Ouyang, Y. (2007), “Applied product capability analysis chart in measure step <strong>of</strong> Six
Sigma”, Quality and Quantity, Vol. 41, pp. 387-400.
Cobb, C (2003). From Quality to Business Excellence: A Systems Approach to Management. USA: American
Society for Quality. pp 124.
De Guerny, J & Guiriec, C. & Lavergne, J. (1990). Principes et mise en place du Tableau de Bord de Gestion.
6th Edition, Paris. pp 14
De Waal, A. (2002), “Quest for Balance: The Human Element in Performance Management Systems” John
Wiley. pp 45-60
Delnista, S. (1999). ISO 9000 and S<strong>of</strong>tware Validation and Verification. Available:
http://people.cis.ksu.edu/~hankley/d841/Su01/Steve.html. Last accessed 20th Oct 2010.
Epstein, M. & Manazoni, J. (1998). “Implementing corporate strategy: from Tableauxbde Bord to Balanced
Scorecard”, <strong>European</strong> Management Journal, Vol. 16, N.2 pp. 190-203
484

Angelos Vouldis and Angelica Kokkinaki
Evans, R. & Lindsay, M. (2005). An Introduction to Six-sigma & Process Improvement, Thompson-Southwestern
Publishing, Belmont, CA.
Feng, M & Terziovski, M & Samson, D (2007). “Relationship <strong>of</strong> ISO 9001:2000 quality system certification with
operational and business performance: A survey in Australia and New Zealand-based manufacturing and
service companies”, Journal <strong>of</strong> Manufacturing Technology Management, Vol. 19, 1, pp. 22 – 37
Gemoets, P. (2010). ‘The Transition Guide - How to upgrade to <strong>the</strong> EFQM Excellence Model 2010’. EFQM 2010.
1.01 (1), p1-18.
Grimes, K (2003). ISO 9001:2000: a practical quality manual explained. Illustrated. ed. USA: American Society
for Quality. pp 12
Hides, M.T., Davies, J. and Jackson, S. (2004). “Implementation <strong>of</strong> EFQM Excellence Model self-assessment in
<strong>the</strong> UK higher education sector – lessons learned from o<strong>the</strong>r sectors”, The TQM Magazine, Vol. 16 No. 3,
pp. 194-201.
Hillman, G.P. (1994). “Making self-assessment successful”, The TQM Magazine, Vol. 6 No. 3, pp. 29-31.
Jackson, S. (2001). Using <strong>the</strong> EFQM Excellence Model within Health Care: A Practical Guide to Success,
Kingsham Press, Chichester, pp. 45
Jiju A., & Maneesh A.,& Madu, M. (2005). “Six sigma in small- and medium-sized UK manufacturing
enterprises”, International Journal <strong>of</strong> Quality & Reliability Management, Vol. 22 No. 8, pp. pp. 860-74.
Kanji, G (2002). Measuring business excellence. USA: Routledge. pp 14-15
Karapetrovic, S. & Willborn, W. (2001). “Audit and self-assessment in quality management: comparison and
compatibility”, Managerial Auditing Journal, Vol. 16, No. 6, pp. 366-77.
Keegan, P. and Eiler, G. and Jones, P. (1989). “Are your performance measures obsolete?” Management
Accounting, June, pp. 45-50.
Li, M. & Yang, J. B. (2003). “A decision model for self-assessment <strong>of</strong> business process based on <strong>the</strong> EFQM
excellence model”, International Journal <strong>of</strong> Quality and Reliability Management, Vol. 20, No. 2, pp. 164–88.
Medori, D. & Steeple, D. (2000). “A framework for auditing and enhancing performance measurement systems”,
International Journal <strong>of</strong> Operations & Production Management, Vol. 20 No. 5, pp. 520-33.
Neely, A. & Mills, J. & Platts, K. & Richards, H & Gregory, M & Bourne, & M. & Kennerley, M. (2000).
“Performance measurement system design: developing and testing a process-based approach.”
International Journal <strong>of</strong> Operations & Production Management . Vol. 20, No. 10, pp 1119- 45.
Neely, A. and Adams C. and Crowe, P. (2001). “The performance prism in practice measuring excellence”, The
Journal <strong>of</strong> Business Performance Management, Vol. 5 No. 2, pp. 6-12.
Neely, A. (2002). Business Performance Measurement, Theory and Practice, Cambridge University Press, UK.
Neely, A & Marr, B & Roos, G & Pike, S & Gupta, O. (2003). ‘Towards <strong>the</strong> Third Generation <strong>of</strong> Performance
Measurement.’ Controlling, Vol. 15, No. 3/4, pp 129-35.
Porter, L. & Tanner, S. (1996). Assessing Business Excellence, Butterwoth Heinemann, Oxford.
Quazi, A. & Padibjo, R. (1998). “A journey toward total quality management through ISO 9000 certification – a
study on small and medium sized enterprises in Singapore”, International Journal <strong>of</strong> Quality and Reliability
Management, Vol. 15, pp.489–508.
Rohm, H and Halbach, L. (2005). “Developing and Using Balanced Scorecard Performance Systems.” Available:
http://www.ag.uky.edu/equine/admin/files/balancingact.pdf. Last accessed 5 July 2010.
Rusjan, B. (2005). “Usefulness <strong>of</strong> <strong>the</strong> EFQM excellence model: <strong>the</strong>oretical explanation <strong>of</strong> some conceptual and
methodological issues”, Total Quality Management & Business Excellence, Vol. 16 No. 3, pp. 363-380.
Schlickman, J (2003). ISO 9001:2000 Quality Management System Design: 2000 Quality Management System
Design. USA: Artech House. pp 14-62.
Svensson, M. & Klefsjo, B. (2006). “TQM-based self-assessment in <strong>the</strong> education sector”, Quality Assurance in
Education, Vol. 14 No. 4, pp. 299-323.
Swinney, Z. (2005). “Six Sigma Is Just A Fad” . Available:
http://www.isixsigma.com/index.php?option=com_k2&view=item&id=1367&Itemid=1&Itemid=1. Last
accessed 20th Oct 2010.
Terziovski, M. & Power, D. & Sohal, S. (2003). “The longitudinal effects <strong>of</strong> <strong>the</strong> ISO 9000 certification process on
business performance”, <strong>European</strong> Journal <strong>of</strong> Operational Research, Vol. 146, No. 3, pp. 580-95.
Tricker, R & Lucas, B (2005). ISO 9001:2000 In Brief. UK: Butterworth-Heinemann. pp 5-15.
West, C & Cianfrani, J (2004). Unlocking <strong>the</strong> Power <strong>of</strong> Your QMS: Keys to Performance Improvement. USA:
American Society for Quality. pp 29.
Wyper, B. & Harrison, A. (2000). “Deployment <strong>of</strong> Six Sigma methodology in human resource function: a case
study”, Total Quality Management, Vol. 11, No. 4, pp. 720-8.
Yeung, L. & Lee, S. & Chan, Y. (2003). “Senior management perspectives and ISO 9000 effectiveness: an
empirical research”, International Journal <strong>of</strong> Production Research, Vol. 41 No. 3, pp. 545-69.
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The Global Position <strong>of</strong> <strong>the</strong> <strong>European</strong> Patent Office (EPO):
Is Europe Capable <strong>of</strong> Protecting its Intellectual Capital
Effectively?
Piotr Wisniewski
Warsaw School <strong>of</strong> Economics, Poland
piotr.wisniewski@sgh.waw.pl
Abstract: The competitiveness <strong>of</strong> <strong>European</strong> intellectual capital (IC) and intellectual property (IP) stems from a
conjuncture <strong>of</strong> contemporary tendencies that are not easily manageable: socioeconomic and technological
dynamism <strong>of</strong> Eastern Asian economies vs. stagnation in Europe, complexity <strong>of</strong> innovation spillovers between
developed and emerging markets, as well as o<strong>the</strong>r geostrategic trends. Despite pressing challenges, Europe has
not yet succeeded in developing a seamless regime <strong>of</strong> protecting its intellectual base. Although <strong>the</strong> <strong>European</strong>
Patent Office (EPO) <strong>of</strong>fers a reasonably convenient route for IP registration, enforcement <strong>of</strong> EPO decisions is still
consigned to individual <strong>European</strong> jurisdictions. The sluggish pace <strong>of</strong> innovation in Europe in recent years has
been blamed on a great deal <strong>of</strong> contributing factors – limited functionality <strong>of</strong> Europe-wide patenting is certainly
one <strong>of</strong> <strong>the</strong>m.
Keywords: intellectual capital vs. intellectual property, <strong>European</strong> Patent Office’s position, global protection and
diffusion <strong>of</strong> intellectual property, single EU patent, international innovation
1. Intellectual property vs. intellectual capital
Intellectual property (IP) is a concept embracing “creations <strong>of</strong> <strong>the</strong> human mind: inventions, literary and
artistic works, and symbols, names, images, and designs used in commerce” – according to <strong>the</strong>
World Intellectual Property Organization (WIPO) – (WIPO 2010a). IP is protected to reward <strong>the</strong> efforts
<strong>of</strong> innovators, just like o<strong>the</strong>r forms <strong>of</strong> entrepreneurial activity. IP protection serves ano<strong>the</strong>r social goal
– it is expected to stimulate innovation, as potential inventors are incentivized by commercial factors.
The first international law governing <strong>the</strong> use <strong>of</strong> IP (adopted as <strong>the</strong> Convention Establishing <strong>the</strong> WIPO
in Paris in 1967) failed to define IP explicitly, yet it cataloged <strong>the</strong> following rights associated with IP
(WIPO 1967), i.e.:
Literary, artistic and scientific works,
Performances <strong>of</strong> performing artists, phonograms, and broadcasts,
Inventions in all fields <strong>of</strong> human endeavor,
Scientific discoveries,
Industrial designs,
Trademarks, service marks, and commercial names and designations,
Protection against unfair competition,
All o<strong>the</strong>r rights resulting from intellectual activity in <strong>the</strong> industrial, scientific, literary or artistic fields
(WIPO 1967).
From <strong>the</strong> current perspective, IP can be classed as industrial property and copyright. Industrial
property connotes commercial application <strong>of</strong> innovative activity, whereas copyright is usually
associated with artistic expression.
Industrial property can take numerous forms. These include patents (to protect inventions), and
industrial designs (es<strong>the</strong>tic creations determining <strong>the</strong> appearance <strong>of</strong> industrial products). Industrial
property also encompasses trademarks, service marks, layout designs <strong>of</strong> integrated circuits,
commercial names and designations, as well as geographical indications, and o<strong>the</strong>r forms <strong>of</strong>
protection against unfair competition (WIPO 2010a).
Copyright is a form <strong>of</strong> protecting artistic creations, e.g. literary and artistic works such as novels,
poems and plays, films, musical compositions, drawings, paintings, photographs and sculptures,
architectural designs and a growing array <strong>of</strong> information technology applications, such as computer
s<strong>of</strong>tware or electronic databases. The right to copy such artistic creations is reserved to <strong>the</strong>ir
author(s), hence <strong>the</strong> origin <strong>of</strong> <strong>the</strong> term. Rights related to copyright include those <strong>of</strong> performing artists
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in <strong>the</strong>ir performances, producers <strong>of</strong> phonograms in <strong>the</strong>ir recordings, and those <strong>of</strong> broadcasters in <strong>the</strong>ir
radio and television programs.” (WIPO 2010b). Copyright differs from industrial property in <strong>the</strong> sense
that it protect <strong>the</strong> form <strong>of</strong> ideas, not <strong>the</strong> ideas <strong>the</strong>mselves, which is <strong>the</strong> case for industrial property.
Clearly, both categories are limited to those intellectual assets for which legal protection is possible
and economically viable. The following constraints apply to IP protection:
Economic rationality – to be economically viable, <strong>the</strong> registration <strong>of</strong> IP has to demonstrate a clear
pay<strong>of</strong>f scenario in excess <strong>of</strong> registration fees and opportunity costs <strong>of</strong> capital – in numerous
circumstances such a scenario is questionable;
Legal enforceability – once IP is registered and protected (at least in <strong>the</strong>ory) each possible
infraction has to be challenged via litigation, which becomes problematic if <strong>the</strong> legal regimes
involved are ineffective or fragmented; and economically doubtful if infractions are numerous,
dispersed (geographically and conceptually) and <strong>of</strong> a small size;
Sensitivity/secrecy – certain genres <strong>of</strong> innovation are so sensitive and vulnerable to copying that
<strong>the</strong> risk <strong>of</strong> <strong>the</strong>ir premature disclosure greatly outweighs benefits related to quick
commercialization, or <strong>the</strong>ir use is formally restricted (e.g. to <strong>the</strong> military);
Technical sophistication – high technologies are becoming increasingly complex while <strong>the</strong>ir
dTvelopment is time consuming, protracted and costly – IP protection at <strong>the</strong> final stages <strong>of</strong>
manufacture does not always properly address this value creating structure;
Supply/demand globalization – due to <strong>the</strong> rising diffusion <strong>of</strong> global innovative activity, it is
increasingly more difficult to ascribe <strong>the</strong> value creation chain to individual companies and
jurisdictions – this is exceptionally cumbersome at <strong>the</strong> interface <strong>of</strong> <strong>the</strong> developed and emerging
worlds.
Last – but not least – IP represents a only fraction <strong>of</strong> IC creation. The IC notion, although still evolving
in international <strong>the</strong>ory and practice, is usually associated with more universal coverage (Cf. Edvinsson
and Malone 1997), (Cf. Brooking 1997), (Cf. Wisniewski 2009). The reasons why IC is not always
afforded protection in <strong>the</strong> form <strong>of</strong> IP are diverse. The key arguments why IC seldom morphs into IP
include:
Novelty: IC is a path-breaking idea – its global use accelerated (in earnest) at <strong>the</strong> turn <strong>of</strong> <strong>the</strong> 20 th
and 21 st centuries, whereas various forms IP have been around for centuries;
Conservatism and materiality: <strong>the</strong> existing frameworks <strong>of</strong> economic reporting at <strong>the</strong>
macroeconomic, industrial and corporate levels clearly favor goods and services <strong>of</strong> a tangible
nature (identifying, branding and protecting <strong>the</strong>m as “assets”), IP is undoubtedly closer to that
paradigm than IC;
Conceptual chasm: IP and IC seem to appeal to largely separate groups <strong>of</strong> people (which partially
determines <strong>the</strong>ir application): IP is (in essence) a legal term, whereas <strong>the</strong> IC idea is usually
promulgated by philosophical, managerial and socioeconomic circles.
Besides <strong>the</strong> aforementioned practicalities limiting <strong>the</strong> usefulness <strong>of</strong> IP registration, <strong>the</strong> following
factors come into play:
Humanity: IP (unlike IC) is, for obvious reasons, incapable <strong>of</strong> fully capturing value embodied in
human assets – whereas <strong>the</strong>y are becoming increasingly vital to modern enterprises and
economies;
Backwardness: due to dynamic innovation, IP lags at least one step behind new products and
services (registration can never keep pace with innovation: <strong>the</strong> essence <strong>of</strong> IC);
Formalism: to be legally executable, IP has to be categorized into an existing kind <strong>of</strong> property,
numerous intellectual concepts transcend such boundaries (many new inventions are, in essence,
interdisciplinary).
The impact <strong>of</strong> IP protection on <strong>the</strong> propensity to innovate (i.e. produce IC) has – for long – been
marked by controversy in worldwide economic literature. Most researchers admit that a healthy
balance needs to be struck between innovators seeking maximum value extraction from <strong>the</strong>ir works,
and <strong>the</strong> risk <strong>of</strong> monopolization on account <strong>of</strong> overaggressive patenting – potentially applicable to
many high-pr<strong>of</strong>ile inventions (Cf. Federal Trade Commission 2003). It is fair to point out that without a
predictable value-extraction pattern (i.e. IC being productively commercialized into IP), innovators’
interests are at risk. Arguably, <strong>the</strong> more ineffective a legal system is, <strong>the</strong> bigger role IP has to play in
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safeguarding IC via formal registration. This is due to <strong>the</strong> fact that commercial courts (especially in
inept jurisdictions) do a poor job <strong>of</strong> protecting sophisticated goods and services (whose character is
not easily recognizable).
Despite <strong>the</strong> unquestionably broader conceptual scope <strong>of</strong> IC, IP has far outnumbered IC in English
language book citations. A ingenuous Google Labs (Books Ngram Viewer) project (Google Labs
2010) affords an intriguing glimpse into <strong>the</strong> occurrence <strong>of</strong> both collocations (i.e. “intellectual capital”
and “intellectual property”, dubbed by Google Labs as “2-grams” or “bigrams”) since <strong>the</strong> year 1500,
with statistical representativeness considered adequate since <strong>the</strong> year 1800 (Google Labs 2010).
IP and IC had enjoyed similarly peripheral usage in English language citations prior to <strong>the</strong> late 1970s
(a period <strong>of</strong> dynamic innovation in <strong>the</strong> United States economy). The early 1980s (in <strong>the</strong> United States
coincident with <strong>the</strong> era <strong>of</strong> Reaganomics) augured a steep upward trend in IP dissemination in English,
unparalleled by IC dynamics until <strong>the</strong> mid-1990s. The occurrence <strong>of</strong> both concepts culminated at <strong>the</strong>
burst <strong>of</strong> <strong>the</strong> “dot-com bubble” (in 2002) to recover ahead <strong>of</strong> an unprecedentedly sharp decline
portending <strong>the</strong> outbreak <strong>of</strong> a global financial crisis in 2007. Overall, in spite <strong>of</strong> rising significance and
correlation with IP, <strong>the</strong> IC notion still represents a miniscule fraction <strong>of</strong> IP references published in <strong>the</strong>
English language (Figure 1).
Figure 1: Google Labs – Books Ngram Viewer: <strong>the</strong> percentage occurrence <strong>of</strong> <strong>the</strong> “intellectual
property” (red line) and “intellectual capital” (blue line) bigrams* in <strong>the</strong> English** corpus <strong>of</strong>
books in 1978-2008
Source: Google Labs: Books Ngram Viewer (online), available at:
http://ngrams.googlelabs.com/graph?content=intellectual+capital,+intellectual+property&year_start=1
978&year_end=2008&corpus=0&smoothing=0 [retrieved: February 9, 2011]. (*)A bigram (o<strong>the</strong>rwise
known as “2-gram”) is a combination <strong>of</strong> two words; (**)<strong>the</strong> American and British English dialects
covered.
2. The patenting system in Europe
To begin with, it is worth illustrating <strong>the</strong> institutional framework <strong>of</strong> intellectual property protection in
Europe.
The <strong>European</strong> Patent Organization is an intergovernmental body established in 1977 on <strong>the</strong> back <strong>of</strong>
<strong>the</strong> <strong>European</strong> Patent Convention (EPC), an accord concluded in 1973 in Munich, Germany. The
<strong>European</strong> Patent Organization, currently comprising 38 member states, operates by way <strong>of</strong> two
specialized vehicles:
<strong>European</strong> Patent Office – acting as <strong>the</strong> executive body <strong>of</strong> <strong>the</strong> Organization, albeit devoid <strong>of</strong>
separate legal personality;
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Administrative Council – charged with supervisory and (limited) legislative functions (<strong>the</strong>ir crux is
left to <strong>the</strong> discretion <strong>of</strong> individual <strong>European</strong> contracting states).
It is noteworthy that <strong>the</strong> execution <strong>of</strong> patenting via <strong>the</strong> <strong>European</strong> Patent Office (hereinafter also
referred to as <strong>the</strong> “EPO”) is a unified procedure solely from <strong>the</strong> perspective <strong>of</strong> patent granting,
however, factual enforcement rests with individual members’ jurisdictions. Consequently, patents
granted via EPO are not seamless “EU patents” or even “Europe-wide patents”, but a motley <strong>of</strong>
national patents (Gowers 2006). Such a combination undoubtedly facilitates <strong>the</strong> patent application
exercise, but results in a porous and costly system <strong>of</strong> compliance (left entirely to <strong>the</strong> governance <strong>of</strong>
national jurisdictions – some <strong>of</strong> <strong>the</strong>m inexperienced, ineffective, self-absorbed and uncooperative).
For <strong>the</strong> past few decades, EU members have struggled to work out a consensus on unitary
enforcement <strong>of</strong> patents, yet (thus far) to limited avail. The fragmented patent enforcement system has
been widely censured as a blatant divergence from <strong>the</strong> four fundamental internal market freedoms
enshrined in <strong>the</strong> Treaty on <strong>European</strong> Union and <strong>the</strong> Treaty Establishing <strong>the</strong> <strong>European</strong> Community
(EUR-Lex 2006) , i.e. free circulation <strong>of</strong> people, goods, services and capital.
The key divergences among EU members on Community-wide patenting have essentially been
tw<strong>of</strong>old:
1. Linguistics (translation): numerous EU member countries have required (costly, time
consuming and arduous) translations <strong>of</strong> all patent documentation into <strong>the</strong>ir national languages on
application or in <strong>the</strong> event <strong>of</strong> infringement related litigation;
2. Sovereignty: to be fully binding on each <strong>of</strong> <strong>the</strong> EU member states, a uniform patent would have
to take unequivocal precedence over national laws, which has been viewed as objectionable by
some EU members.
A breakthrough reportedly came about in December 2009, as <strong>the</strong> Swedish EU presidency tried to
reinvigorate <strong>the</strong> dialog on a single, fully enforceable EU-wide patent. From <strong>the</strong> technical standpoint,
<strong>the</strong> plans involved founding a centralized <strong>European</strong> patent court having jurisdiction over all EU
member states. To facilitate <strong>the</strong> project, <strong>the</strong> EU would formally accede to <strong>the</strong> <strong>European</strong> Patent
Convention.
Despite renewed hopes (Cf. Five IP Offices 2010), a harmonized, easily enforceable and
internationally competitive EU patent still remains a thing <strong>of</strong> <strong>the</strong> future – ra<strong>the</strong>r than a readily
actionable blueprint for radical reform now. The prospect <strong>of</strong> seamless protection for o<strong>the</strong>r types <strong>of</strong>
intellectual property (especially with regard to supranational enforceability) has been ra<strong>the</strong>r embryonic
and even more atomized.
3. The global position <strong>of</strong> <strong>the</strong> <strong>European</strong> Patent Office
The <strong>European</strong> Union (EU), despite numerous social and technological challenges faced by <strong>the</strong> Old
Continent at <strong>the</strong> turn <strong>of</strong> <strong>the</strong> third millennium, still represents <strong>the</strong> largest reasonably uniform economic
system globally. By Gross Domestic Product (GDP) size, a traditional and universally accepted
yardstick <strong>of</strong> economic development – if calculated at Purchasing Power Parity (i.e. accounting for
inter-currency purchasing differentials) – <strong>the</strong> EU at year-end 2009 outnumbered all major economic
superpowers, including <strong>the</strong> US and China. Additionally, in 2009, three individual EU members
(Germany, <strong>the</strong> United Kingdom and France) made <strong>the</strong> global top ten by GDP magnitude (Figure 2).
The EU’s economic sway has never been matched by <strong>the</strong> scale <strong>of</strong> its innovation (cf. Lisbon Strategy
2000), including IP expansion. Since inception in 1977, <strong>the</strong> EPO has grown considerably and has
continued to rank among <strong>the</strong> five largest centers <strong>of</strong> IP globally, yet (with regard to filings for patent
registration) it has never come anywhere near <strong>the</strong> United States Patent and Trademark Office
(USPTO) or <strong>the</strong> Japan Patent Office (JPO) (Figure 3).
Recently, with <strong>the</strong> soaring prominence <strong>of</strong> <strong>the</strong> East Asian economies, <strong>the</strong> EPO has also been
upstaged by <strong>the</strong> State Intellectual Property Office (SIPO) <strong>of</strong> <strong>the</strong> People’s Republic <strong>of</strong> China, and <strong>the</strong>
Korean Intellectual Property Office (KIPO) – Figure 4. Despite sustained progress in patenting in <strong>the</strong>
long term, Europe does not appear to be able to keep pace nei<strong>the</strong>r with <strong>the</strong> United States nor with <strong>the</strong>
Asian powerhouses (notably <strong>the</strong> People’s Republic <strong>of</strong> China). The trend, if continued, will redefine
global economic leadership and shift <strong>the</strong> gravity <strong>of</strong> worldwide innovation fur<strong>the</strong>r eastward.
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Figure 2: Ten largest global economic areas by Gross Domestic Product (GDP) at Purchasing Power
Parity (PPP) at year-end 2009*
Source: Central Intelligence Agency (CIA) World Factbook – Country Comparisons; publicly available
at: https://www.cia.gov/library/publications/<strong>the</strong>-world-factbook/index.html [retrieved: November 1,
2010]. (*)CIA estimates.
Figure 3: Historical trends in global patent filings at selected <strong>of</strong>fices in 1883-2003
Source: World Intellectual Property Organization (WIPO) Intellectual Property Indicators (2010) –
September 2010, available on <strong>the</strong> WIPO web site: http://www.wipo.int/ipstats/en/ [retrieved:
November 10, 2010].
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Figure 4: Percentage share <strong>of</strong> five largest patent <strong>of</strong>fices worldwide in total patent applications (filed in
1985-2008)
Source: World Intellectual Property Organization (WIPO) Intellectual Property Indicators (2010) –
September 2010, available on <strong>the</strong> WIPO web site: http://www.wipo.int/ipstats/en/ [retrieved:
November 10, 2010].
The marginal role played by Europe in worldwide intellectual property creation (especially if adjusted
for macroeconomic potential) could (in <strong>the</strong>ory) be <strong>of</strong>fset by innovation in <strong>the</strong> form <strong>of</strong> broader-based
(e.g. non-patentable) categories <strong>of</strong> intellectual output. None<strong>the</strong>less, a preliminary assessment <strong>of</strong> <strong>the</strong>
Lisbon Strategy, envisaged as a ten-year target to make Europe “<strong>the</strong> most competitive and dynamic
knowledge-based economy in <strong>the</strong> world” (Lisbon Strategy 2000), indicates that <strong>the</strong> primary objectives
have not been accomplished – a fact begrudgingly admitted by <strong>the</strong> EU’s executive management: <strong>the</strong>
<strong>European</strong> Commission, EC (EC 2009).
The low IP/IC penetration (e.g. in relation to GDP or o<strong>the</strong>r macroeconomic benchmarks) in Europe
stems from a variety <strong>of</strong> factors, yet <strong>the</strong> following systemic weaknesses particularly restrict intangible
growth:
Inadequate socioeconomic, political and regulatory integration – Europe has not yet succeeded in
creating a sufficiently homogenous and integrated (socioeconomic, political and legal) universe
capable <strong>of</strong> defending its interests globally and enforcing its judgments internally, which has wideranging
implications for asset classes as vulnerable as intangibles;
Low IP/IC commercialization – Europe, despite immense potential locked in material and
intangible innovation, has not figured out how to make it pay, hence <strong>the</strong> common and baleful
frustration <strong>of</strong> its researchers and entrepreneurs;
Demographics – Europe’s old age is being evidenced by increasing pressures on innovation and
entrepreneurship (especially through higher taxes), without an about-face from defined benefit to
defined contribution entitlement systems and high-skilled immigration, Europe will continue to
stagnate.
Europe’s unobtrusive IP output is seemingly unaccompanied by effective legal protection.
Unfortunately, no comprehensive or consistent database <strong>of</strong> IP infringement statistics is currently run
on <strong>the</strong> Old Continent, yet <strong>the</strong> available estimates are giving serious cause for concern. According to a
EU survey put out in 2009 and encompassing 70 worldwide economies, <strong>the</strong> number <strong>of</strong> goods
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suspected <strong>of</strong> violating IP rights (“detained at EU borders”) soared by 126% in 2008 (in year-over-year
terms). Some 54% <strong>of</strong> such infringements were attributable to China, however, o<strong>the</strong>r Far Eastern
economies, e.g. India (pharmaceuticals) and Indonesia (foodstuffs and beverages) figured
prominently on <strong>the</strong> watch list (IPR Enforcement 2009). Figure 5 displays <strong>the</strong> EU’s concern over IP
violations by category in 2009. Interestingly, <strong>the</strong> priority watch list <strong>of</strong> compiled by <strong>the</strong> Office <strong>of</strong> <strong>the</strong>
United States Trade Representative (USTR) does not lay similar emphasis on East Asia (China in
particular) (Cf. USTR 2010).
Figure 5: “Priority countries” (detrimental to EU intellectual property rights) by category in 2009
China
Indonesia, <strong>the</strong> Philippines,
Thailand, Turkey
Argentina*, Brazil*, Canada, India, Israel, Korea, Malaysia,
Russia*, Ukraine*, <strong>the</strong> USA, Vietnam
Figure 4: Percentage share <strong>of</strong> five largest patent <strong>of</strong>fices worldwide in total patent applications (filed in
1985-2008)
Source: Commission <strong>of</strong> <strong>the</strong> <strong>European</strong> Communities, Commission Staff Working Document,
Intellectual Property Rights (IPR) Enforcement Report 2009, SEC (2009) 1360, Brussels. In each
category countries listed in alphabetical order. (*)Substantial improvements noted in <strong>the</strong>se countries
(according to <strong>the</strong> Commission).
Given <strong>the</strong> mass migration <strong>of</strong> modern goods and services to cyberspace and limitations to IC
registration through IP (discussed in this paper), <strong>the</strong> potential scale <strong>of</strong> IC abuse by emerging
economies is likely to be colossal. More information on <strong>the</strong> scale <strong>of</strong> IC rights infringement can only be
gained as a result <strong>of</strong> rising transparency within and cooperation among individual EU member
jurisdictions, as well as fur<strong>the</strong>r international surveys focused on diverse classes <strong>of</strong> intangibles.
4. The diffusion <strong>of</strong> intellectual property – <strong>the</strong> patenting perspective and
limitations
Patents can be successfully used to monitor global flows <strong>of</strong> innovation among economic areas,
countries, regions, industries and individual enterprises. The reasons why patents serve as a handy
benchmark <strong>of</strong> intellectual capital diffusion are manifold:
Tradition: patenting is almost as old as humankind (it had been mentioned in ancient Greek
scripture), while modern patents originated in Venice in <strong>the</strong> 15 th century AC;
Breadth: patent registration data are available and comparable for most worldwide economies
(which is not <strong>the</strong> case for o<strong>the</strong>r forms <strong>of</strong> IP);
Depth: an average patent application is an abundant source <strong>of</strong> information on <strong>the</strong> inventor,
innovation character and potential claims <strong>the</strong>reto;
Ties to innovation: most high-pr<strong>of</strong>ile inventions have empirically been protected through patenting.
Patents are both measures <strong>of</strong> innovation outputs and inputs. After all, <strong>the</strong>y embody human
inventiveness, yet at <strong>the</strong> same time <strong>the</strong>y produce a powerful signaling effect for would-be inventors
contemplating future commitments to innovation.
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Mindful <strong>of</strong> all <strong>the</strong> advantages <strong>of</strong> patent analysis in measuring intellectual asset diffusion, serious
limitations are applicable to patenting as a benchmark <strong>of</strong> technology growth and spread on
a worldwide scale:
Survivor bias/skewness/time lags: patents have indeed been registered for centuries, however
<strong>the</strong>re is no easy way to relate <strong>the</strong>ir registration to economic productivity on <strong>the</strong> time scale – some
<strong>of</strong> <strong>the</strong>m have for long been commercially dormant, some have dramatically altered <strong>the</strong> course <strong>of</strong>
history (with varying immediacy);
Innovation architecture: innovation, despite occasional fits <strong>of</strong> “creative destruction” (Schumpeter
1942) is – essentially – an organic growth model whereby new products and services are <strong>of</strong>ten
build on <strong>the</strong>ir enhanced predecessors – it is hard to properly allocate innovation to <strong>the</strong> value
adding chain;
Deliberate non-patenting <strong>of</strong> numerous products and services: as previously noted, some
inventions are commercialized through o<strong>the</strong>r means than patenting (secrecy, lead time etc.), an
inverse relationship can be deduced between <strong>the</strong> effectiveness <strong>of</strong> a intellectual property
jurisdiction and <strong>the</strong> average propensity to file for patent registration;
Differing methodologies: international variations in patent laws and practices as well as frequent
reforms <strong>of</strong> national intellectual property jurisdictions complicate a consistent and meticulous
review <strong>of</strong> patenting habits in time and space (Cf. Patent Manual 1994).
Fur<strong>the</strong>r limitations <strong>of</strong> measuring innovation thorough IP registered at <strong>the</strong> EPO were highlighted in
a study compiled by J. Eaton, S. Kortum and J. Lerner (Eaton et al. 2003). The authors identified <strong>the</strong>
EPO’s reformed fee policy (lower registration costs) as a factor responsible for some 40% percent <strong>of</strong>
patenting growth in 1990-2000. Similar distortions can apply to cost induced patenting in <strong>the</strong> surveyed
period. Patenting is also subject to o<strong>the</strong>r behaviorisms reflecting <strong>the</strong> changing nature <strong>of</strong> innovation.
According to <strong>the</strong> Organization for Economic Cooperation and Development (OECD), contemporary
high technology firms resort to a sui generis “arms race” in registrations through <strong>the</strong> EPO. Modern
companies are likely to employ tactics to harm competition by abusing pending patents (<strong>the</strong> so-called
“ambushing”, “flooding” or “trolling”). All <strong>of</strong> <strong>the</strong>se practices are aimed at erecting barriers to entry for
bona fide fresh innovators (Cf. OECD 2010). The growing complexity <strong>of</strong> IP and a certain leeway in
patent application routines does not improve <strong>the</strong> transparency <strong>of</strong> IP registration standards. L.
Striukova additionally stressed <strong>the</strong> human and non-human role played by IP registrations. She also
emphasized marketable and non-marketable ramifications <strong>of</strong> <strong>the</strong> patenting process (Striukova 2009).
Her findings put IP registration in a wholly new perspective going beyond pure economic rationalism.
Despite <strong>the</strong>se (and many o<strong>the</strong>r) limitations, IP remains a natural proxy for IC measurement. Seamless
integration <strong>of</strong> IP into functional IP modeling and broader pan-corporate strategies have empirically
been tested to enhance company performance (Bollen et al. 2005).
The available survey (OECD 2010) <strong>of</strong> patent mobility for Australia, Canada, Japan, <strong>the</strong> Ne<strong>the</strong>rlands,
<strong>the</strong> US, <strong>the</strong> EU 27 and <strong>the</strong> world (as a whole) is made up <strong>of</strong> three categories:
1) Percentage <strong>of</strong> patents owned by foreign residents – Appendix 1;
2) Percentage <strong>of</strong> patents invented abroad – Appendix 2;
3) Percentage <strong>of</strong> patents invented with (a) foreign inventor(s) – Appendix 3.
Judging by <strong>the</strong> extent <strong>of</strong> international patent flows, <strong>the</strong> <strong>European</strong> Union is closely linked to <strong>the</strong> United
States in all <strong>of</strong> <strong>the</strong> aforementioned kinds <strong>of</strong> patent diffusion. Both patenting regimes have a similar
impact on o<strong>the</strong>r intellectual property jurisdictions. In comparison with its peers, Europe does not enjoy
a large proportion <strong>of</strong> foreign developed patents. This makes a strong case for improving IP
commercialization and protection on <strong>the</strong> Old Continent.
5. Conclusion
In spite <strong>of</strong> EU integration, enforcing intellectual property laws in Europe remains an incongruous and
patchy job, predominantly delegated to <strong>the</strong> individual and (<strong>of</strong>tentimes) ill-coordinated discretion <strong>of</strong> EU
national jurisdictions. This adverse phenomenon is being aggravated by a strategic shift <strong>of</strong> intellectual
activity and patent creation to <strong>the</strong> emerging world, chiefly East Asia.
Such an assessment is fur<strong>the</strong>r backed by EU patenting patterns, which can be narrowed to <strong>the</strong>
following major findings:
1) Low patenting penetration (vs. Gross Domestic Product size and o<strong>the</strong>r established measures
<strong>of</strong> economic growth), if compared with <strong>the</strong> United States and East Asia;
493

Piotr Wisniewski
2) Slow growth in patenting – Europe has shown a sluggish upward trend in worldwide patenting
since <strong>the</strong> mid-1980s, elsewhere (except for Japan – whose broader economic challenges have
been mirrored by drastically shrinking patent creation) patent growth has been by far more
spectacular;
3) Intense patent cooperation with <strong>the</strong> United States (and vice-versa), both jurisdictions exhibit
numerous similarities;
4) Limited proportion <strong>of</strong> EU patents invented abroad: this aspect <strong>of</strong> international diffusion trails
behind world and most developed countries’ averages;
5) Indications <strong>of</strong> ballooning infringement – Europe does not have a seamless system <strong>of</strong>
monitoring IP <strong>of</strong>fenses, yet <strong>the</strong> available surveys demonstrate a rising wave <strong>of</strong> infringements
against IP rights, especially originating from East Asian emerging markets (notably China).
Mature jurisdictions (including <strong>the</strong> EU) tend to award numerous protections for innovation developed
in <strong>the</strong> emerging world, however, <strong>the</strong> reverse is seldom true: emerging markets are not equally
concerned over workable safeguards for EU or US intellectual assets. In view <strong>of</strong> such factors,
fragmentation and internal competition (“cannibalism”) <strong>of</strong> EU member jurisdictions governing
intellectual property stand out as a glaring and damaging anachronism. The Europe <strong>of</strong> today is thus
incapable <strong>of</strong> protecting its intellectual base effectively. Establishment <strong>of</strong> a single intellectual property
court and an EU-wide patent would be a prerequisite for a constructive reappraisal <strong>of</strong> current EU
innovation strategy, whose success has been far from staggering. Ultimately, in response to <strong>the</strong>
diminishing gravity <strong>of</strong> Europe and <strong>the</strong> United States in <strong>the</strong> worldwide diffusion <strong>of</strong> intellectual property,
both economic areas should mull <strong>the</strong> merger <strong>of</strong> <strong>the</strong>ir patenting systems.
6. Appendix 1: Percentage <strong>of</strong> patents owned by foreign residents -
international review for 1999-2007
Country/
Year
Australia
Canada
Japan
Ne<strong>the</strong>rlands
US
EU (27)*
Type <strong>of</strong>
cooperation
1999 2000 2001 2002 2003 2004 2005 2006 2007
Total cooperation
with abroad
23.9 28.4 27.8 28.0 29.8 28.6 25.7 28.6 28.9
Japan 0.9 2.0 0.5 0.5 1.1 1.2 1.4 1.4 1.3
US 10.6 12.2 13.1 13.0 15.5 14.4 10.9 13.4 13.0
EU (27) 9.6 10.8 11.0 11.3 9.7 9.4 9.6 9.6 10.3
Total cooperation
with abroad
35.9 36.1 38.1 38.1 42.2 38.7 35.5 38.4 37.2
Japan 1.2 0.5 0.5 0.8 0.6 0.4 0.3 0.6 0.5
US 21.5 23.0 24.8 25.0 25.8 22.5 21.7 22.5 24.6
EU (27) 9.2 9.7 9.3 9.0 12.9 13.1 10.7 12.0 9.8
Total cooperation
with abroad
4.2 4.4 4.3 4.6 4.3 4.1 4.1 3.5 3.4
Japan n/a n/a n/a n/a n/a n/a n/a n/a n/a
US 2.4 2.3 1.9 1.7 1.9 1.8 1.9 1.7 1.3
EU (27) 1.3 1.6 2.0 2.2 2.0 1.8 1.7 1.4 1.6
Total cooperation
with abroad
23.4 20.8 21.6 20.9 22.9 22.6 25.6 26.9 26.5
Japan 0.6 0.4 0.5 0.5 0.3 0.3 0.3 0.2 0.3
US 7.7 6.1 5.4 5.9 6.7 5.9 6.4 6.4 5.9
EU (27) 12.3 11.5 12.5 12.0 13.5 13.5 16.0 17.6 18.0
Total cooperation
with abroad
12.6 13.1 13.6 14.9 14.8 14.5 14.8 15.3 14.6
Japan 1.5 1.4 1.5 1.5 1.5 1.3 1.3 1.3 1.5
US n/a n/a n/a n/a n/a n/a n/a n/a n/a
EU (27) 7.4 8.0 8.0 9.3 8.7 8.8 8.7 8.7 8.3
Total cooperation
with abroad
12.0 12.4 12.2 12.1 12.3 12.6 12.8 12.5 12.1
Japan 0.5 0.5 0.5 0.7 0.8 0.7 0.7 0.8 0.9
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Country/
Year
Worldwide
Piotr Wisniewski
US 7.7 7.8 7.3 7.2 7.3 7.2 7.1 6.6 5.8
EU (27) n/a n/a n/a n/a n/a n/a n/a n/a n/a
Type <strong>of</strong>
cooperation
1999 2000 2001 2002 2003 2004 2005 2006 2007
Total cooperation
with abroad
15.9 16.5 16.9 17.5 17.8 17.6 17.9 17.8 17.5
Japan 0.8 0.7 0.7 0.8 0.9 0.8 0.8 0.8 0.9
US 5.2 5.3 5.1 4.9 5.1 5.0 4.9 4.8 4.4
EU (27) 7.4 7.8 8.1 8.9 8.9 8.8 8.8 8.7 8.7
Source: Organization for Economic Cooperation and Development (OECD 2010) StatExtracts –
International Cooperation in Patents (available via SourceOECD – OECD iLibrary).
7. Appendix 2: Percentage <strong>of</strong> patents invented abroad – international review
for 1999-2007
Country/Year Type <strong>of</strong> cooperation 1999 2000 2001 2002 2003 2004 2005 2006 2007
Australia
Canada
Japan
Ne<strong>the</strong>rlands
US
EU (27)*
Worldwide
data
Total cooperation with
abroad
13.0 14.2 11.4 10.5 13.9 14.1 13.8 15.7 14.5
Japan 0.8 0.3 0.6 0.9 0.8 0.2 0.1 0.6 1.3
US 5.5 6.4 4.3 3.8 5.4 6.9 6.1 7.8 5.4
EU (27) 5.1 6.4 5.1 5.2 6.3 5.0 5.7 6.1 5.2
Total cooperation with
abroad
34.5 32.6 28.6 22.9 25.9 21.7 20.7 21.4 23.1
Japan 0.5 1.4 0.7 0.7 0.2 0.3 0.3 0.5 1.0
US 24.3 19.5 15.9 13.8 15.6 12.7 13.4 13.8 16.9
EU (27) 9.7 11.4 11.2 7.3 9.1 7.4 6.6 6.2 6.7
Total cooperation with
abroad
4.2 3.8 4.0 4.5 4.7 4.3 4.7 4.7 5.0
Japan n/a n/a n/a n/a n/a n/a n/a n/a n/a
US 2.6 2.2 2.4 2.4 2.3 2.1 2.2 2.0 2.0
EU (27) 1.4 1.3 1.4 1.8 1.9 1.7 1.9 2.2 2.5
Total Patents n/a n/a n/a n/a n/a n/a n/a n/a n/a
Total cooperation with
abroad
35.6 34.0 30.7 43.9 46.4 44.0 43.6 36.9 36.7
Japan 1.2 1.0 1.8 2.2 2.1 1.3 1.4 1.1 1.2
US 11.7 10.7 9.4 15.1 14.3 13.2 13.7 13.5 10.8
EU (27) 21.8 21.8 19.3 26.0 28.2 28.4 27.1 20.4 22.2
Total cooperation with
abroad
17.3 18.3 18.1 17.5 18.5 18.2 18.1 18.5 19.4
Japan 1.4 1.6 1.2 1.1 1.2 1.2 1.2 1.1 1.0
US n/a n/a n/a n/a n/a n/a n/a n/a n/a
EU (27) 12.2 12.6 12.3 11.8 12.0 11.9 11.8 11.9 12.5
Total cooperation with
abroad
8.0 8.6 8.6 9.9 9.7 10.1 10.3 9.5 8.5
Japan 0.5 0.7 0.8 0.9 0.8 0.8 0.7 0.5 0.6
US 5.0 5.3 5.2 6.2 5.8 5.8 5.8 5.4 4.3
EU (27) n/a n/a n/a n/a n/a n/a n/a n/a n/a
Total cooperation with
abroad
15.9 16.5 16.9 17.5 17.8 17.6 17.9 17.8 17.5
Japan 0.7 0.9 0.8 0.8 0.8 0.7 0.7 0.6 0.6
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US 3.8 3.8 3.9 4.3 4.2 4.1 4.2 4.1 3.4
EU (27) 9.8 10.1 10.3 10.5 10.6 10.5 10.5 10.6 10.9
Source: Organization for Economic Cooperation and Development (OECD 2010) StatExtracts –
International Cooperation in Patents (available via SourceOECD – OECD iLibrary).
8. Appendix 3: Percentage <strong>of</strong> patents developed with (a) foreign co-inventor(s)
- international review for 1999-2007
Country/Yea
r
Australia
Canada
Japan
Ne<strong>the</strong>rlands
US
EU (27)*
Worldwide
data
Type <strong>of</strong>
cooperation
Total
cooperation with
abroad
1999 2000 2001 2002 2003 2004 2005 2006 2007
18.4 19.3 20.2 20.2 20.8 20.9 20.3 24.0 24.0
Japan 0.7 0.9 0.7 0.5 0.3 0.2 0.4 0.5 0.9
US 8.0 10.0 10.0 9.0 10.3 10.1 9.3 12.0 11.0
EU (27) 8.0 8.5 9.3 10.1 9.0 8.7 9.4 9.8 9.4
Total
cooperation with
abroad
30.8 32.3 33.0 30.9 30.2 26.2 26.0 29.6 28.8
Japan 0.7 0.8 0.4 0.8 0.5 0.2 0.4 0.5 0.3
US 20.8 22.7 23.5 22.0 22.0 18.0 18.8 19.8 20.8
EU (27) 10.4 10.2 9.9 8.2 8.8 7.7 7.4 9.1 7.7
Total
cooperation with
abroad
3.2 2.8 2.9 3.4 2.9 2.9 3.2 2.7 2.6
Japan n/a n/a n/a n/a n/a n/a n/a n/a n/a
US 1.7 1.6 1.6 1.6 1.6 1.5 1.4 1.2 1.0
EU (27) 1.1 1.0 1.1 1.5 1.1 1.2 1.4 1.2 1.2
Total
cooperation with
abroad
16.2 15.7 14.1 17.8 19.7 18.3 19.0 18.2 18.5
Japan 0.5 0.3 0.5 0.7 0.5 0.2 0.5 0.2 0.4
US 5.4 4.0 4.5 5.8 5.8 5.6 5.7 6.1 4.7
EU (27) 10.6 11.3 9.0 11.7 13.5 11.8 12.2 11.1 13.2
Total
cooperation with
abroad
11.1 12.2 12.5 12.2 12.7 13.0 12.9 13.5 13.8
Japan 1.0 1.0 1.0 1.0 1.0 1.0 0.8 0.7 0.7
US n/a n/a n/a n/a n/a n/a n/a n/a n/a
EU (27) 7.2 7.8 7.9 7.6 7.7 8.1 7.7 8.2 8.4
Total
cooperation with
abroad
7.4 7.9 7.9 8.3 8.1 8.9 9.0 8.8 8.1
Japan 0.4 0.4 0.4 0.6 0.5 0.5 0.5 0.4 0.4
US 4.6 4.9 4.8 4.8 4.8 5.0 4.9 4.7 4.0
EU (27) n/a n/a n/a n/a n/a n/a n/a n/a n/a
Total
cooperation with
abroad
6.5 7.0 7.2 7.3 7.3 7.5 7.7 7.8 7.5
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Japan 0.6 0.5 0.5 0.6 0.5 0.5 0.5 0.4 0.5
US 3.3 3.5 3.6 3.6 3.6 3.7 3.6 3.6 3.2
EU (27) 5.1 5.5 5.7 5.7 5.6 5.9 6.0 6.1 6.0
Source: Organization for Economic Cooperation and Development (OECD 2010) StatExtracts –
International Cooperation in Patents (available via SourceOECD – OECD iLibrary).
References
Bollen, L., Vergauwen, P., Schnieders, S. (2005), Linking intellectual capital and intellectual property to company
performance, Management Decision (Journal), Emerald Publishing Limited, Vol. 43 No. 9, Bingley, United
Kingdom, pp. 1161-1185.
Brooking, A., Intellectual Capital – Core Asset for <strong>the</strong> Third Millennium Enterprise, International Thompson
Business Press, London, United Kingdom, pp. 12-16.
Central Intelligence Agency (CIA) World Factbook (2010) – Country Comparisons; publicly available at:
https://www.cia.gov/library/publications/<strong>the</strong>-world-factbook/index.html.
Eaton, J., Kortnum, S., Lerner, J., (2003), International Patenting and <strong>the</strong> <strong>European</strong> Patent Office: A Quantitative
Assessment, National Bureau <strong>of</strong> Economic Research (NBER), Cambridge, MA, USA, August 2003, pp. 1-
38.
Edvinsson, L., Malone, M.S. (1997), Intellectual Capital. The Proven Way To Establish Your Company’s Real
Value By Measuring Its Hidden Brainpower, Biddles Ltd., Guildford & King’s Lynn, United Kingdom, pp. 10-
15.
EUR-Lex (2006), Treaty on <strong>European</strong> Union and <strong>the</strong> Treaty Establishing <strong>the</strong> <strong>European</strong> Community, Official
Journal <strong>of</strong> <strong>the</strong> <strong>European</strong> Union; Brussels, Belgium.
<strong>European</strong> Commission, EC (2010), The Governance Challenge for Knowledge Policies in <strong>the</strong> Lisbon Strategy:
Between Revolution and Illusion, <strong>European</strong> Research Area, 5th Report (EUR 23469), Brussels, Belgium,
pp.1-48.
Federal Trade Commission (2003), To Promote Innovation – The Proper Balance <strong>of</strong> Competition and Patent Law
and Policy, FTC; Washington DC, USA, October 2003, pp. 7.
Google Labs (2010), Books Ngram Viewer (online), available at:
http://ngrams.googlelabs.com/graph?content=intellectual+capital,+intellectual+property&year_start=1978&y
ear_end=2008&corpus=0&smoothing=0.
Gowers, A. (2006), Gowers Review <strong>of</strong> Intellectual Property, Norwich, United Kingdom, pp. 1-150.
IPR Enforcement (2009), Commission <strong>of</strong> <strong>the</strong> <strong>European</strong> Communities, Commission Staff Working Document,
Intellectual Property Rights (IPR) Enforcement Report 2009, SEC(2009) 1360, Brussels.
Lisbon Strategy (2000): overview and links to detailed resources – available on <strong>the</strong> <strong>European</strong> Union web site:
http://europa.eu/scadplus/glossary/lisbon_strategy_en.htm.
Organization for Economic Cooperation and Development (OECD 2010) StatExtracts – International Cooperation
in Patents (available via SourceOECD – OECD iLibrary.
Patent Manual (1994), The Management <strong>of</strong> Scientific and Technological Activities Using Patent Data As Science
and Technology Indicators, Organization for Economic Cooperation and Development (OECD), Paris,
France, pp. 1-108.
Schumpeter J., Capitalism, Socialism and Democracy (1942); Harper, New York, USA, pp. 83.
Striukova, L. (2009), Patents and corporate value creation: <strong>the</strong>oretical approach, University College London,
Management Studies Centre, London, United Kingdom; pp.1-24.
USTR (2010), Office <strong>of</strong> <strong>the</strong> United States Trade Representative, Special 301 Report, Executive Office <strong>of</strong> <strong>the</strong>
President <strong>of</strong> <strong>the</strong> United States, pp. 1-50.
Wisniewski, P. (2009), Modern valuation <strong>of</strong> intellectual assets – world <strong>the</strong>ory and practice. Recommendations for
Polish enterprises. Part 1: Definition and taxonomy <strong>of</strong> intellectual capital., Finance and Management
College Working Papers (Working Paper No. 92), Warsaw School <strong>of</strong> Economics, Warsaw, Poland, pp. 73-
82.
World Intellectual Property Organization (WIPO): Intellectual Property Indicators (2010) – available on <strong>the</strong> WIPO
web site: http://www.wipo.int/ipstats/en/.
World Intellectual Property Organization, WIPO (1967), Convention Establishing <strong>the</strong> World Intellectual Property
Organization.
World Intellectual Property Organization, WIPO (2010), resources available on <strong>the</strong> <strong>of</strong>ficial web site:
http://www.wipo.int/portal/index.html.en.
World Intellectual Property Organization, WIPO (2010a), Understanding Industrial Property, Publication No.
895(E), Geneva, Switzerland.
World Intellectual Property Organization, WIPO (2010b), Understanding Copyright and Related Rights,
Publication No. 909(E), Geneva, Switzerland.
497

498

PhD
Research
Papers
499

500

Intellectual Capital Disclosure Commitment: A Myth or
Reality?
Deborah Branswijck and Patricia Everaert
Ghent University College, Belgium
Deborah.branswijck@hogent.be
Patricia.everaert@ugent.be
Abstract: The objective <strong>of</strong> this empirical research is to assess <strong>the</strong> information dealing with intellectual capital that
firms disclose in <strong>the</strong>ir prospectus and <strong>the</strong> potential influence on <strong>the</strong>ir intellectual capital disclosure in <strong>the</strong> annual
report following to <strong>the</strong> initial public <strong>of</strong>fering. The prospectus <strong>of</strong> companies that applied for initial listing on
Euronext Brussels and Amsterdam between 2005 and 2009 were analyzed, including <strong>the</strong> first annual report after
IPO, by means <strong>of</strong> a content analysis based on <strong>the</strong> disclosure index <strong>of</strong> Bukh et al (2005). First, <strong>the</strong> prospectus and
annual report were compared based on <strong>the</strong>ir intellectual capital disclosure. Second, <strong>the</strong> prospectus and <strong>the</strong>
annual report were studied in order to understand <strong>the</strong> disclosure practices on IC during a 5 year time period
taken <strong>the</strong> recent financial crisis into account. Third, a model was built in order to explain <strong>the</strong> impact from IC
disclosure in <strong>the</strong> prospectus on <strong>the</strong> disclosure in <strong>the</strong> annual report. Next to <strong>the</strong> result on <strong>the</strong> IC index for <strong>the</strong>
prospectus (1), different control variables such as (2) industry, (3) company age, (4) size, (5) auditor and (6)
ownership retention were added to <strong>the</strong> model.
Keywords: initial public <strong>of</strong>fering, intellectual capital, economic crisis, content analysis, disclosure
1. Introduction
In recent years, it has been commonly observed that a company’s market value is well above its book
value. This might suggest that traditional accounting systems deliver a financial statement that does
not fully reflect <strong>the</strong> value relevant information. Previous research has revealed that intellectual capital
(IC) or intangible assets (an intellectual capital component) outside <strong>the</strong> financial statements are <strong>the</strong>
value drivers <strong>of</strong> firms since <strong>the</strong>y increasingly base <strong>the</strong>ir own value on know-how, patents, skilled
employees and o<strong>the</strong>r intangible assets (Bukh, 2003). The importance <strong>of</strong> <strong>the</strong>se assets gained <strong>the</strong>
attention <strong>of</strong> <strong>the</strong> International Accounting Standards Board. Therefore, <strong>the</strong>y developed an accounting
standard on intangible assets (standard IAS 38) which was update in 2008. According to this
standard, some IC elements are disclosed in <strong>the</strong> annual report but most <strong>of</strong> <strong>the</strong>m still remain
undisclosed. Consequently, investors lack information which could result in an increased risk
perception. This can cause difficulties in attracting funds and can possibly lead to an underestimation
<strong>of</strong> future earnings (Walker, 2006). In order to avoid this underestimation, companies can decide to
voluntarily disclose value relevant information. On <strong>the</strong> one hand, Cordazzo (2007) found that in <strong>the</strong>
prospectus, companies provide investors with <strong>the</strong> voluntary disclosure <strong>of</strong> IC by reporting additional
information on <strong>the</strong> companies’ risk, future pr<strong>of</strong>itability and strategy. Brüggen et al. (2009), on <strong>the</strong> o<strong>the</strong>r
hand, studied <strong>the</strong> determinants <strong>of</strong> IC disclosure in <strong>the</strong> annual report and identified industry and firm
size as possible explanatory variables. Since <strong>the</strong> annual report generally focuses on <strong>the</strong> historical
performance <strong>of</strong> <strong>the</strong> company, some differences are likely to be reflected in <strong>the</strong> nature <strong>of</strong> IC disclosure
between <strong>the</strong> prospectus and <strong>the</strong> annual report. It is argued that <strong>the</strong> quality <strong>of</strong> reporting in <strong>the</strong>
prospectus could be seen as a role model for future information disclosure <strong>of</strong> <strong>the</strong> company (Cumby
and Conrad, 2001; Beattie, 1999). However, <strong>the</strong> question could be asked if companies that have a
high level <strong>of</strong> IC disclosure in <strong>the</strong>ir prospectus also disclose relatively more in <strong>the</strong>ir annual report. In
o<strong>the</strong>r words, does IC disclosure commitment exist? According to our knowledge, <strong>the</strong>re is no literature
on comparing IC disclosure in <strong>the</strong> prospectus and <strong>the</strong> annual report. Only a slightly comparable study
<strong>of</strong> Nielsen et al. (2006) indicated similarities between <strong>the</strong> IC disclosure in <strong>the</strong> intellectual capital
statement and in <strong>the</strong> annual report.
Sutthachai and Cooke (2009) found that Tai financial reporting disclosure practices increased over
time, but <strong>the</strong> changes in disclosure occurred mainly in <strong>the</strong> economic crisis period, suggesting that <strong>the</strong>
economic disturbance had an impact on it. Since <strong>the</strong> financial and economical crisis in 2008 caused a
downfall <strong>of</strong> share prices on all global bourses, it is expected that companies disclose more voluntary
information. The capital market-association <strong>the</strong>ory assumes that earnings management and
information disclosure have an impact on capital markets and <strong>the</strong>refore could be linked to an
economic disturbance. The crisis could result in more accurate and relevant disclosure concerning
intellectual capital in order to convince investors to buy shares from newly listed companies. Based on
this outcome, we can investigate whe<strong>the</strong>r <strong>the</strong> recent financial crisis also had an influence on <strong>the</strong> level
<strong>of</strong> voluntary IC disclosure in <strong>the</strong> prospectus and <strong>the</strong> annual report.
501

2. Hypo<strong>the</strong>sis development
Deborah Branswijck and Patricia Everaert
Previous studies on IC disclosure in <strong>the</strong> prospectus used a content analysis to determine whe<strong>the</strong>r
stakeholder groups, with an interest in controlling certain strategic aspects <strong>of</strong> <strong>the</strong> organization, will be
informed voluntarily on <strong>the</strong> company’s IC during <strong>the</strong> initial public <strong>of</strong>fering (IPO) (Bukh et al., 2004 ;
Singh and Van der Zahn, 2008). During an IPO <strong>the</strong> amount <strong>of</strong> stakeholders <strong>of</strong> a company increases.
The stakeholder <strong>the</strong>ory suggests that an organization’s management is expected to undertake
activities deemed important by <strong>the</strong>ir stakeholders. According to <strong>the</strong> latter, a company will voluntarily
disclose information about its intellectual performance above mandatory requirements in order to
meet <strong>the</strong>se expectations (Deegan, 2000). Moreover, <strong>the</strong> traditional accounting models are unable to
reflect <strong>the</strong> new ways <strong>of</strong> creating value. The most intuitive measurement <strong>of</strong> <strong>the</strong> value <strong>of</strong> IC is <strong>the</strong>
difference between <strong>the</strong> net book value and <strong>the</strong> market value <strong>of</strong> a company (Holland, 2001). Firms with
a great difference between <strong>the</strong>se two measures have a high level <strong>of</strong> IC. For some companies this
difference may come from a brand name for o<strong>the</strong>rs it may come from know-how or patents. The value
<strong>of</strong> those intangible assets could represent more than 60 % <strong>of</strong> <strong>the</strong> business assets (Lev, 2001) and
<strong>the</strong>refore <strong>the</strong> necessity to voluntarily report about <strong>the</strong>se value creation indicators increases. Since
reporting on IC is voluntary, firms will only disclose this information if <strong>the</strong>re are advantages related to.
These advantages are, according to Vergauwen and van Alem (2005) and Depoers (2000), among
o<strong>the</strong>rs related to decreasing information asymmetry between <strong>the</strong> company and <strong>the</strong> users <strong>of</strong> financial
statements, lower borrowing costs due to a better estimation <strong>of</strong> <strong>the</strong> risk associated with <strong>the</strong> company
and a higher value relevance <strong>of</strong> <strong>the</strong> financial statements. Fur<strong>the</strong>rmore, economic <strong>the</strong>ory suggests that
a commitment by a firm to an increased level <strong>of</strong> disclosure should lower <strong>the</strong> information asymmetry
component <strong>of</strong> <strong>the</strong> firm’s cost <strong>of</strong> capital. Leuz and Verrecchia (2000) showed that substantially
increased levels <strong>of</strong> disclosure caused several economic benefits. Based on a sample <strong>of</strong> German
companies, <strong>the</strong>y found that an international reporting strategy (which assumes a commitment towards
an increased level <strong>of</strong> disclosure) is associated with lower bid-ask spreads and higher share turnover.
Due <strong>the</strong> nature <strong>of</strong> <strong>the</strong> economic benefits accompanied with it, firms that have undertaken an IPO will
continue to disclose more. Therefore, it could be assumed that IC disclosure commitment starts in <strong>the</strong>
prospectus and will be reflected in <strong>the</strong> subsequent annual report. This results in <strong>the</strong> following
hypo<strong>the</strong>sis
H1: A more than average level <strong>of</strong> IC disclosure in <strong>the</strong> prospectus results in a more than average level
<strong>of</strong> IC disclosure in <strong>the</strong> subsequent annual report due to disclosure commitment.
Previous research on financial reporting (Cooke and Wallace, 1990) revealed that <strong>the</strong> environment in
which <strong>the</strong> company operates shapes financial reporting practices. According to this legitimacy <strong>the</strong>ory,
organizations continually try to operate within <strong>the</strong> boundaries and norms <strong>of</strong> <strong>the</strong>ir societies. From this
perspective, a company would voluntarily report on activities if <strong>the</strong> management perceived that this
was expected by society. These expectations are not fixed but change over time. Consequently, <strong>the</strong>
company needs to be responsive to <strong>the</strong> environment in which it operates (Deegan, 2000). It is
expected that firms are more likely to report on <strong>the</strong>ir IC if <strong>the</strong>y find <strong>the</strong>mselves unable to legitimize
<strong>the</strong>ir status on <strong>the</strong> basis <strong>of</strong> <strong>the</strong> traditionally recognized fixed assets as symbols <strong>of</strong> corporate success.
Since <strong>the</strong> recent economic disturbance changed <strong>the</strong> environment in which companies operate, <strong>the</strong>
following hypo<strong>the</strong>ses can be formulated:
H2a: The economic disturbance has a positive influence on <strong>the</strong> voluntary reporting <strong>of</strong> IC in <strong>the</strong> IPO
prospectus.
H2b: The economic disturbance has a positive influence on <strong>the</strong> voluntary reporting <strong>of</strong> IC in <strong>the</strong> annual
report.
Daily et al. (2003) suggested that <strong>the</strong> IPO prospectus is <strong>of</strong>ten more precise than o<strong>the</strong>r reporting media
because companies are liable for any misleading or inaccurate information. It can be observed that
<strong>the</strong> prospectus usually contains more information about future expectations regarding market
developments and earnings, strategic direction, management, board composition, etc., compared to
<strong>the</strong> annual report. At <strong>the</strong> time <strong>of</strong> admission for listing on <strong>the</strong> stock exchange <strong>the</strong> company has to
convince future shareholders to invest capital. Ma<strong>the</strong>r et al. (2000) found that <strong>the</strong> firms’ management
has an incentive to present <strong>the</strong> company in <strong>the</strong> best possible light in order to maximize <strong>the</strong> proceeds
<strong>of</strong> <strong>the</strong> share issue. Although this could lead to earnings management, <strong>the</strong> IPO prospectus provides
insights into which types <strong>of</strong> information are selected by a company for representing itself in relation to
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Deborah Branswijck and Patricia Everaert
investors and analysts. In o<strong>the</strong>r words, it could be argued that a company sees <strong>the</strong> prospectus as a
publicity brochure in which it reports in detail about its achievements, skills and growth potential. All <strong>of</strong>
<strong>the</strong>se items are related to <strong>the</strong> intellectual capital <strong>of</strong> <strong>the</strong> company. Compared to <strong>the</strong> IPO prospectus,
<strong>the</strong> annual report has not only investors as its readers but it also conveys information to employees,
potential employees, customers, NGOs and o<strong>the</strong>r stakeholders. Due to this enlarged group <strong>of</strong>
readers, it is argued that some differences occur in <strong>the</strong> extent <strong>of</strong> disclosure in both company
documents. As to <strong>the</strong> annual report, <strong>the</strong> prospectus can be assumed to provide additional disclosure
on <strong>the</strong> company’s long term strategy and risks (Cumby and Conrad, 2001). This results in <strong>the</strong>
following hypo<strong>the</strong>sis:
H3: Companies disclose in general more IC information in <strong>the</strong> prospectus than in <strong>the</strong> annual report.
3. Methodology
3.1 Data collection
Prior literature tends to define IC as non-monetary assets without physical substance, such as
innovation, knowledge, research and development, employee training or customer satisfaction, that
have an impact on <strong>the</strong> firm’s value (Lev and Zambon, 2003). Based on this definition, IC can be
divided into structural capital, organizational capital and relational capital. These subdivisions are also
found in <strong>the</strong> disclosure index <strong>of</strong> Bukh et al. (2004). Based on <strong>the</strong> index <strong>of</strong> Bukh et al. (2004), 74
companies in Belgium and The Ne<strong>the</strong>rlands between 2005 and 2009 were coded. The index consists
<strong>of</strong> 86 elements categorized into six subgroups namely ‘Employees’, ‘Customers’, ‘Information
Technology’, ‘Research and Development’, ‘Processes’ and ‘Strategy’. For <strong>the</strong> subgroup ‘Strategy’,
three items were added namely ‘Competitor Names’, ‘Suppliers’ and ‘Business Acquisitions’.
Fur<strong>the</strong>rmore, <strong>the</strong> subgroup ‘Customers’ is extended with <strong>the</strong> items ‘Client Name’, ‘Customer
Satisfaction’ and ‘Customer Knowledge’. Lastly, <strong>the</strong> items ‘Insurance’, ‘Key Employees’, ‘Value Added
on Employees’, ‘Employee Attitude’, ‘Employee Communicative Activities’ and ‘Expert Teams’ were
added to <strong>the</strong> subgroup ‘Employees’. These adaptations were based on <strong>the</strong> differences in indexes
used in Bontis (2002), Vergauwen and van Alem (2005) and Beattie and Thomson (2007). Not only
<strong>the</strong> presence or absence <strong>of</strong> information pertaining to each IC item for a particular company was
documented, but also <strong>the</strong> difference between qualitative and quantitative information was taken into
account. On <strong>the</strong> one hand, Bozzolan et al. (2003) introduced a weighting scheme for <strong>the</strong>ir IC
disclosure index by counting qualitative disclosures as 1 and quantitative disclosures as 2. The
reason lies in <strong>the</strong> fact that companies are more likely to be accurate in quantitative disclosure. Guthrie
and Petty (2000), on <strong>the</strong> o<strong>the</strong>r hand, highlighted <strong>the</strong> difficulty in quantifying IC since it is in many
instances a qualitative item. For this research <strong>the</strong> presence <strong>of</strong> a certain item is coded as 1 if <strong>the</strong> item
is discussed in general, qualitative information specifically described on <strong>the</strong> selected item is coded as
2 and quantitative information as 3. The total score on <strong>the</strong> IC index is calculated as follows:
SCORE = ∑ di
where di expresses itemi with value 1 if <strong>the</strong> itemi contains general information, 2 if <strong>the</strong> itemi contains
qualitative information and 3 if itemi contains quantitative information. This index is used to apply a
content analysis. The method <strong>of</strong> a content analysis is a widely used method to quantify <strong>the</strong> amount <strong>of</strong>
disclosure in company reports (Beattie and Thomson, 2007)
A second researcher independently confirmed <strong>the</strong> coding <strong>of</strong> <strong>the</strong> first researcher in order to maintain
consistency in <strong>the</strong> coding decisions. The prospectus as well as <strong>the</strong> annual report was analyzed
manually for IC information. The annual report regularly contains both mandatory and voluntary
information such as <strong>the</strong> financial statement (balance sheet, income statement, cashflow statement,
notes and auditor’s report), mission statement, chairman’s report and corporate governance. Since
<strong>the</strong>re exists no accounting regulation on IC, corporate managers might choose to include IC items
that are not reported in <strong>the</strong> financial statements but in o<strong>the</strong>r sections <strong>of</strong> <strong>the</strong> annual report in order to
stress <strong>the</strong> importance to <strong>the</strong> reader. Therefore, every single company report is individually scanned
for <strong>the</strong> list <strong>of</strong> IC-related terms <strong>of</strong> <strong>the</strong> index. Since not all corporate documents were available, <strong>the</strong> total
sample resulted in 65 company prospectuses and 41 annual reports and financial statements. Due to
<strong>the</strong>ir specific reporting requirements, we decided not to include <strong>the</strong> banking industry.
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Deborah Branswijck and Patricia Everaert
To formally test whe<strong>the</strong>r <strong>the</strong>re exists a disclosure commitment, a number <strong>of</strong> control variables were
included into <strong>the</strong> analysis. Vergauwen & Van Alem (2005) found that companies in The Ne<strong>the</strong>rlands
disclose relatively low on IC in comparison with French and German companies. Ano<strong>the</strong>r research
(Vandemaele et al., 2005) revealed that Swedish companies disclose on average more about IC than
companies in The Ne<strong>the</strong>rlands and <strong>the</strong> UK. Based on a previous research (Orens & Derboven, 2008)
<strong>of</strong> IC disclosure in <strong>the</strong> prospectus <strong>of</strong> Belgian companies, which indicated that <strong>the</strong>y do not disclose an
elaborated level <strong>of</strong> IC disclosure, we assume that <strong>the</strong>re are no significant differences between <strong>the</strong>se
two countries.
Previous research has <strong>of</strong>ten seen company age as a proxy for risk since more established companies
are less risky. From this perspective, a company’s amount <strong>of</strong> disclosure is expected to be related to
<strong>the</strong> company age. Amir and Lev (1996) found that non-financial information is <strong>of</strong> greater importance
for <strong>the</strong> valuation <strong>of</strong> younger companies. Fur<strong>the</strong>rmore, Jaggi (1996) found that <strong>the</strong> amount <strong>of</strong>
inaccurate information in <strong>the</strong> prospectus is larger for younger companies. These previous studies
might be an indication for a negative relationship between <strong>the</strong> level <strong>of</strong> disclosure on IC and company
age. Company age is measured as <strong>the</strong> amount <strong>of</strong> years <strong>the</strong> company exists since its foundation.
Next to company age, researchers also found a relationship between <strong>the</strong> level disclosure and
company size. Watson et al. (2002) indicate that <strong>the</strong> cost <strong>of</strong> voluntary reporting is relatively high for
smaller companies compared to <strong>the</strong> cost for larger ones. Fur<strong>the</strong>rmore, larger companies have more to
win with an increased level <strong>of</strong> information since <strong>the</strong> trading <strong>of</strong> effects increases due to lower
uncertainty. These firms are under <strong>the</strong> control <strong>of</strong> <strong>the</strong> government and an increased level <strong>of</strong> disclosure
can reduce <strong>the</strong> governmental pressure (Buzby, 1975). Moreover, <strong>the</strong> need for capital for large
companies is higher than for small firms. A lower cost <strong>of</strong> capital is obtained since <strong>the</strong> information
asymmetry reduces. Based on a directive <strong>of</strong> Europe (2003/361/EG <strong>of</strong> <strong>the</strong> Commission <strong>of</strong> 6 may 2003)
turnover, total assets and amount <strong>of</strong> employees can be used to determine <strong>the</strong> size <strong>of</strong> a company. All
<strong>of</strong> <strong>the</strong>se indicators for size were obtained for each company.
Previous research tried to find a link between <strong>the</strong> amount <strong>of</strong> disclosure on IC and <strong>the</strong> industry to
which <strong>the</strong> company is affiliated. Due to historical reasons some industries disclose more information
than o<strong>the</strong>rs. It is expected that if one company in a certain industry reports voluntarily on a specific
topic, o<strong>the</strong>r players in <strong>the</strong> market will also report on that topic. Cooke (1991) found in his study that
Japanese production companies disclosed significantly more in <strong>the</strong>ir reports compared to o<strong>the</strong>r
industries. Also Wallace et al. (1994) and Dye & Sridhar (1995) suggest that <strong>the</strong> industry in which a
company is active will have an influence on <strong>the</strong> voluntary disclosure behavior. A company that
chooses not to disclose on a topic, is seen as a company that wants to hide bad news. The public
attention that companies receive will influence <strong>the</strong> amount <strong>of</strong> disclosure. Different research has been
performed in order to find evidence for this hypo<strong>the</strong>sis. Cooke (1989) used a detailed index for <strong>the</strong>
variable industry that exists out <strong>of</strong> production, commercial, services and conglomerates in his
investigation for Swedish companies. The results indicated that commercial companies report less
voluntary information compared to o<strong>the</strong>rs. The research <strong>of</strong> Abdolmohammadi (2005) shows that
certain industries <strong>of</strong> <strong>the</strong> new economy disclose more on intellectual capital and information systems
compared to mature industries which disclose more on <strong>the</strong>ir brands and strategic alliances. The
importance <strong>of</strong> intellectual capital disclosure is found in high-tech industries. Comparing <strong>the</strong> book value
and <strong>the</strong> market to book ratio <strong>of</strong> <strong>the</strong>se companies, it could be noticed that <strong>the</strong> values for IT and biotech
companies are generally higher. Bukh et al. (2005) indicate that <strong>the</strong>se companies will report more
voluntary information next to <strong>the</strong> traditional financial reporting. In our study, <strong>the</strong> construct industry is
measured by different dummy variables such as “Chemicals”, “Consumer goods”, “Industrial goods
and utilities”, “Financial services” and “IT”. These categories are based on <strong>the</strong> Industry Classification
Benchmark (ICB) used by Euronext. Allocation to <strong>the</strong> appropriate industries in ICB classification
system is made in collaboration with <strong>the</strong> management <strong>of</strong> <strong>the</strong> companies. Some industry classes <strong>of</strong> <strong>the</strong>
ICB system were grouped toge<strong>the</strong>r to increase <strong>the</strong> amount <strong>of</strong> observations for each industry group.
Ano<strong>the</strong>r variable <strong>of</strong> interest is audit firm. An audit firm uses its reputation as a competitive advantage.
This reputation capital is strongly influenced by accounting scandals. The Enron debacle, for
example, showed what can happen to an audit firm involved in such a scandal. Andersen, <strong>the</strong> audit
firm <strong>of</strong> Enron, went out <strong>of</strong> business even before a single lawsuit was filed against it. In order to avoid
this risk <strong>of</strong> litigation, auditors prefer financial statements that are stated and audited strictly according
to accounting regulations. Because <strong>of</strong> <strong>the</strong> vague and contradicting regulations on IC, it could be
argued that auditors omit IC-related items out <strong>of</strong> <strong>the</strong> financial statements. Therefore, auditor
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Deborah Branswijck and Patricia Everaert
conservatism can be considered to have a prominent influence on <strong>the</strong> disclosure <strong>of</strong> IC-related
information. Clarskon et al. (2003) found that international accounting firms in particular show
conservative auditor behavior. Consequently, <strong>the</strong> dummy variable “Big4Auditor” was added to <strong>the</strong>
model.
Ownership retention during <strong>the</strong> IPO could be seen as an indication <strong>of</strong> <strong>the</strong> quality <strong>of</strong> <strong>the</strong> firm. Since it is
costly to retain a significant stake in <strong>the</strong> firm, a large fractional ownership would preclude <strong>the</strong>
entrepreneur from diversifying his personal investment. Leland and Pyle (1977) constructed a model
to predict <strong>the</strong> behavior <strong>of</strong> <strong>the</strong> owner <strong>of</strong> a company when information asymmetry exists. The model
implies that <strong>the</strong> ownership retention will be high if <strong>the</strong> owners expect that <strong>the</strong> firm value is higher than
reflected in <strong>the</strong> financial statements. Consequently, rational investors will perceive ownership
retention as a signal <strong>of</strong> firm value. Fur<strong>the</strong>rmore, according to O’Sullivan (2000), we can expect less
disclosure from <strong>the</strong> company if <strong>the</strong> degree <strong>of</strong> ownership retention is high. If <strong>the</strong> directors do not own a
substantial portion <strong>of</strong> <strong>the</strong> company, it can be expected that <strong>the</strong>y encourage more intensive disclosure
in order to fulfill <strong>the</strong>ir monitoring role. Therefore, <strong>the</strong> variable “Ownership” was added to <strong>the</strong> model.
3.3 Model
In this section <strong>the</strong> defined hypo<strong>the</strong>ses will be tested by means <strong>of</strong> a linear regression. The independent
variable industry will be entered in <strong>the</strong> equation as several dummy variables. In order to avoid <strong>the</strong>
dummy variable trap, one <strong>of</strong> <strong>the</strong> industries, namely “IT” was not included in <strong>the</strong> regression. Admission
<strong>of</strong> this industry would lead to multicollinearity since <strong>the</strong>re is a linear relationship between <strong>the</strong> industryvariables
(Baker, 2006)
Score_ARj = λ0 + λ1 Score_IPOj + λ2 Crisisj + λ3 Sizej + λ4 Chemicalsj + λ5 Cons_Goodsj + λ6
IndGoods_Utulitiesj + λ7 Financial_servicesj + λ8 Agej + λ9 Auditor + λ10 Ownership + µj
where:
Score_ARj = <strong>the</strong> result on <strong>the</strong> index for <strong>the</strong> subsequent annual report after initial public <strong>of</strong>fering
Score_IPOj = <strong>the</strong> result on <strong>the</strong> index for <strong>the</strong> prospectus on <strong>the</strong> year <strong>of</strong> initial public <strong>of</strong>fering
Crisisj = a dummy variable equal to 0 for an initial public <strong>of</strong>fering in 2005, 2006 or 2007 and 1
o<strong>the</strong>rwise
Sizej = <strong>the</strong> total assets <strong>of</strong> <strong>the</strong> company
Chemicalsj = a dummy variable equal to 1 if firmj belongs to that industry and 0 o<strong>the</strong>rwise with IT as a
reference category
Cons_Goodsj = a dummy variable equal to 1 if firmj belongs to that industry and 0 o<strong>the</strong>rwise with IT as
a reference category
IndGoods_Utulitiesj = a dummy variable equal to 1 if firmj belongs to that industry and 0 o<strong>the</strong>rwise
with IT as a reference category
Financial_servicesj = a dummy variable equal to 1 if firmj belongs to that industry and 0 o<strong>the</strong>rwise with
IT as a reference category
Agej = <strong>the</strong> difference between 2010 and <strong>the</strong> year <strong>of</strong> establishment <strong>of</strong> firmj
Auditorj = a dummy variable equal to 1 if firmj is audited by a big 4 company and 0 o<strong>the</strong>rwhise
Ownershipj = <strong>the</strong> amount <strong>of</strong> shares retained by <strong>the</strong> owners during <strong>the</strong> IPO, expressed in percent
4. Research findings
4.1 Descriptive statistics
Table 1 gives an overview <strong>of</strong> <strong>the</strong> different industries and <strong>the</strong> areas <strong>of</strong> IC disclosure. A percentage <strong>of</strong>
33% in <strong>the</strong> area costumers (CU) indicates that 33% <strong>of</strong> <strong>the</strong> companies in <strong>the</strong> chemical industry report
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Deborah Branswijck and Patricia Everaert
on at least one item in <strong>the</strong> area customers. When taking a closer look at <strong>the</strong> areas <strong>of</strong> disclosure, most
companies report on human resources (HR) and strategy (ST). Regarding HR, this can be explained
by <strong>the</strong> obligation <strong>of</strong> companies to deposit a social balance at <strong>the</strong> national bank <strong>of</strong> Belgium. This
obligation also has an impact on <strong>the</strong> nature <strong>of</strong> <strong>the</strong> information reported on. Fur<strong>the</strong>rmore, only 36 % <strong>of</strong>
<strong>the</strong> companies in <strong>the</strong> IT industry disclose information related to IT. Noticeable is that, compared to <strong>the</strong>
annual report, companies tend to report in <strong>the</strong>ir prospectus on at least one item <strong>of</strong> <strong>the</strong> different areas.
Fur<strong>the</strong>rmore, almost each industry reports about its strategy in its prospectus. Moreover, it could be
noted that for each disclosure area <strong>the</strong>re is a possible relationship between <strong>the</strong> annual report and <strong>the</strong>
prospectus. Areas on which companies disclose much (e.g. HR and ST) are <strong>the</strong> same for <strong>the</strong> annual
report and <strong>the</strong> prospectus.
Table 1: Descriptive statistics for IC disclosure areas per industry
4.2 Hypo<strong>the</strong>ses testing
Table 2 presents <strong>the</strong> paired sample t-test for hypo<strong>the</strong>sis 1 that states that a more than average level
<strong>of</strong> IC disclosure in <strong>the</strong> prospectus results in a more than average level <strong>of</strong> IC disclosure in <strong>the</strong>
subsequent annual report due to disclosure commitment. As hypo<strong>the</strong>sized, <strong>the</strong> score for <strong>the</strong>
prospectus is positive and significant at <strong>the</strong> 0.05 level. Company size also significantly influences <strong>the</strong>
results. Since <strong>the</strong> limited amount <strong>of</strong> observations, <strong>the</strong> disconfirmation <strong>of</strong> auditor and age should be
taken as a tentative conclusion. Industry affiliation is found to have a significant influence to <strong>the</strong> extent
<strong>of</strong> IC disclosure.
Table 2: Linear regression
In order to find evidence for <strong>the</strong> second hypo<strong>the</strong>sis, a one-way ANOVA was used (table 3). First, we
look at <strong>the</strong> impact <strong>of</strong> <strong>the</strong> financial crisis on <strong>the</strong> difference in IC reporting in <strong>the</strong> prospectus. Companies
were divided into two groups based on <strong>the</strong> year IPO (before or after 2008). The descriptive statistics
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Deborah Branswijck and Patricia Everaert
indicate that <strong>the</strong> standard deviations <strong>of</strong> <strong>the</strong> observations in each group <strong>of</strong> similar magnitude. This also
follows from <strong>the</strong> Levene’s test <strong>of</strong> homogeneity <strong>of</strong> variances. Hence, <strong>the</strong> condition <strong>of</strong> equality <strong>of</strong>
variance is satisfied. Hypo<strong>the</strong>sis 2(a) is accepted whereas hypo<strong>the</strong>sis 2(b) is not statistically
significant at <strong>the</strong> 0.05 significance level.
Table 3: ANOVA table for IC disclosure by period
Table 4 presents <strong>the</strong> paired sample t-test for hypo<strong>the</strong>sis 3 that confirms that <strong>the</strong>re exists a relationship
between <strong>the</strong> amount <strong>of</strong> IC disclosure that a company reports in its prospectus and its annual report
following to <strong>the</strong> IPO. On average <strong>the</strong> IC disclosure in <strong>the</strong> annual report is 10 units lower compared to
<strong>the</strong> prospectus.
Table 4: Paired sample t-test
5. Conclusion
The objective <strong>of</strong> this study is dual. On <strong>the</strong> one hand we want to determine <strong>the</strong> relationship between IC
disclosure in <strong>the</strong> prospectus and <strong>the</strong> annual report and on <strong>the</strong> o<strong>the</strong>r hand we want to investigate <strong>the</strong>
impact <strong>of</strong> <strong>the</strong> recent economic disturbance on <strong>the</strong> level <strong>of</strong> IC disclosure in <strong>the</strong> prospectus as well as
<strong>the</strong> annual report. Each corporate document was manually scanned for IC information based on <strong>the</strong>
index developed by Bukh et al (2004). The first hypo<strong>the</strong>sis which states that a more than average
level <strong>of</strong> IC disclosure in <strong>the</strong> prospectus results in a more than average level <strong>of</strong> IC disclosure in <strong>the</strong>
subsequent annual report due to disclosure commitment.confirmed is confirmed. In <strong>the</strong> next research
question we determined <strong>the</strong> impact <strong>of</strong> <strong>the</strong> recent economic disturbance on <strong>the</strong> level <strong>of</strong> IC disclosure in
both prospectus and annual report. Only <strong>the</strong> prospectus was found to be influenced by <strong>the</strong> financial
crisis. Lastly, we looked at <strong>the</strong> impact <strong>of</strong> <strong>the</strong> IC disclosure in <strong>the</strong> prospectus on <strong>the</strong> level <strong>of</strong> IC
disclosure in <strong>the</strong> annual report. This impact is significant.
References
Amir, E. and Lev, B. (1996), “Value-relevance <strong>of</strong> nonfinancial information: <strong>the</strong> wireless communication industry”,
Journal <strong>of</strong> Accounting and Economics, Vol 22, pp. 3-30.
Baker S.L., (2006), “Dummy variables (to represent categories) and time series”, University <strong>of</strong> South Carolina.
Beattie, V. (1999) Business Reporting: The inevitable change, Institute <strong>of</strong> Chartered Accountants <strong>of</strong> Scotland,
Edinburgh.
Beattie, V. and Thomson S.J. (2007), “Lifting <strong>the</strong> lid on <strong>the</strong> use <strong>of</strong> content analysis to investigate intellectual
capital disclosures”, Accounting Forum, Vol. 31, pp. 129-163.
Bontis, N. (2002), IC disclosures in Canadian Corporations, McMaster University, Hamilton.
Bozzolan, S., Favotto, F., and Ricceri, F. (2003), “Italian annual intellectual capital disclosure”, Journal <strong>of</strong>
Intellectual Capital, Vol. 4, No.4, pp. 543-558.
Brown, A., Osborn, T., Chan, J. and Jaganathan, V. (2005), “Managing intellectual capital”, Research-Technology
Managemement, Vol. 48, No. 6, pp. 34-41.
Brüggen, A., Vergauwen, P. and Dao, M., (2009), “Determinants <strong>of</strong> intellectual capital disclosure: evidence from
Australia”, Management Decision, Vol. 47, No. 2, pp. 233-245.
Bukh, P. (2003) “The relevance <strong>of</strong> IC disclosure: A paradox?”, Accounting, Auditing and Accountability Journal,
Vol. 16, No.1, pp. 49-56.
507

Deborah Branswijck and Patricia Everaert
Bukh, P., Nielsen, C. and Gormsen, P. (2004) “Disclosure <strong>of</strong> information on intellectual capital in Danish IPO
prospectuses”, Accounting, Auditing & Accountability Journal, Vol 18, No.6, pp. 713-732.
Chen, M., Cheng, S. and Hwang, Y. (2000) “An empirical investigation <strong>of</strong> <strong>the</strong> relationship between intellectual
capital and firms’ market value and financial performance”, Journal <strong>of</strong> Intellectual Capital, Vol. 6, No. 2, pp.
159-176.
Cooke, T. E., and Wallace, R. S. O. (1990) “Financial disclosure regulation and its environment: a review and
fur<strong>the</strong>r analysis”, Journal <strong>of</strong> Accounting and Public Policy, Summer 1990.
Cordazzo, M. (2007). “Intangibles and Italian IPO prospectuses: a disclosure analysis”, Journal <strong>of</strong> Intellectual
Capital, Vol 8, No. 2, pp 288-305.
Clarkson, P.M., Ferguson, C. and Hall, J. (2003), “Auditor conservatism and voluntary disclosure: evidence from
<strong>the</strong> year 200 systems issue”, Accounting and Finance, Vol. 43, No.1, pp. 21-40.
Cumby, J. and Conrad, J. (2001) “Non-financial performance measures in <strong>the</strong> Canadian biotechnology industry”,
Journal <strong>of</strong> Intellectual Capital, Vol 2, No. 3, pp 261-272.
Daily, C.M., Certo, S.T., Dalton, D.R. and Roengpitya, R. (2003), “IPO underpricing: a meta-analysis and
research syn<strong>the</strong>sis”, Entrepreneurship Theory and Practice, Vol. 27, No. 3, pp. 271-295.
Deegan, C. (2000) “Financial Accounting Theory”,, Mcgraw-Hill Book Company, Sydney.
Depoers, F. (2000) “A cost-benefit study <strong>of</strong> voluntary disclosure: some empirical evidence from French listed
companies”, The <strong>European</strong> Accounting Review, Vol 9, No. 2, pp. 245-263.
Holland, J. (2001) “Corporate value creation, intangibles, and valuation: a dynamic model <strong>of</strong> corporate value
creation and disclosure”, paper presented at <strong>the</strong> <strong>European</strong> Accounting Association <strong>Conference</strong>, A<strong>the</strong>ns, 19
April.
Jaggi, B. (1997), “Accuracy <strong>of</strong> forecast information disclosed in <strong>the</strong> IPO prospectuses <strong>of</strong> Hong Kong companies”,
The International Journal <strong>of</strong> Accounting, Vol. 32 No. 3, pp. 301-319.
Leuz, C. and Verrecchia, R.E. (2000), “The economic consequences <strong>of</strong> increased disclosure”, Journal <strong>of</strong>
Accounting Research, Vol. 38, Supplement: Studies on Accounting Information and <strong>the</strong> Economics <strong>of</strong> <strong>the</strong>
Firm ,pp. 91-124
Lev, B. (2001) “Intangibles: management, measurement, and reporting”, Brookings Institution Press, Washington,
DC.
Lev, B. and Zambon, S. (2003), “Intangibles and intellectual capital: an introduction to a special issue”, <strong>European</strong>
Accounting Review, Vol. 12 No. 4, pp. 597-603
Ma<strong>the</strong>r, P., Ramsay, A. and Steen, A., (2000), “The use and representational faithfulness <strong>of</strong> graphs in Australian
IPO prospectuses”, Accounting, Auditing & Accountability Journal, Vol. 13, No. 1, pp. 65-83.
Nielsen C., Bukh P.N., Mouritsen J., Johansen M.R., Gormsen P., (2006), “Intellectual capital statements on <strong>the</strong>ir
way to <strong>the</strong> stock exchange”, Journal <strong>of</strong> Intellectual Capital, Vol 7, No. 2, pp. 221-240.
Orens, R. and Derboven, J. (2008) ”De rapportering van informatie over het intellectueel kapitaal in Belgische
IPO-prospectussen”, Accountancy en Bedrijfskunde, Vol. 7, pp. 16-31.
Petty, P. and Guthrie, J. (2000) “Intellectual capital literature review: measurement, reporting and management”,
Journal <strong>of</strong> Intellectual Capital, Vol 1, No. 2, pp. 155-75.
Singh I. and Van der Zahn M. (2008) “Determinants <strong>of</strong> intellectual capital disclosure in prospectuses <strong>of</strong> initial
public <strong>of</strong>ferings”, Accounting and Business Research, Vol. 38, No. 5, pp. 409-431.
Sutthachai S. and Cooke T. E. (2009) “An analysis <strong>of</strong> Thai financial reporting practices and <strong>the</strong> impact <strong>of</strong> <strong>the</strong>
1997 economic crisis’”, Journal <strong>of</strong> Accounting, Finance and Business Studies, Vol 45, No.4, pp. 492-517.
Vandemale, S.N., Vergauwen P.G.M.C. and Smits A.J. (2005) “Intellectual capital disclosure in The Ne<strong>the</strong>rlands,
Sweden and <strong>the</strong> UK: a longitudinal and comparative study”, Journal <strong>of</strong> Intellectual Capital, Vol 6, No. 3, pp.
417-426.
Vergauwen P. and van Alem F. (2005) “Annual report IC disclosures in The Ne<strong>the</strong>rlands, France and Germany”,
Journal <strong>of</strong> Intellectual Capital, Vol 6, No. 1, pp. 89-104.
508

The More Satisfaction, <strong>the</strong> Best Productivity: Examining
<strong>the</strong> Relationship Between Social Capital and job
Satisfaction Among Staff at an Iranian Company
Korosh Gholami 1 , Behjat Yazdkhasti 1 , Rasool Rabbani 1 and Abdoulbaghi
Roushani 2
1
Isfahan University, Isfahan, Iran
2
Researcher at Iranian Welfare Organization, Sanandaj , Iran
korosh_gholamiko@yahoo.com
b.yazdkasti@ltr.ui.ac.ir
rarabani@ltr.ui.ac.ir
Roshani_a2000@yahoo.com
Abstract: The aim <strong>of</strong> this research was investigation <strong>of</strong> relationships between social capital and job satisfaction.
The research population included 1000 staffs (630 males and 370 females) from an Iranian organization. Among
this population, 293 subjects (187 males and 106 females) were studied as research sample. The sampling
method was a combination <strong>of</strong> snowball and simple random methods. This study was survey-based. The data
have been collected throughout two types <strong>of</strong> questionnaires: The first one is Minnesota job satisfaction and <strong>the</strong>
second one was researcher-designed social capital questionnaire. Dimensions like network, norm, trust, and
participation were measured via social capital questionnaire. By drawing network relations among people under
<strong>the</strong> study, two types <strong>of</strong> closed and open networks were recognized. This investigation carried out using UCENET
s<strong>of</strong>tware scales. In addition to UCENET, o<strong>the</strong>r statistical analyses were accomplished using SPSS s<strong>of</strong>tware
(Version 14). The research findings reveal two states <strong>of</strong> job satisfaction among research population: one is
instrumental and <strong>the</strong> o<strong>the</strong>r one is social. In <strong>the</strong> instrumental case, social capital in open networks has led to
increase job satisfaction and conversely, in social job satisfaction state, social capital in closed networks has
resulted in increasing job satisfaction. However, in general, social capital has positive effect on job satisfaction.
(r=0.594, sig=0.000)
Keywords: social capital, job satisfaction, norm, trust, network (close & open), participation
1. Introduction
In recent decades <strong>the</strong> progress <strong>of</strong> countries like Japan in employing human power in <strong>the</strong> best way,
especially participant management for employees, has grabbed <strong>the</strong> attention <strong>of</strong> various societies
including western countries toward this subject and has seriously encouraged <strong>the</strong>m to invest in this
field. Therefore, utilizing this factor, large organizations such as Ford, IBM and so on have been
successful in improving efficiency and job satisfaction among <strong>the</strong>ir staff. (Zohoori, 2007, P162)
Job satisfaction is one <strong>the</strong> basic concepts that play a crucial role in increasing job performance
among employees and considered as a determinant for most <strong>of</strong> <strong>the</strong> organizational variables. Different
studies have shown that job satisfaction is counted as an important factor in improving productivity,
increasing staff responsibility for <strong>the</strong> organization, <strong>the</strong>ir dependency and interest toward job
environment, and reinforcing <strong>the</strong> quality and quantity <strong>of</strong> work. Motivated human power is <strong>the</strong> most
important factor <strong>of</strong> productivity.(Bahrololoom, 2004, P84).
There are a lot <strong>of</strong> factors that form job satisfaction in each organization which, in general, can be
divided into two categories: individual and organizational. However, for o<strong>the</strong>rs this categorization is
different; <strong>the</strong>y categorize <strong>the</strong>m into internal and external factors. In this categorization, <strong>the</strong> internal
aspects include personal characteristics, emotional feelings and states and external aspect consists
<strong>of</strong> organizational, social, and cultural conditions and qualities.(Mirkamali, 2008, P75)
Individual or internal factors are embedded in psychological explanations in which factors such as
age, level <strong>of</strong> education, sex and gender, experience, and emotional intelligence can be mentioned.
In organizational factors <strong>the</strong> indicators like job content, supervision, wage, and promotion chances
can be referred. However, among <strong>the</strong> organizational factors <strong>the</strong> most significant one is <strong>the</strong> individual's
network <strong>of</strong> relations in <strong>the</strong> organization, embedded in sociological explanation, in o<strong>the</strong>r words
individual's social capital in <strong>the</strong> organization which play a fundamental role in forming individual's job
satisfaction. Hence, <strong>the</strong> aim <strong>of</strong> this study is to investigate <strong>the</strong> relationship between social capital and
job satisfaction.
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Korosh Gholami et al.
Durkheim believes that social relationships affect <strong>the</strong> individuals' satisfaction. (Salarzadeh ad
HassanZadeh, 2006, P3)
Nowadays social capital has achieved great popularity in <strong>the</strong> organization. The role <strong>of</strong> social capital is
greater than <strong>the</strong> physical capital one in <strong>the</strong> organizations. In <strong>the</strong> absence <strong>of</strong> social capital, <strong>the</strong> o<strong>the</strong>r
types <strong>of</strong> capital lose <strong>the</strong>ir effectiveness and without social capital, it seems hard and rough to take
step on <strong>the</strong> way <strong>of</strong> cultural and economical development and evolution. Social capital has a lot <strong>of</strong>
function for societies and organizations. For example by establishing communications through social
capital employees' job satisfaction increase and organizational performance progress will be possible.
(Requena 2003, P3). In an article, Herington argues that <strong>the</strong> increase <strong>of</strong> network social capital leads
to improve financial performance in organizations. (Harington, 2001, P867).
In organizations, social capital is a set <strong>of</strong> norms and values belong to group which gives <strong>the</strong> members
opportunities for better cooperation. The current study seeks to examine <strong>the</strong> role <strong>of</strong> social capital in
order to explain job satisfaction among Iran National Gas Company staff department (Tehran Office).
In 1916, for <strong>the</strong> first time <strong>the</strong> term <strong>of</strong> social capital was applied by a young social reformist educator
called L.J. Hanifan. He found a kind <strong>of</strong> seclusion and stagnancy <strong>of</strong> family in social life, so emphasizing
resuscitation <strong>of</strong> social commitment for protect democracy, he established <strong>the</strong> term <strong>of</strong> social capital. In
his explanation regarding this concept, we can almost discover all <strong>the</strong> elements for later
interpretations about this concept, but apparently innovative notion could not draw o<strong>the</strong>r <strong>the</strong>orists'
attention and disappeared ineffectively.
The term <strong>of</strong> capital which was merely common in economical discussions and considered as a basis
its analysis previously has nowadays gained a great position in social science. In this sense, capital is
not only economic, but it covers o<strong>the</strong>r types such as human, cultural, and social capital in particular.
Social capital is a multi-dimensional concept in social science which came to exist in economic
discourses in <strong>the</strong> early 20 th century and entered <strong>the</strong> political and sociological texts from 1980. This
notion was firstly presented by Jacbs, Bourdieu, and Lori, but was developed and spread by Colman,
Burt, Putnam, and portez. (Azkia and Ghafari, 2004, P278). Social capital is an inter-disciplinary
concept that studied by great <strong>the</strong>orists in different areas. However, it does not mean that it has no
trace in <strong>the</strong> works <strong>of</strong> classical sociologists. In <strong>the</strong> works <strong>of</strong> sociologists and thinkers like Marx,
Webber, and Durkheim, this concept can be sought. For example Marx, Simmel, Durkheim, Weber,
and Parsons have concentrated on notions like emergency, collective usefulness, values and social
trust which today each is considered as a dimension for social capital (Tavsoli, 2005, P3). Based on
Colman's <strong>the</strong>ory social capital is defined according to its functions. He believes it is not a single object
but it contains types <strong>of</strong> various things which have two common traits:
1. They all include an aspect <strong>of</strong> a single social structure,
2. They facilitate certain actions which are impossible in <strong>the</strong> absence <strong>of</strong> social capital.
In his different works, Robert Putnam, defines social capital as social networks, norms <strong>of</strong>
communication, trust and ability derived from it. In fact, he puts emphasis on <strong>the</strong> relationships among
individuals and social sources which facilitate such a relation. Many researches study <strong>the</strong>
relationships between variables <strong>of</strong> social capital such as organizational membership and economic
outcomes. While carrying out a study about social capital, in Italy Putnam found out that social capital
strongly affects civic participation, that is social capital makes <strong>the</strong> government encourages social
participation and in turn this leads to political development (Glaeser et al, 2002, P2).
According to <strong>the</strong> abovementioned, social capital refers to <strong>the</strong> resources that are available in vocation
networks and can be obtained throughout <strong>the</strong> same resources. These resources include information,
thoughts, guidelines, vocational chances, financial capital, power and influence, emotional support,
good intention, trust and cooperation.
Alder and Woon(1999) also present a definition for social capital. They suggest that social capital is a
resource that an actor achieves via network links (Harington, 2001, P84).
Social capital has different aspects, so that this concept is explored by its dimensions. Network, norm
and participations are <strong>of</strong> examples.
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2. 1BMethodology
Korosh Gholami et al.
This study is survey-based. The data have been collected throughout two types <strong>of</strong> questionnaires:
The first one is Minnesota job satisfaction and <strong>the</strong> second one is researcher-designed social capital
questionnaire. This study has been conducted among 950 Iran National Gas Company staff
department (Tehran Office). This research population was 290 people which calculated by Cochran
formula. The sampling method is a combination <strong>of</strong> snowball and simple random methods. Unit <strong>of</strong>
analysis in this study is individual or employee.
3. 2BDescriptive findings
In this study %36.1 <strong>of</strong> <strong>the</strong> respondents were female and %63.9 was males. Also %21.8 was singles
and %78.2 was married. Their job experience ranged from 1 to 40 years, but <strong>the</strong> average was 14
years. In case <strong>of</strong> education degree, maximum <strong>of</strong> frequency distribution belongs to BA which equals to
%9.46 and <strong>the</strong> minimum pertains to under diploma equals to %4.1. Also <strong>the</strong> level <strong>of</strong> education for
%19 <strong>of</strong> respondents was higher than BA degree. In general %75.1 <strong>of</strong> <strong>the</strong> population has university
degree: this indicate that high level <strong>of</strong> education and specialization are very important for Iran National
Gas Company. The respondents' age varies from 20-64 years old, but <strong>the</strong> average <strong>of</strong> this variable
was 38 years. Also %55 <strong>of</strong> <strong>the</strong>m belonged to <strong>the</strong> group aged 26-30 years old. We observed <strong>the</strong>
variation regarding intimate friends that employees have among <strong>the</strong>ir colleagues. This number ranged
10 to 0, but <strong>the</strong> average <strong>of</strong> intimate friend for each respondent among his or her colleagues was 3.4. It
deserves to be said that %7.93 <strong>of</strong> respondents had at least one intimate friend. More than %93 <strong>of</strong>
respondents trusted <strong>the</strong>ir organizational friends highly.
The score average for this variable was 2.4 out <strong>of</strong> 5 that show a good atmosphere <strong>of</strong> friendship and
trust among <strong>the</strong> colleagues in this organization. The rate <strong>of</strong> participation <strong>of</strong> <strong>the</strong> employees in decision
making was to an extent lower than <strong>the</strong> average. Almost %70 <strong>of</strong> <strong>the</strong> respondents believed that
dominant norms in <strong>the</strong> organization encourage <strong>the</strong> spirit <strong>of</strong> friendship and cooperation.
4. 3BTesting <strong>the</strong> hypo<strong>the</strong>ses
Due to <strong>the</strong> level <strong>of</strong> measurement <strong>of</strong> <strong>the</strong> variables, T-test and Pearson were employed in order to test
<strong>the</strong> hypo<strong>the</strong>ses. The results show that men were more satisfied with <strong>the</strong>ir jobs than women. Also we
observed that job experience had direct relation with job satisfaction. Married people were more
satisfied with <strong>the</strong>ir jobs than singles. As mentioned previously, social capital was measured within four
dimensions including trust, network <strong>of</strong> relations, norms, and participation in organizational decision
making. Then by using network analysis method and calculating <strong>the</strong> density <strong>of</strong> network for each
individual, <strong>the</strong>ir networks were divided into two types <strong>of</strong> networks: closed and opened networks. The
effect <strong>of</strong> each dimension on job satisfaction is presented in <strong>the</strong> following table:
Table 1: Opened and closed network
Social Trust
Network <strong>of</strong> relations
Participation in decision making
Norm
Social Capital
Opened Network
R=- o.058
Sig= 0.751
R=- 0.215
Sig= 0.182
R= 0.520
Sig= 0.000
R= 0.271
Sig= 0.087
R=0.450
Sig=0.013
Closed Network
R=o.743
Sig= 0.014
R=0.336
Sig= 0.147
R= 0.319
Sig= 0.159
R= 0.453
Sig= 0.045
R=0.788
Sig=0.012
Looking at <strong>the</strong> above table we can conclude for <strong>the</strong> employees with closed network, social capital and
its dimensions (except for decision making participation) play a greater and stronger role in explaining
<strong>the</strong>ir job satisfaction. Of course it should be pointed out that opened network is necessary for
managers because <strong>the</strong>y need to make larger decisions. Therefore such an atmosphere is very
appropriate for <strong>the</strong>m.
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Korosh Gholami et al.
The effect <strong>of</strong> each dimension for social capital, in opened and closed networks, on jib satisfactioninstrumental
and social dimensions- is presented in <strong>the</strong> four following tables:
Table 2: Opened networks and instrumental satisfaction
Social trust
Network <strong>of</strong> relations
Participation in decision making
Norms
Social capital
Table 3: Opened network and social satisfaction
Social trust
Network <strong>of</strong> relations
Participation in decision making
Norms
Social capital
Table 4: Closed network and social satisfaction
Social trust
Network <strong>of</strong> relations
Participation in decision making
Norms
Social capital
Table 5: Closed networks and instrumental satisfaction
Social trust
Network <strong>of</strong> relations
Participation in decision making
Norms
Social capital
512
Job satisfaction
R=o.153
Sig= 0.123
R=0.102
Sig= 0.243
R= 0.472
Sig= 0.000
R= 0.338
Sig= 0.000
R=0.459
Sig=0.000
Job satisfaction
R=0.310
Sig= 0.013
R=0.253
Sig= 0.019
R= 0.427
Sig= 0.000
R= 0.348
Sig= 0.001
R=0.506
Sig=0.000
Job satisfaction
R=0.731
Sig= 0.025
R=0.512
Sig= 0.061
R= 0.522
Sig= 0.046
R= 0.650
Sig= 012
R=0.780
Sig=0.022
Job
satisfaction
R=0.
Sig= 0
R=0.
Sig= 0.
R= 0.
Sig= 0.
R= 0.
Sig= 0.
R=0.
Sig=0.

5. 4BConclusion
Korosh Gholami et al.
By Comparing four tables (2 to 5) we can conclude that in <strong>the</strong> state <strong>of</strong> opened network and for those
who seek instrumental satisfaction, except for participation <strong>the</strong> o<strong>the</strong>r aspects <strong>of</strong> social capital have no
effect on job satisfaction. Therefore in general we can say that in this state social capital has a trivial
effect on job satisfaction.
In <strong>the</strong> state <strong>of</strong> closed network and for those who seek social satisfaction, social capital and its four
aspects have a strong effect on job satisfaction. This state is in which social capital explains job
satisfaction in <strong>the</strong> best way, is completely against <strong>the</strong> previous one. Bert explains this distinction very
well. He believes that <strong>the</strong> existence <strong>of</strong> structural holes in open networks doesn’t lead to satisfaction.
Because someone in <strong>the</strong>ir network <strong>of</strong> relations have <strong>the</strong> individuals who are not connected to each
o<strong>the</strong>r. So he infers that structural holes make <strong>the</strong> job promotion possible ra<strong>the</strong>r than job satisfaction.
On <strong>the</strong> contrary, in case <strong>of</strong> closed network, individual relates to those who <strong>the</strong>mselves are related to
each o<strong>the</strong>r. And this in turn provides a kind <strong>of</strong> joy and satisfaction for individual.
In <strong>the</strong> state <strong>of</strong> opened network and for those who seek social satisfaction, social capital and its four
aspects have a weaker effect on job satisfaction.
In <strong>the</strong> state <strong>of</strong> closed network and for those who seek instrumental satisfaction, social capital and its
four aspects have no effect on job satisfaction. In more accurate word those who seek <strong>the</strong>
instrumental satisfaction are not going to form <strong>the</strong> closed network at all. That is why <strong>the</strong> number <strong>of</strong>
people who has closed network and sought instrumental satisfaction was so small that were not
considered in statistical assessments.
5BReferences
Azkia , M and Ghafari , G (2004) Study <strong>of</strong> relationship between Trust and Social Participation in rural area <strong>of</strong>
kashan , Social Science Letter, N.17
Bahrololoom & collegues (2004) The relationship between organizational culture and job satisfaction among
Body Education Office Staff in Tehran, Olympic Magazine N.10
Beugelsdijk S. & van schaik T.( 2005) Differences in social capitals between 54 western <strong>European</strong> Regions,
Regional Studies 39
Burt S. Ronald, (2000) The network structure <strong>of</strong> social capital, Research in Organizational Behavior, Vol 22.
Glaeser L& collegues. (2002). AN ECONOMIC APPROACH TO SOCIAL CAPITAL The Economic Journal, 112
(November), F437-F458.
Harington,Brooke, (2001) Organizational performance and corporate social capital: A contingency model, social
capital <strong>of</strong> organization, vol 18.
Herreros, Francisco, (2004) The problem <strong>of</strong> forming social capital: why trust? Palgrave mcmillan press.
Keefer & Knack, Philip & Stephen, (2005) Handbook <strong>of</strong> new institutional economics, Springer us press.
Mirkamali , M ,and Narenji(2008) A Study on <strong>the</strong> Relationship between <strong>the</strong> Quality <strong>of</strong> Work Life and Job
Satisfaction among <strong>the</strong> Faculty Members <strong>of</strong> <strong>the</strong> University <strong>of</strong> Tehran and Sharif University , Quarterly Jurnal
<strong>of</strong> Research and Planning in Higher Education , N.48
Requena, Felix, (2002) Social Capital in <strong>the</strong> Spanish Quality <strong>of</strong> Working Life Survey, country paper prepared by
Fleix Requena Spanish Ministry <strong>of</strong> labour and Social Affairs, for <strong>the</strong> OECD-UK ONS International
<strong>Conference</strong> on Social Capital Measurment, Septemberr 25-27.
Salarzadeh ad HassanZadeh (2006) A Study on <strong>the</strong> Relationship between social capital and job satisfaction
among teachers, Quarterly Journal <strong>of</strong> Social Sciences, N.33
Tavasoli , G (2005) Social Capital , Invisible Capital , New Life Economic Magazine
Zohoori & Collegues (2007) <strong>the</strong> view <strong>of</strong> Participative Decision Making Effects on Job Satisfaction (case study :
Khozestan Agriculture Bank) , Management Knowledge , N.80
513

Measure <strong>the</strong> Unmeasurable? Intangible Assets as <strong>the</strong> Major
Strategic Keys <strong>of</strong> Enterprises: Their Contribution,
Difficulties and Proposals for Reliable Financial
Statements
Emmanouil Gkinoglou
University <strong>of</strong> Macedonia, Greece
gkinoglou@uom.gr
Abstract: It is common belief, for <strong>the</strong> last two decades, that we can observe <strong>the</strong> transformation <strong>of</strong> international
economy, from industrial to knowledge economy. In a continuous changing economy, <strong>the</strong> main advantage <strong>of</strong> <strong>the</strong>
companies is not <strong>the</strong> buildings, <strong>the</strong> machines, <strong>the</strong> trucks, or <strong>the</strong> total equipment. The strategic key <strong>of</strong> a today
company is <strong>the</strong> capital that can not be copied easy, that is not disclosed and is not tangible, <strong>the</strong> intellectual
capital <strong>of</strong> <strong>the</strong> company. The intangible assets can be characterized as those without physical appearance and <strong>the</strong>
value <strong>of</strong> which is limited by <strong>the</strong> rights and anticipative benefits that possession confers upon <strong>the</strong> owner. The
expansion <strong>of</strong> companies into foreign markets presupposes <strong>the</strong> aggregation <strong>of</strong> financial information that includes
non homogeneous elements. The purpose <strong>of</strong> this paper is to examine <strong>the</strong> framework <strong>of</strong> identification, as well as,
<strong>the</strong> disclosure requirements <strong>of</strong> brand names as <strong>the</strong>y have been set by several articles <strong>of</strong> Commercial Law and
recognized by pr<strong>of</strong>essional accounting institutions. Emphasis will be given in analyzing existing accounting
recognition and measurement, and proposals worldwide. In conclusion, this study indicates <strong>the</strong> accounting
problems <strong>of</strong> define, measure and disclose <strong>the</strong> majority <strong>of</strong> <strong>the</strong>se intangible assets, to users <strong>of</strong> financial statements
<strong>of</strong> <strong>the</strong> company. Despite all <strong>the</strong> difficulties, this property <strong>of</strong> <strong>the</strong> company, must some way been measured and
disclosed to lead to more reliable financial statements. The proposals <strong>of</strong> this paper,will help <strong>the</strong> accounting
community to solve this major problem.
Keywords: accounting, intangible assets, measurement <strong>of</strong> intangible assets, intellectual capital, brand name,
intellectual capital
1. Introduction
The major and <strong>the</strong> most common problem that face companies today, is <strong>the</strong> reason why two same
products, manufactured by <strong>the</strong> same materials, <strong>the</strong> same machines, in similar factories and also
distributed in same way and in same places are faced in different ways from <strong>the</strong> consumers – clients.
The answer is hidden somewhere in <strong>the</strong> field <strong>of</strong> Intangible Assets. The strategic key for an enterprise
to add value to products is more than ever now, her Intellectual Property.
The last two decades, from <strong>the</strong> middle 90‟s, <strong>the</strong> Intangible Assets is <strong>the</strong> main problem for Academics
and <strong>the</strong> pr<strong>of</strong>essional Accountants – Consultants. The main problem is <strong>the</strong> asymmetry information for
<strong>the</strong> users <strong>of</strong> Financial Statements (Banks – Suppliers – Investors – Personnel etc). This information
about <strong>the</strong> Intellectual Property <strong>of</strong> <strong>the</strong> Company does not appear in <strong>the</strong> Annual Financial Statements.
That is <strong>the</strong> reason why <strong>the</strong> information loose a major piece, <strong>the</strong> Intellectual Capital.
2. The immeasurable
What differentiates two similar, competitive enterprises, that are activated in <strong>the</strong> same sector –
commercial or productive -, in <strong>the</strong> same region, with similar suppliers and similar quality <strong>of</strong> produced
product, are not <strong>the</strong> factories, not <strong>the</strong> buildings <strong>of</strong> administration, not <strong>the</strong> machines, not <strong>the</strong> trucks for
<strong>the</strong> distribution, not <strong>the</strong> products. What differs two products from different enterprises, in <strong>the</strong> brain and
<strong>the</strong> choice <strong>of</strong> consumer, is <strong>the</strong> intellectual capital <strong>of</strong> enterprises, which constitutes property <strong>of</strong> each
enterprise, and is not presented and not valued most times in <strong>the</strong> Balance-sheet <strong>of</strong> Enterprise.
However, this capital is <strong>the</strong> one that <strong>of</strong>fers in each Enterprise <strong>the</strong> competitive advantage, and <strong>the</strong>
possibility that her own product is been preferred from <strong>the</strong> consumers, against competition.
Characteristic example appears to be <strong>the</strong> product Personal Computer (PC) in <strong>the</strong> modern season but
also in <strong>the</strong> direct past.
Even if a simple, daily computer, is constituted by <strong>the</strong> same quantity <strong>of</strong> raw material <strong>of</strong> which
computer was manufactured 5 years ago (iron, plastic, silicone), <strong>the</strong>se raw materials are used with
such way today that makes <strong>the</strong> computers 30 times more powerful. The reason is that, <strong>the</strong> materials
are manufactured with such way so that <strong>the</strong>y attribute in <strong>the</strong> Computer more technological
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Emmanouil Gkinoglou
possibilities, usefulness and extension add value. What <strong>the</strong>refore, was added in <strong>the</strong> final product in
order to it acquires higher value and possibilities is <strong>the</strong> Intellectual Capital <strong>of</strong> Producer <strong>of</strong> Enterprise.
3. Categories <strong>of</strong> intangible assets <strong>of</strong> strategic importance for <strong>the</strong> enterprises
With a broader interpretation <strong>of</strong> <strong>the</strong> contribution <strong>of</strong> intellectual capital, that does not appear, is not
portrayed nor is counted but it adds value to <strong>the</strong> enterprise and reinforces <strong>the</strong> opinion <strong>of</strong> strategic
importance <strong>of</strong> intangible in <strong>the</strong> value <strong>of</strong> enterprise, we can distinguish moreover categories. The
existence <strong>of</strong> <strong>the</strong>se categories in <strong>the</strong> economic environment <strong>of</strong> enterprise, contributes to <strong>the</strong> good
operation <strong>of</strong> entire company, participating thus in <strong>the</strong> creation <strong>of</strong> satisfied general working
environment. With a good environment <strong>of</strong> work, <strong>the</strong> enterprise functions better and this output is
translated in superior quality, better service <strong>of</strong> customers from each opinion, restriction <strong>of</strong> losses or
natural –damage - or financing better agreements and o<strong>the</strong>r elements that render competitive <strong>the</strong>
enterprise.
Under <strong>the</strong> wide regard <strong>the</strong>refore, we can distinguish as contribution to <strong>the</strong> maximisation <strong>of</strong> output <strong>of</strong>
enterprise, <strong>the</strong> good labour relations from <strong>the</strong> state or o<strong>the</strong>r organisms. The pr<strong>of</strong>essional behaviour <strong>of</strong>
enterprise to third person creates climate <strong>of</strong> confidence in and around <strong>the</strong> enterprise.
A good labour environment could also constitute <strong>the</strong> base for <strong>the</strong> consolidation <strong>of</strong> competitive
advantage <strong>of</strong> enterprise. With <strong>the</strong> term "good labour environment" are fixed <strong>the</strong> ways <strong>of</strong> behaviour <strong>of</strong>
management to <strong>the</strong> workers also <strong>the</strong> workers between <strong>the</strong>m.
We could distinguish in regard to <strong>the</strong> relations <strong>of</strong> administration to workers factors as: fair and equal
confrontation, remuneration depending on <strong>the</strong> objective value and <strong>the</strong>ir <strong>of</strong>fer, respect in <strong>the</strong>
personality each involved in <strong>the</strong> life <strong>of</strong> enterprise, in any level, interest <strong>of</strong> administration for all <strong>the</strong>
workers not as <strong>the</strong>ir fortune but as individuals, good building installations even technologically but
also with most excellent conditions <strong>of</strong> hygiene, guarantee –as far as possible - for <strong>the</strong> diachronic
safety in <strong>the</strong> work etc.
All <strong>the</strong> above contribute in <strong>the</strong> creation <strong>of</strong> good labour environment, which improves <strong>the</strong> fame <strong>of</strong>
enterprise while it contributes also in <strong>the</strong> productivity and <strong>the</strong> quality <strong>of</strong> products and services. Thus,
although individual factors (equal confrontation, justice, respect, solidarity, safety, hygiene etc) cannot
constitute distinguishable intangible assets <strong>of</strong> enterprise, as <strong>the</strong>y do not accomplish <strong>the</strong> before
mentioned terms <strong>of</strong> recognition <strong>of</strong> intangible asset, <strong>the</strong>y contribute in <strong>the</strong> consolidation <strong>of</strong> o<strong>the</strong>r
intellectual – intangible assets as fame, contracts with customers, clients list, know-how etc. One
more factor constitutes <strong>the</strong> significance <strong>of</strong> knowledge, which leads to a competitive advantage. The
modern enterprising and economic environment in which participate <strong>the</strong> enterprises <strong>the</strong>mselves,
requires <strong>the</strong> exploitation <strong>of</strong> knowledge not only in individual elements <strong>of</strong> enterprise (channels <strong>of</strong>
distribution – list <strong>of</strong> clients - market – marketing etc) but also in <strong>the</strong> total <strong>of</strong> enterprise. This knowledge
is found incorporated in <strong>the</strong> systems that are used but also in <strong>the</strong> competences and <strong>the</strong> basic
advantages <strong>of</strong> her executives. Thus <strong>the</strong> challenges that face <strong>the</strong> enterprises are <strong>the</strong> growth <strong>of</strong>
mechanisms capable <strong>of</strong> <strong>the</strong> localisation and <strong>the</strong>n <strong>the</strong> management <strong>of</strong> this particular knowledge that
exists in <strong>the</strong> enterprise, with primary target <strong>the</strong> increase <strong>of</strong> value <strong>of</strong> Knowledge Management.
4. Different approaches
For a so –relatively –new subject, is reasonable that different approaches and different confrontations
are proposed from a lot <strong>of</strong> academics but also from practitioners <strong>of</strong> auditing and accounting
pr<strong>of</strong>ession. Therefore, different interpretations are met in <strong>the</strong> international bibliography for <strong>the</strong>
confrontation <strong>of</strong> same subject.
Without doubt, from <strong>the</strong> terms used in <strong>the</strong> recognition and interpretation <strong>of</strong> secret fortune <strong>of</strong> Enterprise
are:
Intangible Assets
Intellectual Property
Intellectual Assets
Intellectual Capital
Knowledge Based Assets
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5. Efforts for definition
Emmanouil Gkinoglou
As in every field <strong>of</strong> research, <strong>the</strong> effort to be given concrete and final definition <strong>of</strong> dimension <strong>of</strong>
intangible assets is particularly difficult. As a result <strong>of</strong> this complexity, <strong>the</strong> point <strong>of</strong> view from which
each expert approaches <strong>the</strong> subject but mainly <strong>the</strong> objective that has each researcher through his
inquiring work as well as <strong>the</strong> results in which he aims identify intangible assets as a multidimensional
subject. In <strong>the</strong> international literature, a lot <strong>of</strong> proposals were mad, different approaches were followed
and also tones <strong>of</strong> ink were poured in Congresses, Laboratories, scientific articles and scientific books.
Great names were distinguished for <strong>the</strong> proposals that <strong>the</strong>y have made on <strong>the</strong> particular subject,
which many times are met in <strong>the</strong> reports <strong>of</strong> many articles, between <strong>of</strong> which are Baruch Lev, Leif
Edvinsson, Peer Bukh, Daniel Andriessen, Jan Mouritsen as well as o<strong>the</strong>r.
Efforts both individual, and combinated from institutions – companies (SKANDIA –ALTEC) –
Universities (in national and in international level <strong>of</strong> collaborations from institutions (MERITUM)),
become more intense after henceforth become perceptible that something exists that we cannot
distinguish.
After a lot <strong>of</strong> efforts and a lot <strong>of</strong> proposals for categorisation and recognition <strong>of</strong> this type <strong>of</strong> property,
that adds value in an enterprise, <strong>the</strong> next step was made to <strong>the</strong> direction <strong>of</strong> assessment. The
objective <strong>of</strong> all efforts, national or international, collaborations <strong>of</strong> - pr<strong>of</strong>essionals or academic
proposals, were based on <strong>the</strong> same common way <strong>of</strong> thought: "a reliable system <strong>of</strong> recording and
depicting <strong>of</strong> intangible assets, that leads to assessment <strong>of</strong> inconspicuous fortune <strong>of</strong> enterprise with
final aim <strong>the</strong>ir depiction to <strong>the</strong> financing situations <strong>of</strong> enterprise for relevance and reliability in <strong>the</strong>
Financial Statements <strong>of</strong> <strong>the</strong> company.
6. Proposals for categorization
Figure 1: Scheme 1 (Seetharaman et all, 2006)
The Financial Accounting Standard Boards- FASB and <strong>the</strong> German Society working on intangible
research, Schmalenbach Society for Business (Arbeitskreis, 2002), propose two different approaches,
more detail and clear views for <strong>the</strong> categorization <strong>of</strong> different Intangible Assets <strong>of</strong> a company.
Concretely <strong>the</strong>y propose <strong>the</strong> segregation in seven categories, using as a base <strong>the</strong> financing
appearance in <strong>the</strong> economic situations. This proposals are described analytically, with concrete
examples, helping thus in <strong>the</strong> explicit segregation <strong>of</strong> categories.
Thus FASB‟s proposal (N.N,2001) includes:
Technology
Human Capital
Employee
Competences,
Special Skills
Know-How-
Innovation
Education
Intellectual Capital
Structural
Culture, Company‟s
Spirit, Copyrights,
Trademarks,
Patents, Internal
Data Bases,
Management
Processes etc
516
Relations
Brand, Reputation,
Marketing Strategic,
Alliances, Clients
Lists, Licencies,
Distribution
Channels etc

Customers
Market
Workforce
Contracts
Organisational Structure
Assets, recognized from <strong>the</strong> Law.
Emmanouil Gkinoglou
while <strong>the</strong> German Proposal, recognizes <strong>the</strong> Intellectual Capital that is based on:
Innovation
Human Potential
Customers
Suppliers
Inventors
Processes in <strong>the</strong> Enterprise
Choice <strong>of</strong> Space
FASB‟s opinion, helps particularly because it appears more explicit, creates fewer coverings between
<strong>the</strong> categories, gives a more centralized and complete opinion <strong>of</strong> intangible and helps better <strong>the</strong>
companies.
7. Partial recognition <strong>of</strong> some intangible assets
Some characteristic examples <strong>of</strong> <strong>the</strong> most common intangible assets that a company helds in her
“portfolio”, that constitute <strong>the</strong> intellectual property <strong>of</strong> <strong>the</strong> company and can be sold separately or be
transferred to o<strong>the</strong>rs with specific “life cycle” are listed above according to Seetharaman et all (2006).
Depending on <strong>the</strong> nature <strong>of</strong> every company, <strong>the</strong>re are different assets. Assets without physical
substance, without appearance in <strong>the</strong> financial statements, that <strong>the</strong> environment <strong>of</strong> <strong>the</strong> company
(banks, suppliers, investors etc) does not know <strong>the</strong>ir existence. This gives to a company <strong>the</strong>
opportunity, <strong>the</strong> strategic key, <strong>the</strong> competitive advantage to become stronger between <strong>the</strong>
competitors.
Airport gates and slots
Customers Lists (Deposits, Loans, Credit Cards etc)
Libraries
Trademarks
Licences
Deals
Chemical Formulas
Computer S<strong>of</strong>tware
Electronic Data Bases
Contracts
Agreements <strong>of</strong> Cooperation
Lists <strong>of</strong> Clients
Contracts with Clients Συμβόλαια με πελάτες
Customers Relationships
Manuscripts
Product rights
Distribution Channels
Drilling Rights
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Exclusive use <strong>of</strong> Land Property
Contracts with <strong>the</strong> Employers
Environmental Rights-Air polluting
Recipes
Franchise
Joint Ventures
Emmanouil Gkinoglou
Know How in production, organization, technology etc.
Contract Management
Natural Resources
Patents
Exclusive use <strong>of</strong> Computer S<strong>of</strong>tware
Agreements
Schemes
Suppliers Agreements- contracts
Well trained employees or team – workers
All <strong>the</strong> above, are only some <strong>of</strong> <strong>the</strong> Intangibles that a company holds. There are more types <strong>of</strong>
Intangibles, depending on <strong>the</strong> firm, <strong>the</strong> company and <strong>the</strong> product. There are not all kinds <strong>of</strong>
Intellectual Capital <strong>of</strong> <strong>the</strong> above list in each company. For example, <strong>the</strong> main Capital <strong>of</strong> a sports club,
a football or a basketball team that aims at <strong>the</strong> victory and <strong>the</strong> championship <strong>of</strong> league are <strong>the</strong>
players, <strong>the</strong> entire team, <strong>the</strong> captain, <strong>the</strong> coach, <strong>the</strong> training team and <strong>the</strong> fans too. All <strong>the</strong>se kinds <strong>of</strong>
Assets, without doubt are Assets for <strong>the</strong> Club, but <strong>the</strong>y aren‟t mentioned in <strong>the</strong> above list.
But trying to define <strong>the</strong> undefined, are we still trying to measure something that does not exist? How
exactly <strong>the</strong> immeasurable is measured?
8. Tools for measurement – <strong>the</strong> intangibles worldwide
Many tools for <strong>the</strong> evaluation <strong>of</strong> this type <strong>of</strong> company‟s property are developed. One <strong>of</strong> <strong>the</strong> most
important inquiring programs, in <strong>the</strong> field <strong>of</strong> intangibles, in which are reported and supported a lot <strong>of</strong>
later researchers <strong>the</strong>mselves, constitutes <strong>the</strong> MERITUM Project (2003). The acronym <strong>of</strong> <strong>the</strong> name <strong>of</strong>
this program is related to <strong>the</strong> measurement <strong>of</strong> <strong>the</strong> intangible, in order to be comprehended and get
improved by <strong>the</strong> administration <strong>of</strong> innovation (Measuring Intangibles <strong>the</strong> Understand and Improve
Innovation Management). With <strong>the</strong> cooperation <strong>of</strong> six <strong>European</strong> countries (France, Finland, Denmark,
Norway, Spain, Sweden) <strong>the</strong> project began in November <strong>of</strong> 1998 and had been continued for 30
months.
The objective <strong>of</strong> this particular program, which was financed by <strong>the</strong> <strong>European</strong> Committee, was to
place limits for <strong>the</strong> measurement <strong>of</strong> this property and to help and improve <strong>the</strong> decision-makings for
<strong>the</strong> Management. More analytically, <strong>the</strong> five objectives <strong>of</strong> specific program were to create a form for
categorisation <strong>of</strong> intangibles, a recorded system for management and control, <strong>European</strong> practices in
<strong>the</strong> measurement <strong>of</strong> intangible assets and <strong>the</strong> determination <strong>of</strong> contribution <strong>of</strong> Intellectual Property in
<strong>the</strong> operation <strong>of</strong> capital markets as a result <strong>of</strong> market‟s data analysis and enter limits in <strong>the</strong>
measurement and <strong>the</strong> appearance <strong>of</strong> <strong>the</strong>se intangible in <strong>the</strong> financial statements <strong>of</strong> enterprise.
The specific inquiring program categorizes <strong>the</strong> Intangible Assets to Intellectual Capital and o<strong>the</strong>r
assets (Intangibles - Intangible Assets). It fixes, <strong>the</strong>refore, as intangible non financing sources, like
future economic utilities, without material substance, that are controlled by <strong>the</strong> enterprise as a result
<strong>of</strong> previous synergies or transactions and can or cannot be object <strong>of</strong> transaction individually from
o<strong>the</strong>r corporate assets. The Intellectual Capital includes all <strong>the</strong> types <strong>of</strong> intangibles which belong or
are used by <strong>the</strong> enterprise, developed <strong>of</strong>ficially or informally. It is something more than total human,
structural dynamic and <strong>the</strong> sources <strong>of</strong> <strong>the</strong> entire enterprise that <strong>the</strong> enterprise uses in order to create
value. According to this program, <strong>the</strong> intangible assets portray <strong>the</strong> total <strong>of</strong> intangible elements <strong>of</strong>
intellectual capital, which are recognized as assets, according to <strong>the</strong> accounting models.
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From <strong>the</strong> earliest examples <strong>of</strong> tools that solve <strong>the</strong> problem was <strong>the</strong> “Navigator” from <strong>the</strong> Swedish
Security Company Skandia (Edvisson L,1997). This tool, was developed due to an intense wish for
more information in <strong>the</strong> annual financial statements.
A different approach, is presented in <strong>the</strong> work <strong>of</strong> Sveiby (1997). The model that Sveiby developed, <strong>the</strong>
"intangible assets matrix ", was used by <strong>the</strong> Swedish Company Celmi. This form provides information
with regard to indicators <strong>of</strong> growth, renewal, efficiency, stability and dangers that have to make with
three categories <strong>of</strong> intangible that are recognized in an enterprise: <strong>the</strong> competences <strong>of</strong> workers, <strong>the</strong>
internal structure and <strong>the</strong> exterior structure <strong>of</strong> enterprise. This method recognizes <strong>the</strong> intangible
assets in non monetary indicators with roots in <strong>the</strong> management <strong>of</strong> knowledge.
Ano<strong>the</strong>r proposal is <strong>the</strong> "IC Navigator" (Steward) , a map that detects, portrays and measures <strong>the</strong>
intangible assets <strong>of</strong> enterprise. In this method, each part (human capital, cliental relations and
structure <strong>of</strong> company), is portrayed in separate axis. The great advantage <strong>of</strong> this method is <strong>the</strong>
possibility <strong>of</strong> comparison between <strong>the</strong> enterprises.
Facing <strong>the</strong> problem <strong>of</strong> regular examination <strong>of</strong> occasions <strong>of</strong> investment, Pr<strong>of</strong>essor Philip McPherson <strong>of</strong>
Systems and Values Ltd, proposes a very powerful opinion for <strong>the</strong> measurement <strong>of</strong> intangible
resources, IVM (Intangible VALUE Measurement). Similar tool is table IC - Index that was developed
by <strong>the</strong> London - based Intellectual Capital Services (ICS), which uses a line <strong>of</strong> indicators, calculate a
total value <strong>of</strong> enterprise, something particularly useful for occasions <strong>of</strong> investment and very important
for analysis <strong>of</strong> cost <strong>of</strong> – pr<strong>of</strong>it.
In order to stimulate <strong>the</strong> administration <strong>of</strong> enterprise ano<strong>the</strong>r tool was developed, <strong>the</strong> EVA (Economic
VALUE Added). The problem which this tool was called to solve was <strong>the</strong> false decisions that are
taken due to false calculations <strong>of</strong> traditional indicators instead <strong>of</strong> Cash Flow, focusing <strong>the</strong> interest <strong>of</strong>
<strong>the</strong> management in <strong>the</strong> creation <strong>of</strong> intangible value.
The opinion <strong>of</strong> Kaplan and Norton (2001), is a tool which clarifies and applies <strong>the</strong> strategies <strong>of</strong>
enterprise. With main purpose <strong>the</strong> creation <strong>of</strong> operational strategies, Kaplan‟s and Norton‟s table <strong>of</strong>
Balanced Scorecard, allows <strong>the</strong> measurement and management <strong>of</strong> strategically important assets <strong>of</strong>
enterprise. With <strong>the</strong> five prospects (financing, customers, internal activities, knowledge and growth),
<strong>the</strong> table <strong>of</strong> balanced scorecard, was not drawn exclusively for <strong>the</strong> management <strong>of</strong> intangibles, but for
<strong>the</strong> measurement <strong>of</strong> strategic output <strong>of</strong> enterprise in total. The table <strong>of</strong> Kaplan and Norton not only
measures <strong>the</strong> output but also is an important mechanism <strong>of</strong> feedback for <strong>the</strong> attribution <strong>of</strong> activities <strong>of</strong>
Management. An interesting field for development <strong>of</strong> Kaplan‟s and Norton‟s approach, is a model
which allows <strong>the</strong> internal control <strong>of</strong> intangibles while simultaneously <strong>of</strong>fers information for <strong>the</strong> exterior
shareholders. The problem that was emerged was in which way <strong>the</strong> long-term strategy <strong>of</strong> enterprise
would be connected with her short-term actions.
Table 1: Internationals efforts for explain intangibles
Why / How Financial Methods Measurement <strong>of</strong>
Value
Improve The Technology Factors Holistic Value
internal
(Khoury, 1994) Approach (Pike
Management
and Roos,2000)
Improvement <strong>of</strong>
Exterior
Information
Motives that
arise from
Legislation or
Transactions
Intangible Capital (Gu and
Lev, 2002)
Cost,Market & Income
Approach (Reily &
Schweihs, 1999)
Value Chain
Scoreboard (Lev,
2001)
Estimate <strong>of</strong> Value Measure
Intellectual Capital
Benchmarking System
(Viedma, 2001)
IC Audit
(Brooking,19
96)
Skandia
Navigator
(Edvinsson &
Malone,
1997)
The proposed methods are only some <strong>of</strong> <strong>the</strong> international proposals in <strong>the</strong> intangible field. It depends
on what we want, what and why do we try to define and measure. The appropriate tool or method
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Emmanouil Gkinoglou
from <strong>the</strong> entire literature depends on what is <strong>the</strong> aim <strong>of</strong> <strong>the</strong> research (evaluation, measurement etc) or
on <strong>the</strong> users <strong>of</strong> <strong>the</strong> research product (management, suppliers, investors etc).
9. The brand advertising campaign as an intangible asset
The fixed assets <strong>of</strong> an enterprise consist a long-term tangible piece <strong>of</strong> property, with natural
substance, that a firm owns and uses in <strong>the</strong> production <strong>of</strong> its income and is not expected to be
consumed or converted into cash any sooner than at least one year's time.
An intangible asset is an asset that is not physical in nature, such as patents, trademarks, copyrights,
goodwill and brand recognition. The firm acquires <strong>the</strong>m with <strong>the</strong> intention <strong>of</strong> keeping <strong>the</strong>m for a period
longer than a year.
An intangible asset can be characterized as ei<strong>the</strong>r an indefinite or a definite asset depending on its
specifics. A company brand name is considered to be an indefinite asset, as it stays within <strong>the</strong>
company as long as <strong>the</strong> company continues operations. However, if a company enters a
legal agreement to operate under ano<strong>the</strong>r company's patent, with no plans <strong>of</strong> extending <strong>the</strong>
agreement, it would have a limited life and would be classified as a definite asset.
9.1 Definition <strong>of</strong> advertisement
An advertisement is <strong>the</strong> activity that contributes in <strong>the</strong> reinforcement <strong>of</strong> demand, in <strong>the</strong> increase <strong>of</strong>
market share and in <strong>the</strong> increase <strong>of</strong> pr<strong>of</strong>its in <strong>the</strong> long run.
Enterprise implements an advertising program, in order to achieve various objectives. These
objectives define <strong>the</strong> different types <strong>of</strong> Advertisement, which are:
Primary Demand Advertising
Selective Demand advertising
Brand Loyalty Advertising
Sales promotion Advertising
Display Advertising
Business to Business Advertising
Retail Advertising
General Advertisement <strong>of</strong> Enterprise, Organism, Institution
Cooperative Advertising
Political Advertisement, aiming at <strong>the</strong> consolidation <strong>of</strong> Brand Name <strong>of</strong> <strong>the</strong> enterprise.
9.2 Types <strong>of</strong> advertisement
The objective <strong>of</strong> establishing a Firm‟s Brand Name is realised with <strong>the</strong> specific advertising campaigns:
1. Primary Demand Advertising
2. Selective Demand Advertising
3. Brand Loyalty Advertising
4. General Advertisement <strong>of</strong> Enterprise, Organism, Institution.
9.3 Contribution <strong>of</strong> advertising program to <strong>the</strong> aim <strong>of</strong> <strong>the</strong> enterprise
From <strong>the</strong> above definitions, it can be elicited that an advertising program that aims at <strong>the</strong>
establishment <strong>of</strong> firm‟s brand name, also, contributes to <strong>the</strong> realisation <strong>of</strong> pr<strong>of</strong>it, which is <strong>the</strong> primary
target <strong>of</strong> an enterprise.
On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> fixed assets, also, contribute to <strong>the</strong> realisation <strong>of</strong> firm‟s primary target.
Therefore, it can be suggested that advertising program, which aims at <strong>the</strong> establishment <strong>of</strong> a firm‟s
brand name can be viewed as a fixed asset. Moreover, as advertisement has no material essence, it
can be considered as an intangible asset
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Consequently, based on <strong>the</strong> above syllogism, it can be assumed that this kind <strong>of</strong> advertising
expenses should be recorded as an intangible asset and be depreciated as all assets.
By behavioural researches, a 3-year period is considered as an expected duration <strong>of</strong> an advertising
program‟s impact on consumers‟ conscience. Thus, this expense should be depreciated ei<strong>the</strong>r at a
constant rate or at a decreasing rate.
According to a Research in enterprises <strong>of</strong> foods world 3, <strong>the</strong> expenses <strong>of</strong> advertising program
contribute to <strong>the</strong> pr<strong>of</strong>itability <strong>of</strong> <strong>the</strong> enterprise for more than one year. Fur<strong>the</strong>rmore, <strong>the</strong> creation <strong>of</strong>
brand name and <strong>the</strong> guarantee <strong>of</strong> customer devotion yield pr<strong>of</strong>its in a long-term horizon.
10. PACE as a measuring tool
In 2006, Altec Research Development, developed a new methodology, based in <strong>the</strong> Weightless
Wealth Toolkit by Andriessen (2004) , a tool to measure <strong>the</strong> intangible assets that contribute in a
Project Management. Based on <strong>the</strong> experience established from <strong>the</strong> team‟s involvement in several
projects, <strong>the</strong>re is clear evidence that a considerable majority <strong>of</strong> projects fail because <strong>the</strong>y do not
succeed in identifying <strong>the</strong>ir individual purpose in terms <strong>of</strong> knowledge produced and excellence
achieved.
The <strong>European</strong> Research Programs, in <strong>the</strong> concretisation <strong>of</strong> which <strong>the</strong>y participate with collaborations
various institutions (Companies, Universities, Pr<strong>of</strong>essional and Social Institutions etc), are faced as
enterprises o<strong>the</strong>rwise intangible assets and <strong>the</strong>ir value <strong>of</strong> which should be recognized so that is
completed <strong>the</strong> Program. Therefore, it will be supposed that it is managed as operational entity <strong>the</strong>
tries and achieves some concrete aim.
The aim <strong>of</strong> this tool <strong>of</strong> measurement is simply a quantitative recording in monetary units, <strong>of</strong> all <strong>the</strong>
intangible that came out as a Project‟s Product. This intangibles, will be useful ei<strong>the</strong>r for <strong>the</strong> entire
team-project or for all <strong>the</strong> individual - parties <strong>of</strong> research division
10.1 The suggested approach
The approach we follow in PACE is built on a seven-step operation:
Step 1: SWOT Analysis
Step 2: Identification <strong>of</strong> each partner‟s Core Competences
Step 3: Stress tests and Valuation <strong>of</strong> Core Competences:
a. Added value test;
b. Competitiveness test;
c. Potentiality test;
d. Sustainability test;
e. Robustness test.
f. Valuation <strong>of</strong> Core Competences
Step 4: Project Assets
Step 5: Exploitation Strategies
Step 6: Roadmaps
Step 7: Strategy Quantification
Step 1: SWOT analysis
The approach is based on <strong>the</strong> recognition and examination <strong>of</strong> Strengths, Weaknesses, Opportunities
and Threats (SWOT), a ra<strong>the</strong>r all-time classic technique that aims at helping at <strong>the</strong> early stages <strong>of</strong>
pre-processing input in order to achieve <strong>the</strong> formation and classification <strong>of</strong> <strong>the</strong> set <strong>of</strong> particular project
developments and results in which <strong>the</strong> project will delivered. SWOT will be performed for <strong>the</strong> project
as a whole. This includes <strong>the</strong> project approach, methodology, and partners‟ assets. In this respect, it
can be treated as a „rough guide‟ to help people like corporate decision-makers and Research
Directors to improve <strong>the</strong>ir processes and increase <strong>the</strong> value <strong>the</strong>y shall be getting from <strong>the</strong> project,
while it can also possibly help <strong>the</strong>m to focus better on <strong>the</strong>ir research work items.
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Project
Assets
Need for
synergies
Quantification <strong>of</strong>
strategies
Assets to exploit
Figure 2: A schematically approach Of PACE tool
Emmanouil Gkinoglou
SWOT
Analysis
TIP oriented
strategies
Exploitation
Strategies
Prioritized CCs
Identification <strong>of</strong> Core
Competencies
Value
Assessments
stress tests
Valuation <strong>of</strong> CC
Roadmaps
Strengths category includes an internal list (internal: to <strong>the</strong> consortium and each partner separately,
and regarding <strong>the</strong> project itself) <strong>of</strong> all <strong>the</strong> “strong” points <strong>of</strong> <strong>the</strong> subject under study (can be ei<strong>the</strong>r <strong>the</strong>
overall integrated project outcome or <strong>the</strong> particular developments which will be lead by <strong>the</strong> partner
under consideration), while <strong>the</strong> Weaknesses category includes an internal list <strong>of</strong> all <strong>the</strong> possible
“weak” points. Respectively <strong>the</strong> Opportunities category holds an external list (external: to <strong>the</strong>
consortium and each partner separately, and regarding <strong>the</strong> project itself) <strong>of</strong> <strong>the</strong> opportunities that
might exist regarding <strong>the</strong> exploitation <strong>of</strong> <strong>the</strong> project outcomes, while <strong>the</strong> threats category includes <strong>the</strong>
external threats that might be faced while trying to exploit <strong>the</strong> project outcomes.
10.2 Step 2: Identification <strong>of</strong> core competencies
The second step refers to <strong>the</strong> identification <strong>of</strong> each partner‟s core competencies (CC) with respect to
<strong>the</strong> project – both those that are contributed by each partner to <strong>the</strong> project and which shall affect its
final outcomes, and those that are affected by <strong>the</strong> project. For each <strong>of</strong> his core competence <strong>the</strong>
partner has to define which intangible assets are related with and what is <strong>the</strong> current contribution
margin in a monetary fashion. A special point should be made for non-commercial partners. These
partners should identify <strong>the</strong> core competencies contributing to <strong>the</strong> participating project. The
contribution margin <strong>of</strong> <strong>the</strong>se CCs should be identified as such. i.e. if partner X participates in a project,
this has been based on one or more Core Competencies that contributes to this project. The partner‟s
income is based on his work and expertise, which in turn can be related to <strong>the</strong> core competencies
owned by <strong>the</strong> partner, and <strong>of</strong>fered to <strong>the</strong> project. Thus, a monetary estimation <strong>of</strong> <strong>the</strong> CCs contribution
margin can be made. In <strong>the</strong> end <strong>of</strong> this step <strong>the</strong> partner should get a complete list <strong>of</strong> <strong>the</strong> core
competencies <strong>of</strong> his organisation, a clear view <strong>of</strong> his legacy intangible assets and an indication
(trough <strong>the</strong> contribution margins) <strong>of</strong> <strong>the</strong> most valuable core competencies.
10.3 STEP 3: Evaluation <strong>of</strong> core competencies
At this stage, according to <strong>the</strong> methodology, each partner tries to evaluate <strong>the</strong> core competencies
<strong>of</strong>fered and/or affected to <strong>the</strong> projected is valuated. Valuation is carried out with respect to <strong>the</strong>
contribution <strong>of</strong> each particular core competence to <strong>the</strong> current and foreseen business <strong>of</strong> each partner.
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Emmanouil Gkinoglou
The valuation is based upon five stress tests, in terms <strong>of</strong> checklists that should be completed for each
identified core competence. These checklists are shown below. For each question <strong>the</strong> partner should
place a binary (yes=1/no=0) indicator. The sum <strong>of</strong> <strong>the</strong>se indicators will comprise <strong>the</strong> total score <strong>of</strong> <strong>the</strong>
stress test and will be taken into account into <strong>the</strong> actual valuation. The total effort <strong>of</strong> valuation (based
in pr<strong>of</strong>. Andriessen method) is based in <strong>the</strong> questionnaire (yes-no), where every core competence
that is contribute to <strong>the</strong> Project, evaluates for <strong>the</strong> value added in <strong>the</strong> Project, <strong>the</strong> Competitiveness, <strong>the</strong>
Potentiality, <strong>the</strong> Sustainability and <strong>the</strong> Robustness. The results are presented in a total matrix (table
7), in which, based in <strong>the</strong> steps 1-8, and in <strong>the</strong> contribution margin <strong>of</strong> each core competence in 5
years life-cycle, as a result we have a monetary evaluation for each core competence. As an example
in <strong>the</strong> tables 2-7, <strong>the</strong> entire methodology can be seen. Continuing this method, we can assume that if
we have 2 different strategies to choose from, taking into consideration <strong>the</strong> present value <strong>of</strong> each
strategy (<strong>the</strong> cost <strong>of</strong> following <strong>the</strong> specific strategy), taking into account <strong>the</strong> result from <strong>the</strong> PACE for
each strategy, we have <strong>the</strong> Future Value <strong>of</strong> money that invest today.
Table 2: Added value checklist
Added value checklist
Added value Score (1=yes,
0=no)
The core competence <strong>of</strong>fers a substantial benefit for your customers or a substantial cost
saving for your company.
Customers demand this specific benefit or cost saving.
This benefit is important for a large number <strong>of</strong> customers; it goes fur<strong>the</strong>r than just ‘nice to
have’.
Customers will continue expecting this benefit in <strong>the</strong> near future; it is not simply a passing
fancy.
Leadership in this core competence makes customers think you are different from <strong>the</strong>
competition, ra<strong>the</strong>r than just better.
Total score added value 0
Table 3: Competitiveness checklist
Competitiveness checklist
Competitiveness Score (1=yes,
0=no)
Fewer than five <strong>of</strong> your competitors share this particular competence.
You are superior to your competitors in most aspects <strong>of</strong> this particular competence.
You invest substantially more time and money in this competence than your competitors.
Your customers choose your products or services largely because you have this competence.
Your leadership in this competence is generally recognized and can be illustrated by articles in
trade journals, patents, and so on.
Total score competitiveness 0
Table 4: Potential checklist
Potential checklist
Potential Score (1=yes,
0=no)
There is an increasing demand for products / services that can be provided thanks to this
core competence.
The core competence allows <strong>the</strong> development <strong>of</strong> new products and services in <strong>the</strong> future.
The core competence allows new markets to be entered in <strong>the</strong> future.
There are no economic threats (customers, suppliers, competitors) that will adversely affect
<strong>the</strong> use <strong>of</strong> this competence.
There are no social threats (regulatory and social) that will adversely affect <strong>the</strong> use <strong>of</strong> this
competence.
Total score potential 0
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Table 5: Sustainability checklist
Emmanouil Gkinoglou
Sustainability checklist
Sustainability Score (1=yes,
0=no)
This core competence is scarce in your branch.
It would require considerable investments in time and / or money for competitors to master
this competence.
Patents, trademarks, and o<strong>the</strong>r legal measures protect components <strong>of</strong> <strong>the</strong> competence.
This competence is a combination <strong>of</strong> a number <strong>of</strong> intangibles such as skills, knowledge,
processes, and corporate culture, thus making it difficult to copy.
This competence cannot be obtained through acquisition or from o<strong>the</strong>r outside sources.
Total score sustainability 0
Table 6: Robustness checklist
Robustness checklist
Robustness Score (1=yes,
0=no)
The group <strong>of</strong> people that possesses <strong>the</strong> skills and knowledge crucial for this competence is
vulnerable.
The values and norms on which this competence is built are under pressure.
The technology and information technology systems that form part <strong>of</strong> this competence are
vulnerable.
The primary and management processes that this competence uses are unreliable.
The endowments on which this core competence depends (like <strong>the</strong> corporate image or <strong>the</strong>
installed client base) are vulnerable.
Total = A
Total score robustness = 5 – A 5
Table 7: Competence
Competence CM G S t=1 t=2 t=3 t=4 t=5 R Value
EXTENSIVE DOMAIN KNOW-
HOW
120.000,00 0 0 120.000,00 120.000,00 120.000,00 120.000,00 120.000,00 100% 600.000,00
EXPERTISE IN ERP SYSTEMS 1.100.000,00 0 0 1.100.000,00 1.100.000,00 1.100.000,00 1.100.000,00 1.100.000,00 100% 5.500.000,00
0,00 0 0 0,00 0,00 0,00 0,00 0,00 100% 0,00
0,00 0 0 0,00 0,00 0,00 0,00 0,00 100% 0,00
Total: 0,00 - - 1.220.000,00 1.220.000,00 1.220.000,00 120.000,00 1.220.000,00 - 6.100.000,00
CM: Contribution Margin in Euros
G: Growth (%) = Added Value + Competitiveness + Potential
S: Sustainability
t 1, t2, …: returns for year 1, year 2, …
R: Robustness (%).
Value: in Euros
This is <strong>the</strong> most important step. Each project partner needs three sets <strong>of</strong> information for conducting
his exploitation strategies. The first is <strong>the</strong> complete SWOT matrix as this was defined in <strong>the</strong> first step,
<strong>the</strong> second is <strong>the</strong> list <strong>of</strong> his core competencies with <strong>the</strong>ir total values, and <strong>the</strong> third is <strong>the</strong> list <strong>of</strong> <strong>the</strong>
defined project Assets.
The strategies will be oriented as <strong>the</strong> Technology Implementation Plan orders. This means that <strong>the</strong>
framework should <strong>of</strong>fer strategic alternatives that should/must fall into <strong>the</strong> following categories. In
order to accomplish this task each partner should look at his core competencies and prioritize <strong>the</strong>m
according to <strong>the</strong>ir contribution margin. Following this, for each one <strong>of</strong> <strong>the</strong> project‟s assets, <strong>the</strong> partners
should look at <strong>the</strong> SWOT table to try to identify elementary strategies (through <strong>the</strong> SWOT
combinations: SO, WO, WT, ST) by exploiting <strong>the</strong> asset under examination. Mentioned earlier, <strong>the</strong>se
strategies should fall under <strong>the</strong> one <strong>of</strong> <strong>the</strong> following (TIP) categories:
IMP: improvement or change <strong>of</strong> internal processes
NPS: new product/ service development
LIC: Revenues through License agreement
MKT: Revenues through Marketing agreement
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Emmanouil Gkinoglou
MAN: Revenues through Manufacturing agreement
JV: Revenues through establishment <strong>of</strong> a joint enterprise or partnership
PPP: Revenues through establishment <strong>of</strong> a Private-public partnership)
FIN: Revenues through development financing
VC: Revenues through venture capital/spin-<strong>of</strong>f fundraising
CONS: Revenues through provision <strong>of</strong> consultancy
R&D: Revenues through fur<strong>the</strong>r research or development)
11. Unmeasurable or measurable?
Finally, <strong>the</strong> subject <strong>of</strong> intangible assets is a daily pastime for <strong>the</strong> enterprises. Measurement and
management <strong>of</strong> <strong>the</strong> intangible property are not so easy and do not take place in <strong>the</strong> same way with
<strong>the</strong> materials. By empirical research, it is realised that traditional industries as aeronautics, defence,
oil have big and intense presence <strong>of</strong> intangible assets (Gu F and Lev B. 2001) . It could constitute
element <strong>of</strong> future research <strong>the</strong> comparison <strong>of</strong> intangible assets, between <strong>the</strong> traditional heavy
industries and <strong>the</strong> new industries as <strong>the</strong> industry <strong>of</strong> multimedia. As pr<strong>of</strong>essor S. Zambon observes,
<strong>the</strong> under investigation scientific region known and as intangible assets or Intellectual Capital", he still
does not give a explicit and strict term while likely he cannot never be delimited <strong>of</strong> course what are <strong>the</strong>
intangible assets. Even if this field <strong>of</strong> research seems to be deprived as an internationally acceptable
language <strong>of</strong> communication, <strong>the</strong> researches are found in a good level <strong>of</strong> determination <strong>of</strong> objective <strong>of</strong>
(intangible assets) but also o<strong>the</strong>r assets that are related with <strong>the</strong>m. A lot <strong>of</strong> articles, opinions have
been written and a wide interest has been expressed by all <strong>the</strong> involved in <strong>the</strong> enterprises parts
(managerial executives, accountants, academicians, advisers etc) for <strong>the</strong> comprehension <strong>of</strong> <strong>the</strong>se
enterprise‟s assets.
Paradox that has to face <strong>the</strong> economic practice, despite <strong>the</strong> uncertain scientific delimitation <strong>of</strong>
particular subject, is that as long as <strong>the</strong> economic system and <strong>the</strong> enterprises base more and more on
<strong>the</strong>ir intangibles and <strong>the</strong>ir intellectual capital, even more powerful <strong>the</strong>y become, while <strong>the</strong>se resources
are <strong>the</strong> key stones for <strong>the</strong> growth and <strong>the</strong> creation <strong>of</strong> value. Of course as long as more intense
investment in intangible resources make not only <strong>the</strong> enterprises but also <strong>the</strong> general economic
system, so much more vulnerable <strong>the</strong>y are.
As a result, few examples <strong>of</strong> empirical study exist. Moreover in <strong>the</strong> international literature is observed
lack <strong>of</strong> <strong>the</strong>oretical frame which, could be argued in <strong>the</strong> practice. Is absent that is to say, a concrete
definition <strong>of</strong> intangible and mental – intellectual capital while also <strong>the</strong> segregation in 3 categories, is
not satisfactory. Most models that have been developed internationally for <strong>the</strong> measurement and
assessment <strong>of</strong> intangible assets and intellectual capital are more qualitative than quantitative and this
does not render this models particularly useful for <strong>the</strong> enterprises. The objectives <strong>of</strong> international
bibliography are <strong>of</strong>ten very narrow and <strong>the</strong>y cannot help <strong>the</strong> enterprise in <strong>the</strong> management <strong>of</strong> <strong>the</strong>se
resources. They are usually focused in <strong>the</strong> benefit <strong>of</strong> information with regard to <strong>the</strong> acquisition <strong>of</strong>
intangibles, without however managing to describe in which way such information be useful for <strong>the</strong>
enterprise.
The lack <strong>of</strong> practical approach is obvious, in <strong>the</strong> subject <strong>of</strong> intellectual capital, which could provide
information and help in <strong>the</strong> enterprises. Future research, will have various subjects as:
particularisation <strong>of</strong> objectives <strong>of</strong> research in <strong>the</strong> intangible with parallel proposals for management <strong>of</strong>
<strong>the</strong>se assets, proposals for exploitation and exploitation in <strong>the</strong> practice <strong>of</strong> information that result from
<strong>the</strong> study <strong>of</strong> intangibles to remain only in <strong>the</strong>ir localisation, examination <strong>of</strong> application in <strong>the</strong> practice <strong>of</strong>
<strong>the</strong>ories that have been developed, focalisation in concrete subjects <strong>of</strong> intangibles except <strong>the</strong>
knowledge, growth <strong>of</strong> <strong>the</strong>oretical background, applicable in <strong>the</strong> practice in regard to <strong>the</strong> management
<strong>of</strong> this fortune <strong>of</strong> enterprises, generalisation <strong>of</strong> model <strong>of</strong> measurement, which might express, portray
and include all <strong>the</strong> types <strong>of</strong> intangible assets that likely possesses <strong>the</strong> enterprise, or growth <strong>of</strong> a new
model. Also it would be important <strong>the</strong> effort for concretisation in <strong>the</strong> practice <strong>of</strong> empirical research, in
order to investigate even if how much is functional <strong>the</strong> management <strong>of</strong> intangible assets.
Deductively, we can realise, how much distinct is <strong>the</strong>ir contribution in <strong>the</strong> creation <strong>of</strong> competitive
advantage and consequently maintenance <strong>of</strong> enterprise in high level <strong>of</strong> competition.
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The next challenge for all <strong>the</strong> involved parts (enterprises - state - shareholders - investors - workers -
administration - economic advisers - accountants – academicians etc) is <strong>the</strong> recognition and <strong>the</strong>
establishment <strong>of</strong> way <strong>of</strong> management, quantity survey and depiction in <strong>the</strong> continuously more
Intangible - Based Economic Environment.
The entire “intangible community”, seems to be very closed, now than ever, to measure <strong>the</strong>
unexploitable and mysterious, unmeasurable, non-tangible fortune <strong>of</strong> enterprise that <strong>of</strong> Intangible
Assets.
References
Altec SA, Research Programs Division “Pace Exploitation Toolkit”, 2006. Altec is a computer s<strong>of</strong>tware and
hardware supplier, in Greece. For more analysis can visit www.altec.gr
Andriessen, D, Making Sense <strong>of</strong> Intellectual Capital: Designing a method for <strong>the</strong> valuation <strong>of</strong> Intangibles,
Butterworth – Heinemann, 2004
Arbeitskreis (2002), “Immaterielle Werte im Rechnungswesen” der Schmalenbach- Gesellschaft fur
Betriebswirtschaft e.V. (Working Group, Intangible Assets in Accounting <strong>of</strong> <strong>the</strong> Schmalenbach Society)
(2002),“Kategorisierung und Bilanzielle Erfassung immaterieller Werte (Categorization and financial
coverage <strong>of</strong> Immaterial Values) „ Der Betrieb Vol.54, No19, pp 989-95
Edvinsson L. (1997), “Developing Intellectual Capital at Skandia”, Long Range Planning, Vol.30, No 3, pp 366-73
Gu F.and Lev B. (2001), “Intangible Assets - Measurement, Drivers, Usefulness”, Working Paper, Boston
University,/New York University
Kaplan R.S and Norton D.P. “The Strategy-Focused Organization”, Harvard Business School Press, Boston, MA,
(2001)
Kristandl G., working paper
M'Pherson P.K and Pike S. “Accounting, Empirical Measurement and Intellectual capital”, Journal <strong>of</strong> Intellectual
Capital, Vol.2, No3, pp 246-60
Meritum (2002)
N.N (2001), “Getting a grip on Intangible Assets – What <strong>the</strong>y are, why <strong>the</strong>y matter, and who should be managing
<strong>the</strong>m in your organization”, Harvard Management Update, pp 6-7
Seetharaman A, Lock Teng Low K, Saravanan A.S, “Comparative Justification on Intellectual Capital”, Journal <strong>of</strong>
Intellectual Capital, Vol.5, N4, 2006, p522-539
Stewart T.A, “Intellectual Capital - The New Wealth <strong>of</strong> Organizations”, 1 st edition, nicolas Brealey Publishing,
London
Sveiby K.E. “The New Organization Wealth – Managing and Measuring Knowledge-based Assets”, Berret-
Koehler Publishers, As Francisco, (1997),
Zambon St., “Is <strong>the</strong>re a Disciplinary field called Intangibles and Intellectual Capital?”, Introduction From Journal <strong>of</strong>
Intellectual Capital, Vol 7, Iss4.
526

Integrating Intellectual Capital and Sustainability
Management: Perspectives for <strong>the</strong> Internal Management
and External Reporting in Small and Medium Sized
Enterprises
Kai Mertins and Ronald Orth
Fraunh<strong>of</strong>er IPK, Berlin, Germany
kai.mertins@ipk.fraunh<strong>of</strong>er.de
ronald.orth@ipk.fraunh<strong>of</strong>er.de
Abstract: As goals for implementing sustainability management eco-efficiency, cost savings, improved
reputation, innovation ability, pr<strong>of</strong>it and sales growth are named. Sustainability management improves <strong>the</strong>
planning security, increases <strong>the</strong> acceptance and <strong>the</strong> legitimacy as well as it allows <strong>the</strong> utilization <strong>of</strong> differentiation
and market potential. Study results show that sustainability management is operated in particular by large
companies. Small and medium sized companies <strong>of</strong>ten lack <strong>the</strong> time and financial resources as well as <strong>the</strong> right
tools in order to integrate tasks <strong>of</strong> a sustainability management into <strong>the</strong> ongoing business activities. At <strong>the</strong> same
time, <strong>the</strong>re is hardly any doubt that for <strong>the</strong> successful implementation <strong>of</strong> sustainable strategies in companies, <strong>the</strong>
intelligent management <strong>of</strong> knowledge and o<strong>the</strong>r intangible resources is a fundamental basis. This intellectual
capital is <strong>the</strong> driver for a sustainable development at <strong>the</strong> corporate level, that has to be measured and regarding
an increasing <strong>of</strong> <strong>the</strong> value creation has to be applied. An integrated view <strong>of</strong> both perspectives has not taken place
yet. Therefore, within <strong>the</strong> framework <strong>of</strong> this paper an integrative approach as well as first requirements for future
methods will be examined and outlined.
Keywords: sustainability management, intellectual capital statements, sustainability balanced scorecard, internal
management, external reporting
1. Initial situation: Sustainability and intellectual capital at <strong>the</strong> company level
In a worldwide survey conducted by <strong>the</strong> Boston Consulting Group regarding "The Business <strong>of</strong>
Sustainability" about 90 percent <strong>of</strong> managers surveyed indicated that sustainability is part <strong>of</strong> <strong>the</strong>ir
corporate strategy. The reasons <strong>the</strong>refore mentioned among o<strong>the</strong>rs were customer requirements, <strong>the</strong>
legal framework, staff expectations and environmental responsibility. Companies consider as <strong>the</strong>
largest benefits <strong>of</strong> a sustainability strategy an improved image, competitive advantages and
innovation, employee motivation, and a better risk management (Boston Consulting Group 2009).
The implementation <strong>of</strong> <strong>the</strong> sustainability concept at <strong>the</strong> enterprise level is discussed under <strong>the</strong> term
"sustainability management" (Hauff et al. 2008). Sustainability management at <strong>the</strong> corporate level can
be understood as a strategy that respects not only economic goals but also environmental and social
aspects, weigh against each o<strong>the</strong>r and thus, ensures <strong>the</strong> long-term business success. Only if
companies in <strong>the</strong> future take into account environmental and social criteria in <strong>the</strong>ir activities besides
economic key figures, innovations and competitive advantages could be achieved for example by
developing new technologies, but also by committed employees. Consequently in this context <strong>the</strong>
development and use <strong>of</strong> intellectual capital provides an important lever for <strong>the</strong> implementation <strong>of</strong>
sustainability management. Thereby, intellectual capital (IC) has a comprehensive impact as it affects
equally <strong>the</strong> performance <strong>of</strong> all three dimensions <strong>of</strong> sustainability (economic, social, and
environmental).
Basically, it can be noted that <strong>the</strong> awareness in enterprises is growing that this issue will gain more
relevance for <strong>the</strong> own company in <strong>the</strong> near future. Indeed, study results prove that <strong>the</strong> number <strong>of</strong>
enterprises which are oriented towards sustainability has increased in recent years, but <strong>the</strong>
implementation still encounters a variety <strong>of</strong> limits. This especially applies to small and medium sized
enterprises (SME). Due to time and financial restrictions, many SMEs do not see <strong>the</strong>mselves in a
position to implement sustainable development as a part <strong>of</strong> <strong>the</strong> corporate strategy (ifo 2002). While
large companies and groups have pr<strong>of</strong>essionalized <strong>the</strong>ir activities <strong>of</strong> sustainable development and are
supported by <strong>the</strong>ir own departments or staff units, SMEs are <strong>of</strong>ten left alone here. Therefore concepts
and methods have to be found in order to provide new and promising instruments in particular for
SMEs which constitute <strong>the</strong> bulk <strong>of</strong> Europe’s economic strength.
In this context <strong>the</strong> intangible resources are <strong>of</strong> central importance for sustainable development <strong>of</strong>
companies. It is common sense that classical driving forces <strong>of</strong> economic growth changed towards <strong>the</strong>
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Kai Mertins and Ronald Orth
generation, application and exploitation <strong>of</strong> knowledge. The key to competitiveness increasingly turns
on <strong>the</strong> way people combine, manage and commercialise <strong>the</strong>ir know-how. To implement sustainability
management, it is crucial for companies to utilise knowledge efficiently and to enhance <strong>the</strong>ir
innovation potential. Thus, managing <strong>the</strong>ir specific intellectual capital actively becomes more and
more important for future-oriented organisations. Fur<strong>the</strong>rmore, reporting those intangibles to
customers, partners and investors systematically has become a critical factor <strong>of</strong> success in <strong>the</strong>
context <strong>of</strong> <strong>the</strong> globalisation process (Mertins et al. 2006).
2. Objectives <strong>of</strong> this paper
In order to act sustainable, enterprises have to be aware <strong>of</strong> <strong>the</strong>ir own strengths as well as
weaknesses, and out <strong>of</strong> it to elaborate and implement practicable and competitively viable action and
development options. Consequently, <strong>the</strong> equal consideration <strong>of</strong> economic, environmental and social
objectives must be projected at <strong>the</strong> company level and be transformed in management approaches.
Not only tangible, but in particular intangible resources such as expertise and pr<strong>of</strong>essional
competence or relations with stakeholders count to <strong>the</strong> critical success factors specific for enterprises.
A variety <strong>of</strong> sustainability management concepts point out <strong>the</strong> relevance <strong>of</strong> intangible resources but
appropriate assessment and management, approaches which reveal <strong>the</strong> contribution <strong>of</strong> IC are not or
only very limited provided. Therefore <strong>the</strong> question arises how such intangible resources can be
measured and communicated as well as managed systematically considering <strong>the</strong> background <strong>of</strong> <strong>the</strong>
vision <strong>of</strong> sustainable development? To answer <strong>the</strong>se questions just insufficiently suitable concepts are
available up to now.
The objective <strong>of</strong> this research paper is to evaluate <strong>the</strong> integration potentials <strong>of</strong> intellectual capital and
sustainability management. Within this context two sub-goals will be examined in detail. A promising
starting point, for <strong>the</strong> integration <strong>of</strong> IC and sustainability management are intellectual capital
statements. Among o<strong>the</strong>r things intellectual capital statements provide methods for <strong>the</strong> development
and controlling <strong>of</strong> intangible resources in terms <strong>of</strong> an internal management and <strong>the</strong>y are promoted as
an instrument <strong>of</strong> an enhanced external reporting (Günter 2005).
(1) Requirements for an internal management system: If intellectual capital statements are developed
fur<strong>the</strong>r to a comprehensive internal management system <strong>of</strong> intangible assets, <strong>the</strong> question arises how
linkages to adjacent systems such as quality management, environmental management or
performance measurement system can be designed. These systems process partially identical
indicators but pursue different objectives. It is aim <strong>of</strong> this paper to examine and outline <strong>the</strong> integration
potentials <strong>of</strong> instruments as <strong>the</strong> “Sustainability Balanced Scorecard" (Schaltegger/Dyllick 2002) and
<strong>the</strong> "Intellectual Capital Statement – Made in Europe" (InCaS 2008).
(2) Integrated prospect for <strong>the</strong> external reporting: Companies see <strong>the</strong>mselves exposed to a growing
flow <strong>of</strong> required reports both internally as well as externally (e.g. IC-Statements, environmental
reports, corporate social responsibility reports or sustainability reports). Therefore regarding <strong>the</strong>
external reporting perspective a greater integration <strong>of</strong> various reports seems to be meaningful. An
integrated reporting format would not only reduce <strong>the</strong> internal preparation efforts but also meet <strong>the</strong>
standards as for example formulated in <strong>the</strong> EU directive "Accounts Modernization Directive” (EU
2003). These requirements are aimed to increase, through <strong>the</strong> reporting via non-financial indicators,
<strong>the</strong> transparency and self-regulation in <strong>the</strong> business reporting and thus to contribute to <strong>the</strong>
reinforcement <strong>of</strong> corporate integrity (Clausen et al. 2006). It is aim <strong>of</strong> <strong>the</strong> paper to conduct a
systematic review <strong>of</strong> existing guidelines and concepts in order to formulate requirements regarding an
integrated external reporting format and procedure. Different guidelines for sustainability reporting as
well as intellectual capital reporting will be considered within this work.
3. Existing concepts <strong>of</strong> sustainability management
3.1 Sustainability Balanced Scorecard
The Balanced Scorecard (BSC) is an instrument to <strong>the</strong> successful implementation <strong>of</strong> enterprise
strategies. A characteristic <strong>of</strong> <strong>the</strong> BSC is to consider systematically also non-monetary and s<strong>of</strong>t
success factors and to correlate <strong>the</strong>se to <strong>the</strong> long-term corporate success. The concept <strong>of</strong> <strong>the</strong> BSC
originated in <strong>the</strong> beginning <strong>of</strong> <strong>the</strong> 1990s as a new approach <strong>of</strong> <strong>the</strong> performance measurement by
enterprises from <strong>the</strong> criticism <strong>of</strong> <strong>the</strong> one-sided, short-term and past-oriented financial key figures. It
assumes that not only <strong>the</strong> invested capital and its efficient use are primarily crucial but also
increasingly s<strong>of</strong>t factors (e.g., employee's qualification, customer relations) for <strong>the</strong> long-term creation
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<strong>of</strong> competitive advantages and enterprise value (Kaplan/Norton 1997). Kaplan and Norton suggest a
performance measurement aligned on <strong>the</strong> enterprise strategy in four perspectives. The four
conventional perspectives are: finances, customers, internal processes as well as learning and
development. However, <strong>the</strong> authors point out that it is not a rigid precept but that <strong>the</strong> structure <strong>of</strong> <strong>the</strong>
BSC should be adapted to <strong>the</strong> individual strategy <strong>of</strong> an enterprise.
In this way <strong>the</strong> integration <strong>of</strong> environmental and social aspects in <strong>the</strong> general management system is
<strong>of</strong> interest – also as an instrument for <strong>the</strong> enterprise sustainability management. By now, different
<strong>the</strong>oretical and practical approaches are given to <strong>the</strong> formulation <strong>of</strong> a Sustainability Balanced
Scorecard (SBSC). The aim <strong>of</strong> SBSC is <strong>the</strong> integration <strong>of</strong> <strong>the</strong> three dimensions <strong>of</strong> <strong>the</strong> sustainability
concept – economy, environment and social – in <strong>the</strong> successful realization <strong>of</strong> strategies.
According to Bieker et al. 2001 <strong>the</strong> BSC seems to be appropriate for two reasons for an integrated
sustainability management: (1) <strong>the</strong> BSC is "balanced", i.e. it also <strong>of</strong>fers place for non-monetary and
s<strong>of</strong>t success factors. Environmental and social aspects are <strong>of</strong>ten qualitative and frequently affect nonmarket
mechanisms on enterprises and (2) <strong>the</strong> BSC shows causal connections (e.g. via strategy
maps) and environmental and social aspects are aimed at cause-effect chains on <strong>the</strong> long-term
corporate success.
The conventional BSC remains with its perspectives almost exclusively in <strong>the</strong> economic market
sphere. Exchange processes which run <strong>of</strong>f beyond <strong>the</strong> market mechanism hardly find any
consideration. Never<strong>the</strong>less, environmental and social aspects influence enterprises <strong>of</strong>ten about not
market exchange processes (e.g. legal or political pressure, demands <strong>of</strong> NGOs or neighbours, etc.).
With <strong>the</strong>se thoughts in mind, three possible starting points result to <strong>the</strong> formulation <strong>of</strong> a SBSC, which
integrates environmental and social aspects in <strong>the</strong> classical BSC (Figge et al. 2001). Firstly,
environmental and social aspects can be arranged in existing four perspectives <strong>of</strong> <strong>the</strong> BSC and be
subsumed, secondly <strong>the</strong> BSC can be extended by an additional perspective taking into account
environmental aspects and social aspects and thirdly a special environment and/or social scorecard
can be derived (figure 1).
Figure 1: Dimensions <strong>of</strong> <strong>the</strong> Sustainability Balanced Scorecard (referring to Figge et al. 2001)
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Kai Mertins and Ronald Orth
Never<strong>the</strong>less, <strong>the</strong> decision which integration variation is suitable for <strong>the</strong> different environmental and
social aspects cannot be made in <strong>the</strong> run-op <strong>of</strong> <strong>the</strong> formulation <strong>of</strong> a BSC. It ra<strong>the</strong>r depends on <strong>the</strong>
specific impact and strategic relevance <strong>of</strong> <strong>the</strong>se environmental and social aspects. Fur<strong>the</strong>r, three
variations do not exclude each o<strong>the</strong>r but can occur simultaneously with <strong>the</strong> formulation <strong>of</strong> a specific
SBSC.
3.2 Sustainability reporting
Many enterprises are already living <strong>the</strong> social responsibility by integrating ecological and social
standards into <strong>the</strong>ir management processes and value chains. Partially, <strong>the</strong>y document this
engagement in sustainability reports.
Sustainability reports prove environmental, social and economic engagements which enterprises are
making in dealing with internal and external resources. They satisfy <strong>the</strong> increased information needs
<strong>of</strong> stakeholders. Mostly, as motives and use <strong>of</strong> <strong>the</strong> sustainability reporting are mentioned <strong>the</strong>
improvement <strong>of</strong> <strong>the</strong> enterprise image and <strong>the</strong> credibility, <strong>the</strong> increase <strong>of</strong> transparency towards all
interest groups, creation <strong>of</strong> competitive advantages, encouragement <strong>of</strong> <strong>the</strong> enterprise culture and
support <strong>of</strong> <strong>the</strong> management (Orth/Grewatsch 2010).
Since more than ten years now <strong>the</strong> number <strong>of</strong> enterprises which report integrated about <strong>the</strong>
economic, ecological and social aspects <strong>of</strong> <strong>the</strong>ir corporate activities has been risen strongly –
although outgoing from a low quantitative level. Hence, sustainability reports are crucial for <strong>the</strong>
increase <strong>of</strong> international non-financial enterprise reporting. In 1997 worldwide 350 enterprises
published a non-financial report, in 2006 it already were more than 2000 enterprises (figure 2).
However, since 2003 this increase has slowed down and in 2006 it was declining for <strong>the</strong> first time.
Therefore, it can be stated that sustainability reports are increasingly <strong>the</strong> "driver" <strong>of</strong> <strong>the</strong> growth <strong>of</strong> nonfinancial
enterprise reports. Never<strong>the</strong>less, <strong>the</strong> decline <strong>of</strong> non-financial reports all toge<strong>the</strong>r points to <strong>the</strong>
fact that to <strong>the</strong> growth potential <strong>of</strong> sustainability reports are also set limits (BMU 2007a).
non-financial company report
sustainability reports
Figure 2: Non-financial reporting from 1997-2006 (BMU 2007a)
These numbers prove that <strong>the</strong> discussion about sustainability reports has outgrown <strong>the</strong> initial stage by
now. Not only for environmental reports but also for sustainability reports, criteria are already
available. Worldwide attention has found above all <strong>the</strong> Global Reporting Initiative (GRI). In 2000, for
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<strong>the</strong> first time <strong>the</strong> "Sustainability Reporting Guidelines" has been published as a result <strong>of</strong> a several
years' discussion between economy, governmental authorities and NGOs. In <strong>the</strong> end <strong>of</strong> 2006 <strong>the</strong>
meanwhile third version (so-called "G3 Guidelines") is available.
The GRI guideline is <strong>the</strong> leading frame directive for sustainability reporting. Worldwide <strong>the</strong> standards
and suggestions <strong>of</strong> <strong>the</strong> Global Reporting Initiative are recognized and applied. The objective <strong>of</strong> <strong>the</strong>
Global Reporting Initiative is <strong>the</strong> generation <strong>of</strong> <strong>the</strong> comparability <strong>of</strong> sustainability reports by means <strong>of</strong>
a standardised representation <strong>of</strong> <strong>the</strong> areas <strong>of</strong> economy, environment and society. Accordingly <strong>the</strong>
guideline is directed at all enterprises horizontally and vertically along <strong>the</strong> value chain regardless <strong>of</strong> its
size and branch. Also governments and NGOs orientate <strong>the</strong>mselves on <strong>the</strong>se standards. The GRI
framework considers existing international standards and general management principles (e.g.
guiding principles <strong>of</strong> <strong>the</strong> OECD, ISO 14000). 1
4. The IC perspective and <strong>the</strong> InCaS project
It is a common ground, that intellectual capital has become <strong>the</strong> critical success factor for enterprises
operating in a knowledge driven economy. Especially for <strong>European</strong> SMEs it is crucial to utilise and
manage <strong>the</strong>ir intangible resources efficiently in order to obtain <strong>the</strong>ir competitive advantage. Therefore,
<strong>the</strong> EU project “InCaS: Intellectual Capital Statement – Made in Europe” has been designed to assist
<strong>European</strong> SMEs in detecting, analysing, managing and reporting <strong>the</strong>ir IC in order to streng<strong>the</strong>n <strong>the</strong>ir
capability to respond to market needs and thus, increase <strong>the</strong>ir competitiveness (Mertins et al. 2009).
In order to bridge <strong>the</strong> gap between <strong>the</strong> requirements for internal management purposes and external
reporting <strong>the</strong> InCaS research team developed an instrument to assess, develop and report an
organisation’s IC systematically. At <strong>the</strong> same time, <strong>the</strong>re was a clear focus to develop a methodology
which is suitable for <strong>the</strong> application in SMEs, meaning to pay strong attention to a good cost-benefit
relationship <strong>of</strong> <strong>the</strong> management method.
With <strong>the</strong> development and recurring testing <strong>of</strong> <strong>the</strong> methodology, InCaS has harmonised <strong>the</strong>
intellectual capital statements on different levels. As <strong>the</strong> main project result <strong>the</strong> “<strong>European</strong> Guideline
for Intellectual Capital Statements (ICS)” has been published in November 2008 summarising <strong>the</strong>
InCaS methodology that has been developed and empirically tested in 25 SMEs from five <strong>European</strong>
countries (EU Commission 2008). The guideline describes <strong>the</strong> single steps <strong>of</strong> <strong>the</strong> ICS implementation
in detail with <strong>the</strong> aim to provide practical support for companies who want to implement an intellectual
capital statement. Templates and checklist supplements <strong>of</strong> <strong>the</strong> <strong>European</strong> ICS guideline and <strong>the</strong> ICS
toolbox provides technical support for <strong>the</strong> collection and analysis <strong>of</strong> <strong>the</strong> IC information.
5. Preliminary research results
5.1 Adopted structural model
Starting point for <strong>the</strong> integration is an adopted structure model based on <strong>the</strong> InCaS concept (figure 3).
The model is a result <strong>of</strong> a consolidation process <strong>of</strong> international approaches on IC management and
reporting. The structural model has been set up taking a systemic view on <strong>the</strong> organisation. It aims to
display all <strong>of</strong> <strong>the</strong> relevant organisational structures linking Intellectual capital to business processes
and business success and embedding <strong>the</strong> organisation in its business environment. The starting point
is <strong>the</strong> vision and strategy <strong>of</strong> <strong>the</strong> organisation with a view to <strong>the</strong> possibilities and risks encountered in
<strong>the</strong> business environment. Following <strong>the</strong> most frequently used structure to describe intangible
resources, <strong>the</strong> InCaS methodological framework divides intellectual capital into <strong>the</strong> three dimensions:
human, structural and relational capital. According to this model <strong>the</strong> interaction <strong>of</strong> business and
knowledge based processes, toge<strong>the</strong>r with <strong>the</strong> o<strong>the</strong>r tangible and financial resources, leads to
business success. 2 In this context Human Capital (HC) refers to <strong>the</strong> staff’s competencies, attitudes
and skills. It is owned by <strong>the</strong> employee and can be taken home or onto <strong>the</strong> next employer. Structural
Capital (SC) comprises all structures and processes needed by <strong>the</strong> employee in order to be
productive and innovative. It “consists <strong>of</strong> those intangible structures which remain with <strong>the</strong>
organisation when <strong>the</strong> employee leaves” (Edvinsson, Malone 1997). Relational Capital (RC) sums up
1 Beside <strong>the</strong> GRI guidelines o<strong>the</strong>r recommendations are available illustrating how sustainability reports can be prepared and
issued. These recommendations were mostly published in <strong>the</strong> form <strong>of</strong> guidelines (see chapter 5.2).
2 Based on <strong>the</strong> structural model an InCaS procedural model was developed. Whereas <strong>the</strong> structural model defines <strong>the</strong>
taxonomy and vocabulary as well as <strong>the</strong> basic interrelations between <strong>the</strong> single elements <strong>of</strong> intellectual capital, <strong>the</strong> procedural
model was developed in order to structure <strong>the</strong> process <strong>of</strong> implementing an ICS. It defines and describes <strong>the</strong> single ICS steps as
well as methodologies applied when going through <strong>the</strong> process <strong>of</strong> ICS implementation in structured detail (Mertins et al. 2009).
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<strong>the</strong> organisation’s relations to <strong>the</strong> stakeholders <strong>of</strong> <strong>the</strong> external environment. Based on empirical
results <strong>of</strong> <strong>the</strong> InCaS project a set <strong>of</strong> standard IC factors was developed as shown in table 1.
Table 1: Standard IC factors according to <strong>the</strong> InCaS approach
Human Capital Structural Capital Relational Capital
Pr<strong>of</strong>essional Competence
Social Competence
Employee Motivation
Leadership Ability
Internal Co-operation and
Knowledge Transfer
Management Instruments
IT and Explicit Knowledge
Product Innovation
Process Optimisation and
Innovation
Corporate Culture
Customer Relationships
Supplier Relationships
Public Relationships
Investor Relationships
Relationships to Co-operation
Partners
The development and use <strong>of</strong> intellectual capital provides an important lever for <strong>the</strong> implementation <strong>of</strong>
sustainability management. Thereby, intellectual capital has a comprehensive impact as it affects
equally <strong>the</strong> performance <strong>of</strong> all three dimensions <strong>of</strong> sustainability. Within in <strong>the</strong> adopted InCaS
structural model <strong>the</strong> sustainability dimensions are considered as aspects <strong>of</strong> <strong>the</strong> corporate
performance. This will refer to <strong>the</strong> so called “Triple Bottom Line” (TBL). For internal management and
external reporting <strong>the</strong> triple bottom line perspective means expanding <strong>the</strong> traditional framework taking
into account environmental as well as social performance in addition to economic/financial
performance.
Initial
situation
Vision
Organisational environment (Stakeholder perspective)
Organisation
corporate
Strategy
Measures
(Opportunities & Threats)
Intellectual capital
Human
capital
Structural
capital
Relational
capital
Business processes
Knowledge processes
O<strong>the</strong>r
resources
External
impact
Dimensions <strong>of</strong>
corporate
success:
-Economic
-Social
-Environmental
Figure 3: Adopted ICS structural model – including <strong>the</strong> sustainability perspective
Triple
Bottom
Line
A fur<strong>the</strong>r step <strong>of</strong> integration can be seen in a harmonised set <strong>of</strong> indicators. The concept <strong>of</strong> <strong>the</strong>
Sustainability Balanced Scorecard provides indicators for <strong>the</strong> measurement <strong>of</strong> triple bottom line
results. Additionally specific indicators for sustainability reporting are highlighted by various guidelines
as described in chapter 5.2 <strong>of</strong> this paper. At <strong>the</strong> same time <strong>the</strong> standardised process and structure <strong>of</strong>
<strong>the</strong> ICS report proposed by InCaS supports <strong>the</strong> communication <strong>of</strong> IC to external stakeholders as well.
If some basic quality requirements outlined in <strong>the</strong> InCaS guideline are met, <strong>the</strong> method can also serve
as a basis for comparability between different organisations. Table 2 shows examples for indicators
proposed by <strong>the</strong> guideline.
Table 2: Selected IC factors and corresponding indicators
Pr<strong>of</strong>essional competence (HC) Internal Co-operation and
Knowledge Transfer (SC)
Number <strong>of</strong> employees Number <strong>of</strong> internal reconciliation
Employees with university
meetings
degree
Number <strong>of</strong> collaborative projects
Employees with pr<strong>of</strong>essional Succession regulations for CEO
education
Succession regulations for o<strong>the</strong>r
Apprentices
Days for vocational training
top executives
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Customer Relationships (RC)
Total numbers <strong>of</strong> customers
Number <strong>of</strong> recorded customers
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Kai Mertins and Ronald Orth
5.2 Sustainability reporting – requirements and standards for external reporting
Especially in <strong>the</strong> field <strong>of</strong> sustainability reporting different guidelines and standards are available. There
is no doubt that <strong>the</strong> G3-Guidelines published by GRI provide <strong>the</strong> most elaborated and detailed
framework. However especially for SMEs it is hard to adopt all proposed criteria <strong>of</strong> <strong>the</strong> G3-Guideline.
Therefore different initiatives were started in order to “translate” ideas and procedures proposed by
GRI into appropriate approaches for SME.
In a comprehensive literature search national as well as international guidelines for sustainability
reporting were determined and evaluated. The following criteria were defined and applied for <strong>the</strong>
comparison <strong>of</strong> <strong>the</strong> different guidelines:
1. Stakeholder Orientation: Which target groups (stakeholders) are named as an addressee <strong>of</strong> <strong>the</strong>
sustainability report?
2. Structure <strong>of</strong> report: Which recommendations are made with regard to <strong>the</strong> structure and content
<strong>of</strong> sustainability reports?
3. Indicators: Are indicators mentioned resp. recommended to <strong>the</strong> measurement <strong>of</strong> sustainability?
4. Reporting Principles: Which requirements for <strong>the</strong> increase <strong>of</strong> quality and credibility to
sustainability reports are mentioned and described in <strong>the</strong> guide?
The examined guidelines by a majority address all organisations regardless <strong>of</strong> size and branch as for
example <strong>the</strong> GRI and <strong>the</strong> WBCSD guideline. Therefore, implicitly <strong>the</strong>y are also suitable for SMEs.
Explicitly SMEs are addressed in <strong>the</strong> guidelines <strong>of</strong> <strong>the</strong> IÖW and <strong>the</strong> BMU. These have adapted its
action recommendations especially to <strong>the</strong> needs and aims <strong>of</strong> SMEs. An overview regarding <strong>the</strong>
selected guidelines for <strong>the</strong> content analysis is shown in table 3.
Table 3: Guidelines to sustainability reporting
Editor 3 Title
BMU (2007b) EMAS - From <strong>the</strong> environmental statement to <strong>the</strong> sustainability report
GRI (2006) G3 - Guides to Sustainability Reporting
IFEU (2002) Future oriented business – A guide for sustainability reporting <strong>of</strong> enterprises
IÖW (2001) The sustainability report – A guide to <strong>the</strong> practice <strong>of</strong> reliable communication for
sustainable enterprises
ÖIN (2003) Reporting about Sustainability – 7 Steps to <strong>the</strong> sustainability report
WBCSD (2003) Sustainable development reporting – Striking <strong>the</strong> Balance
Results
Ad 1 Stakeholder Orientation
Every enterprise is embedded in a social-economic context. Internal and external forces have an
effect on <strong>the</strong> business environment equally. Thereby, stakeholders receive a special meaning. They
are <strong>the</strong> claim groups which are affected by <strong>the</strong> activities, products and services <strong>of</strong> <strong>the</strong> enterprise in
any manner and vice versa have effect on <strong>the</strong> enterprise at <strong>the</strong> strategy implementation and
achievement <strong>of</strong> objectives. Stakeholders can appear in <strong>the</strong> form <strong>of</strong> natural persons or legal entities
and <strong>the</strong>y differ by specfic ethical, social and economic interests.
In nearly every guideline <strong>the</strong> most important stakeholder groups are illustrated. Mostly <strong>the</strong>y are
divided in direct and indirect, internal and external or market or not market stakeholder. A particularly
detailed listing <strong>of</strong> all available stakeholder types with <strong>the</strong> differentiation in important and potential
interest groups is deposited in <strong>the</strong> EMAS-guide. Also <strong>the</strong> ÖIN guide covers almost <strong>the</strong> whole
spectrum. Therefore, <strong>the</strong> spectrum <strong>of</strong> stakeholders ranges to employee, owner, suppliers, sponsors,
business partners, customers, final consumers, and competitors about authorities, state, politics,
environmental and consumer protection associations, NGOs, trade unions, media up to potential
employees, nature, science and research. A representation going about <strong>the</strong> simply enumeration is
found in <strong>the</strong> GRI guide. Definition, meaning, understanding and inclusion <strong>of</strong> stakeholders are
displayed here basically.
3 List <strong>of</strong> abbreviations: (1) BMU: Bundesministerium für Umwelt; (2) GRI: Global Reporting Initiative, (3) Ifeu:
Institut für Energie- und Umweltforschung, (4) IÖW: Institut für ökologische Wirtschaftsforschung, (5) ÖIN:
Österreichisches Institut für Nachhaltigkeit, (6) WBCSD: World Business Council for Sustainable Development
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A comprehensive structure is important in order to guarantee <strong>the</strong> clarity <strong>of</strong> <strong>the</strong> sustainablity report.
Defining <strong>the</strong> structure is <strong>the</strong> central step in planning <strong>the</strong> report. The majority <strong>of</strong> <strong>the</strong> examined
guidelines contain no concrete structure recommendation. Only <strong>the</strong> essential components <strong>of</strong> a
sustainability report are <strong>of</strong>ten mentioned as with <strong>the</strong> guidelines <strong>of</strong> IÖW, ÖIN, GRI and BMU. All
guidelines have in common <strong>the</strong> following structural elements:
Prologue <strong>of</strong> <strong>the</strong> management
Pr<strong>of</strong>ile <strong>of</strong> <strong>the</strong> enterprise and <strong>the</strong> operating activities
Visions and strategies
Corporate structure, corporate policy and management systems
Sustainability policy
Indicators to describe and measure <strong>the</strong> sustainability performance
Ad 3 Indicators
Indicators are measurement parameters which display quantifiable circumstances in compressed
form. They are important for sustainability reporting because, indicators have a documentation and
performance control function. In this context <strong>the</strong> indicator protocol <strong>of</strong> economic, environmental and
social perspective developed by <strong>the</strong> GRI is indicative. All toge<strong>the</strong>r it comprises 79 key figures.
Primarily it is referred to this indicator list by <strong>the</strong> ifeu, EMAS and ÖIN guideline. The WBCSD and <strong>the</strong>
IÖW guideline have no concrete catalogues <strong>of</strong> key figures but <strong>the</strong>y provide general recommendations
and suggestions for indicators.
A sustainability report needs essential key figures in order to be trustworthy. However, <strong>the</strong> focus
should stronger lie on <strong>the</strong> qualitative reporting than on <strong>the</strong> quantitative as primarily sustainability
involves a s<strong>of</strong>t subject. Hereby, indicators serve as a test criterion. Fur<strong>the</strong>rmore <strong>the</strong> application <strong>of</strong> <strong>the</strong>
indicators proposed by <strong>the</strong> GRI guideline is hard to use for SMEs. O<strong>the</strong>r sources could be more
useful here. The VDI-Guidance 4070 “Sustainable management in small and medium-sized
enterprises - Guidance notes for sustainable management” (2006) for instance provides an indicators
list tailored to SME needs. A distinction between recommended, additional and complementary
indicators is made. Table 4 provides an overview on <strong>the</strong> recommended indicators according to VDI
4070.
Table 4: Recommended Indicators according to <strong>the</strong> VDI 4070 directive
Economic performance indicators Environmental performance
indicators
Operating result
Equity-to-assets ratio
Return on equity
Return on borrowed capital
Return on Investment (ROI)
Ad 4 Reporting Principles
Raw material use
Energy use Differentiation
Water use
Waste water rate
Emissions to air
Emissions to water
Wastes
Social performance
indicators
Number <strong>of</strong> employees
Percentage <strong>of</strong> trainees
Working days lost through sickness
absence
Working days lost through
accidents
Employee turnover
The objective <strong>of</strong> a report is to display an entire and understandable picture <strong>of</strong> certain circumstances.
A report must contain exact descriptions and give account to <strong>the</strong> situation. Besides <strong>the</strong> economic
situation, in corporate reports lies increasingly in <strong>the</strong> centre <strong>of</strong> interest also statements about <strong>the</strong>
future development <strong>of</strong> <strong>the</strong> enterprise. But due to missing legal duties and directives in Germany for
instance, doubts are growing about <strong>the</strong> credibility <strong>of</strong> sustainability reports in parallel. O<strong>the</strong>r EU
countries like Denmark, <strong>the</strong> Ne<strong>the</strong>rlands and France, have already introduced a report duty for
sustainability aspects in enterprises reports.
In order to raise <strong>the</strong> credibility <strong>of</strong> sustainability reports and to streng<strong>the</strong>n attention in <strong>the</strong> market,
almost all analyzed guidelines have put up <strong>the</strong>ir own catalogue <strong>of</strong> requirements to a report. In <strong>the</strong> GRI
guide <strong>the</strong> requirements are described especially in detail and are divided into report contents, quality
assurance and report borders. Internationally, <strong>the</strong>se demands are also looked as standards for <strong>the</strong>
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sustainability reporting. With <strong>the</strong> exception <strong>of</strong> <strong>the</strong> ÖIN guide which does not address at all <strong>the</strong> topic, all
guides come correspondently to <strong>the</strong> same basic report standards:
1. Truth: The statements must correspond to <strong>the</strong> facts and show an adequate appraisal. Positive
as well as negative circumstances should be illustrated in an adequate extent.
2. Essentiality: The report must contain all necessary and sufficient information.
3. Clarity: The representations and formulations must be unequivocal and clear.
Steadiness & comparability: The temporal and spatial borders <strong>of</strong> balancing must be documented.
Benchmark sources as well as elevation and assessment methods are to be published in <strong>the</strong>
report. Key figures must be used according to <strong>the</strong>ir general definition.
4. Public: The access to <strong>the</strong> report is to every customer freely and easily possibly.
Beside <strong>the</strong>se five requirement criteria, all guides recommend to incorporate <strong>the</strong> stakeholders actively
in <strong>the</strong> report creation process and to carry out, in addition, a voluntary external verification <strong>of</strong> <strong>the</strong>
sustainability report. With <strong>the</strong> integration <strong>of</strong> stakeholders an open, constructive dialogue is to be
sought.
6. Conclusion and outlook
This paper aims to provide an overview <strong>of</strong> <strong>the</strong> integration potentials <strong>of</strong> intellectual capital and
sustainability management. Therefore different concepts <strong>of</strong> both perspectives – in particular <strong>the</strong>
Sustainability Balanced Scorecard, different sustainability reporting guidelines and <strong>the</strong> InCaS
approach – have been examined. The preliminary results show that <strong>the</strong>re is especially integration
potential regarding <strong>the</strong> aspects <strong>of</strong> internal management and external reporting. An integrated
approach, fur<strong>the</strong>r conceptual development as well as pilot runs should focus on three aspects at least:
Firstly, a harmonized set <strong>of</strong> indicators for external reporting <strong>of</strong> <strong>the</strong> sustainability performance and <strong>the</strong>
intellectual capital <strong>of</strong> an organisation is appreciated. This can facilitate <strong>the</strong> communication towards
external stakeholders. Field reports and surveys have shown that complementing financial data with
information on intangibles can sharpen <strong>the</strong> view on SMEs’ creditworthiness (Will et al. 2007).
The ICS methodology developed and tested in <strong>the</strong> InCaS project has proved to be a valuable
instrument for <strong>the</strong> analysis and <strong>the</strong> development <strong>of</strong> Intellectual Capital. The implementation <strong>of</strong> an ICS
according to <strong>the</strong> InCaS approach is based on a procedural model. It defines and describes <strong>the</strong> single
ICS steps as well as methodologies applied when going through <strong>the</strong> process <strong>of</strong> ICS implementation in
structured detail. So far <strong>the</strong> procedure model does not explicitly consider aspects <strong>of</strong> <strong>the</strong> Triple Bottom
Line. Therefore a second future task is <strong>the</strong> development <strong>of</strong> an adapted procedural model
incorporating <strong>the</strong> aspect <strong>of</strong> sustainability.
Thirdly, experiences from GRI, ISO 9001 or <strong>the</strong> EFQM assessment clearly show <strong>the</strong> necessity <strong>of</strong>
validation from a third party in order to streng<strong>the</strong>n <strong>the</strong> general credibility <strong>of</strong> an external report.
Therefore a concept for an integrated quality audit should be drafted in <strong>the</strong> future.
References
Boston Consulting Group (2009): The Business <strong>of</strong> Sustainability. Imperative, Advantages, and Actions, [online]
http://www.bcg.com/documents/file29480.pdf.
Bieker, T.; Dyllick, T.; Gminder, C.-U; Hockerts, K. (2001): Towards a Sustainability Balanced Scorecard. Linking
Environmental and Social Sustainability to Business Strategy. <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> Business Strategy and
<strong>the</strong> Environment <strong>Conference</strong>, Leeds, p. 22–31.
BMU (2007a): Nachhaltigkeitsberichterstattung von Unternehmen. Status Quo Report, Berlin.
BMU (2007b): EMAS - Von der Umwelterklärung zum Nachhaltigkeitsbericht, Berlin.
Clausen, J.; Loew, T.; Kahlenborn, L. (2006): Lagebericht zur Lageberichterstattung, Berlin.
Edvinsson, L.; Malone (1997): Intellectual Capital. New York: Harper.
<strong>European</strong> Commission (2008) InCaS: Intellectual Capital Statement – Made in Europe. <strong>European</strong> ICS Guideline,
[online] www.incas-europe.org
<strong>European</strong> Union (2005): Vierte Richtlinie: Jahresabschluss von Kapitalgesellschaften, [online]
http://europa.eu/scadplus/leg/de/lvb/l26009.htm#AMENDINGACT.
Figge, F.; Hahn.; Schaltegger, S.; Wagner, M. (2001): Sustainability Balanced Scorecard. Wertorientiertes
Nachhaltigkeitsmanagement mit der Balanced Scorecard, Lüneburg.
GRI - Global Reporting Initiative (2006): Guides to Sustainability Reporting, Amterdam.
Gün<strong>the</strong>r, T. W (2005): Unternehmenssteuerung mit Wissensbilanzen. Möglichkeiten und Grenzen. In: ZfCM –
Zeitschrift für Controlling und Management, Nr. 3, Wiesbaden, Gabler Verlag.
535

Kai Mertins and Ronald Orth
Hauff, M.; Lingnau, V.; Zink, K.J. (2008): Nachhaltiges Wirtschaften. Integrierte Konzepte. 1. Aufl. Nomos,
Baden-Baden.
Ifeu (2002): Zukunftsfähiges Wirtschaften- Ein Leitfaden zur Nachhaltigkeitsberichterstattung von Unternehmen,
Stuttgart.
Ifo-Insitut (2002): Auswertung der Unternehmensbefragung für das Verbundprojekt „Ökoradar“, Endbericht,
Institut für Wirtschaftsforschung, Munich.
IÖW - Institut für ökologische Wirtschaftsforschung (2001): Der Nachhaltigkeitsbericht - Ein Leitfaden zur Praxis
glaubwürdiger Kommunikation für zukunftsfähige Unternehmen, Berlin.
Kaplan, R. S.; Norton, D. P. (1996): The Balanced Score Card. Translating Strategy into Action. Boston: Harvard
Business School Press.
Mertins, K.; Alwert, K.; Will, M. (2006): Measuring Intellectual Capital in <strong>European</strong> SME, <strong>Proceedings</strong> <strong>of</strong> I-KNOW
'06, 6th International <strong>Conference</strong> on Knowledge Management, Graz, Austria, pp 21-25.
Mertins, K.; Will, M.; Meyer, C. (2009): InCaS: Intellectual Capital Statement. Measuring Intellectual Capital in
<strong>European</strong> Small- and Medium sized Enterprises, <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> <strong>European</strong> <strong>Conference</strong> on Intellectual
Capital 2009.
Orth, R.; Grewatsch, S. (2010): Sustainability Reporting Guidelines. A comparative analysis. Internal working
paper, Fraunh<strong>of</strong>er IPK, Berlin.
ÖIN (2003): Reporting about Sustainability - 7 Steps to <strong>the</strong> Sustainability Report, Österreichisches Institut für
Nachhaltige Entwicklung, Wien.
Schaltegger, Dyllick (2002): Nachhaltig managen mit der Balanced Scorecard. Gabler Verlag, Wiesbaden.
VDI (2006): Sustainable management in small and medium-sized enterprises - Guidance notes for sustainable
management. Verein Deutscher Ingenieure, VDI Guidance 4070, Beuth Verlag, Berlin.
WBCSD (2003): Sustainable Development Reporting - Striking <strong>the</strong> Balance, World Business Council for
Sustainable Development, Genf.
Will M.; Alwert K.; Bornemann M.; Wuscher S. (2007): Auswirkungen eines Berichts über Intellektuelles Kapital
auf die Unternehmensbewertung. Studie des Fraunh<strong>of</strong>er IPK, Berlin.
536

The Investment in Human Capital Development in Public
Administration in Latvia
Maria Simonova
University <strong>of</strong> Latvia, Latvia
S_Marija@inbox.lv
Abstract: The Article examines and evaluates <strong>the</strong> investment in <strong>the</strong> development <strong>of</strong> employees <strong>of</strong> public
administration or <strong>of</strong> human capital in <strong>the</strong> conditions <strong>of</strong> economic downturn in Latvia, as well as determines <strong>the</strong>
subjects <strong>of</strong> investment and evaluates <strong>the</strong> role <strong>of</strong> each subject. At <strong>the</strong> end <strong>of</strong> <strong>the</strong> Article <strong>the</strong> conclusions about <strong>the</strong>
main shortcomings in this sphere are given and solutions are <strong>of</strong>fered. The research is based on <strong>the</strong> analysis <strong>of</strong>
existent (secondary) researches and on <strong>the</strong> monographic method.
Keywords: human capital, project, public administration, human capital development, investment in human
capital
1. Introduction
The main resource <strong>of</strong> <strong>the</strong> public administration institutions as intellectual organisations is <strong>the</strong>
personnel or human capital, whose knowledge, skills, abilities and attitudes, as well as motivation and
loyalty, is a crucial factor for efficient operation <strong>of</strong> <strong>the</strong> public administration.
Upon deterioration <strong>of</strong> <strong>the</strong> economic situation in Latvia, in public administration several measures have
been carried out by a gradual abolishing <strong>of</strong> various social guarantees, thus diminishing <strong>the</strong> differences
between <strong>the</strong> civil servants and employees, and <strong>the</strong> public service has lost <strong>the</strong> “priority” status granted
in its initial formation stage: management contracts, bonuses, material incentives have been annulled,
types <strong>of</strong> additional payment have been limited, personnel assessment system has been altered and
<strong>the</strong>re exist o<strong>the</strong>r restrictions, which adversely affect <strong>the</strong> motivation <strong>of</strong> employees to increase <strong>the</strong>ir
work efficiency. Thus, in conditions <strong>of</strong> economic downturn it is particularly important to find a solution
how to prevent <strong>the</strong> drain to foreign countries or to <strong>the</strong> private sector <strong>of</strong> civil servants and employees
who have gained experience in public administration. One <strong>of</strong> such solutions might be increasing <strong>the</strong>
level <strong>of</strong> employee motivation with <strong>the</strong> help <strong>of</strong> investment in human capital development at institutional
level.
Human capital development means ensuring to <strong>the</strong> employees <strong>the</strong> possibility <strong>of</strong> learning and career
progress, by planning, organising and evaluating it in appropriate manner. According to P. Taylor, <strong>the</strong>
personnel training or development <strong>of</strong> human capital (human resources) development is any
systematic process used by an organisation for perfection <strong>of</strong> knowledge <strong>of</strong> <strong>the</strong> employees or change
<strong>of</strong> <strong>the</strong>ir behaviour or tendencies to increase <strong>the</strong> contribution into achievement <strong>of</strong> <strong>the</strong> organisation’s
goals.
In order to enhance <strong>the</strong> satisfaction level <strong>of</strong> employees with <strong>the</strong> work and <strong>the</strong>ir loyalty, certain actions
should be made to help replace <strong>the</strong> outdated pattern <strong>of</strong> awareness <strong>of</strong> one’s pr<strong>of</strong>essional growth by a
new one, which would be oriented not to <strong>the</strong> repetition <strong>of</strong> ano<strong>the</strong>r employee’s path, but to acquiring <strong>of</strong>
unrepeatable pr<strong>of</strong>essional experience, going through <strong>the</strong> cyclic path <strong>of</strong> career development within <strong>the</strong>
organisation or outside it ( Dubra 2004).
Consequently, <strong>the</strong> objective <strong>of</strong> <strong>the</strong> Article is to evaluate <strong>the</strong> opportunities <strong>of</strong> investment in human
capital development in public administration in Latvia. The tasks to be performed for achievement <strong>of</strong>
<strong>the</strong> objective are: to explore <strong>the</strong>ories concerning <strong>the</strong> human capital and promotion <strong>of</strong> human capital
development (investment in human capital), to examine <strong>the</strong> obstacles to human capital development
in public administration, to analyse <strong>the</strong> results and propose solutions.
2. Essence <strong>of</strong> <strong>the</strong>ories on human capital development
In <strong>the</strong> recent years <strong>the</strong>re exists a viewpoint that <strong>the</strong> pr<strong>of</strong>itability <strong>of</strong> development in a contemporary
state to a large extent depends on <strong>the</strong> amount <strong>of</strong> money which it invests in its people. Without this
investment <strong>the</strong> state cannot ensure its gradual development. Thus, in America, according to some
calculations, <strong>the</strong> portion <strong>of</strong> investment in human capital is bigger than 15% <strong>of</strong> <strong>the</strong> GDP, which
exceeds <strong>the</strong> total sum <strong>of</strong> investment in private capital, factories, equipment etc.
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Maria Simonova
“Concept <strong>of</strong> human capital” studies <strong>the</strong> relationship between <strong>the</strong> investment in people, human capital
accrual and <strong>the</strong> benefits gained by <strong>the</strong> society from this investment. There are very different attitudes
among today’s economists towards <strong>the</strong> notion “human capital”, but all <strong>of</strong> <strong>the</strong>m agree that <strong>the</strong> human
capital is <strong>the</strong> principal driving force in <strong>the</strong> society and that also <strong>the</strong> state, not only <strong>the</strong> individual, must
pay special attention to <strong>the</strong> formation <strong>of</strong> human capital (Dobrinin 1999).
Human capital is such a totality <strong>of</strong> human capabilities and skills on which <strong>the</strong> potential <strong>of</strong> his/her
economic and social activity is dependent. The notion <strong>of</strong> human capital is mainly related to <strong>the</strong>
economic behaviour <strong>of</strong> individuals, especially to <strong>the</strong> manner how <strong>the</strong> knowledge and skills
accumulated by <strong>the</strong>m increase <strong>the</strong>ir productivity and income, thus increasing also <strong>the</strong> productivity and
income <strong>of</strong> <strong>the</strong> entire society. By a purposeful investment <strong>of</strong> efforts and finances in education and
skills, <strong>the</strong> society can obtain <strong>the</strong> desirable economic return – both on <strong>the</strong> level <strong>of</strong> individuals, and
community (Коrchagin 2004).
Gary Becker, one <strong>of</strong> <strong>the</strong> founders <strong>of</strong> <strong>the</strong> concept <strong>of</strong> human capital, characterises it in such a
way:”New technological discoveries cannot give benefit to <strong>the</strong> countries if in <strong>the</strong>se countries <strong>the</strong>re are
few qualified employees who would know how to use <strong>the</strong>m. The economic growth is very dependent
on <strong>the</strong> synergy between new knowledge and human capital. Therefore <strong>the</strong> increase in education and
training has followed after <strong>the</strong> progress <strong>of</strong> technological knowledge in all countries that have achieved
a significant economic growth” (Becker 1983).
Investment in human capital is any action that increases qualification level and skills, thus raising <strong>the</strong>
work productivity. Investment in human capital comprises <strong>the</strong> costs for healthcare, acquisition <strong>of</strong>
special and general education, expenses related to search <strong>of</strong> work, acquisition <strong>of</strong> pr<strong>of</strong>essional skills in
production, migration, upbringing <strong>of</strong> children etc. (Schultz 1971).
One can separate <strong>the</strong> following sources <strong>of</strong> human resources investment: <strong>the</strong> state, non-governmental
organisations, enterprises, international foundations and organisations. Each <strong>of</strong> <strong>the</strong> above-said
sources can be a subject <strong>of</strong> human capital investment. Nowadays <strong>the</strong> state’s role in this domain is
quite large (Dobrinin 1999).
Investment in education is very important, because <strong>the</strong> human capital determines both <strong>the</strong> work
productivity and capacity <strong>of</strong> <strong>the</strong> state to produce new technologies and to use <strong>the</strong> existent ones. In
contemporary conditions <strong>the</strong> competitive ability <strong>of</strong> an economy and its modernisation is determined
within <strong>the</strong> state and is implemented by <strong>the</strong> human resources. They are persons with education and
high level <strong>of</strong> qualification, whose pr<strong>of</strong>essional experience is determined by <strong>the</strong> possibilities and limits
<strong>of</strong> necessary changes. Thus, one <strong>of</strong> <strong>the</strong> basic tasks for creation <strong>of</strong> efficient and competitive structure
<strong>of</strong> industries in <strong>the</strong> long-term economic strategy <strong>of</strong> Latvia is <strong>the</strong> human capital development (Latvia.
Report on Nation’s Development 2007).
One <strong>of</strong> <strong>the</strong> priorities in Latvia’s development is <strong>the</strong> use <strong>of</strong> human resources in our state and
evaluation <strong>of</strong> <strong>the</strong>ir development prospects. According to I. Macconnell and S. Brue, “Expenses can be
regarded as investment because <strong>the</strong>y are realised upon reckoning that <strong>the</strong>se expenses will be
compensated several times by <strong>the</strong> increase <strong>of</strong> pr<strong>of</strong>it in future” (Мacconnell 1992).
Russian scientist Y. Korchagin divided <strong>the</strong> human capital in two groups: negative and positive human
capital.
Positive human capital is <strong>the</strong> human capital, which ensures a positive return on <strong>the</strong> investment during
<strong>the</strong> development process: rise in living standards <strong>of</strong> <strong>the</strong> society, growth <strong>of</strong> innovation and institutional
potential, development <strong>of</strong> education system, augment <strong>of</strong> knowledge, growth <strong>of</strong> science, improvement
<strong>of</strong> human health, rise in quality and accessibility <strong>of</strong> information. Negative human capital is <strong>the</strong> human
capital, which does not provide any positive return on investment during <strong>the</strong> development process and
improvement in life quality (Коrchagin 2004). Which trends will increase in <strong>the</strong> human capital
development – positive or negative ones? It depends on <strong>the</strong> attitude <strong>of</strong> all involved parties – <strong>the</strong> state,
institutions and population. If <strong>the</strong>ir behaviour is economically and socially active, <strong>the</strong>n <strong>the</strong> negative
trends will diminish. Nowadays <strong>the</strong> state’s role in this aspect is ra<strong>the</strong>r great. The principal objectives <strong>of</strong>
state investment in human capital are: raising <strong>of</strong> <strong>the</strong> education level and increase <strong>of</strong> intellectual capital
<strong>of</strong> <strong>the</strong> nation. Today <strong>the</strong> problem <strong>of</strong> sustainable development is very topical, also by including it into
538

Maria Simonova
<strong>the</strong> economic, social and ecological context. Thus, <strong>the</strong> return from such investment is expected at
least in three directions: economic, social and ecological sphere (Shuvalov 2008).
Participation <strong>of</strong> <strong>the</strong> state in determination <strong>of</strong> human capital development is very crucial. Taking into
account <strong>the</strong> consequences <strong>of</strong> <strong>the</strong> crisis, for <strong>the</strong> economy <strong>of</strong> Latvia it is required to rapidly change <strong>the</strong>
quality and structure <strong>of</strong> human capital. This situation cannot be solved without <strong>the</strong> help <strong>of</strong> <strong>the</strong> state,
but it is unrealistic to rely only on <strong>the</strong> state.
Functions <strong>of</strong> <strong>the</strong> state in human capital development are:
Drafting <strong>of</strong> <strong>the</strong> policy for human capital development at <strong>the</strong> national and regional level;
Implementation <strong>of</strong> corresponding legislation and administration process;
Involvement <strong>of</strong> NGOs and state-owned enterprises for creation <strong>of</strong> conditions favourable to <strong>the</strong>
human capital development;
Co-ordination <strong>of</strong> cooperation between <strong>the</strong> population, NGOs, state-owned enterprises and social
partners <strong>of</strong> unions and association that represent <strong>the</strong>ir interests.
Since Latvia’s accession to <strong>the</strong> <strong>European</strong> Union, <strong>the</strong> most important instruments in human resources
development are <strong>the</strong> structural funds <strong>of</strong> <strong>the</strong> EU.
3. Human capital development in public administration
In May <strong>of</strong> 2008 <strong>the</strong> basic statements regarding development <strong>of</strong> public administration for <strong>the</strong> next
planning period were confirmed – “Basic statements <strong>of</strong> public administration development policy for
2008 – 2013. Better management: quality and efficiency <strong>of</strong> administration.” A work group was formed
for <strong>the</strong>ir drafting, in which representatives <strong>of</strong> ministries and non-governmental organisations were
included. In accordance with what is said in <strong>the</strong>se basic statements, main directions <strong>of</strong> public
administration development policy are such:
1) Development <strong>of</strong> <strong>the</strong> system <strong>of</strong> policy planning and financial management;
2) Quality <strong>of</strong> administration;
3) Rule <strong>of</strong> law in administration’s operation;
4) Human resources development in public administration;
5) Participation and cooperation <strong>of</strong> <strong>the</strong> society in public administration.
But in <strong>the</strong> year <strong>of</strong> <strong>the</strong> economic crisis at <strong>the</strong> meeting <strong>of</strong> <strong>the</strong> Cabinet <strong>of</strong> Ministers on September 14,
2009 <strong>the</strong> objective was set: till 2013 <strong>the</strong> reduction <strong>of</strong> number <strong>of</strong> employees in <strong>the</strong> general
governmental sector is to be ensured, whereupon <strong>the</strong> number <strong>of</strong> employees in <strong>the</strong> public sector out <strong>of</strong>
<strong>the</strong> total number <strong>of</strong> employed persons does not exceed 8% <strong>of</strong> <strong>the</strong> population. In <strong>the</strong> first half-year <strong>of</strong>
2009 <strong>the</strong> actual number <strong>of</strong> employees in <strong>the</strong> general governmental sector (state and municipal budget
institutions and <strong>the</strong>ir capital companies) on average was 205,263, which is 9.1% <strong>of</strong> <strong>the</strong> total
population, consequently, substantial measures must be carried out to ensure in middle term <strong>the</strong>
reduction <strong>of</strong> number <strong>of</strong> employees to approximately 180 thousand (Table 1). This figure still might
change depending on <strong>the</strong> dynamics <strong>of</strong> population, because <strong>the</strong> set goal is to achieve a particular
specific weight <strong>of</strong> this indicator.
Table 1: Number <strong>of</strong> employees in <strong>the</strong> public sector
(Concept <strong>of</strong> Simplification <strong>of</strong> General and Specialised Public Service 2009)
The number <strong>of</strong> employees in public administration
Number <strong>of</strong> employees (on average % <strong>of</strong> <strong>the</strong> total population
in first half-year <strong>of</strong> 2009)
State budget institutions
(including civil servants and civil
servants <strong>of</strong> specialised public
service
76 804 (9154; 4864) 3.4
Municipal budget institutions 97 848 4.3
State-owned capital companies 17 760 0.8
Municipal capital companies 12 852 0.6
539

Maria Simonova
The concept regarding <strong>the</strong> simplification <strong>of</strong> <strong>the</strong> general and specialised public service sets <strong>the</strong>
following objective – a compact, numerically small, pr<strong>of</strong>essional and politically neutral civil service.
The solutions mentioned in <strong>the</strong> concept are <strong>of</strong>fered for achievement <strong>of</strong> <strong>the</strong> above-said objective, by
integrating it into <strong>the</strong> laws and regulations to be developed for implementation <strong>of</strong> a unified civil service
system. The adherence to <strong>the</strong> principle <strong>of</strong> political neutrality is especially to be promoted in <strong>the</strong> civil
service, thus ensuring that a civil servant <strong>of</strong> <strong>the</strong> public service in performance <strong>of</strong> his/her duties is
guided only by pr<strong>of</strong>essional criteria and in decision-making is not dependent on political influence
(Concept <strong>of</strong> Simplification <strong>of</strong> General and Specialised Public Service 2009).
Simplification <strong>of</strong> <strong>the</strong> public service system would enable to achieve <strong>the</strong> following goals:
It would substantially improve <strong>the</strong> administrating <strong>of</strong> <strong>the</strong> public service, determining unified
procedures in legal relationship <strong>of</strong> <strong>the</strong> work or service, including <strong>the</strong> saving <strong>of</strong> human resources in
various institutions that are engaged in formation, application and perfection <strong>of</strong> legal norms, as
well as making easier <strong>the</strong> operation <strong>of</strong> courts, because more frequently <strong>the</strong>re are such cases
when <strong>the</strong> decisions in event <strong>of</strong> imprecise interpretation <strong>of</strong> norms are appealed against at court <strong>of</strong>
justice;
It would make easier <strong>the</strong> processes <strong>of</strong> human resources management, for example, by
introduction <strong>of</strong> unified criteria for recruitment, assessment, payment <strong>of</strong> work, thus forwarding <strong>the</strong>
pr<strong>of</strong>essionalism <strong>of</strong> all employees in <strong>the</strong> public sector irrespective <strong>of</strong> <strong>the</strong> status <strong>of</strong> <strong>the</strong>ir post;
It would provide a unified and clear understanding on <strong>the</strong> legal status <strong>of</strong> <strong>the</strong> employees in <strong>the</strong>
public sector not only in <strong>the</strong> public administration, but also in <strong>the</strong> society, thus facilitating <strong>the</strong>
possibilities to analyse <strong>the</strong> reduction <strong>of</strong> number <strong>of</strong> employees in <strong>the</strong> general governmental sector,
ensuring achievement <strong>of</strong> <strong>the</strong> objective – 8% <strong>of</strong> <strong>the</strong> total population.
The civil service system <strong>of</strong> Latvia is not formed as a career-oriented civil service, where <strong>the</strong> civil
servant begins to work from position <strong>of</strong> a lower post and forms his/her career within this system, but
as a system <strong>of</strong> posts, which by an open competition enables him/her to occupy any post in <strong>the</strong> civil
service, if <strong>the</strong> person conforms to <strong>the</strong> requirements set for <strong>the</strong> relevant post, thus promoting mobility
and openness not only within <strong>the</strong> public administration but also in relation to <strong>the</strong> private sector. In <strong>the</strong>
civil service system <strong>of</strong> posts, a greater significance pertains to <strong>the</strong> work performance level <strong>of</strong> <strong>the</strong> civil
servant through definition <strong>of</strong> concrete targets and orientation to achievement <strong>of</strong> results, and <strong>the</strong>
remuneration is closely linked to <strong>the</strong> results <strong>of</strong> work and job duties to be performed, in contrast to <strong>the</strong>
situation in <strong>the</strong> career-oriented civil service, where <strong>the</strong> remuneration depends on <strong>the</strong> hierarchy <strong>of</strong>
posts, work experience and acquired education.
Upon <strong>the</strong> deterioration <strong>of</strong> <strong>the</strong> economic situation, in Latvia <strong>the</strong> following measures in public
administration were carried out:
Pay <strong>of</strong> work: management contracts, bonuses, material incentives have been abolished and types
<strong>of</strong> additional payment have been limited. On September 15, 2009 <strong>the</strong> Cabinet <strong>of</strong> Ministers has
approved <strong>the</strong> amendments in <strong>the</strong> Law <strong>of</strong> Public Service, stipulating <strong>the</strong> exclusion <strong>of</strong> articles that at
present regulate <strong>the</strong> compensation <strong>of</strong> travel expenses and <strong>of</strong> a part <strong>of</strong> tuition fee. The Ministry <strong>of</strong>
Finances has worked out <strong>the</strong> draft law “On Unified Remuneration System <strong>of</strong> Officials and
Employees <strong>of</strong> Public and Municipal Institutions”, where <strong>the</strong> principle already used in public
administration is streng<strong>the</strong>ned – equal pay for equal work, irrespective <strong>of</strong> <strong>the</strong> status <strong>of</strong> <strong>the</strong> post;
Evaluation <strong>of</strong> performance: results <strong>of</strong> activity <strong>of</strong> civil servants and employees are evaluated
according to one assessment system, setting equal competencies and thus streng<strong>the</strong>ning <strong>the</strong>
principle – results <strong>of</strong> activity are evaluated irrespective <strong>of</strong> <strong>the</strong> status <strong>of</strong> <strong>the</strong> post;
Unified pre-trial procedure for disputing <strong>of</strong> decisions for civil servants and employees, abolishing
<strong>the</strong> instance <strong>of</strong> pre-trial disputing (public service administration).
For <strong>the</strong> employees within <strong>the</strong> public administration <strong>the</strong>re is no special rotation mechanism, thus it
limits <strong>the</strong>ir pr<strong>of</strong>essional and career growth, because it is not possible to transfer employees form one
public institution to ano<strong>the</strong>r, and in case <strong>of</strong> necessity <strong>the</strong> employee must be dismissed from <strong>the</strong> post
and taken into employment anew at ano<strong>the</strong>r institution.
At present <strong>the</strong> Latvian School <strong>of</strong> Public Administration ensures <strong>the</strong> improvement <strong>of</strong> pr<strong>of</strong>essional skill
<strong>of</strong> civil servants. The fur<strong>the</strong>r education <strong>of</strong> o<strong>the</strong>r employees <strong>of</strong> public administration till now has not
been planned and implemented in a unified manner. There exists no unified system for evaluation to
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Maria Simonova
what degree <strong>the</strong> knowledge acquired at <strong>the</strong> training courses is used in practice and whe<strong>the</strong>r it
enhances <strong>the</strong> quality <strong>of</strong> pr<strong>of</strong>essional activity. In practice one can observe <strong>the</strong> necessity to improve <strong>the</strong>
cooperation <strong>of</strong> universities with <strong>the</strong> public administration institutions, ensuring <strong>the</strong> acquisition <strong>of</strong> initial
knowledge and skills required for <strong>the</strong> pr<strong>of</strong>essional activity <strong>of</strong> public administration under <strong>the</strong> curricula
<strong>of</strong> university studies, as well to use <strong>the</strong> library resources <strong>of</strong> public administration institutions for fur<strong>the</strong>r
education, improvement <strong>of</strong> pr<strong>of</strong>essional skill and increase <strong>of</strong> efficiency <strong>of</strong> employees <strong>of</strong> public
administration.
In conditions <strong>of</strong> an economic downturn, <strong>the</strong> most topical problem is <strong>the</strong> reduction <strong>of</strong> financing in <strong>the</strong>
sphere <strong>of</strong> human capital development in public administration, because in comparison with 2005
when in total more than 10 thousand civil servants participated in training at <strong>the</strong> School <strong>of</strong> Public
Administration with <strong>the</strong> available financing 115 500 LVL from <strong>the</strong> state budget, in 2010 this financing
has been stopped completely (Law “On <strong>the</strong> State Budget for 2010”).
Section 5.3 <strong>of</strong> <strong>the</strong> Law <strong>of</strong> 2010 “On <strong>the</strong> State Budget <strong>of</strong> Year 2010” says that <strong>the</strong> training <strong>of</strong> civil
servants from <strong>the</strong> subsidy finances <strong>of</strong> <strong>the</strong> state budget must be stopped and <strong>the</strong> functions <strong>of</strong> <strong>the</strong>
School <strong>of</strong> Public Administration must be reduced. Hiring <strong>of</strong> teaching staff for training <strong>of</strong> civil servants
for budget finances and in corresponding way <strong>the</strong> expenses <strong>of</strong> teaching staff remuneration. The
planned timetable <strong>of</strong> training pursuant to <strong>the</strong> order <strong>of</strong> training by <strong>the</strong> State Chancellery for 2008 –
2010 was annulled, agreement with teaching staff, planning <strong>of</strong> study premises, study material
preparation plan were suspended. The cooperation with regional training centres was interrupted
(Law “On <strong>the</strong> State Budget for 2010”).
Since accession <strong>of</strong> Latvia to <strong>the</strong> <strong>European</strong> Union, one <strong>of</strong> <strong>the</strong> most important instruments in human
resources development are <strong>the</strong> EU structural funds, because in <strong>the</strong> planning period 2007 – 2013 <strong>the</strong>
financing available for implementation <strong>of</strong> <strong>the</strong> activity “Streng<strong>the</strong>ning <strong>of</strong> Human Resources Capacity” is
12 848 702 euro (9 030 118 LVL), Within this program not only <strong>the</strong> human resources capacity not only
<strong>of</strong> <strong>the</strong> institutions that realise public power, but also <strong>of</strong> social partners and non-governmental
organisations, thus promoting <strong>the</strong> preparation <strong>of</strong> appropriate human resources for work in public
administration institutions and perfecting <strong>the</strong> human resources management system <strong>of</strong> public
administration, as well as improving <strong>the</strong> cooperation between non-governmental organisations, social
partners and public administration institutions. Within this planning period also o<strong>the</strong>r activities
supported by <strong>the</strong> structural funds are planned.
Thus, it is necessary to enlarge <strong>the</strong> knowledge <strong>of</strong> employees on <strong>the</strong> legislation and institutional
system <strong>of</strong> <strong>the</strong> <strong>European</strong> Union. Finances <strong>of</strong> <strong>the</strong> <strong>European</strong> Union funds can be used for improvement
<strong>of</strong> competency <strong>of</strong> <strong>the</strong> public administration employees engaged in administrating <strong>the</strong> EU funds.
Moreover, a system must be timely created to ensure <strong>the</strong> development <strong>of</strong> those skills and knowledge
that will be required for a successful presidency <strong>of</strong> Latvia in <strong>the</strong> <strong>European</strong> Union in 2015.
4. Conclusions
By summarising <strong>the</strong> results <strong>of</strong> <strong>the</strong> research, one can arrive at <strong>the</strong> following conclusions and
proposals:
In <strong>the</strong> conditions <strong>of</strong> economic downturn <strong>the</strong> state’s role in forwarding <strong>of</strong> human capital
development has substantially diminished;
In parallel to this, <strong>the</strong> financial support by <strong>the</strong> structural funds <strong>of</strong> <strong>the</strong> <strong>European</strong> Union significantly
increases;
Main obstacles in <strong>the</strong> domain <strong>of</strong> human capital development are determined by <strong>the</strong> laws and
regulations adopted during last two years on reduction <strong>of</strong> financing and most recent amendments
in <strong>the</strong> Civil Law;
Taking into account <strong>the</strong> availability <strong>of</strong> finances <strong>of</strong> structural funds in Latvia for solving <strong>the</strong>
problems <strong>of</strong> public administration, attention must be paid to <strong>the</strong> factor <strong>of</strong> human resources,
pr<strong>of</strong>essionalism and competence <strong>of</strong> personnel, and requirements must be set for project
managers, in such manner increasing <strong>the</strong> capacity <strong>of</strong> organisations.
References
Basic Statements <strong>of</strong> Development <strong>of</strong> Public Administration Policy for 2008-2014, (June 3, 2008) Order No. 305 <strong>of</strong>
Cabinet <strong>of</strong> Ministers, p. 39 (in Latvian).
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Maria Simonova
Becker, G. S. (1983) Human Capital: a Theoretical and Empirical Analysis with Special Reference to Education,
2 nd Edition. N.Y., p. 28.
Concept <strong>of</strong> Simplification <strong>of</strong> General and Specialised Public Service (2009) Riga (in Latvian).
Dobrinin, A.I., Dyatlov S.A., Cirenkova E.D. (1999) Human Capital in Transitive Economy: Formation, Evaluation,
Efficiency <strong>of</strong> Use, St. Petersburg: Nauka, p. 21 (in Russian).
Dubra V., Nyetunakhina J. (2004) “Contemporary Trends <strong>of</strong> Personnel Development”, Vadības zinātne, No. 674,
University <strong>of</strong> Latvia, p. 282 (in Latvian).
Коrchagin Y.Y. (2004) Human Capital and Development Processes at Macro- and Microlevels, Voronezh: CIRE,
p. 106 (in Russian).
Latvia. Report on Nation’s Development 2006/2007. Human Capital: My Gold Is My Nation? (2007) Riga: Institute
<strong>of</strong> Social and Political Studies, University <strong>of</strong> Latvia, pp. 10-19 (in Latvian).
Law “On <strong>the</strong> State Budget for 2010” (01.12.2009) (in Latvian).
Law “On <strong>the</strong> State Budget for 2005” (31.12.2004) (in Latvian).
Мacconnell K.R., Brue S.L. (1992) Principles, Problems and Policy <strong>of</strong> Economy, Vol. 2, Moscow: Respublika, p.
49 (in Russian).
Schultz, T. (1971) Investment in Human Capital, N.Y., pp. 34-35.
Shuvalov S., Efficiency <strong>of</strong> Investment in Human Capital in <strong>the</strong> Knowledge-based Economy, available:
http://www.turiba.lv/darba_tirgus_2008/pages/Shuvalov_ru.html (in Russian).
542

Summary on Intellectual Capital Value Added (VAIC) and
Calculated Intangible Value (CIV) all Over <strong>the</strong> World:
Lessons to be Learnt
Nellija Titova
University <strong>of</strong> Latvia, Riga, Latvia
nellija.titova@inbox.lv;
Abstract: Over <strong>the</strong> period 1959-1997 a diverse set <strong>of</strong> academic researchers and economists developed a new
view on business strategy that emphasized resource efficiency ra<strong>the</strong>r than <strong>the</strong> generally accepted competitive
forces. The researchers discovered <strong>the</strong> intellectual capital. In <strong>the</strong> late 1990s <strong>the</strong> problems encountered in trying
to put into practice <strong>the</strong> prevailing IC models and methodologies led to <strong>the</strong> development <strong>of</strong> new methodologies
and an alternative <strong>the</strong>oretical paradigm. Among <strong>the</strong> most popular concepts <strong>of</strong> that period were Value Added
Intellectual Capital (VAICTM) and Calculated Intangible Value (CIV). The first one was invented in 1993 by Pr<strong>of</strong>.
Dr. Ante Pulic, University pr<strong>of</strong>essor and businessmen, who started to investigate into <strong>the</strong> changes in current
economy and widely presented in <strong>the</strong> years 1998-2001. The latter was developed and popularized in <strong>the</strong> year
1997 by Thomas Stewart. Both represent so called group <strong>of</strong> <strong>the</strong> applications <strong>of</strong> <strong>the</strong> models and methods based
on <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> monetary values <strong>of</strong> <strong>the</strong> companies. CIV measures <strong>the</strong> monetary value <strong>of</strong> IC or IC stock,
VAICTM describes how a company‟s IC adds value to <strong>the</strong> company. Since 1998 results <strong>of</strong> <strong>the</strong> application <strong>of</strong> <strong>the</strong>
models and fur<strong>the</strong>r analysis <strong>of</strong> <strong>the</strong> results have been presented at numerous scientific conferences throughout
<strong>the</strong> world. Indeed, <strong>the</strong> researches using <strong>the</strong> same methods did not get identical results, though analyzing <strong>the</strong>
same industry and testing <strong>the</strong> same hypo<strong>the</strong>sis. Developing strategic planning system, in <strong>the</strong> beginning <strong>of</strong> <strong>the</strong>
21st century appeared <strong>the</strong> idea on testing <strong>the</strong> interaction <strong>of</strong> <strong>the</strong> Standard financial indicators and Intellectual
capital performance indicators. Analyzing <strong>the</strong> impact <strong>of</strong> <strong>the</strong> Intellectual capital on enterprise financial data in <strong>the</strong>
current period <strong>the</strong>re were several interactions discovered. The results were sometimes controversial; <strong>the</strong>refore
additional research is still needed. Fur<strong>the</strong>rmore <strong>the</strong>re is already one research published on <strong>the</strong> longitudinal
analysis <strong>of</strong> IC indicators and financial performance indicators. The author <strong>of</strong> <strong>the</strong> paper aims to make one <strong>of</strong> <strong>the</strong>
first attempts to make <strong>the</strong> extensive summary on application <strong>of</strong> CIV and VAIC in different countries, providing <strong>the</strong>
information on various aspects <strong>of</strong> <strong>the</strong> analysis and its interpretation and extracting <strong>the</strong> key findings. Summarizing
<strong>the</strong> results <strong>of</strong> <strong>the</strong> researches, <strong>the</strong> key finding is that some <strong>of</strong> <strong>the</strong> results seem to be <strong>the</strong> same for all <strong>the</strong> segments
<strong>of</strong> economies and countries analyzed, some seems to be controversial. The main question <strong>of</strong> <strong>the</strong> paper is what
lessons we can learn from <strong>the</strong> application <strong>of</strong> <strong>the</strong> models.
Keywords: intellectual capital, evaluation, intangible assets, calculated intangible value (CIV), value added
intellectual coefficient (VAICTM), human capital, structural capital and capital employed, financial performance
indicators
1. Introduction
In <strong>the</strong> 1995 <strong>the</strong> VAIC concept was developed by Pr<strong>of</strong>. Dr. Ante Pulic, pr<strong>of</strong>essor and businessmen.
His prime interest was <strong>the</strong> processes <strong>of</strong> value creation in contemporary economy and <strong>the</strong> role <strong>of</strong>
Intellectual capital (IC) in this context.
In <strong>the</strong> 1998 <strong>the</strong> VAIC concept and its application in business practice were <strong>of</strong>ficially presented to
academia and practitioners and in <strong>the</strong> year 1999 <strong>the</strong> first VAIC analysis <strong>of</strong> Croatian top 400
companies and its results were presented at round table organized by leading Croatian economic
magazine.
By now VAIC has been applied at all levels <strong>of</strong> business activity both at macro level - at national,
sector, regional and city level and micro level and <strong>the</strong> results <strong>of</strong> <strong>the</strong> application <strong>of</strong> <strong>the</strong> models have
been presented at numerous scientific conferences throughout <strong>the</strong> world. VAIC methodology is
receiving increasing research attention and applied use.
The CIV was developed and popularized in <strong>the</strong> year 1997 by Thomas Stewart but little or no empirical
research has been carried out related to CIV.
The author <strong>of</strong> <strong>the</strong> paper aims to make one <strong>of</strong> <strong>the</strong> first attempts to make <strong>the</strong> extensive summary on
application <strong>of</strong> CIV and VAIC in different countries, providing <strong>the</strong> information on various aspects <strong>of</strong> <strong>the</strong>
analysis and its interpretation and extracting <strong>the</strong> key findings. Summarizing <strong>the</strong> results <strong>of</strong> <strong>the</strong>
researches, <strong>the</strong> key finding is that some <strong>of</strong> <strong>the</strong> results seem to be <strong>the</strong> same for all <strong>the</strong> segments <strong>of</strong>
economies and countries analyzed, some seems to be controversial. The main question <strong>of</strong> <strong>the</strong> paper
is what lessons we can learn from <strong>the</strong> application <strong>of</strong> <strong>the</strong> models.
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2. The aim <strong>of</strong> applying <strong>the</strong> methods
Nellija Titova
According to <strong>the</strong> papers <strong>the</strong>re are certain reasons behind <strong>the</strong> decision to elaborate on Intellectual
capital evaluation techniques that could allow comparing and developing intellectual-type resources in
<strong>the</strong> certain industry or group <strong>of</strong> enterprises. The author would like to quote some <strong>of</strong> <strong>the</strong>m, i.e.:
„...Given <strong>the</strong> traditional measures continue to dominate it is important to determine <strong>the</strong>
extent to which such measures may intrinsically capture <strong>the</strong> contribution from IC
resources such as human resources, customer reputation and research and
development. This is <strong>of</strong> particular importance in emerging economies that have borrow
long held financial models from developed economies but are striving to streng<strong>the</strong>n <strong>the</strong>ir
IC base is an effort to increase economic development” (Anggreni T. 2008)
„...Although <strong>the</strong>re is a surplus <strong>of</strong> human capital in terms <strong>of</strong> absolute numbers, skilled and
pr<strong>of</strong>essional human capital are limited in relative terms. Therefore, efficiency analysis
becomes important to evaluate <strong>the</strong> performance <strong>of</strong> <strong>the</strong> key resources <strong>of</strong> <strong>the</strong> economy.
(Barathi G. 2007)
„... <strong>the</strong>re are no evaluation methods extensively tested and able to be applied to large
samples. .... Lastly, although in <strong>the</strong> last 10 years many things have been written and
researched about IC and its impact on <strong>the</strong> organizations’ performance, researches
aiming to quantify, broadly this impact, are not significant” (Ricieri. F. 2007)
„...Many <strong>of</strong> <strong>the</strong> measures are non-financial and thus not comparable between companies.
However, <strong>the</strong>re are also financial (i.e. monetary) measures that can be compared
between companies, for example, VAIC and CIV.” (Lonnqvist A. 2007)
Some <strong>of</strong> <strong>the</strong> research state that although <strong>the</strong> research was conducted in o<strong>the</strong>r countries it did not take
place in some o<strong>the</strong>r countries or sector and group <strong>of</strong> enterprises, thus stating <strong>the</strong> need to extend <strong>the</strong>
scope <strong>of</strong> <strong>the</strong> countries/sectors/enterprises‟ group under analysis.
Summarizing <strong>the</strong> purposes mentioned <strong>the</strong>se are:
To investigate <strong>the</strong> association between <strong>the</strong> efficiency <strong>of</strong> value added by <strong>the</strong> major components <strong>of</strong>
a firm‟s resourse base (physical capital, human capital and structural capital) and traditional
dimensions <strong>of</strong> corporate performance and also to add to <strong>the</strong> literature on <strong>the</strong> determinants <strong>of</strong> IC
performance. In particular, UK authors make <strong>the</strong> attempt to test <strong>the</strong> <strong>the</strong>ories that investment in IT
systems, bank efficiency, barriers to entry and efficiency <strong>of</strong> investment in IC have impact on IC
performance;
To highlighting which industries outperformed or underperformed for <strong>the</strong> efficiency <strong>of</strong> value added
from <strong>the</strong> employment <strong>of</strong> key resources;
To evaluate IC performance <strong>of</strong> firms and to rank <strong>the</strong>m with high level <strong>of</strong> human capital efficiency
(HCE), capital employed efficiency (CEE) and structural capital efficiency (SCE).
The papers published contain information <strong>of</strong> <strong>the</strong> advantages and disadvantages <strong>of</strong> <strong>the</strong> application <strong>of</strong>
VAIC, very limited information on CIV and alternative models. Table 1 presents <strong>the</strong> summary on
comparison.
The target groups and situations when we can use <strong>the</strong> results are very diverse:
1) policymakers;
2) investors;
3) management <strong>of</strong> <strong>the</strong> companies;
4) <strong>the</strong> banking authorities;
5) when a company or a part <strong>of</strong> it is being purchased;
7) valuating individual intangible assets;
8) from a methodological/academic perspective;
9) Providing specific measurement method implemented in practice.
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Nellija Titova
Table 1: Comparison <strong>of</strong> VAIC and alternative IC measures
CIV and VAIC Alternative IC measures
standardized and consistent basis <strong>of</strong> measure, <strong>the</strong>reby,
better enabling <strong>the</strong> effective conduct <strong>of</strong> an international
comparative analysis using a large sample size across
various industrial sectors;
all data used is based on <strong>the</strong> audited information.
Therefore <strong>the</strong> calculations can be considered objective
and verifiable;
VAIC is straightforward technique. Ease <strong>of</strong> calculations
is a feature that has enhanced <strong>the</strong> universal acceptance
<strong>of</strong> many traditional measures <strong>of</strong> corporate performance
(such as ROA);
This method considers <strong>the</strong> expenditures with employees
shall not be treated merely as expenses, but as
investments.
CIV and VAIC can be easily applied by someone
external to <strong>the</strong> company without company‟s specific
(internal) information.
it can be used within <strong>the</strong> organization to measure <strong>the</strong>
intellectual performance over a period <strong>of</strong> time without
much change in <strong>the</strong> existing business setup.
BUT:
„-„use basic financial information in <strong>the</strong>ir composition;
„-„ for calculation <strong>of</strong> CIV you need average return on
assets in <strong>the</strong> industry, that sometimes is difficult to find;
„-„ its measure for SC may be incomplete.
utilize information associated with a select group
<strong>of</strong> firms. They only be calculated by internal
parties or rely upon sophisticated models and
analysis;
involve unique financial and non-financial
indicators that can be readily combined into a
single comprehensive measure, and/or;
are customized to fit <strong>the</strong> pr<strong>of</strong>ile <strong>of</strong> individual firms.
Consequently, <strong>the</strong> ability to apply alternative IC
measures consistently across a large and
diversified sample for comparative analysis is
diminished;
subjectitivity associated with <strong>the</strong>ir underlying
indicators and,
difficulties in verifying information used in
calculating indicators comprising o<strong>the</strong>r IC
measures.
And finally before starting with <strong>the</strong> analysis and proceeding <strong>the</strong>re are two quotes to mention:
„After two years <strong>of</strong> researches and tests with different methods and IC evaluation
indexes, this paper adopts CIV and ICE„ (Ricieri. F. 2007)
„Corporate performance is a term frequently used by various stakeholder groups,
scholars and policy makers alike. Whilst <strong>the</strong> common use <strong>of</strong> this phrase may imply a
shared understanding a search <strong>of</strong> a precise definition <strong>of</strong> corporate performance is highly
illusive” (Anggreni T. 2008)
3. The analysis
3.1 Calculation <strong>of</strong> VAIC
1. Capital Employed Efficiency (CEEi) - indicator <strong>of</strong> VA efficiency <strong>of</strong> capital employed for firm i.
Σ CEEi = VAi / CEi , where CE (capital employed) = total assets – current liabilities
2. Human Capital Efficiency (HCEi) - indicator <strong>of</strong> VA efficiency <strong>of</strong> human capital for firm i.
Σ HCEi = VAi / HCi, where HC (human capital) = total labor costs
3. Structural Capital Efficiency (SCEi) - indicator <strong>of</strong> VA efficiency <strong>of</strong> structural capital for firm i.
Σ SCEi = SCi / Vai, where SC (structural capital) = VA – HC
Where VA means value added.
As <strong>the</strong> equation already indicates, structural capital is dependent on <strong>the</strong> created VA and in reverse
proportion to HC. This means that <strong>the</strong> bigger <strong>the</strong> share <strong>of</strong> HC in <strong>the</strong> created VA, <strong>the</strong> smaller is <strong>the</strong>
share <strong>of</strong> SC. In some cases SC does not even have to occur, for instance, if VA is less than <strong>the</strong>
investments in HC. Because <strong>the</strong>y have to be brought into <strong>the</strong> same position towards VA, <strong>the</strong>
efficiency <strong>of</strong> HC and SC is calculated in a different manner. If SC were calculated in <strong>the</strong> same way as
in HC (VA/SC) an illogical result would be obtained, meaning that <strong>the</strong> efficiency <strong>of</strong> SC would rise with
<strong>the</strong> fall <strong>of</strong> efficiency <strong>of</strong> HC, which is impossible. Contrary to that, it is logical that <strong>the</strong> efficiency <strong>of</strong> both
HC and SC raises, as this increases <strong>the</strong> total efficiency <strong>of</strong> IC.
According to <strong>the</strong> VAIC TM <strong>the</strong> value added (VA) is <strong>the</strong> difference between total revenues (OUT) and
total expenses (IN) and represents <strong>the</strong> value that has been produced in <strong>the</strong> firm through <strong>the</strong> firm‟s
resources or capital. Prior research has defined VA by <strong>the</strong> following algebraic equation: Rev-B-Inv =
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Nellija Titova
W+I+DP+D+T+M+R (equation 7a – gross VA) or S-B+Inv-DP=W+I+DP+D+T+M+R (equation 7B –
net VA). Theoretical arguments have been forwarded supporting both approaches. Empirical research
indicates both methods have been used in practice (Anggreni T. 2008). The Japanese Ministry <strong>of</strong>
Finance uses ano<strong>the</strong>r way to define <strong>the</strong> value added <strong>of</strong> firms: salaries and wages + interest and
discounting + rental or leasing expenses for fixed and liquid assets + taxes and public charges + net
operating income (operating income-interest and discounting expenses). Japanese approach seems
to be ra<strong>the</strong>r suitable for a process or cost oriented (manufacturing firms) philosophy and less for a
market or value (trade and service sector) oriented valuation.
3.2 Calculation <strong>of</strong> CIV
1. Calculate <strong>the</strong> company‟s average pre-tax earnings for <strong>the</strong> latest three years. (a)
2. Calculate average year-end tangible assets <strong>of</strong> <strong>the</strong> company (b) for <strong>the</strong> latest three years (i.e. all
<strong>of</strong> <strong>the</strong> „Assets‟ from <strong>the</strong> financial statement except „Intangible Assets‟).
3. Divide <strong>the</strong> earnings by <strong>the</strong> tangible assets and you get <strong>the</strong> company‟s return on tangible assets
(ROA) (c): c = a/b
4. Calculate <strong>the</strong> average ROA for industry (alike <strong>the</strong> ROA for <strong>the</strong> company) for <strong>the</strong> latest three
years. (d). If and only if <strong>the</strong> return on tangible assets <strong>of</strong> <strong>the</strong> company is greater than <strong>the</strong> return on
tangible assets <strong>of</strong> <strong>the</strong> industry, c>d, executing <strong>the</strong> method can be continued.
5. Calculate <strong>the</strong> “excess return” by multiplying <strong>the</strong> industry ROA by <strong>the</strong> average year-end tangible
assets <strong>of</strong> <strong>the</strong> company. Subtract <strong>the</strong> result from <strong>the</strong> pre-tax earnings <strong>of</strong> <strong>the</strong> company. Multiply this
by <strong>the</strong> following clause: 1 less <strong>the</strong> three-year-average 3 income tax rate <strong>of</strong> <strong>the</strong> company:
Excess_return = (a-d*b)*(1-_average_income_tax)
6. Finally, divide <strong>the</strong> after-tax number by an appropriate percentage, e.g. <strong>the</strong> company‟s cost <strong>of</strong>
capital.
CIV = ((a-d*b)*(1-_average_income_tax))/ <strong>the</strong> company’s cost <strong>of</strong> capital
3.3 Data
Annex 1 presents <strong>the</strong> summary <strong>of</strong> <strong>the</strong> data obtained from <strong>the</strong> 23 researches worldwide on <strong>the</strong>
application <strong>of</strong> VAIC and CIV methods. It is important to mention that although <strong>the</strong> fiscal periods and
number <strong>of</strong> sectors/enterprises are different <strong>the</strong> results and especially <strong>the</strong> VAIC values allow a
justificatory benchmarking even as a snapshot.
3.4 Research hypo<strong>the</strong>sis
Annex 2 presents <strong>the</strong> <strong>the</strong>oretical framework for developing research hypo<strong>the</strong>ses <strong>of</strong> <strong>the</strong> studies
summarized, where:
Return on Assets (ROA) is an indicator <strong>of</strong> how pr<strong>of</strong>itable a company is relative to its total assets.
ROA reflects firms‟ efficiency in utilizing total assets, holding constant firms‟ financing policy. The
formula used by Chen et al (2005) is used to eliminate <strong>the</strong> tax effect for <strong>the</strong> calculation <strong>of</strong> ROA.
ROA = Pre-tax income / Total Assets
Return on equity (ROE) represents returns to shareholders <strong>of</strong> common stocks, and is generally
considered an important financial indicator for investors. (ROE) = pre - tax income / average
stockholders‟ equity.
The productivity level (P) is <strong>the</strong> turnover <strong>of</strong> assets <strong>of</strong> a company (ATO). It measures a firm's
efficiency at using its assets in generating sales or revenue. P = ATO = Sales Revenue/Book
Value <strong>of</strong> Total assets
Market-to-book value ratios <strong>of</strong> equity (MB) is ratio <strong>of</strong> total market capitalization (share price times
number <strong>of</strong> outstanding common shares) to book value <strong>of</strong> net assets <strong>of</strong> <strong>the</strong> firm;
Growth in revenues (GR) measures <strong>the</strong> changes in firms‟ revenues in this case, from year to year.
Increases in revenues usually signal firms‟ opportunities for growth. Growth in revenue is
measured by dividing firm‟s revenue from <strong>the</strong> latest financial report by <strong>the</strong> previous year‟s
revenue. This variable is used as a proxy measure <strong>of</strong> pr<strong>of</strong>itability. GR = ((Revenue t / Revenue t-
1)-1) x 100%;
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Employee productivity (EP) is a measure for <strong>the</strong> net value added per employee, reflecting
employees‟ productivity: (EP) = pre- tax income / number <strong>of</strong> employees;
Operating Cash Flow Ratio (OCF) is <strong>the</strong> net cash generated from operations. It is produced by
taking net income, adding back <strong>the</strong> amount <strong>of</strong> depreciation, and making adjustments to reflect
changes in <strong>the</strong> working capital accounts, i.e. receivables, payables, inventories and o<strong>the</strong>r current
accounts, on <strong>the</strong> balance sheet. Operating cash flow is debatably a better measure <strong>of</strong> a
business's pr<strong>of</strong>its than earnings because a company can show positive net income on <strong>the</strong> income
statement and still not be able to pay its liabilities. OCF = Total Operating Cash Flow/ Total
Assets;
Barriers to entry (BE): it can be argued that firms that are protected from competition in <strong>the</strong>ir
sector by heavy barriers to entry are less more likely to encourage and motivate <strong>the</strong>ir staff to
generate innovation and this situation might have a negative impact on <strong>the</strong> performance <strong>of</strong> <strong>the</strong>
staff (human capital). There are several ways <strong>of</strong> measuring obstacles to entry in <strong>the</strong> banking
literature, e.g. BE = ratio <strong>of</strong> fixed assets/ total assets;
The ratio <strong>of</strong> staff cost to total revenue for <strong>the</strong> bank i in year t will be used to represent <strong>the</strong>
efficiency <strong>of</strong> investment in human capital (SC);
Bank risk is measured as <strong>the</strong> ratio <strong>of</strong> intangible assets to total assets <strong>of</strong> banks i in year t (BR);
R&D expenditures (RD) and advertising expenditures (AD). Besides <strong>the</strong> three VA efficiency
indicators, we also include R&D and advertising expenditures to proxy for innovative and
relational capital.
RD = R&D expenditures / book value <strong>of</strong> common stocks
AD = Advertising expenses / book value <strong>of</strong> common stocks:
Special care was taken with inserting controlling variables for purposes <strong>of</strong> trying to isolate <strong>the</strong> IC
effect from o<strong>the</strong>r factors linked to tangible and financial assets <strong>of</strong> companies. (Ricieri. F. 2007),
(Anggreni T. 2008) (Size <strong>of</strong> <strong>the</strong> firm, Debt-to-equity ratio (leverage), ROE, and Industry Type).
4. The results
4.1 General common findings
There is significant positive relationship between IC and financial performance;
Pulic proposes <strong>the</strong> VAIC as an aggregate, standardized measure <strong>of</strong> corporate intellectual ability,
but empirical results indicate that <strong>the</strong> three components <strong>of</strong> VAIC have substantial higher
explanatory power for firm market value than does <strong>the</strong> aggregate measure <strong>of</strong> VAIC;
Results from <strong>the</strong> studies revealed significant differences in bank/enterprise ranking based on
efficiency and traditional accounting measures. For example, „Comparison between VAIC ranking
and shareholders‟ equity ranking again proves that mere higher equity does not connote a
healthier position <strong>of</strong> a bank in this competitive market; ra<strong>the</strong>r, it is <strong>the</strong> utilization <strong>of</strong> <strong>the</strong> fund that
has influential impact on <strong>the</strong> performance <strong>of</strong> <strong>the</strong> bank” (Mohhobot A. 2008);
4.2 General unique findings
Finnish research (Kujansivu, 2007) indicates that, for example, <strong>the</strong> IC efficiency (sum <strong>of</strong> Human
and Structural capital efficiencies) <strong>of</strong> companies representing electricity, gas and water supply is
mainly due to <strong>the</strong> efficient utilization <strong>of</strong> human capital employed. At <strong>the</strong> same time, <strong>the</strong> IC
efficiency <strong>of</strong> business services companies for example is mostly due to <strong>the</strong> structural capital
efficiency. O<strong>the</strong>r utilize both <strong>the</strong>ir IC-related resources almost equally;
The same research (Kujansivu, 2007) states that in many industries <strong>the</strong> total efficiency <strong>of</strong> value
creation from all resources employed is higher in small and medium-sized enterprises than that in
larger companies. Instead, in <strong>the</strong> chemical industry, <strong>the</strong> electricity, gas and water supply industry
and in <strong>the</strong> transportation, storage and telecommunication sector <strong>the</strong> efficiency is higher in large
companies;
Bangladesh (Mohhobot, 2008) and Indian (Barahti, 2007) group <strong>of</strong> researches have also
evaluated <strong>the</strong> efficiency <strong>of</strong> use <strong>of</strong> IC comparing foreign and domestic banks. The results are
controversial. Bangladesh domestic banks are more efficient than <strong>the</strong> foreign banks and are
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performing better. In India <strong>the</strong> value-added average <strong>of</strong> <strong>the</strong> State Bank group is 20 times that <strong>of</strong>
<strong>the</strong> foreign banks‟ average. However, this trend is reversed when observed in terms <strong>of</strong> <strong>the</strong> value
creation efficiency. The efficiency <strong>of</strong> utilization <strong>of</strong> <strong>the</strong>se resources is much higher on average in
foreign banks, especially in <strong>the</strong> case <strong>of</strong> Human Capital Efficiency. In <strong>the</strong> case <strong>of</strong> Capital Employed
Efficiency, <strong>the</strong> average figures <strong>of</strong> public sector banks are much higher, indicating a performance
that is better than foreign banks on this front. Indian researches explain it by <strong>the</strong> fact that to meet
<strong>the</strong> social obligations <strong>of</strong> employment generation for <strong>the</strong> Indian population, <strong>the</strong>se banks invested a
huge amount in Human Capital, which could not increase or contribute much to value creation
efficiency. High infrastructure costs, a huge work force, poor image, low efficiency, and poor
usage <strong>of</strong> technology can also be mentioned. Foreign banks in turn do not employ much HC, most
<strong>of</strong> <strong>the</strong>m have only corporate clients, very few branches, are highly technology intensive, perform
only specialized activities and <strong>of</strong>fer specific high-value customized products, have low penetration
in <strong>the</strong> market and insignificant investments.
4.3 The results <strong>of</strong> multiple regressions’ models
4.3.1 IC v.s. current financial performance
Annex 3 presents <strong>the</strong> Summary on <strong>the</strong> results <strong>of</strong> multiple regressions' models. Descriptions <strong>of</strong> <strong>the</strong>
variables can be found in part 2.4. All <strong>the</strong> results available to <strong>the</strong> author were summarized in one table
and classified into four groups:
Light green group – <strong>the</strong> results coincide in terms <strong>of</strong> significance (significant and non-significant)
and direction (positive or negative);
Dark green group – <strong>the</strong> results by countries are similar with majority <strong>of</strong> <strong>the</strong> data but with minor
differences by country;
Red group – results are controversial;
Grey group – not enough information, <strong>the</strong>re is only one research on this issue.
The findings <strong>of</strong> <strong>the</strong> first group prove that:
IC positively affects ROA, ROE and RG;
HCE positively affects VAIC and RG;
CEE positively affects MB.
The findings <strong>of</strong> <strong>the</strong> second group show that with certain degree <strong>of</strong> ambiguity:
SCE positively affects ROA, RG and MB;
CEE positively affects VAIC and ATO and RG;
Time have small positive influence on VAIC.
The third group shows results that are not unique but controversial:
The impact <strong>of</strong> HCE on ROA and ATO;
The impact <strong>of</strong> SCE on ATO;
The impact <strong>of</strong> <strong>the</strong> CEE on ROA and ROE.
Some <strong>of</strong> <strong>the</strong> findings prove that IC is more important than physical assets. Never<strong>the</strong>less <strong>the</strong> empirical
findings <strong>of</strong> African researches (Nazari 2008) suggest physical capital remains <strong>the</strong> most significant
underlying resource <strong>of</strong> corporate performance despite efforts to increase <strong>the</strong> nation‟s IC base. The
research may not be used fully used as it is based on one year data only. Brasizian paper (Ricieri
2007) argues that physical assets have only short term effect. „The increase <strong>of</strong> physical and financial
assets level ceteris paribus seem to reduce companies‟ performance, contrary to <strong>the</strong> business logic in
force in most organizations (Ricieri. F. 2007). Taiwanese, Japanese (Mavridis 2004) and Malaysian
(Goh 2005) results prove that SC and PC are dominating.
A remark that <strong>the</strong> author could not ignore putting <strong>the</strong> results toge<strong>the</strong>r on control variables: „... it is also
curious to note that <strong>the</strong> independent variable Cresc_Vendas (sales increase), an index highly valued
by managers and market analysts, seemed to be non-significant regarding variables ROE and ROS;
and in case <strong>of</strong> variable ROA, despite <strong>of</strong> being significant, its influence is much smaller than from o<strong>the</strong>r
evaluated variables” (Ricieri. F. 2007)
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Fourth group shows how many grey cells – unanswered questions we still have in preceding <strong>the</strong>
results <strong>of</strong> <strong>the</strong> analysis. For example, according to Taiwanese suggestion R&D and advertisement
expenditure may capture additional information on firms‟ innovative capital, an important component
<strong>of</strong> structural capital. The UK (El-Bannany 2008) paper has raised plenty <strong>of</strong> new issues analyzing
impact <strong>of</strong> different variables on VAIC.
4.3.2 IC vs future financial performance
Table 2 presents <strong>the</strong> summary <strong>of</strong> <strong>the</strong> results <strong>of</strong> multiple regressions' models. The information on <strong>the</strong>
impact is very limited still homogenous.
Table 2: The summary on <strong>the</strong> results <strong>of</strong> multiple regressions' models
VAIC S+(Ta),
S+(In)
ROA ROE GR EP OCF
S+(Ta), S+(In) S+(Ta), S+(In) S+(Ta), S+(In) S+(Ta),
S+(In)
CE S+ (Ta) S+ (Ta) S+ (Ta) S+ (Ta)
RD S+ (Ta) S+ (Ta) S+ (Ta)
The relationship between IC invested today and future performance is more significant than that
between IC and current performance. This means that it takes time to yield results from <strong>the</strong> efficiency
<strong>of</strong> intellectual capital. Interesting finding by Taiwanese researches „However, IC seems to have a
significant effect on RG on <strong>the</strong> lagged one year result but not on <strong>the</strong> lagged two years result. This
increase could be attributed to <strong>the</strong> fact that <strong>the</strong> effect <strong>of</strong> operating cash flow will take about two years„
CE for Taiwan is <strong>the</strong> most significant but explained by <strong>the</strong> fact that most Taiwan firms are
manufacturers, and thus <strong>the</strong> efficiency with which <strong>the</strong>y utilize capital assets is an important factor for
financial performance. The results for HC and SC are ambiguous.
4.4 Classification <strong>of</strong> VAIC
Unexpectedly <strong>the</strong> most difficult task appeared to be classification <strong>of</strong> VAIC and CIV performance
groups. In spite <strong>of</strong> vast variety <strong>of</strong> information on <strong>the</strong> calculations <strong>the</strong>re is no information on CIV and
lack <strong>of</strong> information on scale <strong>of</strong> evaluations for VAIC.
Table 3: Classification <strong>of</strong> VAIC
Country Top performers Good Common Bad performers Averages
performance performers
India >5 4-5 2,5-4

5. Conclusions and fur<strong>the</strong>r research
5.1 Conclusions
Nellija Titova
Summarizing <strong>the</strong> above, <strong>the</strong> main logic for using VAIC and CIV as tools for performance
measurement is as follows:
The results proved that <strong>the</strong>re are very good reasons to pay higher attention to intellectual
potential;
There are several facts about IC that could be expected to be proven worldwide;
VAIC has proved its suitability as a tool for <strong>the</strong> measurement <strong>of</strong> IC.
But:
There is no common system <strong>of</strong> analyzing <strong>the</strong> results obtained from VAIC calculation,
There are still blank spots to explore and discuss and <strong>the</strong>y are partly identified;
The results on applying CIV are very poor and do not prove CIV as a valuable and objective
instrument to use.
5.2 Fur<strong>the</strong>r research
Providing various insights that should be <strong>of</strong> interest <strong>of</strong> scholars, shareholders, policy makers and
o<strong>the</strong>r relevant parties, <strong>the</strong> finding from <strong>the</strong> present study indicate avenues for <strong>the</strong> future
investigations:
Future research can be undertaken to investigate associations studied in <strong>the</strong> present paper
across time;
Additional research should be conducted using <strong>the</strong> data from alternative groups <strong>of</strong> enterprises, for
example, firms from non-IC business sector;
More evidence is needed on <strong>the</strong> determinants <strong>of</strong> IC performance before any generalization <strong>of</strong> <strong>the</strong>
results can be made;
It is clear that <strong>the</strong>re are plenty <strong>of</strong> econometric techniques to be applied such as controlling
variables, fixed and random effects estimators, etc, and
There is a clear need for <strong>the</strong> most systemic approach to fur<strong>the</strong>r analysis <strong>of</strong> <strong>the</strong> results <strong>of</strong> <strong>the</strong> VAIC
calculations.
The research is financed by <strong>the</strong> ESF project „Support for <strong>the</strong> doctoral studies in <strong>the</strong> University <strong>of</strong>
Latvia”, Nr. 0009/0138/1DP/1.1.2.1.2/09/IPIA/VIAA/004
References
Barathi Kamat G. (2007), The IC performance <strong>of</strong> <strong>the</strong> Indian banking sector, Journal <strong>of</strong> Intellectual Capital;
Volume: 8; Issue: 1; 2007;
Chen Goh P. (2005), IC performance <strong>of</strong> commercial banks in Malaysia, Journal <strong>of</strong> Intellectual Capital; Volume: 6
Issue: 3;
El-Bannany M. (2008), A study <strong>of</strong> determinants <strong>of</strong> IC performance in banks: <strong>the</strong> UK case, Journal <strong>of</strong> Intellectual
Capital; Volume: 9 Issue: 3;
Firer S., S. Williams M. (?) „IC and Traditional Measures <strong>of</strong> Corporate Performance”, internet link;
Kujansivu P. and Lonnqvist A. (2007) Investigating <strong>the</strong> value and efficiency <strong>of</strong> intellectual capital, Journal <strong>of</strong>
Intellectual Capital; Volume: 8 Issue: 2;
Mavridis D.G. (2005 IC performance drivers in <strong>the</strong> Greek banking sector, Management Research News; Volume:
28 Issue: 5;
MavridisD.G. (2004), The IC performance <strong>of</strong> <strong>the</strong> Japanese banking sector”, Journal <strong>of</strong> Intellectual Capital;
Volume: 5 Issue: 1;
Mohhobot A., Khan H-U-Z., Fatima Z. K. (2008), IC reporting Practices: A study on selected Companies in
Bangladesh, Journal <strong>of</strong> Business Studies, Vol. XXIX, No.1, June 2008, http://ssrn.com/abstract=1332585;
Nazari J., Herremans J. (2008), Extended VAIC model: measuring intellectual capitals components,
www.emeraldinsight.com;
N.M. Muhamad, F. Isa, N. Ismail (2007), IC Efficiency Level <strong>of</strong> Malaysian Financial sector: panel data analysis,
www.emeraldinsight.com;
Razafindrambinina D., Anggreni T. (2008), Am empirical research on <strong>the</strong> Relationship between IC and corporate
financial performance on Indonesian listed companies, www.emeraldinsight.com;
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Nellija Titova
Ricieri. F., Basco C., Martin D. (2007), Intelectual capital and <strong>the</strong> creation <strong>of</strong> value in Brazilian companies,
http:/srrn.com/abstract=1081849;
Saengchan S. (2003), The role <strong>of</strong> IC in Creating Value in <strong>the</strong> banking sector, www.emerald.com;
2007, The performance Analysis <strong>of</strong> <strong>the</strong> Turkish banks through VAIC and MB/BV Ratio, www.turkishweekly.net;
Yalama A., Coskun M. (2007), IC performance <strong>of</strong> quoted banks on <strong>the</strong> Istanbul stock exchange market, Journal
<strong>of</strong> Intellectual Capital; Volume: 8 Issue: 2.
Annex 1: Summary on methods and data used by country
South
Africa
Method VAIC
Sectors/
industries
banking
;
electric
al IT
and
service
s
Mala
y
sia
CIV
and
VAIC
No <strong>of</strong>
companie
s 75 18
Period 2001
Bras
il
CIV
and
ICE,
VAI
C
Finlan
d
CIV
and
ICE,
VAIC
finan
cial 21 11
2004
-
2006
Ban
glad
esh Indonesia Japan
Thail
and India
Gree
ce
VAI
C VAIC VAIC VAIC VAIC VAIC
bank
s
100
0
com
pani
es 20000 17
200
0-
200
5
Not included in <strong>the</strong>
New
repor
t:
Zealand no information
Singapou 9 industries, 3000, 2000re
2002
banking sector, 20, 1997-
Croatia 2001
Austria banking sector, 98, no infrormation
Canada no information
2001-
2003 2004
Turke
y UK Taiwan
VAIC
and
DEA
no
informatio
n banks banks banks banks banks
36
consumer
goods
firms 141 17
2003-
2006 2001
551
2000-
2007
VAI
C VAIC
bank
s
98
commerci
al banks 17 17 29
2000-
2005
1996-
1999
1995-
2004
1995
-
2005
electroni
cs
all
listed,
4254
firmyear
observat
ions
1992-
2002

Nellija Titova
Annex 2: Summary on hypo<strong>the</strong>sis tested
Return to
Assets (ROA)
Calculated
Intangible
value
(CIV)
Employee
productivity
(EP)
Efficiency <strong>of</strong>
investments in
human capital
(IEHC)
Barriers to entry
(BtoE)
Return to
Equity
(ROE)
Return to
Sales
(ROS)
Value Added Intellectual Capital
(VAIC)
t.sk. tā elementu:
HCE – human capital efficiency;
SCE – structural capital efficiency;
CEE – capital employed efficiency.
Relative bank
efficiency
(BRE)
Investments in
IT
(IIT)
552
Asset turnover
(ATO)
Bank risk
(BR)
Operating
cash flow
(OCF)
Revenue
growth
(RG)
Cost to assets
(CTA)
Market-to-book
value
(MB)
Years

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Annex 3: Summary on results <strong>of</strong> multiple
regressions'
VAI
C
ICE
HCE
SCE
CEE
R&D
VAIC ROA ROS ROE EP ATO
S+
(Br)
S+
(Ma)
S+
(Gr)
S+
(Ma)
N+
(Ma)
S+
(Gr)
S+(Uk
)
S+(In),
S+(Th)
S+(Ta)
S+
(Ta)
S+
(UK)
S+ S+ S+
(Br)
S+(In);
S-(Th);
S+(Ta)
;
N-(SA)
(Br) (Br)
S-(Ja)
S+
N(Id)
S+ (In)
N+(Th
)S+(Ta
),
S+(SA
(Ta)
)
S+ (In)
S+(Th)
S+(Ta)
,
N-SA),
S+(Ja)
N-(Ta)
,
S+
S-(Br), S+ (Ta) S-
N (Ind) (Br) (Br)
S+
(Ta) N-(Ta)
AD S-(Ta) S-(Ta)
S+
(Ta) S+(In)
S+
(Ta)
N-
(Ta)
S+
(Ta)
N-
(Ta)
N-
(Ta)
S+ (In)
S-(SA)
S+ (In)
N-(SA)
S+
(In),
N+
(SA)
OC
F RG MB CIV IIT BR
S+
(In)
S+
(In)
S+
(In)
S+
(In)
Source <strong>of</strong> information: <strong>the</strong> summary made by <strong>the</strong> author
VAIC Value added intellectual coefficient
ICE Intellectual capital efficiency
HCE Human capital efficiency
SCE Structural capital efficiency
CEE Capital employed efficiency
ROA return to assets
ROE Return on equity
ROS Return on sales
EP Employee productivity
ATO asset turnover
OCF operating cash flow
RG revenue growth
MB market to book value
CIV Calculated intangible value
IIT Investment in IT
BE bank efficiency
BR bank risk
BtoE barriers to entry
553
S+
(In)
S+
(Ta
)
S+
(In)
S+
(Ta
)
S+
(In)
N+
(Ta
)
N+
(In)
S+
(Ta
)
S+(Ta)
, differ
on
bank
(Tu)
S+(Ta)
, S-
(SA)
S+(Ta)
,
N+(SA
)
S+(Ta)
,
S+(SA
)
S+
(Ta
) S+(Ta)
N+
(Ta
) N -(Ta)
N+
(Fi)
S+
(Fi)
S+
(Br)
S-
(UK)
S+
(UK)
B to
E
S-
(UK)
BR
E
S+
(UK
)

Meaning in <strong>the</strong> table in brackets – countries:
Br – Brazil;
In – Indonesia;
Th – Thailand;
UK – United Kingdom;
Ta – Taiwan;
SA – South Africa;
Ma – Malaysia;
Ja – Japan;
Fi – Finland;
Gr – Greece;
Tu – Turkey;
Id – India;
Ba – Bangladesh.
Meanings in <strong>the</strong> table – results <strong>of</strong> econometrics:
S +: significant and positive,
S –: significant and negative,
N +: non significant positive,
N -: non significant negative,
Nellija Titova
554

A Multi-Stakeholder Perspective on <strong>the</strong> Value Relevance <strong>of</strong>,
Human Capital; Practice <strong>of</strong> Human Capital Accounting and
Human Capital Disclosure: A Review <strong>of</strong> Existing Literature
Krishanthi Ganga Vithana, Riham Rizk and Amir Michael
Durham Business School, Durham University, UK
v.k.vithana@durham.ac.uk
riham.rizk@durham.ac.uk
a.e.iskander@durham.ac.uk
Abstract: The potential <strong>of</strong> employees to generate more and more wealth for firms, identified by scholars as <strong>the</strong>
Human Capital (HC) <strong>of</strong> <strong>the</strong> firm, has become a vital factor in determining success in turbulent business
environments. Though ample research evidence are found on aspects such as HC accounting (Becker, 1962;
Brummet et al 1968; Lev and Schwartz, 1971; 1972; Flamholtz, 1971; 1972a; 1972b; 1972c), accounting for <strong>the</strong>
worth <strong>of</strong> employees (Roslender and Dyson, 1992; Roslender, 1997), HC reporting practice and disclosure
(Abeysekera, 2008; Abeysekera and Guthrie, 2004; Subbarao and Zeghal 1997), <strong>the</strong> behavioural impact <strong>of</strong>
human capital disclosure (Ax and Marton, 2008; Lajili and Zeghal, 2006;), a consensus on HC accounting and
disclosure practice has not been achieved via a standard set <strong>of</strong> guidelines. Consequently, a practical gap is
observed between <strong>the</strong> attempts <strong>of</strong> scholars on developing methodologies and frameworks to practice HC
accounting and reporting and subsequent voluntary practices by listed firms. Fur<strong>the</strong>rmore, although <strong>the</strong> problem
<strong>of</strong> information asymmetry has arguably been reduced via voluntary disclosures, <strong>the</strong> value relevance <strong>of</strong> HC
disclosure has rarely been explored in <strong>the</strong> existing literature, particularly from a multiple stakeholder perspective
due to conflicting interest amongst stakeholder groups (Lev, 1988; Petersen and Plenborg, 2006; Zhou, 2007;
Leuz and Verrecchia, 2000). Addressing <strong>the</strong> above identified practical and research gap, this review work
critically evaluate existing literature on <strong>the</strong> value relevance <strong>of</strong> three aspects; HC, HC accounting practice and <strong>the</strong>
disclosure <strong>of</strong> HC information in <strong>the</strong> annual reports <strong>of</strong> <strong>the</strong> firms. Through this critical review, ultimately, <strong>the</strong>
requirement <strong>of</strong> an objective mechanism to measure HC accounting and disclosure is emphasised and
additionally it is suggested that <strong>the</strong> balanced scorecard framework be utilised as a tool to capture <strong>the</strong> human
capital accounting and reporting practice specially in terms <strong>of</strong> discovering <strong>the</strong> value relevance.
Keywords: HC, HC accounting, HC disclosure, worth <strong>of</strong> employees, value relevance
1. Introduction
HC accounting has been debated by scholars over <strong>the</strong> past several decades. However, this
phenomenon has become a diversified research interest <strong>of</strong> many academicians and researchers even
to day (Abeysekera, 2006, Ax and Marton, 2008; Lajili and Zeghal, 2006). The concept <strong>of</strong> simply
treating <strong>the</strong> spending on people in valuing <strong>the</strong> economic pr<strong>of</strong>it under <strong>the</strong> neo classical approach has
been criticized by many researchers relying on <strong>the</strong> Marx’s labour <strong>the</strong>ory <strong>of</strong> “surplus value” where <strong>the</strong>y
have fur<strong>the</strong>r declared Marx’s labour <strong>the</strong>ory <strong>of</strong> value as a foundation for describing and explaining <strong>the</strong>
role and practice <strong>of</strong> financial reporting (Bryer, 1994). Additionally, many <strong>of</strong> <strong>the</strong> attempts to formalise
<strong>the</strong> practice <strong>of</strong> HC accounting started decades back through critical arguments on valuing <strong>the</strong> HC <strong>of</strong>
<strong>the</strong> firm on different bases (Brummet et al 1968; Lev and Schwartz, 1971; Flamholtz, 1971; Flamholtz,
1972a; Flamholtz, 1972b; Flamholtz, 1972c). Recent research evidence on <strong>the</strong> subject <strong>of</strong> HC has
focused on <strong>the</strong> HC reporting and disclosure aspect ra<strong>the</strong>r than <strong>the</strong> accounting and valuation
(Abeysekera, 2006; Abeysekera and Guthrie, 2004; Subbarao and Zeghal 1997; Ax and Marton,
2008; Lajili and Zeghal, 2006). Against this backdrop, this review paper has been divided into main
sections to critically review <strong>the</strong> literature on value relevance <strong>of</strong> HC, HC accounting and HC disclosure.
2. Human capital
HC is simply understood as <strong>the</strong> potential <strong>of</strong> employees <strong>the</strong>mselves to generate more wealth for
organizations in future which becomes surplus value over <strong>the</strong> returns <strong>of</strong> <strong>the</strong> o<strong>the</strong>r physical and
financial assets <strong>of</strong> <strong>the</strong> firm. In mergers and acquisitions this is treated under current accounting
practice as <strong>the</strong> goodwill <strong>of</strong> a firm. Due to <strong>the</strong> unique potential <strong>of</strong> employees, however, researchers
have argued that <strong>the</strong> spending on employees should not be treated as an expense in <strong>the</strong> year it is
incurred particularly due to <strong>the</strong> fact that some employee expenditures may generate returns over a
period <strong>of</strong> time (Brummet et al, 1968; Flamholtz, 1972a). Flamholtz (1972a). It is also claimed that <strong>the</strong>
value <strong>of</strong> <strong>the</strong> human resources is derived through <strong>the</strong> ability <strong>of</strong> employees to render service which
have economic value. The treatment for HC accounting by Lev and Schwartz (1971) is developed
similarly whereby HC is treated as “a source <strong>of</strong> income embedded in a person in <strong>the</strong> form <strong>of</strong> his brute
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force and his natural and acquired skills” (p. 104). Thus, <strong>the</strong> accounting concept <strong>of</strong> “service potential”
is used as <strong>the</strong> principle to calculate HC. According to <strong>the</strong> Lev and Schwartz’s (1971) arguments, even
though <strong>the</strong> current spending on employees will not have a direct influence over <strong>the</strong> service potential <strong>of</strong>
<strong>the</strong> employees, <strong>the</strong> special programmes and <strong>the</strong> spending associated with those, e.g. employee
induction, training and development, might increase <strong>the</strong> service potential <strong>of</strong> employees as such
expenditures are made with <strong>the</strong> expectation <strong>of</strong> future pr<strong>of</strong>it. Although a rough general understanding
<strong>of</strong> <strong>the</strong> concept HC exists, a universally accepted and widely applicable definition does not.
3. Human capital accounting
Measuring <strong>the</strong> HC <strong>of</strong> firms has been <strong>the</strong> interest <strong>of</strong> economists and accountants due to <strong>the</strong> concern
on <strong>the</strong> potential impact <strong>of</strong> ignoring HC in financial decisions. This has led to <strong>the</strong> development <strong>of</strong> <strong>the</strong>
new field Human Resource Accounting which is defined as “<strong>the</strong> process <strong>of</strong> identifying and measuring
data about human resources and communicating this information to interested parties” (American
accounting association, 1973 p.169).
Relying on <strong>the</strong> assumption ‘if some thing can be measured, it can be managed’, researchers have
made several attempts at measuring <strong>the</strong> HC <strong>of</strong> firms at different levels using different approaches
such as direct measure <strong>of</strong> HC (Brummet et al 1968; Lev and Schwartz, 1971; Flamholtz, 1971;
Flamholtz, 1972a; Flamholtz, 1972b; Flamholtz, 1972c) or measuring HC as efficiency indicators
(Pulic, 1998; Chan, 2009a; Chan, 2009b ; Chen et al, 2005; Tan et al, 2008; Nazari and Herremans,
2007). Understanding <strong>the</strong> difficulty <strong>of</strong> linking human capital with financial accounting and reporting
through hard accounting numbers, researchers have fur<strong>the</strong>r explored <strong>the</strong> potential <strong>of</strong> accounting for
employee wealth as a provision <strong>of</strong> s<strong>of</strong>ter accounting information (Roslender and Dyson, 1992;
Roslender, 1997; Roslender and Fincham, 2001). These research findings are explained below
mostly in chronological order, emphasising <strong>the</strong> <strong>the</strong>ories developed and <strong>the</strong> subsequent modifications
<strong>the</strong>reafter.
The arguments on HC valuation were initiated in <strong>the</strong> fields <strong>of</strong> economics (Becker, 1962) and
accounting (Brummet et al., 1968) in terms <strong>of</strong> <strong>the</strong> value creation for firms through people. Identifying
<strong>the</strong> inadequacies <strong>of</strong> <strong>the</strong> conventional accounting practice in treating human resources <strong>of</strong> firms
specially in <strong>the</strong> accounting and financial reporting process, Brummet et al., (1968) have proposed to
treat <strong>the</strong> outlays for human resources as “capital ra<strong>the</strong>r than consumption” or as “asset ra<strong>the</strong>r than
expenses” especially due to <strong>the</strong> future services potential <strong>of</strong> employees. In this research multiple
techniques including, acquisition cost (<strong>the</strong> historical cost), replacement cost (<strong>the</strong> cost to replace firm’s
existing human resources and <strong>the</strong> economic value (<strong>the</strong> present value <strong>of</strong> <strong>the</strong> portion <strong>of</strong> firms future
earnings attributable to human resources) have been proposed to measure HC (Brummet et al.,
1968). Though <strong>the</strong> method has particularly been generalised for management, to what extent this
model is applicable considering <strong>the</strong> entire workforce as well as marginal benefit over <strong>the</strong> cost <strong>of</strong> <strong>the</strong>
practice still remain questionable.
Flamholtz (1971), focusing upon measurement <strong>of</strong> an individual’s value to a firm, has proposed a
normative model for <strong>the</strong> economic valuation <strong>of</strong> people based on individuals as individuals become <strong>the</strong>
primary focus in many <strong>of</strong> <strong>the</strong> organizational decisions such as selection, training, allocation
(placement), job design, promotion, compensation etc.. Under this <strong>the</strong> expected service life <strong>of</strong> a
person states in terms <strong>of</strong> service level and <strong>the</strong> service group has been taken into account and have
estimated <strong>the</strong> present monetary equivalent <strong>of</strong> <strong>the</strong> expected services as <strong>the</strong> HC value <strong>of</strong> an individual.
Lev and Schwartz (1971) proposed ano<strong>the</strong>r model for individual valuation in which <strong>the</strong> aggregate
value <strong>of</strong> HC is <strong>the</strong> sum <strong>of</strong> <strong>the</strong> values <strong>of</strong> <strong>the</strong> individuals calculated using <strong>the</strong> accounting concept <strong>of</strong>
“service potential” as <strong>the</strong> principle. The sums <strong>of</strong> discounted future earnings <strong>of</strong> <strong>the</strong> employees
according to <strong>the</strong> earnings pr<strong>of</strong>ile <strong>of</strong> each have been treated as <strong>the</strong> HC <strong>of</strong> <strong>the</strong> firm. However, <strong>the</strong> uses
<strong>of</strong> current data on earning distribution classified by age, education, skill etc., as well as problems such
as <strong>the</strong> use <strong>of</strong> prevailing interest rate, inability to determine <strong>the</strong> expected service life, retirement age,
and accidental loss <strong>of</strong> employees due to death or chronic illness, lead to pragmatic difficulties in
estimating <strong>the</strong> HC <strong>of</strong> <strong>the</strong> firm. In a commentary article, <strong>the</strong> work <strong>of</strong> Lev and Schwartz (1971) has been
criticised for <strong>the</strong> lack <strong>of</strong> relevance and utility to decision makers by Flamholtz (1972c) emphasising
that significant applications and implications for management and investors has not been considered
by Lev and Schwartz (1971). In response, Lev and Schwartz (1972) note <strong>the</strong> non-existence <strong>of</strong> a well
defined and empirically valid set <strong>of</strong> decision models used by investors. They fur<strong>the</strong>r elaborated that
due to <strong>the</strong> absence <strong>of</strong> such a formal model it has been impossible to define precisely <strong>the</strong> role <strong>of</strong> HC
information in financial decision making. The lack <strong>of</strong> a valid decision model to employ HC and a
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standard mechanism to account for and discover its value relevance remain grey areas in <strong>the</strong>
accounting literature.
The failure in defusing many <strong>of</strong> <strong>the</strong> academic methods developed for HC accounting by way <strong>of</strong>
practical application has lead researchers to look at <strong>the</strong> old problem in a new light proposing a
paradigm shift (Roslender and Dyson, 1992; Roslender, 1997). “Shifting away from <strong>the</strong> narrow
economic-accounting perspective <strong>of</strong> <strong>the</strong> past to a broader social scientific perspective” <strong>the</strong> previous
attempts <strong>of</strong> putting people in <strong>the</strong> balance sheet has been diverted to generating s<strong>of</strong>ter accounting
information (Roslender and Dyson, 1992 p. 311) with fur<strong>the</strong>r researchers emphasising that external
reporting <strong>of</strong> HR accounting information can impact <strong>the</strong> decision <strong>of</strong> financial statement users including
managers, investors and o<strong>the</strong>r stakeholders.
Fur<strong>the</strong>rmore, <strong>the</strong> question <strong>of</strong> utility <strong>of</strong> many <strong>of</strong> <strong>the</strong> above models in real world decision making has
been addressed by researchers via <strong>the</strong> development <strong>of</strong> a coefficient to indirectly quantify <strong>the</strong> HC
efficiency as a component <strong>of</strong> intellectual capital efficiency, (Pulic, 1998; Pulic, 2000). Pulic (1998)
initially developed <strong>the</strong> Value Added Intellectual Coefficient (VAIC) as <strong>the</strong> sum <strong>of</strong> <strong>the</strong> HC coefficient
(VAHU) and <strong>the</strong> structural capital coefficient (STVA), as an aggregate measure <strong>of</strong> corporate
intellectual ability. This model has subsequently been utilised by many <strong>of</strong> <strong>the</strong> researchers in different
contexts particularly to address <strong>the</strong> impact <strong>of</strong> HC on firm’s financial performances and <strong>the</strong> capital
market performances. The public availability <strong>of</strong> input data to <strong>the</strong> model has expanded <strong>the</strong> application
<strong>of</strong> this model for <strong>the</strong> statistical analysis (Chan, 2009a; Chan, 2009b; Chen et al, 2005; Tan et al, 2008;
Nazari and Herremans, 2007).
Chen et al, (2005) adopting <strong>the</strong> VAIC model developed by Pulic, (1998, 2000) revealed that <strong>the</strong> firm’s
intellectual capital has a positive impact on firms’ market value and financial performance both current
and future. Though firm’s market value is positively associated with corporate intellectual ability and
its two sub-component capital employed efficiency and HC efficiency, results demand fur<strong>the</strong>r analysis
to be carried out aiming <strong>the</strong> individual IC component since stakeholders are placing different value on
individual components, structural and human, than <strong>the</strong> overall intellectual capital efficiency.
Referring to one <strong>of</strong> <strong>the</strong> prominent intellectual capital management framework Skandia Navigator
(Edvinsson, 1997) model, Nazari and Herremans (2007) also attempted to extend <strong>the</strong> VAIC model
developed by Pulic (1998, 2000). The expansion <strong>of</strong> VAIC model has resulted in six coefficients to
measure intellectual efficiency including; HC efficiency, structural capital efficiency, overall value
creation efficiency, customer capital efficiency, innovation capital efficiency and process capital
efficiency. Though researchers wanted <strong>the</strong>se efficiency measures to be tested for <strong>the</strong> impact <strong>of</strong> <strong>the</strong>
value creation efficiencies, <strong>the</strong> model is still being tested by <strong>the</strong> same researchers in <strong>the</strong> North
American setting and is yet to be tested in differing contexts world wide (Nazari and Herremans,
2007).
However, evidence indicates that VAIC model (Pulic, 1998, 2000) also generates contradictory results
in different contexts where Chan (2009a and 2009b) revealed an overall lack <strong>of</strong> association between
IC and financial performance in <strong>the</strong> Hong Kong context. Nei<strong>the</strong>r <strong>the</strong> analysis through breakdown
provided any statistical support for <strong>the</strong> relationship between efficiency indicators and organizational
performance (Chan, 2009b). The negative association between HC efficiency and productivity, as well
as HC efficiency and market valuation indicate that investors hold a negative view <strong>of</strong> companies that
have relatively high employee related expenditure. However, this indicator warrants fur<strong>the</strong>r
examination <strong>of</strong> <strong>the</strong> subject as this reasoning might arguably vary in different socio-economic contexts.
Arguably, nei<strong>the</strong>r <strong>the</strong> direct HC measures nor HC efficiency measures have been successful in
explaining <strong>the</strong> impact <strong>of</strong> HC on organizational or capital market performance. This paves <strong>the</strong> way for
more detailed explorations <strong>of</strong> HC value for financial and investment decision making. This has been
fur<strong>the</strong>r emphasised through <strong>the</strong> research evidence on HC accounting and disclosure literature
examined below.
3.1 The Impact <strong>of</strong> human capital accounting on decision making
It is accepted among researchers (Flamholtz, 2005) that “accounting for <strong>the</strong> worth <strong>of</strong> employees has
implications for both managers and investors” (Roslender and Dyson, 1992 p. 319). However, <strong>the</strong>
absence <strong>of</strong> a proper framework to capture <strong>the</strong> impact <strong>of</strong> HC or HC accounting on decision behaviour
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still act as a limitation in discovering this through <strong>the</strong> empirical analysis some <strong>of</strong> which are reviewed
below.
Elias (1972) revealed that in general <strong>the</strong> company choice by <strong>the</strong> respondents is associated with <strong>the</strong>
experimental treatment for <strong>the</strong> HC in annual reports though <strong>the</strong> degree <strong>of</strong> association measured was
not very strong. Specially, <strong>the</strong> inclusions <strong>of</strong> human asset statements have affected <strong>the</strong> decision
behaviour <strong>of</strong> advance accounting and finance students while not so significant for <strong>the</strong> intermediate
students. However, <strong>the</strong> difference in <strong>the</strong> response between <strong>the</strong> occupational groups for <strong>the</strong> HC
treatment has not been statistically significant. This implies that <strong>the</strong> response for <strong>the</strong> inclusion <strong>of</strong> <strong>the</strong>
human asset statement in <strong>the</strong> financial statements would not be perceived in <strong>the</strong> same way by all <strong>the</strong>
stakeholder categories. Fur<strong>the</strong>rmore, <strong>the</strong> education level and discipline might have a significant
influence over <strong>the</strong> response to this additional information in <strong>the</strong> annual reports. One limitation to this
study is identified as <strong>the</strong> difference in responses being recognised as more attributable to <strong>the</strong> income
between <strong>the</strong> firms ra<strong>the</strong>r than <strong>the</strong> inclusion <strong>of</strong> <strong>the</strong> HC information.
Avoiding many inherent limitations <strong>of</strong> Elias (1973), such as using a student sample, exclusion <strong>of</strong>
annual report information o<strong>the</strong>r than abbreviated financial statements, simple decision <strong>of</strong> selecting
one company than different types <strong>of</strong> <strong>the</strong> decisions and no reasoning behind <strong>the</strong> decision making;
Schwan (1976) tested <strong>the</strong> effect <strong>of</strong> human resource accounting data on financial decisions by use <strong>of</strong>
two sets <strong>of</strong> financial reports. In set A, conventional financial report; and in <strong>the</strong> set B, human resource
cost has been allocated to expense over a five year period. The findings supported <strong>the</strong> hypo<strong>the</strong>sis
that bankers who read financial statement which report human resource data make significantly
different decisions about <strong>the</strong> firm than bankers who read <strong>the</strong> firms conventional reports. Detailed
analysis emphasised that this was particularly <strong>the</strong> case regarding <strong>the</strong> management’s preparedness on
challenges and <strong>the</strong> opportunities in future than <strong>the</strong> present management situations.
One common limitation for both <strong>of</strong> <strong>the</strong> above studies is that <strong>the</strong> research is conducted to discover <strong>the</strong>
practice <strong>of</strong> HC accounting from <strong>the</strong> point <strong>of</strong> view <strong>of</strong> limited stakeholder groups and particularly
external. However, <strong>the</strong> multiple stakeholder perspective on financial disclosure demanded this issue
be explored both from <strong>the</strong> internal and external stakeholder point <strong>of</strong> view. Never<strong>the</strong>less, <strong>the</strong>
experimental approach might be suitable to research <strong>the</strong> practice HC accounting treatments in a
ra<strong>the</strong>r controlled atmosphere which is not <strong>the</strong> case in <strong>the</strong> Schwan (1976) and Elias (1972) studies.
Consequently, <strong>the</strong> validity and generalisability <strong>of</strong> <strong>the</strong> findings become questionable.
Maher (1996), discovering <strong>the</strong> inadequacy in attempts to formally evaluate <strong>the</strong> cost and benefit <strong>of</strong>
different human resource management practices proposed that a “business like” approach needs to
be adopted to <strong>the</strong> management <strong>of</strong> people if <strong>the</strong>y are to gain any strategic credibility. The study
concluded that “in order to evaluate <strong>the</strong> human resource management decisions not only will human
resource people need to familiarise <strong>the</strong>mselves with accounting practice but <strong>the</strong>y will also need <strong>the</strong>
support to setup information systems that will enable <strong>the</strong>m to identify <strong>the</strong> outcomes <strong>of</strong> specific human
resource investments” (Maher, 1996 p. 31). “..Majority <strong>of</strong> personnel people don’t get involved in <strong>the</strong>
pr<strong>of</strong>itability <strong>of</strong> <strong>the</strong>ir business… and to me that’s a must. I think <strong>the</strong>y should be numerate, <strong>the</strong>y should
understand business accounting and should understand <strong>the</strong> effect that <strong>the</strong>ir action can have on that
business…”. This statement fur<strong>the</strong>r emphasises <strong>the</strong> importance <strong>of</strong> <strong>the</strong> practice <strong>of</strong> HC accounting and
moreover, <strong>the</strong> vital importance <strong>of</strong> linking HC accounting with employee performance in a more formal
way.
Moving away from <strong>the</strong> individual perspective <strong>of</strong> calculation <strong>of</strong> <strong>the</strong> HC <strong>of</strong> firm, Flamholtz (2005) has
suggested a different approach which attempts to capture <strong>the</strong> economic value <strong>of</strong> <strong>the</strong> HC <strong>of</strong> three
kinds. The research posits three distinct and related components <strong>of</strong> economic value <strong>of</strong> HC in firms
termed as, value <strong>of</strong> individual competencies, incremental value <strong>of</strong> synergetic terms <strong>of</strong> people in
relatively small groups and incremental synergetic value <strong>of</strong> <strong>the</strong> human organization as a whole as
distinct from <strong>the</strong> value <strong>of</strong> <strong>the</strong> o<strong>the</strong>r two components (Flamholtz, 2005 p.79). Studies revealed that <strong>the</strong>
HC <strong>of</strong> third kind (corporate culture) can be measured as well as it does have a statistically significant
impact upon financial performances. In this approach <strong>the</strong> incremental value <strong>of</strong> synergy <strong>of</strong> <strong>the</strong> human
organization as a whole has been taken in to account under <strong>the</strong> company’s cultural paradigm i.e. “<strong>the</strong>
way we treat our people affects <strong>the</strong> way our people treat our customers, and in turn, our success,
which includes financial performance.” (Flamholtz, 2005 P. 82). However, restriction <strong>of</strong> <strong>the</strong> sample to
a single organization (medium sized industrial enterprise) and measuring <strong>the</strong> HC <strong>of</strong> third kind using
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corporate culture as a proxy as well as estimating <strong>the</strong> value <strong>of</strong> culture using a questionnaire were
some <strong>of</strong> <strong>the</strong> areas <strong>of</strong> concern regarding future studies.
Though HC researchers (Brummet et al, 1968; Lev and Schwartz, 1971; Flamholtz, 1971; Flamholtz,
1972a; Flamholtz, 1972b; Flamholtz, 1972c; Schwan, 1976; Elias, 1972) have attempted to develop
human resource accounting system and <strong>the</strong> valuation basis, still <strong>the</strong> involvement <strong>of</strong> <strong>the</strong> firms in this
practice is mostly limited to qualitative disclosures <strong>of</strong> information by <strong>the</strong>se firms (Hussain et al., 2004;
Subbaroa and Zeghal, 1997; Abeysekera and Guthrie, 2004; Ax and Marton, 2008). Recent studies
(Abeysekera and Guthrie, 2004 and 2005; Abeysekara, 2008) reveal that most firms do not even use
<strong>the</strong> terms HC or intellectual capital in <strong>the</strong>ir annual reports, than merely providing a qualitative
description on <strong>the</strong> people component whenever necessary. Fur<strong>the</strong>r, <strong>the</strong> conventional reporting
structure itself have failed to evolve a methodology to capture it under <strong>the</strong> existing reporting
mechanism (Stittle, 2004)
4. Human capital disclosure
Given that firms’ practice <strong>of</strong> HC accounting is limited to <strong>the</strong> qualitative descriptions in <strong>the</strong> annual
reports, researchers have also diverted <strong>the</strong>ir attention recently towards qualitative disclosures. Much
research evidence can be found on HC disclosure in annual report and despite <strong>the</strong> absence <strong>of</strong> a
sound HC reporting framework (Abeysekera, 2006; Abeysekera and Guthrie, 2004; Subbarao and
Zeghal 1997; Ax and Marton, 2008; Lajili and Zeghal, 2006). Studies are critically evaluated mostly in
chronological order denoting recent developments in <strong>the</strong> field.
An initial international comparison study <strong>of</strong> human resource information disclosure using <strong>the</strong> content
analysis covering USA, Canada, Germany, UK, Japan, and South Korea revealed that <strong>the</strong>re is a clear
difference between <strong>the</strong> countries studied in terms <strong>of</strong> <strong>the</strong> incidence and word count <strong>of</strong> <strong>the</strong> information
disclosure in <strong>the</strong>ir annual reports (Subbarao and Zeghal, 1997). Results <strong>of</strong> <strong>the</strong> analysis indicated that
<strong>European</strong> firms disclose more on human resources than Asian and North American firms and <strong>the</strong>re is
a clear difference between <strong>the</strong> financial services sector and <strong>the</strong> manufacturing service sector. From
<strong>the</strong> very beginning <strong>of</strong> <strong>the</strong> HC disclosure studies, results implied a huge variation <strong>of</strong> firms practice as
well as how <strong>the</strong> variation is lead by firm specific or <strong>the</strong> o<strong>the</strong>r socio economic factors which require
fur<strong>the</strong>r examinations.
Proving that many different factors might affect <strong>the</strong> practice HC disclosure, Abeysekera and Guthrie
(2004) results also showed a deviation from <strong>the</strong> studies carried out in developed countries in terms <strong>of</strong>
<strong>the</strong> attributes mostly reported by <strong>the</strong> firms. Even though, <strong>the</strong> same content analysis technique was
adopted no any consensus was observed on HC attributes included in disclosure index. The
comparison <strong>of</strong> <strong>the</strong> results with Australian studies conducted following <strong>the</strong> same duration revealed <strong>the</strong>
fact that <strong>the</strong> difference in <strong>the</strong> frequency and <strong>the</strong> extent <strong>of</strong> <strong>the</strong> disclosure are attributable to <strong>the</strong> sociocultural
values <strong>of</strong> <strong>the</strong> countries such that entrepreneurial spirit has been highly valued in Australia but
very less in Sri Lanka through reporting and valuing results driven attributes such as value added by
Sri Lanka and process driven attributes such as work related knowledge by Australian firms.
Without limiting to <strong>the</strong> descriptive analysis Abeysekera, (2008) has extended <strong>the</strong> research on HC
disclosure to provide <strong>the</strong> reasoning or <strong>the</strong> motivation behind <strong>the</strong> practice. The content analysis and
<strong>the</strong> in-depth analysis through eleven case studies revealed that firms have used disclosure in order to
reduce tension between firms and stakeholders specially in <strong>the</strong> interest <strong>of</strong> fur<strong>the</strong>r capital
accumulation.
Stittle (2004) argued that many <strong>of</strong> <strong>the</strong> attempts on HC accounting in a UK context are still limited to
descriptive disclosures. Fur<strong>the</strong>rmore, many <strong>of</strong> <strong>the</strong> regulatory bodies have limited <strong>the</strong>ir efforts on
developing regulatory frameworks to merely qualitative HC disclosure, ra<strong>the</strong>r than a quantification <strong>of</strong>
HC to include in <strong>the</strong> traditional financial statements. Particularly, <strong>the</strong> researcher argues that <strong>the</strong>
practical gap in moving ahead with HC accounting and reporting arise because <strong>of</strong> <strong>the</strong> minimal
involvement <strong>of</strong> <strong>the</strong> regulatory bodies and legislation. Even current studies on HC accounting seems
have had some prejudices in <strong>the</strong>ir minds at outset, biasing <strong>the</strong>m not to look into formal mechanisms to
put people into <strong>the</strong> balance sheet. In order to avoid <strong>the</strong> above, <strong>the</strong> accounting regulations, state
control and <strong>the</strong> legislations should take heed <strong>of</strong> this regard to develop best practice guidelines for
firms to meaningfully account for and disclose on people (Stittle, 2004).
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5. Conclusion
Krishanthi Ganga Vithana et al.
The literature review evaluated <strong>the</strong> findings on <strong>the</strong> subject human capital; covering HC valuation, HC
accounting, disclosure and <strong>the</strong> value relevance <strong>of</strong> HC reporting undertaken using different
methodologies. However, through this extensive review, it is identified that researchers are moving
around <strong>the</strong> topic human capital, addressing different aspect in an ad-hoc manner ra<strong>the</strong>r than linking
<strong>the</strong>m with previous studies to give a holistic picture. Many human capital disclosure studies have
been limited to ei<strong>the</strong>r valuation or content analysis while some intellectual capital disclosure studies
have adopted different approaches such as VAIC (Chan, 2009a; Chan, 2009b; Chen et al, 2005; Tan
et al, 2008), event study (Dumay and Tull, 2007), etc. Fur<strong>the</strong>r, one common limitation with HC studies
is that <strong>the</strong> descriptive nature <strong>of</strong> research undertaken where very limited or no attempts are found on
<strong>the</strong> <strong>the</strong>oretical reasoning behind HC disclosure and <strong>the</strong> impact or consequences <strong>of</strong> HC disclosure.
The absence <strong>of</strong> a standard framework to quantify qualitatively disclosed HC information might explain
many <strong>of</strong> <strong>the</strong> above observations. This indicates <strong>the</strong> need for future studies to adopt context specific
disclosure indices to improve <strong>the</strong> validity <strong>of</strong> findings as well as to extend <strong>the</strong> HC disclosure related
researches towards <strong>the</strong>oretical reasoning and <strong>the</strong> value relevance <strong>of</strong> <strong>the</strong> practice. Fur<strong>the</strong>rmore, ra<strong>the</strong>r
than mere word count, line count or sentence count in estimating <strong>the</strong> HC disclosure an objective
mechanism needs to be developed looking at <strong>the</strong> aspects <strong>of</strong> HC as intellectual capital management.
With this regards <strong>the</strong> well-known intellectual capital management framework balanced scorecard
(Kaplan and Norton, 1992) would be suggested as <strong>the</strong> four perspectives will provide a basis for
categorization <strong>of</strong> HC attributes for grouping purposes and <strong>the</strong> presence or absence <strong>of</strong> information in
<strong>the</strong> levels <strong>of</strong> balanced scorecard could provide an objective criteria for quantification <strong>of</strong> <strong>the</strong> extent <strong>of</strong>
HC disclosure. This justifies <strong>the</strong> fact that employees who lead <strong>the</strong> organizations towards strategic
success are accounted in a way that <strong>the</strong> strategic positioning <strong>of</strong> <strong>the</strong>m too is well reflected.
References
Abeysekera, I. (2008) “Motivation Behind Human Capital Disclosure in Annual Reports”, Accounting Forum, Vol
32. pp 16-29.
Abeysekera, I. (2006) “The Project <strong>of</strong> Intellectual Capital Disclosure: Researching <strong>the</strong> Research”, Journal <strong>of</strong>
Intellectual Capital, Vol 7, No. 1, pp 61-77.
Abeysekera, I. and Guthrie, J. (2004), “Human Capital Reporting in a Developing Nation”, <strong>the</strong> British Accounting
Review, Vol 36, pp 251-268.
American accounting association, (1973), “Report <strong>of</strong> committee on Human Resource Accounting”, The
Accounting Review, 1973 Supplement, Vol 48, No. 4, pp 168-185.
Ax, C and Marton, J. (2008) “HC Disclosure and Management Practices”, Journal <strong>of</strong> Intellectual Capital, Vol 9,
No. 3, pp 433-455.
Becker, G. S. (1962), “Investment in HC: A Theoretical analysis”, The Journal <strong>of</strong> Political Economy, Vol 70, No. 5
pp 9-49.
Brummet, R.L., Flamholtz, E.G. And Pyle, W.C. (1968) “Human Resource Measurement- A Challenge for
Accountants”, <strong>the</strong> Accounting Review, Vol 43, No. 2, pp 217-224.
Bryer, R.A. (1994), “Why Marx’s Labour Theory is Superior to <strong>the</strong> Marginalist Theory <strong>of</strong> Value: <strong>the</strong> Case From
Modern Financial Reporting”, Critical Perspectives on Accounting, Vol 5, pp 313-340.
Chan, K.H. (2009a), “Impact <strong>of</strong> Intellectual Capital on Organizational Performance: An Empirical Study <strong>of</strong> <strong>the</strong>
Companies in <strong>the</strong> Hang Seng Index (Part 1)”, The Learning Organization, Vol 16, No. 1, pp 4-21.
Chan, K.H. (2009b), “Impact <strong>of</strong> Intellectual Capital on Organizational Performance: An Empirical Study <strong>of</strong> <strong>the</strong>
Companies in <strong>the</strong> Hang Seng Index (Part 2)”, The Learning Organization, Vol 16, No. 1, pp 22-39.
Chen, M.C.,Cheng, S.J and Hwang, Y. (2005), “An Empirical Investigation <strong>of</strong> <strong>the</strong> Relationship Between
Intellectual Capital and Firm’s Market Value and Financial Performance”, Journal <strong>of</strong> intellectual capital, Vol
6, No. 2, pp 159-176.
Dumay, J. And tull, J.A. (2007) “Intellectual Capital Disclosure and Price Sensitive Australian Stock Exchange
Announcements” Journal <strong>of</strong> Intellectual Capital, Vol 8, No. 2, pp 236-255.
Edvinsson. L (1997), “Developing Intellectual Capital at Skandia”, Long range planning, Vol 30, No. 3, pp 366-
373.
Elias, N. (1972), The Effect <strong>of</strong> Human Asset Statement on <strong>the</strong> Investment Decision: An Experiment, Journal <strong>of</strong>
Accounting Research, Vol 10 No. 3, pp 215-233.
Flamholtz, E. (2005) “Conceptualizing and Measuring <strong>the</strong> Economic Value <strong>of</strong> HC <strong>of</strong> <strong>the</strong> Third Kind Corporate
Culture”, The Journal <strong>of</strong> Human Resource Costing and Accounting, Vol 9 No. 2, pp 78-93.
Flamholtz, E. (1972a) “Human Resource Accounting : A Review <strong>of</strong> Theory and Research”, Organizational
Behaviour Division at <strong>the</strong> Thirty Second Annual Meeting <strong>of</strong> <strong>the</strong> Academy <strong>of</strong> Management, Minneapolis,
Minnesota, (Journal <strong>of</strong> Management Studies February)
Flamholtz, E. (1972b) “Towards a Theory <strong>of</strong> Human Resource Value in Formal Organization”, The Accounting
Review, Vol 47 No. 4, pp 666-678.
Flamholtz, E.G. (1972c) “On <strong>the</strong> Use <strong>of</strong> Economic Concept <strong>of</strong> HC in Financial Statements: A Comment”, The
Accounting Review, Vol 47, No. 1, pp 148-152.
560

Krishanthi Ganga Vithana et al.
Flamholtz, E. (1971) “A Model for Human Resource Valuation: A Stochastic Process with Service Rewards”, The
Accounting Review, Vol 46, No. 2, pp 253-267.
Hussain, D.M., Khan, A.R. And Yasmin, I. (2004) “The Nature <strong>of</strong> Voluntary Disclosures on Human Resources in
<strong>the</strong> Annual Resources <strong>of</strong> Bangladeshi Companies”, Dhaka University Journal <strong>of</strong> Business Studies, Vol 25,
No. 1, pp 221-231.
Lajili, K. and Zeghal, D. (2006) “Market Performance Impacts <strong>of</strong> HC Disclosure”, Journal <strong>of</strong> Accounting and
Public Policy, Vol 25, pp 171-194.
Leuz, C and Verrecchia, R.E (2000) “The Economic Consequences <strong>of</strong> Increased Disclosure”, Journal <strong>of</strong>
Accounting Research, Vol 38 Supplement: Studies on Accounting Information and <strong>the</strong> Economics <strong>of</strong> <strong>the</strong>
Firm. Pp. 91-124.
Lev, B. (1988) “Toward a Theory <strong>of</strong> Equitable and Efficient Accounting Policy”, The Accounting Review. Vol 63,
No. 1, pp 1-22.
Lev, B. and Schwartz, A. (1971) “On <strong>the</strong> Use <strong>of</strong> Economic Concept <strong>of</strong> HC in Financial Statements”, The
Accounting Review, Vol 46, No. 01, pp 103-112.
Lev, B. and Schwartz, A. (1972) “On <strong>the</strong> Use <strong>of</strong> Economic Concept <strong>of</strong> HC in Financial Statements: A Reply”, The
Accounting Review, Vol 47, No. 01, pp153-154.
Maher, A. (1996) Measuring Human Resource Value: An Analysis Based on <strong>the</strong> Hotel Industry, Journal <strong>of</strong>
Human Resource Costing and Accounting, vol. 1 No. 1, pp. 15-33.
Nazari, J.A. and Herremans, I. M. (2007) Extended VAIC Model: Measuring Intellectual Capital Components,
Journal <strong>of</strong> Intellectual Capital, Vol 8, No. 4, pp. 595-609.
Petersen, C. and Plenborg, T. (2006) “Voluntary Disclosure and Information Asymmetry in Denmark”, Journal <strong>of</strong>
International Accounting, Auditing and Taxation, Vol 15 pp 127-149.
Pulic, A. (1998) “Measuring <strong>the</strong> Potentials <strong>of</strong> Intellectual Potential in Knowledge Economy”, Presented in Second
McMaster World Congress on Measuring and Managing Intellectual Capital by <strong>the</strong> Austrian Team for
Intellectual Potential.
Roslender, R. and Fincham, R. (2001) Thinking Critically About Intellectual Capital Accounting, Accounting
Auditing and Accountability Journal, Vol 14, No.4, pp 383-398.
Roslender, R. (1997) Accounting for <strong>the</strong> Worth <strong>of</strong> Employees: Is <strong>the</strong> Discipline Finally Ready to Respond to <strong>the</strong>
Challenge, Journal <strong>of</strong> Human Resource Costing and Accounting, Vol 2, No. 1, pp 9-26.
Roslender, R. and Dyson, J.R. (1992) Accounting for <strong>the</strong> Worth <strong>of</strong> Employees: a New Look at an Old Problem”,
British Accounting Review, Vol 24, pp 311-329.
Schwan, E.S. (1976) “The Effect <strong>of</strong> Human Resource Accounting Data on Financial Decisions: An Empirical
Test”, Accounting, Organizations and Society, Vol 1, No. 2-3, pp 219-237.
Stittle, J. (2004) “UK Corporate Reporting <strong>of</strong> HC: A Regulatory Failure to Evolve”. Business and Society Review,
Vol 109 No. 3, pp 311-337.
Subbarao, A.V. and Zeghal, D. (1997) “Human Resource Information Disclosure in Annual Reports: An
International Comparison”, Journal <strong>of</strong> Human Resource Costing and Accounting, Vol 2 No. 2, pp 53-73.
Tan, H.P., Plowman, D. And Hancock, P. (2008) “The Evolving Research on Intellectual Capital”, Journal <strong>of</strong>
Intellectual Capital, Vol 9, No. 4, pp 585-608.
Zhou, H. (2007) “Auditing Standards Increased Accounting Disclosure and Information Asymmetry: Evidence
from an Emerging Market”, Journal <strong>of</strong> Accounting and Public Policy. Vol 26, pp 584-620.
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564

The Beehive: A Practitioner’s Metaphor for Knowledge
Markets
Philippe Leliaert
SyntaxisNetworking, Blaasveld, Belgium
pl@syntaxisnetworking.com
Abstract: This presentation provides practical insights into how <strong>the</strong> bee-keeper metaphor, first presented at
ECIC09, can help understand and manage knowledge market dynamics within organisations (and beyond), in a
significant departure from <strong>the</strong> way markets traditionally operate. Knowledge markets that mirror <strong>the</strong> dynamics <strong>of</strong>
physical or financial markets fail because <strong>the</strong> value <strong>of</strong> knowledge assets - and intangibles in general - cannot be
determined using typical spot-transaction based approaches. Crucially, <strong>the</strong> extreme context-dependent nature <strong>of</strong>
knowledge makes that its true value can only be determined as and when – and every time –it is used, i.e. mostly
some time after <strong>the</strong> exchange took place. By its nature, <strong>the</strong>re is no “objective market value” <strong>of</strong> knowledge, and
<strong>the</strong>refore nei<strong>the</strong>r can its price be determined. Pentaho’s bee-keeper model, which has been used as a metaphor
to describe and explain commercial open source business models, has previously also served to visualise <strong>the</strong>
workings <strong>of</strong> internal knowledge markets at an international network <strong>of</strong> independent consultants. Using this model,
<strong>the</strong> development and sharing <strong>of</strong> knowledge are kept separate from its application in commercial contexts, at
which point (financial) value is determined. In doing so, <strong>the</strong>re is no longer any pressure to put a financial value (or
price) to knowledge being shared; but ra<strong>the</strong>r <strong>the</strong> value <strong>of</strong> knowledge is determined retrospectively every time it is
used .Individuals’ contributions to <strong>the</strong> “Communal Body <strong>of</strong> Knowledge” (CBOK) are tracked through an
intermediate construct, which can be called “credits”. Thus, each individual can hold a number <strong>of</strong> credits in
proportion to his/her contributions made to any given knowledge asset. That same proportion later serves to
determine each individual’s allocation <strong>of</strong> revenue from <strong>the</strong> use <strong>of</strong> that knowledge asset. The more one contributes
to a given knowledge asset (relative to o<strong>the</strong>r individuals), <strong>the</strong> higher one’s proportion <strong>of</strong> related credits and
<strong>the</strong>refore also <strong>the</strong> higher one’s allocation <strong>of</strong> future revenues earned from <strong>the</strong> use <strong>of</strong> that knowledge asset.
Conversely, as soon as one elects to no longer contribute to a given knowledge asset <strong>the</strong>n one’s amount <strong>of</strong>
related credits will remain fixed but likely decrease as a proportion <strong>of</strong> all related credits (assuming o<strong>the</strong>rs continue
to make contributions).The credits essentially act as options on (an allocation <strong>of</strong>) future revenues. It should be
clear that a secondary internal market in credits is <strong>the</strong>refore possible: credits can be traded since <strong>the</strong>y represent
a right to part <strong>of</strong> future revenues generated by <strong>the</strong> use <strong>of</strong> <strong>the</strong> related knowledge assets. In that respect, <strong>the</strong>
credits related to different knowledge assets may well carry a different value, since credit value is linked to <strong>the</strong>
asset’s likely or potential future revenues. A fur<strong>the</strong>r refinement is that contributions to <strong>the</strong> CBOK may be weighted
according to <strong>the</strong> community’s appreciation <strong>of</strong> <strong>the</strong> added value <strong>the</strong>y bring: for instance, ano<strong>the</strong>r classification
model for Intellectual Capital may at this point bring little added value to <strong>the</strong> related CBOK, whereas cases
studies detailing <strong>the</strong> practical use <strong>of</strong> Intellectual Capital Measurement in companies remain rare and are
<strong>the</strong>refore very valuable. In that case it is essential to incorporate a rating or voting functionality into <strong>the</strong>
knowledge sharing platform (cf. <strong>the</strong> reputation functionality at amazon.com or eBay.com). The bee-keeper
metaphor was recently updated and expanded to explain <strong>the</strong> differences with business models for proprietary
s<strong>of</strong>tware and for open source service/support companies. In <strong>the</strong> same vein <strong>the</strong>se updated versions can now also
serve to visualise how different organisations deal with <strong>the</strong> exchange <strong>of</strong> knowledge both within <strong>the</strong>ir organisation
and with external entities (incl. customers, partners, competitors, suppliers, regulators, former and prospective
employees, etc.), and how this is reflected in <strong>the</strong>ir respective business models. By using holo-maps - graphical
representations <strong>of</strong> how value, including knowledge, is exchanged in each <strong>of</strong> <strong>the</strong>se business models – one can
demonstrate how significantly different <strong>the</strong> respective business models treat in particular motivation and reward
for sharing knowledge. They moreover illustrate how o<strong>the</strong>r components <strong>of</strong> Intellectual Capital (Human, Structural,
and Relational Capital) contribute to <strong>the</strong> mix <strong>of</strong> value being exchanged between <strong>the</strong> various actors. The
presentation will fur<strong>the</strong>rmore discuss <strong>the</strong> managerial implications <strong>of</strong> applying <strong>the</strong> above insights into one’s
knowledge management processes, and <strong>the</strong> crucial role that trust and reputation have in measuring and
managing <strong>the</strong> flow <strong>of</strong> knowledge in an organisation, and beyond.
Keywords: knowledge markets; bee-keeper model; reputation; holo-maps
565

The Tobing Knowledge Management Architecture
Paul Lumbantobing, Nelson Rikardo Pasaribu and Juli Purwanti
PT. Telekomunikasi Indonesia, Tbk, Indonesia
paul.lumbantobing@gmail.com
Abstract: This article proposes design <strong>of</strong> knowledge management architecture as a framework for <strong>the</strong>
development and implementation <strong>of</strong> KM initiatives and as an aid for management in realizing <strong>the</strong> benefit <strong>of</strong> KM
for organization. The article identifies <strong>the</strong> main elements <strong>of</strong> KM architecture and details <strong>the</strong> nature each element’s
role and inter elements relationship conceptually and practically. The architecture was developed using <strong>the</strong>
Integrated Business Architecture (Accenture), literature research and some personal experiences. Through this
article, we found that <strong>the</strong> KM strategy shall has a feasible value proposition extracted from corporate strategy and
shall define <strong>the</strong> process, technology and structure needed to deliver <strong>the</strong> value proposition to all KM stakeholders.
This architecture provides guidance in placing KM, corporate strategy and enterprise systems at a more
appropriate and integrated position. This architecture also has potential in moderating and combining various
extreme poles <strong>of</strong> <strong>the</strong> KM strategy.
Keywords: knowledge management (KM), architecture, knowledge and strategy
1. Introduction
The importance <strong>of</strong> <strong>the</strong> KM role to leverage <strong>the</strong> corporate competitiveness nowadays is increasing, but
still many organizations are implementing KM as a separated initiative from o<strong>the</strong>r initiatives, especially
<strong>the</strong> company's business strategy itself. So <strong>the</strong> gap between KM programs with o<strong>the</strong>r programs <strong>of</strong> <strong>the</strong>
organization remains a major issue (Fonseca, 2003). Zack (1999) stated that critical issues in
implementing KM are how to build links between strategy and knowledge. Failure to build a
knowledge-strategy link can reduce <strong>the</strong> effectiveness <strong>of</strong> KM implementation in maximizing <strong>the</strong>
company's competitive advantage.
So effective KM implementation requires an appropriate KM business architecture (for <strong>the</strong> rest <strong>of</strong> this
paper, we call “KM business architecture” as “KM architecture”). KM architecture is required to enable
an organization to commercialize or to convert knowledge into business value. As a consequence, it
is necessary to build a KM architecture that ensures that <strong>the</strong> implementation <strong>of</strong> KM is fully integrated
with <strong>the</strong> strategic elements <strong>of</strong> <strong>the</strong> organization such as <strong>the</strong> external environment, business strategy,
leadership, people, process, technology, organization and culture.
KM architecture should assist organization in understanding <strong>the</strong> characteristics and dynamics <strong>of</strong>
knowledge possessed and required by <strong>the</strong> organization, for, <strong>the</strong> dynamics <strong>of</strong> knowledge greatly
depends on <strong>the</strong> KM stakeholders such as users, leaders, contributors and knowledge manager. In
addition, understanding <strong>the</strong> dynamics <strong>of</strong> <strong>the</strong> internal and external <strong>of</strong> organization, represented by <strong>the</strong>
business strategy will assist managers in determining <strong>the</strong> KM value proposition. KM value proposition
explains <strong>the</strong> role and position <strong>of</strong> KM in <strong>the</strong> organization and what benefits must be produced and how
<strong>the</strong> benefits are delivered to KM stakeholders.
This article proposes a KM Architecture that is a crystallization <strong>of</strong> our retrospect and learning process
as practitioners who are involved daily in <strong>the</strong> KM implementation.
2. Approach
The purpose <strong>of</strong> KM Architecture conception is to provide a framework and a foundation for <strong>the</strong>
development and operation <strong>of</strong> KM initiatives. KM Architecture is defined as a description <strong>of</strong>
components and capabilities as well as <strong>the</strong>ir synergic interrelationship in realizing <strong>the</strong> strategic
advantages and benefits <strong>of</strong> KM for <strong>the</strong> company.
The approach used in <strong>the</strong> development <strong>of</strong> KM architecture is based on <strong>the</strong> Integrated Business
Architecture that was used by Accenture Global Management Consulting in its report to management
<strong>of</strong> PT. Telekomunikasi Indonesia (for <strong>the</strong> rest <strong>of</strong> this paper we call as Telkom) in 2004.
The Integrated Business Architecture from Accenture (shown at Figure 1) consists <strong>of</strong> several
components:
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Vision/Strategic Intent that determines <strong>the</strong> direction <strong>of</strong> a company and becomes <strong>the</strong> primary basis
for determining corporate strategy. Achieving <strong>the</strong> vision is <strong>the</strong> focus <strong>of</strong> <strong>the</strong> entire company and is <strong>the</strong>
main reason for <strong>the</strong> existence <strong>of</strong> a company.
Value Proposition describes <strong>the</strong> benefits/value added that can be <strong>of</strong>fered to customer compared with
o<strong>the</strong>r products/services in <strong>the</strong> market. Thus, <strong>the</strong> value proposition is also <strong>the</strong> basis for determining
how a company's strategy differentiates itself with o<strong>the</strong>r competitors.
Figure 1: IBA: Integrated Business Architecture (source: Accenture, 2004)
Business Model describes <strong>the</strong> products/services <strong>of</strong>fering, to whom <strong>the</strong> <strong>of</strong>fer, how <strong>the</strong> distribution
channel, and which revenue base model used. Business model also outlines <strong>the</strong> main capabilities
required and how to build or obtain <strong>the</strong>se capabilities.
Business Architecture describes <strong>the</strong> required organizational capabilities in terms <strong>of</strong> process
capabilities (business processes, policies, procedures, etc.), organizations (performance
management, competency, etc.), and technology (infrastructure, operational support systems, etc.).
These capabilities need to be arranged so that <strong>the</strong>y become <strong>the</strong> main framework <strong>of</strong> a company in
running <strong>the</strong> day-to-day operational activities.
By adopting and modifying <strong>the</strong> Accenture’s Integrated Business Architecture, we define <strong>the</strong> elements
<strong>of</strong> KM Architecture as follows: KM strategies, role and value proposition, operation model,
and operation architecture ((see Figure 2).
KM strategies are in <strong>the</strong> forms <strong>of</strong> vision, mission and strategic objectives <strong>of</strong> KM that must
be aligned with <strong>the</strong> company’s vision, mission and strategic objectives. Management shall
ensure that <strong>the</strong> existence <strong>of</strong> KM must support <strong>the</strong> company in attaining its strategic
objective.
The next element <strong>of</strong> KM Architecture is KM role and value proposition. In order to point out its
contribution, management must declare <strong>the</strong> role and value <strong>of</strong>fered by KM to <strong>the</strong> company. This is
important, especially to convince <strong>the</strong> management and organizational members about <strong>the</strong> imperative
<strong>of</strong> KM implementation in <strong>the</strong> company. The clarity <strong>of</strong> <strong>the</strong> position and role <strong>of</strong> KM is important to reduce
<strong>the</strong> confusion in its implementation.
The operation model is a component that describes how a company realizes its vision, mission and
strategic objectives, as well as how <strong>the</strong> company can communicate <strong>the</strong> KM role and value proposition
to organizational members and management. In <strong>the</strong> operation model, it is established a KM target
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Paul Lumbantobing et al.
user, knowledge to be managed, as well as methodology and technology used for conveying benefits
and services <strong>of</strong> KM to <strong>the</strong> users.
The final element is operation architecture that consists <strong>of</strong> three sub-elements: process,
organization, and technology. The operation architecture defines <strong>the</strong> processes, unit and qualification
<strong>of</strong> <strong>the</strong> people who execute <strong>the</strong> processes and by what technology <strong>the</strong> processes to be executed in
order to realize <strong>the</strong> operation model.
Figure 2: Four basic elements <strong>of</strong> knowledge management architecture (adapted from IBA, Accenture,
2004)
3. KM architecture analyzes
3.1 KM strategy
KM strategy is an elaboration <strong>of</strong> <strong>the</strong> company’s business strategy. In <strong>the</strong> KM strategy, <strong>the</strong> vision,
mission and strategic objectives <strong>of</strong> knowledge management are formulated to support <strong>the</strong> company’s
vision, mission and objectives. And <strong>the</strong>n in <strong>the</strong> next stage, it is carried out an identification <strong>of</strong> what
steps must be done from <strong>the</strong> side <strong>of</strong> KM in supporting <strong>the</strong> implementation <strong>of</strong> business strategy and in
achieving <strong>the</strong> company’s strategic objectives. The alignment <strong>of</strong> KM strategy with <strong>the</strong> company’s
business strategy is conducted through a chart shown in Figure 3.
The process <strong>of</strong> KM implementation is a long journey that requires vision, clear direction and high level
<strong>of</strong> commitment and discipline that is expressed in <strong>the</strong> KM strategy. As a consequence, <strong>the</strong> KM
implementation requires a visionary leader who not only has short-term achievement, but also can
reflect how <strong>the</strong> future <strong>of</strong> company in <strong>the</strong> five or ten years.
Vision should be <strong>the</strong> result <strong>of</strong> collaboration <strong>of</strong> all elements in <strong>the</strong> company. The involvement <strong>of</strong> all
stakeholders in <strong>the</strong> vision formulation will not only generate a qualified vision, but also will gain a
commitment from all elements in <strong>the</strong> organization for its achievements.
Strategic objective is <strong>the</strong> translation <strong>of</strong> KM vision and mission to <strong>the</strong> various performance targets. The
targets can be in <strong>the</strong> forms <strong>of</strong> indicators that describe <strong>the</strong> intensity <strong>of</strong> <strong>the</strong> knowledge use, service
quality indicators, or competency improvement indicators. The indicators can be divided based on <strong>the</strong>
principles <strong>of</strong> balance score card, so that <strong>the</strong>re is a balance between short-term and long-term or
strategic indicators.
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Knowledge
Distribution
Company
Knowledge
Base
Knowledge
Storage
Paul Lumbantobing et al.
Strategy Formulation
Initiatives Formulation that needed for strategy
implementation
Knowledge Identification that required
implementing strategic initiatives
Knowledge Existing
Environment
l
Knowledge Gap Analysis
Knowledge Needs
KM Strategy Formulation
Knowledge Acquisition: benchmark, training,
internship, research, merger, etc.
Integration <strong>of</strong> knowledge with corporate strategic
initiatives
Figure 3: Process <strong>of</strong> alignment and integration <strong>of</strong> company strategy with KM strategy
3.2 KM role and value proposition
KM Strategic
Effectiveness
Analysis
In <strong>the</strong> early implementation <strong>of</strong> KM, employees and management frequently have a highly varied
understanding <strong>of</strong> KM. This varied understanding also leads to a different expectation <strong>of</strong> employees
and management, and it likely ends up to <strong>the</strong> confusion and excessive load for <strong>the</strong> KM, especially if
KM is required to fulfil <strong>the</strong> desire <strong>of</strong> all parties.
To control <strong>the</strong> expectations that arise and also to focus <strong>the</strong> stages <strong>of</strong> KM implementation,
management must decide <strong>the</strong> KM role and value proposition for a certain period, which is in <strong>the</strong> next
period can be evaluated and extended.
3.2.1 KM role
There are three role options that can emerge in KM. First option, KM is directed to manage <strong>the</strong>
knowledge as a product. It means that <strong>the</strong> knowledge management concentrates itself in doing
knowledge codification and to store it in knowledge repository that can be accessed by employees.
This approach is based on cognitivism perspective (Varela, 1992 in Dalkir, 2005)
Second option, KM is directed to connect people who have knowledge to <strong>the</strong> people who need <strong>the</strong>
knowledge. The consequence <strong>of</strong> this option is <strong>the</strong> knowledge manager must be able to identify people
who have certain knowledge and to connect <strong>the</strong>m to o<strong>the</strong>r people who need it. In order to facilitate <strong>the</strong>
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people connectivity, <strong>the</strong> KM is demanded to create various media and to moderate meetings
creatively. This approach is based on connectionist perspective (Dalkir, 2005)
The third option is to play <strong>the</strong> two roles above simultaneously, which we call as balanced approach,
because <strong>of</strong> <strong>the</strong> balance <strong>of</strong> emphasis between <strong>the</strong> cognitivism and <strong>the</strong> connectionist. The third choice
that combines <strong>the</strong> first and second options, needs a larger resource, if <strong>the</strong> resource is not enough,
<strong>the</strong>n <strong>the</strong> KM may become stagnant and not focus.
The choice <strong>of</strong> <strong>the</strong> role must be conducted with respect to <strong>the</strong> availability <strong>of</strong> resources allocated to
knowledge management. Compared with <strong>the</strong> first option, second option clearly requires more active
participation and higher commitment from many parties, namely people who act as experts,
audiences, and <strong>the</strong> facilitators.
But <strong>the</strong> advantage <strong>of</strong> <strong>the</strong> second option is richer than first option especially from <strong>the</strong> aspect <strong>of</strong>
personal interaction and will be easier to build a trust, which is <strong>the</strong> foundation for <strong>the</strong> establishment <strong>of</strong>
both strong sharing cultures as <strong>the</strong> core <strong>of</strong> KM and knowledge communities.
3.2.2 KM value proposition
In KM publications, we found that advantages and benefits <strong>of</strong> KM are very diverse and quite a lot. But
from many advantages <strong>of</strong>fered by KM, Anantatmula (2005) concluded that <strong>the</strong> results or benefits
which are most preferred by <strong>the</strong> pr<strong>of</strong>it organizations are:
Improving collaboration.
Improving employees’ skills.
Improving <strong>the</strong> quality <strong>of</strong> product and service.
In selecting <strong>the</strong> KM benefits, management needs to identify crucial problems being faced by
company currently and in <strong>the</strong> future. Then, from <strong>the</strong> various KM benefits, <strong>the</strong> management
selects which benefits that can be realistically achieved, and uses <strong>the</strong>m as a solution for <strong>the</strong>
problems both being faced currently and likely faced by company in <strong>the</strong> future. How <strong>the</strong>
benefits <strong>of</strong> KM are realized to overcome <strong>the</strong> problems faced by company will be formulated
in <strong>the</strong> operation model.
3.3 KM operation model
By taking <strong>the</strong> analogy with business terminology, KM must have services and products that must be
delivered to users.The users must be also established based on <strong>the</strong> classification available at <strong>the</strong>
company. In <strong>the</strong> value proposition it has been formulated a solution promised by KM, <strong>the</strong>n in <strong>the</strong>
operation model it is formulated who provides <strong>the</strong> solution, and how <strong>the</strong> mechanisms <strong>of</strong> production
and delivery <strong>of</strong> <strong>the</strong> solution to <strong>the</strong> target users.
In <strong>the</strong> operation model design, <strong>the</strong> knowledge manager must conduct an analysis on <strong>the</strong> condition <strong>of</strong>
<strong>the</strong> availability <strong>of</strong> company’s knowledge to determine <strong>the</strong> company’s knowledge needs. The output <strong>of</strong>
<strong>the</strong> analysis is <strong>the</strong> identified knowledge gap in <strong>the</strong> form <strong>of</strong> <strong>the</strong> list <strong>of</strong> knowledge needs but not fully
owned and managed by <strong>the</strong> company, <strong>the</strong> list <strong>of</strong> units and personnel who need <strong>the</strong> knowledge, and
<strong>the</strong> list <strong>of</strong> personnel, expert, or <strong>the</strong> external organization/expert that can provide <strong>the</strong> knowledge.
Next, <strong>the</strong> unit KM must formulate a delivery method that is used to supply knowledge in order to meet
<strong>the</strong> knowledge gap. Organizations can provide knowledge in many ways, among <strong>the</strong>m, with:
Perform knowledge codification, and store it in knowledge base and give workers authority to
access <strong>the</strong> knowledge.
Send selected personnel to attend training to acquire <strong>the</strong> knowledge needed.
Invite expert to share his/her knowledge.
Hire an expert to work in <strong>the</strong> company during a certain period
Perform merger and acquisition.
Encourage employees to develop certain knowledge independently.
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The operation architecture consists <strong>of</strong> three sub-components: process, organization, and technology.
Process: determine <strong>the</strong> main processes needed to realize <strong>the</strong> operation model.
Organization: define <strong>the</strong> functions and characteristics <strong>of</strong> <strong>the</strong> organization to execute <strong>the</strong> KM
processes.
Technology: sets requirement <strong>of</strong> technology to accelerate <strong>the</strong> execution <strong>of</strong> KM processes
The main processes in <strong>the</strong> KM are very diverse, both in terms <strong>of</strong> <strong>the</strong> terminology and understanding <strong>of</strong>
<strong>the</strong> process itself. As an example, Telkom as a Telco operator uses eTOM (enhanced Telecom
Operations Map). eTOM is a reference framework in <strong>the</strong> classification <strong>of</strong> elements <strong>of</strong> <strong>the</strong> business
processes for telecommunication services and information company.
The organizational sub component concerns with <strong>the</strong> functions that is necessarily provided
for supporting <strong>the</strong> activities and process <strong>of</strong> KM. These functions directly handle KM, or support
<strong>the</strong> implementation <strong>of</strong> KM itself. Organization needs to provide a special unit to handle KM not only
from <strong>the</strong> side <strong>of</strong> content management but also related to <strong>the</strong> socialization and promotion <strong>of</strong> KM
culture.
The companies also need to harmonize policies and systems so that <strong>the</strong>y integrated with KM. Things
that need to be prioritized are human resources policies, such as: competence development, career
development, remuneration and reward. The next alignment, is to improve <strong>the</strong> architecture <strong>of</strong>
knowledge, by doing so, <strong>the</strong>re is a better flow <strong>of</strong> knowledge to all elements <strong>of</strong> <strong>the</strong> process in each
unit.
The organization sub-component also concerns with corporate culture. To be more conducive for KM
implementation, organizations needs to develop learning organization, by growing <strong>the</strong>
organizational skills in <strong>the</strong> activities <strong>of</strong> systematic problem solving, new approaches
experimentation, learning from past experience, learning best practice from o<strong>the</strong>r parties, and transfer
knowledge quickly and efficiently to <strong>the</strong> entire organization. (Garvin, 1998)
The final sub component in <strong>the</strong> operation architecture is technology. Information technology is
an enabler that makes <strong>the</strong> execution <strong>of</strong> KM processes more effective and efficient. Giraldo (2005),
called four main roles <strong>of</strong> technology for global companies that is also believed relevant for
national-scaled companies, those are:
Maintain and keep track <strong>of</strong> <strong>the</strong> operational transaction data.
Analyzing business environment
Providing support in <strong>the</strong> decision making process.
Improve <strong>the</strong> collaboration and group decision-making
The technology selection is adapted to <strong>the</strong> business process, knowledge flow and knowledge
distribution system, as well as organizational functions that have been developed. Some capabilities
or applications <strong>of</strong> <strong>the</strong> technology have been probably owned by <strong>the</strong> company, so it is necessarily to
evaluate and leverage <strong>the</strong> capability <strong>of</strong> existing information technology infrastructures.
4. The Tobing KM architecture as a syn<strong>the</strong>sis <strong>of</strong> KM architecture components
In systems philosophy, <strong>the</strong> whole is greater than <strong>the</strong> sum <strong>of</strong> its parts. In sections 3 previously it has
been carried out a component development and analysis <strong>of</strong> KM architecture. So in this part, all those
components are recombined into KM architecture but with <strong>the</strong> more detailed and comprehensive
components (sub components). Or in o<strong>the</strong>r words, after doing system analysis, <strong>the</strong>n <strong>the</strong> next step is
to do system syn<strong>the</strong>sis. Dentailed explanation <strong>of</strong> each component / sub component is done through a
case study in section 5.
Two elements are added namely Strategic Environmental Factors that serves as an interface between
<strong>the</strong> organization to its external, and business strategy that formulates <strong>the</strong> organization response to its
environment. The Strategic Environmental Factors concern with <strong>the</strong> situation <strong>of</strong> competitive intensity,
macroeconomic condition, regulation, social situation and technological trend. The external factors
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Paul Lumbantobing et al.
influence <strong>the</strong> company’s business strategy, and <strong>the</strong> company’s business strategy will become a main
reference for all components in <strong>the</strong> KM architecture.
In designing architecture, system syn<strong>the</strong>sis is done to guarantee that <strong>the</strong> components in <strong>the</strong>
architecture have been integrated in solid and synergic ways so it can be viewed as systems, as
showed in Figure 4 and we called it as The Tobing KM Architecture. This architecture is a moredetailed
and more complete description <strong>of</strong> KM architecture than showed in Figure 2.
Strategic Environmental
Factors (competition,
economy, social and
technology)
Business Strategy
Target User
Storage and Distribution Systems
Online Offline
Knowledge Commodity
Explicit
Tacit Knowledge
Knowledge
Organization (functions, structure, culture)
Figure 4: The Tobing KM architecture
In Figure 4 <strong>the</strong> component <strong>of</strong> KM strategy in Figure 2 has been detailed into <strong>the</strong> elements <strong>of</strong>
leadership and strategy. The elements <strong>of</strong> leadership and strategy by considering <strong>the</strong> organizational
business strategy will determine <strong>the</strong> KM role and value proposition.
The operation model has been detailed into target user, those are consumers and contributors <strong>of</strong>
knowledge, <strong>the</strong> type <strong>of</strong> knowledge managed and distributed (tacit/explicit), as well as distribution
system and storage (online or <strong>of</strong>fline). And <strong>the</strong> last element is <strong>the</strong> operation architecture that consists
<strong>of</strong> <strong>the</strong> process, technology and organization.
5. Implementation <strong>of</strong> <strong>the</strong> Tobing KM architecture in Telkom
PT.Telekomunikasi Indonesia, Tbk (Telkom) is <strong>the</strong> largest network and service provider in Indonesia.
As <strong>of</strong> December 31, 2009, Telkom common share is owned by <strong>the</strong> Indonesian Government (52.4%)
and <strong>the</strong> rest is owned by public shareholders. This company has been 154 years old. Telkom realized
that its business was already in <strong>the</strong> maturity level, and driven by <strong>the</strong> high intensity <strong>of</strong> competition with
10 local competitors, <strong>the</strong>n on 16 October 2009 Telkom transformed its business by changing its
business portfolio from TMM (Telecommunications, Mobile and Multimedia) to TIME
(Telecommunications, Information, Media and Edutaintment / Education and Entertainment).
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Paul Lumbantobing et al.
Actually, this architecture has been implemented in Telkom. Telkom's business strategy is formulated
in a document called <strong>the</strong> CSS (Corporate Strategic Scenario). Changes in <strong>the</strong> business portfolio as
outlined in <strong>the</strong> CSS from TMM to TIME have knowledge implications, because Telkom has been very
rich in T (telecommunication) competence, but has a serious knowledge gap related to IME
(Information, Media and Edutaintment) competence.
Based on this CSS, knowledge strategy is formulated in <strong>the</strong> form <strong>of</strong> KM vision, mission, and directory
competency. Knowledge strategy also determines ways and methods to acquire knowledge /
competencies needed to <strong>the</strong> success <strong>of</strong> CSS and sets a KM role (what <strong>the</strong> duties and responsibilities
<strong>of</strong> each business unit in implementing KM) and KM value proposition. The benefits <strong>of</strong>fered by <strong>the</strong> KM
in Telkom is to prioritize <strong>the</strong> development <strong>of</strong> content knowledge related to IME competence and to
provide access to employees who want to do <strong>the</strong> "competence migration" from old competence to
IME competence.
Based on <strong>the</strong>se formulations, <strong>the</strong> vision <strong>of</strong> KM is to become a knowledge company that acts as a
lever <strong>of</strong> competitiveness in order to achieve <strong>the</strong> vision <strong>of</strong> <strong>the</strong> company as a Leading TIME
(Telecommunications, Information, Media and Edutaintment) Player in <strong>the</strong> Region.
The purpose <strong>of</strong> KM Telkom is to support <strong>the</strong> implementation <strong>of</strong> <strong>the</strong> company's business strategy
through:
a. Provision <strong>of</strong> knowledge that <strong>the</strong> company needs
b. Maintain, transfer and store <strong>the</strong> competence, skills and experience <strong>of</strong> employees and
organizational innovation in <strong>the</strong> form <strong>of</strong> corporate knowledge
c. Support <strong>the</strong> establishment <strong>of</strong> knowledge-based corporate culture
Operation Model is designed to create a mechanism to meet <strong>the</strong> knowledge needs <strong>of</strong> employees dayto-
day. The provision <strong>of</strong> explicit knowledge is done by developing IME content that can be accessed
by employee, in particular employee who will work on IME product line. Included in <strong>the</strong> operation
model, Telkom build competitive intelligence application called CIA (Competitive Intelligence Analysis)
that provides knowledge resulting from <strong>the</strong> data warehousing and analytic processing systems and
EXIS (Executive Information System) that serves as a dashboard for BOD in controlling <strong>the</strong> business
day-to-day. While tacit knowledge is provided by hiring people who are competent in <strong>the</strong> field <strong>of</strong> IME
for a specific period, thus <strong>the</strong>y will be able to transfer <strong>the</strong>ir tacit knowledge through <strong>the</strong>ir daily work. In
<strong>the</strong> corporate level, Telkom meets knowledge needs by acquiring companies that have IME
competence.
Online storage and distribution system are provided through <strong>the</strong> provision <strong>of</strong> KM technology called <strong>the</strong>
Kampiun, while <strong>of</strong>fline media is done through <strong>the</strong> establishment <strong>of</strong> community <strong>of</strong> practice and various
forums that discuss specific issues. Last element <strong>of</strong> <strong>the</strong> operation model is <strong>the</strong> target user, <strong>the</strong> target
users <strong>of</strong> KM is <strong>the</strong> employees who will be assigned to <strong>the</strong> IME sector that is required to master
ano<strong>the</strong>r competence.
The next component that is necessarily designed is <strong>the</strong> operation architecture. The subelements
<strong>of</strong> operation architecture are process, organization and technology. From <strong>the</strong>
side <strong>of</strong> process, it has been conducted an identification and inventory <strong>of</strong> <strong>the</strong> processes
required to implement <strong>the</strong> operation model. Telkom as a Telco operator uses eTOM (enhanced
Telecom Operations Map). Example <strong>of</strong> <strong>the</strong> KM main process derived from <strong>the</strong> process <strong>of</strong> Knowledge
Management in eTOM, as shown in Figure 5.
Processes always have a technology, knowledge, and organizational characteristics. Technology
characteristic is related to how to identify technology needs for executing <strong>the</strong> process. With regard to
technology, Telkom has built a KM system and e-learning accessible to all workers. Knowledge
characteristic is related to <strong>the</strong> knowledge that must be owned to execute <strong>the</strong> process. In connection
with this knowledge, Telkom provides a Directory <strong>of</strong> Competency and DJM (Distinct Job Manual) that
contains <strong>the</strong> knowledge requirements <strong>of</strong> each position. Directory <strong>of</strong> competency and DJM are always
tailored to <strong>the</strong> business strategy
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Develop KM
Strategy
Description
Develop KM
policies,
procedures and
structure.
Knowledge
Management
Capture
Knowledge
Description
To ensure that
knowledge
emerged in
activities is
captured and
retained according
to <strong>the</strong> needs <strong>of</strong>
company
Paul Lumbantobing et al.
Knowledge & Research Management (K&RM)
Classify
Knowledge
Description
Research
Management
Classify knowledge
captured according
to policies and
structure <strong>of</strong> KM.
Classification can be
based on
competency stream,
level <strong>of</strong>
confidentiality, or
business process.
Store
Knowledge
Description
Put classified
knowledge into
company’s
knowledge base,
and make it
accessible to <strong>the</strong>
authorized
employee.
Maintain
Knowledge
Description
Keep knowledge
up-to-date, secure
and accessible to
<strong>the</strong> employee.
Technology
Scanning
Distribute
Knowledge
Description
Provide processes
and capabilities to
distribute
knowledge to <strong>the</strong>
entire <strong>of</strong>
organization.
Figure 5: The main process <strong>of</strong> KM described from eTOM
All elements above are supported by organizational elements. The organization provides <strong>the</strong> functions
and structures needed in executing <strong>the</strong> process and directing <strong>the</strong> use <strong>of</strong> technology. The company’s
commitment can be seen through <strong>the</strong> allocation <strong>of</strong> function, structure, personnel, and o<strong>the</strong>r resources
<strong>of</strong> organization. Related organizations, Telkom has established some units dedicated to <strong>the</strong>
implementation <strong>of</strong> KM. For innovation (knowledge creation), Telkom has R & D Centre. Telkom has
Learning Centre and Management Consulting Centre for IME content development and unit SICP
(Strategic Investment and Corporate Planning) for performing Merger & Acquisition.
Organization also concerns with <strong>the</strong> culture. Related to culture, Telkom has a knowledge culture
called 5Cs, are: Commitment to Long Term, Customer first, Caring meritocracy, Co-creation <strong>of</strong> winwin
partnership, and Collaborative innovation.
Figure 6 shows <strong>the</strong> mapping <strong>of</strong> <strong>the</strong> implementation <strong>of</strong> KM Telkom to <strong>the</strong> Tobing KM Architecture.
6. Discussion
In this section, not all elements <strong>of</strong> <strong>the</strong> architecture are discussed, but only a few elements whose
influences are significant. Discussions associated with its application in Telkom or associated with <strong>the</strong>
relevant reference.
Our main motivation in developing this architecture here is <strong>the</strong> growing realizations that KM is a
critical factor for building firm’s competitive advantage. In <strong>the</strong> resource-based view (Barney, 1986 and
Peteraf, 1993 in Mahoney and Pandian, 1992), knowledge is seen as a strategic asset with <strong>the</strong>
potential to be a source <strong>of</strong> sustainable competitive advantage <strong>of</strong> an organization. In order to be a
source <strong>of</strong> competitive advantage, <strong>the</strong> knowledge should be managed in an integrated way with o<strong>the</strong>r
corporate initiatives.
The first implication <strong>of</strong> this architecture is emphasized again that business strategy is a key element
that directs <strong>the</strong> implementation <strong>of</strong> KM (Zack, 1999 and McDonough III, et al 2008). In addition to
product / market and innovation, ano<strong>the</strong>r key component <strong>of</strong> an effective strategy is knowledge
(McDonough III, Zack, Lin and Berdrow, 2008). The question is how to build links between knowledge
with <strong>the</strong> strategy? At Telkom, any change in strategy always implies <strong>the</strong> knowledge needs, which are
formulated in <strong>the</strong> form <strong>of</strong> changes in directory <strong>of</strong> competency, change in directory <strong>of</strong> competency
followed by change in Distinct Job Manual (DJM) and training needs and subsequently changes in <strong>the</strong>
knowledge content.
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SAP, CRM, HRIS, EXIS, CIA
etc
eTOM
Paul Lumbantobing et al.
PESTE (Political
&Regulation, Economy,
Socio-Cultural, Technology
and Environmental Concern)
Corporate Strategic Scenario
Employee assign to IME business
Storage and Distribution Systems
Kampiun CoP/Forum
Knowledge Commodity
DJM, Directory
Competence, IME
Content
Outsource IME Expert/
M&A IME Company
KM Strategy: Role &Value
Proposition
Organization Dedicated to KM: Learning Centre, IS Centre, R&D Centre, KM;
Culture: 5Cs
Figure 6: The Tobing KM architecture: Implementation in Telkom
In a higher level, in addition to streng<strong>the</strong>ning <strong>the</strong> business portfolio, M & A is also intended to acquire
IME competence, which is very rare in <strong>the</strong> parent company. For example, Telkom has acquired Sigma
(competent in Information) and in <strong>the</strong> future may acquire TV stations (competent in media and
entertainment).
In addition to <strong>the</strong> strategic level, KM also should serve <strong>the</strong> workers in meeting <strong>the</strong>ir day-to-day
knowledge needs. Consequently, <strong>the</strong> operation model is designed by describing and defining <strong>the</strong>
mechanism and system used in realizing <strong>the</strong> value-added <strong>of</strong>fered that supports <strong>the</strong> users and
capability required to realize <strong>the</strong> benefits KM. In <strong>the</strong> operation model, it also establishes <strong>the</strong> main
target users (knowledge users and contributors), and <strong>the</strong>y become <strong>the</strong> focus <strong>of</strong> knowledge
management.
The next implication <strong>of</strong> this architecture makes <strong>the</strong> debate whe<strong>the</strong>r <strong>the</strong> enterprise system with <strong>the</strong> KM
needs to put toge<strong>the</strong>r or not, is irrelevant. Various literatures have explored different view about how
collaboration between KM and <strong>the</strong> enterprise systems, such as ERP, DSS and CRM (Chan, 2009).So
with <strong>the</strong> existence <strong>of</strong> this architecture, <strong>the</strong> KM, corporate strategy and enterprise systems can be
positioned more appropriately and can be seen in an integrated way.
Ano<strong>the</strong>r important implication is related to corporate culture. Well formulated corporate strategy and it
derivatives in KM strategy, does not guarantee that <strong>the</strong> implementation <strong>of</strong> strategy will be successful.
Cultural factors potentially inhibit or accelerate KM strategy execution (Davenport et al., 1998). 5Cs
new culture <strong>of</strong> Telkom, although this is very knowledge-centric culture, but not yet have a significant
influence in encouraging <strong>the</strong> implementation <strong>of</strong> KM. Many KM implementations particularly on <strong>the</strong>
operational level are still artificial, for example, not many people share <strong>the</strong>ir best knowledge.
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Obejctives

Paul Lumbantobing et al.
In <strong>the</strong> academic and practical discourses, <strong>of</strong>ten appears <strong>the</strong> polar extremes <strong>of</strong> <strong>the</strong> KM strategy, such
as tacit versus explicit orientation (Jordan & Jones, Choi and Lee, 2003), personalization versus
codification (Hansen et al. in Choi and Lee, 2003), aggressive versus conservative styles (Zack,
1999), cognitive vs. community styles (Swan et al. in Choi and Lee, 2003), which is similar to
cognitivism versus connectionist (Dalkir, 2005) and exploitation versus exploration. This architecture
has <strong>the</strong> potential to moderate and to combine <strong>the</strong> various extreme <strong>of</strong> KM strategies. And
organizations that are able to place <strong>the</strong> various poles <strong>of</strong> strategy dynamically, will be more successful
in improving corporate performance (Choi and Lee, 2003),
7. Conclusion
The architecture is emphasized again that business strategy is a key element that directs <strong>the</strong>
implementation <strong>of</strong> KM. The ability to build strong links between knowledge and strategy is <strong>the</strong> key
success factor <strong>of</strong> KM implementation, especially in supporting <strong>the</strong> implementation <strong>of</strong> business
strategy.
KM should serve <strong>the</strong> workers in meeting <strong>the</strong>ir daily knowledge needs. Consequently, <strong>the</strong> operation
model is designed by describing and defining <strong>the</strong> mechanism and system used in realizing <strong>the</strong> KM
value-added.
This architecture can arrange KM, corporate strategy and enterprise systems with more appropriate
and in an integrated framework.
This architecture has <strong>the</strong> potential to moderate and to combine <strong>the</strong> various extreme <strong>of</strong> KM strategies.
And organizations that are able to place <strong>the</strong> various poles <strong>of</strong> strategy dynamically will be more
successful in improving corporate performance.
Cultural factors potentially inhibit or accelerate KM strategy execution. As a foundation <strong>of</strong> all
elements, it is found that <strong>the</strong> organization shall build a specific and supportive knowledge culture.
References
Accenture (2004). Integrated Business Architecture: PT.Telekomunikasi Indonesia, Tbk.
Anantatmula, V. (2005). Knowledge Management Criteria. Chapter 11 in Stankosky, M., (ed.) Creating <strong>the</strong>
Discipline <strong>of</strong> Knowledge Management, Elsevier Inc.
Barney, Jay B. (2001). Is <strong>the</strong> Resource Based-View a Usefull Perspective for Strategic Management
Reasearch?Yes, Journal Academy <strong>of</strong> Management Review, vol 28 pp 43-45.
Chan, J.O. (2009). A Conceptual Framework for an Integrated Knowledge-Driven Enterprise Model, Journal <strong>of</strong>
International Technology and Information Management, vol 18 No 2, pp 161-185.
Dalkir, Kimiz (2005). Knowledge Management in Theory and Practice, Elsevier Butterworth-Heinemann.
Davenport, T.H., and Prusak, L. (1998). Working Knowledge, Harvard Business School Press.
Fonseca, A.F., (2003), The effect <strong>of</strong> an integrated knowledge management architecture on organizational
performance and impact: <strong>the</strong> case <strong>of</strong> <strong>the</strong> World Bank, University <strong>of</strong> Maryland (dissertation)
Garvin, D.A. (1998). Building a Learning Organization, Harvard Business Review On Knowledge Management, p
47-80.
Giraldo, J.P. (2005). Relationship between Knowledge Management Technologies and Learning Actions <strong>of</strong>
Global Organizations, Chapter 7 in Stankosky, M., (ed.) Creating <strong>the</strong> Discipline <strong>of</strong> Knowledge Management,
Elsevier Inc.
IBM (2008). Knowledge Management: The Transformation to Web 2.0 – Beyond <strong>the</strong> Hype and Making It Real.
Mahoney, J.T. and Pandian, R., (1992) The Resource Based View Within The Conversation Of Strategic
Management, Strategic Management Journal,Vol 13, pp.363-380
McDonough III, E.F., Zack, M.H., Lin, Hsing-Er, and Irish Berdrow (2008) Integrating Innovation Style and
Knowledge Into Strategy, MIT Sloan Management Review, Fall 2008.
Nonaka, I., and Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create <strong>the</strong>
Dynamics <strong>of</strong> Innovation, New York: Oxford University Press.
Tobing, Paul L. (2007). Knowledge Management: Konsep, Arsitektur dan Implementasi, Graha Ilmu.
Turban, E., McLean, E., and We<strong>the</strong>rbe, J. (2004). Information Technology for Management: Transforming
Organizations in <strong>the</strong> Digital Economy, 4 th edition, MA: John Wiley & Sons.
Weill, P., and Broadbent, M. (1998). Leveraging The New Infrastructure, Harvard Business School Press.
Zack, Michael H. (1999). Developing a Knowledge Strategy, California Management Review, 41, No. 3, Spring,
pp.125-145.
576

Harmonization Process Between Individual Performance
Appraisal and Business Unit Performance Appraisal
Without Decreasing Employee Engagement
Yuli Purwanti, Nelson Rikardo Pasaribu and Paul Lumbantobing
PT. Telekomunikasi Indonesia, Tbk, Bandung, Indonesia
yuli_purwanti@telkom.co.id
Abstract: This paper is a case study <strong>of</strong> how <strong>the</strong> process to synchronize Individual Performance Appraisal and
Business Unit Performance Appraisal while maintaining Employee Engagement in PT. Telekomunikasi
Indonesia, Tbk., which is <strong>the</strong> largest telecommunications operator in Indonesia. In 2004, TELKOM improved its
human resource management by implementing competence-based human resource management (CBHRM).
Performance Management is one <strong>of</strong> CBHRM processes, which is important to motivate employee to perform his
or her best to <strong>the</strong> company so company goals can be achieved. Telkom Performance Management was designed
with <strong>the</strong> principle <strong>of</strong> maintaining <strong>the</strong> sustainability growth <strong>of</strong> corporate performance through employee
performance management. Therefore, appraisal <strong>of</strong> employee performance must always associate with
achievement <strong>of</strong> company performance. It means that employee performance should reflect corporate
performance or business unit performance in this case. As a stimulant, <strong>the</strong> company provides a budget as an
excellent achiever rewards given to <strong>the</strong> business units, which managed to reach its target, to be distributed to all
employees in <strong>the</strong> unit based on <strong>the</strong> contribution <strong>of</strong> each employee. The Problem is although <strong>the</strong> business unit did
not reach its, Individual performance appraisal data from 2004 to 2006 showed that appraisal value <strong>of</strong> individual
performance always above-average business unit performance. So, Employees still got excellent achiever
rewards (incentives) periodically. As a result, employees became less attention on business unit performance.
They have already got what <strong>the</strong>y needed. The condition became a major concern and management tried to find
<strong>the</strong> solution. At <strong>the</strong> end <strong>of</strong> 2007, TELKOM implemented a new performance management policy that includes
regulations governing <strong>the</strong> process <strong>of</strong> harmonization <strong>of</strong> <strong>the</strong> appraisal value <strong>of</strong> employee performance with <strong>the</strong>
achievement <strong>of</strong> business unit performance. This process aims to harmonize <strong>the</strong> appraisal value <strong>of</strong> <strong>the</strong> individual
performance with business unit performance as well as to get <strong>the</strong> composition <strong>of</strong> individual performance value
which distributed normally, meaning that <strong>the</strong>re will be an outstanding, average and underperformed employee
classifications. These classifications will affect directly or indirectly to <strong>the</strong> employee remuneration, career
development, and employee development. The process has been going every year since 2007 until now and it is
a learning organization process. It said that be a learning organization process because in its implementation has
been occurred many problems that appears to be solved and demanded to modify <strong>the</strong> scoring system for <strong>the</strong>
company's expectations achieved yet employee engagement maintained. The role <strong>of</strong> a leader is needed in this
harmonization process because <strong>the</strong> problem that <strong>of</strong>ten arises is a leader not expressly dares to provide different
appraisal <strong>of</strong> employees so that after <strong>the</strong> harmonization <strong>of</strong> <strong>the</strong> result continued to show <strong>the</strong> average rating score. It
will reduce employee engagement, which performs nicely but getting <strong>the</strong> average value. To overcome <strong>the</strong> above
problems, this paper provides some proposed solutions, which addresses to <strong>the</strong> company and employee and
also be given as a contributions <strong>of</strong> practitioners to <strong>the</strong> enrichment <strong>of</strong> human resource management science in <strong>the</strong>
academic world.
Keywords: performance appraisal, harmonization process, employee engagement, excellent achiever incentive,
learning organization
1. Introduction
Telkom has been implementing Competency-Based Performance Appraisal to measure employee
performance since 2004. Employee is demanded to prepare individual work program at <strong>the</strong> beginning
<strong>of</strong> <strong>the</strong> year, which is called “Sasaran Kinerja Individu (SKI)”. It will be assessed based on <strong>the</strong>
achievement at <strong>the</strong> end <strong>of</strong> <strong>the</strong> year and <strong>the</strong> result is called “Nilai Kinerja Individu (NKI)” or Individual
Performance Score. Individual work program is prepared based on business unit work program, which
is followed Annual Corporate Program that already agreed by Board <strong>of</strong> Directors. Therefore, Unit
Leader Work Program must exactly <strong>the</strong> same as business unit work program.
Performance Appraisal System will provide scoring in <strong>the</strong> form <strong>of</strong> P1 for x > 110%, P2 for 103% ≤ x <
110%, P3 for 96% ≤ x < 103%, P4 for 90% ≤ x < 96%, and P5 for < 90%. P1 means <strong>the</strong> highest score
in Telkom Performance Appraisal System.
Business Unit Performance is ideally a manifestation <strong>of</strong> all employees work programs in one unit. So,
if <strong>the</strong> member <strong>of</strong> unit do not perform maximum, it will definitely affect business unit performance.
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Figure 1: Image above describes how <strong>the</strong> Telkom Performance Appraisal System works
In former implementation, <strong>the</strong> logical thinking behind <strong>the</strong> performance appraisal system above never
happened because <strong>the</strong>re was no high correlation between individual performance and business unit
performance in terms <strong>of</strong> work program. It can be seen from data below.
Table 1: Table shows difference between business and individual performance
By <strong>the</strong> way, Employee incentive which called Excellent Achiever Incentive, one <strong>of</strong> Telkom
remuneration system elements, is paid based on individual performance score. Because <strong>of</strong> former
implementation <strong>of</strong> performance appraisal system, <strong>the</strong> incentive did not seem as a reward given by
company as a form <strong>of</strong> excellent achiever in order to boost business unit performance. In fact, it treated
like a fixed benefit provided to employee without considering <strong>the</strong> contribution to business unit
achievement.
In response to <strong>the</strong> issue, company started formulating new method than can align individual
performance and business unit performance in 2007. In 2008, company declared a method as a
solution <strong>of</strong> <strong>the</strong> issue, which is called harmonization process between individual performance and
business unit performance. Telkom harmonization process method is able to synchronize between
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Yuli Purwanti et al.
individual performance score and business unit performance score. Therefore, incentive can be
optimal and meaningful for <strong>the</strong> company to motivate <strong>the</strong> employee to work beyond <strong>the</strong> limit.
However, <strong>the</strong>re is a risk in implementing <strong>the</strong> harmonization process. Continuous harmonization can
possibly impact on employee satisfaction and employee engagement particularly to performance
management system. It created new issue, which is demotivation. Company must seriously take care
<strong>of</strong> <strong>the</strong> issue.
2. Theoretical background
Employees know that appraisals form <strong>the</strong> basis <strong>of</strong> many important promotion and salary decisions.
When employees believe <strong>the</strong>y are judged fairly, <strong>the</strong>y will respect your system and view appraisal as a
way to improve <strong>the</strong>ir performance (Alexander Hamilton Institute, INC). Formal performance appraisal
plans are designed to provide systematic judgements to back up salary increases, promotions,
transfers, and sometime demotions and terminations (Douglas McGregor, 1959). David McClelland
(1987) mentioned that <strong>the</strong> motivation for maximum performance achievement is a strong incentive to
perform tasks <strong>of</strong> daily work with <strong>the</strong> best until <strong>the</strong>y get predicate commendable.
According to Wellins, Bernthal and Phelps (2006) right employees in right jobs, exceptional leadership
and organizational systems and strategies are <strong>the</strong> key employee engagement drivers. An
organization drives engagement by leveraging three sources <strong>of</strong> influences for change employees,
leaders and organizational systems and strategies. Such as fostering engagements are for example
hiring, promotion, performance management, recognition, compensation, training and career
development. Zachary Dechev hypo<strong>the</strong>sis is “There is correlation between clear purpose and
understanding <strong>of</strong> performance appraisal and <strong>the</strong> level <strong>of</strong> satisfaction and staff engagement. Fair
evaluation <strong>of</strong> an employee's performance is an important criterion for determining <strong>the</strong> level <strong>of</strong>
employee engagement. The company which follows an appropriate performance appraisal technique
(which is transparent and not biased) will have high levels <strong>of</strong> employee engagement (Nitin Vazirani,
2007).
3. Harmonization process between individual performance and business unit
performance
Generally, harmonization step process is as follows:
Unit Leader provides Previous Individual Performance Score (NA awal) based on employee's
target achievement.
The Previous Individual Performance Score from all employees in one unit is calculated in
average = Averaged NA.
The next process is Calculating deviation a constant (k Dev = Business Unit Performance (NKU)
– Averaged NA)
The we convert to final score; NA awal + K Dev = NA akhir
Final score converted to performance value with referencing to <strong>the</strong> specified table (P1, P2, P3, P4
and P5).
As illustration, <strong>the</strong> following is example <strong>of</strong> harmonization process. Supposed that in one unit, <strong>the</strong>re are
7 (seven) employees with business performance score is 102.
Table 2: Table describes how <strong>the</strong> harmonization process is to be done
NA awal Rata-Rata Konstanta Konversi Nilai
NA awal Deviasi NA Akhir Prestasi
(1) (2) (3) = Average (2) (4)=NKU - (3) (5) = (2) + (4) (6)
A 110 -3 107 P2
B 108 -3 105 P2
C 112 -3 109 P2
D 106 105
-3 103 P3
E 106 -3 103 P3
F 98 -3 95 P4
G 95 -3 92 P4
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Table below is comparison score between before using harmonization process and after <strong>the</strong>
implementation in 2008 and 2009.
Table 3: Table shows <strong>the</strong> comparison score between before and after <strong>the</strong> harmonization process
Harmonization process forces individual performance score to get closer with business unit
performance score. Disadvantage <strong>of</strong> <strong>the</strong> harmonization process is <strong>of</strong>ten involved with compromise
between unit leader and employee unit. Harmonization process was designed with <strong>the</strong> reference <strong>of</strong>
normal distribution which <strong>the</strong>oretically means employee will be clustered in outstanding, average, and
underperformed. To avoid underperformed employee performance score, unit leader usually pulls
down <strong>the</strong> score <strong>of</strong> outstanding clustered employee so <strong>the</strong> employees <strong>of</strong> <strong>the</strong> unit will be clustered in
average or equal to business unit performance score. Therefore, some employees might feel satisfied
and some might feel been cheated.
4. Harmonization process and it's impact on employee engagement problem
analysis
As already explained above in general, <strong>the</strong> inability <strong>of</strong> unit leader in implementing harmonization
process will consistently leads to compromise that can be benefiting employee but can harm o<strong>the</strong>r
employee. Based on harmonization process conducted in 2008 and 2009, employees who were
undergoing a process <strong>of</strong> decline in scores after harmonization was approximately 80%. The condition
needs serious attention from company due to apathy towards work achievement. Employee might
think that achieving target or not will provide <strong>the</strong> same score for <strong>the</strong> employee. The disappointment
towards performance appraisal will possibly affect on employee satisfaction and engagement.
Telkom conducts Employee Opinion Survey to measure satisfaction and engagement, which one <strong>of</strong>
<strong>the</strong> dimensions is performance appraisal system. Table below shows outcome <strong>of</strong> Employee Opinion
Survey from 2007 to 2009.
Table 4: Results <strong>of</strong> <strong>the</strong> employee opinion survey
Based on <strong>the</strong>se results, it showed that employee satisfaction level in 2008 dramatically dropped. At
that time, employees shocked with <strong>the</strong> implementation because individual performance score
adjusted with <strong>the</strong> business unit performance score. Many employees experienced decreasing in
individual performance score. Although harmonization process still implemented in 2009, <strong>the</strong>
satisfaction level went up. Management realized that harmonization process must be implemented
carefully in order not to cause any worse issue than unsynchronized between individual performance
score and business performance score, which is decreasing in employee engagement that will impact
in motivation and quality <strong>of</strong> work. Those two will ultimately impact on company’s business
performance. Therefore, management must take preventive steps to avoid negative impact in
conducting harmonization as follows:
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Yuli Purwanti et al.
Communicate policy <strong>of</strong> harmonization process to all employees before implementation
Provide time for employees to understand <strong>the</strong> intention and purpose <strong>of</strong> harmonization process
Instruct all unit leaders to provide adequate counseling time in setting <strong>the</strong> initial score <strong>of</strong> individual
performance
Instruct all employees to prepare individual work plan refer to unit work plan and take counseling
time to revise if <strong>the</strong>re is change in implementation
Various efforts to prevent <strong>the</strong> possibility <strong>of</strong> decreasing level <strong>of</strong> satisfaction and engagement due to
harmonization process has been done. However, it does not guarantee that similar negative impact
will arise in <strong>the</strong> future. Some proposed solutions are expected to anticipate <strong>the</strong> issue above, such as:
Management:
Evaluate whe<strong>the</strong>r <strong>the</strong> harmonization can be applied in <strong>the</strong> long term or not
Conduct Employee Opinion Survey towards harmonization process
Monitor establishment <strong>of</strong> individual work plan to keep aligned with business work plan so <strong>the</strong>re
will be significant difference
Monitor harmonization process in <strong>the</strong> unit so <strong>the</strong>re will be no compromise that adversely affect
outstanding employee
Provide reward for unit with insignificant difference between average individual performance and
business unit performance
Employee:
Provide inputs to improve harmonization process in performance appraisal system
Establish individual work plan that support in achieving target <strong>of</strong> business unit performance
Participate in monitoring <strong>the</strong> occurrence <strong>of</strong> fraud or compromise on harmonization process
5. Conclusion
Harmonization Process still can be used as a tool for aligning individual performance score and
business unit performance score
Implement continuous improvement should be reconsidered because it possibly affects
satisfaction and engagement. Employee might feel be constrained in achieving performance
individual score.
Harmonization process does not need anymore if individual work plan aligns with unit work plan.
The difference between individual performance score and business unit performance will not be
significant.
6. Recommendation
Harmonization process should only be treated as one <strong>of</strong> organization learning process that aims
<strong>the</strong> employee awareness <strong>of</strong> <strong>the</strong> important <strong>of</strong> alignment between individual performance and
business unit performance
Need to increase <strong>the</strong> role <strong>of</strong> unit leader in conducting counseling so employee target achievement
supports business unit achievement as well as on setting program and implementing program.
Propose reward program for appreciating unit with <strong>the</strong> lowest deviation between average
individual performance and business unit performance
References
_________”How to counsel your manager through performance appraisal”, Alexander Hamilton Institute.
Archie Thomas, CMA, and Ann MacDi anmid (2004), “Encouraging Employee Engagement”, CMA Management.
Jteresko (2004), “Driving Employee Engagement”, www.industryweek.com.
McClelland, David C. (1987),”Human Motivation” The Press Syndicate <strong>of</strong> <strong>the</strong> University <strong>of</strong> Cambridge.
Mc. Gregor, Douglas (1959), “An Uneasy Look at Performance Appraisal”, Harvard Business Review.
Nitin Vazirani (2007), “Employee Engagement”, SIES College <strong>of</strong> Management Studies Nerul.
Zachary Dechev (2010), “Effective Performance appraisal – a Study Into The Relation Between Employer
Satisfaction and Optimizing Business Results”, Erasmus University Rotterdam.
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Theoretical and Practical Aspects <strong>of</strong> Implementation <strong>of</strong>
Intellectual Capital Approaches for Sustainable Economic
Development
Nargiza Abdullaeva 1 and Campbell Warden 2
1 The University <strong>of</strong> World Economy and Diplomacy, Tashkent, Uzbekistan
2 Instituto de Astr<strong>of</strong>isica de Canarias, Tenerife, Spain
Nargiza_abdullaeva@yahoo.com
campbell@iac.es
Abstract:
All that is valuable in human society depends upon <strong>the</strong> opportunity for development accorded <strong>the</strong>
individual. Albert Einstein
The dynamics <strong>of</strong> <strong>the</strong> development <strong>of</strong> Intellectual Capital (IC) approaches <strong>of</strong>fer new horizons for establishing and
fostering economic development. For <strong>the</strong> countries with a low level <strong>of</strong> income <strong>the</strong> development and
implementation <strong>of</strong> <strong>the</strong>se approaches are <strong>of</strong> considerable interest to both government and private sectors. In view
<strong>of</strong> this, <strong>the</strong>re is a need for research development <strong>of</strong> not only <strong>the</strong>oretical aspects <strong>of</strong> IC approaches, but also <strong>the</strong>
study <strong>of</strong> <strong>the</strong> practical side <strong>of</strong> international experience <strong>of</strong> IC methods implementation. This will be crucial in <strong>the</strong>
programmes to support and foster countries’ economic development. Assuring sustainable development is one <strong>of</strong>
<strong>the</strong> key issues <strong>of</strong> human and economic development. It includes governmental and <strong>the</strong> private sector’s support <strong>of</strong>
economic, social and cultural development <strong>of</strong> <strong>the</strong> nation by <strong>the</strong> use <strong>of</strong> methods and resources in such a way as to
avoid harming future generations. From this point <strong>of</strong> view, development and implementation <strong>of</strong> new methods take
<strong>the</strong> intangible factors into consideration, which are renewable and more important for sustainable development
than those <strong>of</strong> tangible ones. Human Capital, which is supposed to be <strong>the</strong> most significant factor <strong>of</strong> development
in comparison with <strong>the</strong> social and physical factors, should be efficiently managed in terms <strong>of</strong> assuring sustainable
development <strong>of</strong> national economic, social and political systems, including sustainable economic development on
<strong>the</strong> micro, i.e. company level. Sustainable management, including Intellectual Capital Management, in its turn can
be improved by a tool such as Technology Foresight. The Paper reveals <strong>the</strong> key <strong>the</strong>oretical and practical aspects
<strong>of</strong> Intellectual Capital Approaches dynamics for assuring sustainable economic development. The use <strong>of</strong> a
comparative method in <strong>the</strong> Paper helps to investigate <strong>the</strong> differences in <strong>the</strong> approaches in Intellectual Capital in
gaining <strong>the</strong> results <strong>of</strong> sustainability <strong>of</strong> economic development. The interdisciplinary character <strong>of</strong> <strong>the</strong> Research
makes <strong>the</strong> results more interesting and helps to combine and solve <strong>the</strong> social and economic issues, which are
significantly related to each o<strong>the</strong>r. The results <strong>of</strong> <strong>the</strong> Paper can be used by academics and government
organizers and practitioners, involved in activities related to IC and economic development, in <strong>the</strong> aims <strong>of</strong> fur<strong>the</strong>r
development and implementation <strong>of</strong> <strong>the</strong> ideas and results <strong>of</strong> <strong>the</strong> research.
Keywords: intellectual capital, economic development, sustainable development, dynamics
1. Intellectual capital and sustainable economic development: Theoretical
overview
Economic Development (ED) is one <strong>of</strong> <strong>the</strong> strategic goals <strong>of</strong> any country’s development, while it
implies <strong>the</strong> process <strong>of</strong> improving <strong>the</strong> wealth <strong>of</strong> <strong>the</strong> nation, including, on <strong>the</strong> one hand, <strong>the</strong>
enhancement <strong>of</strong> people’s living standards, and on <strong>the</strong> o<strong>the</strong>r, growth <strong>of</strong> <strong>the</strong> country’s economic,
political and social performance. ED results in <strong>the</strong> progress <strong>of</strong> those countries with low-income status
towards a high-income one, from an agriculture-based economy to industrial, service and knowledgebased
economies. While economic growth is <strong>the</strong> main component <strong>of</strong> economic development, it does
not always result in ED, for several reasons, including inefficient social policy, demographic growth
that is higher than economic growth, and so on.
There are different preconditions and causes/factors <strong>of</strong> economic growth, such as <strong>the</strong> level <strong>of</strong>
democratic values <strong>of</strong> <strong>the</strong> society, natural resources endorsement, institutional infrastructure
development level (such as rule <strong>of</strong> law, trust and honesty, good governance, etc). At <strong>the</strong> same time,
Human Capital (HC) is acknowledged as <strong>the</strong> most significant driver <strong>of</strong> economic growth and
development. The dynamics <strong>of</strong> HC <strong>the</strong>ory helped to develop Intellectual Capital (IC) <strong>the</strong>ory, which
embraces o<strong>the</strong>r types <strong>of</strong> capital, created by human’s intellect. In o<strong>the</strong>r words, we can consider HC as
a component <strong>of</strong> IC, Organizational Capital as its infrastructure and Relational Capital as a connection
between links <strong>of</strong> human-human, human-organizational capitals.
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Nargiza Abdullaeva and Campbell Warden
The research involved in <strong>the</strong> implementation <strong>of</strong> issues <strong>of</strong> IC in sustainable economic development is
related to several interrelated and interdisciplinary realms.
Firstly, clearly defining Intellectual Capital and Economic Development and <strong>the</strong>ir components, which
is not easy because <strong>of</strong> <strong>the</strong>ir abstract and complex character.
Secondly, <strong>the</strong> measurement issues <strong>of</strong> IC and ED.
Thirdly, <strong>the</strong> IC-ED impact methodology, which is directly related to <strong>the</strong> above mentioned realms.
Researching <strong>the</strong>se questions in this Paper in general, <strong>the</strong> results <strong>of</strong> <strong>the</strong> practical overview <strong>of</strong>
implementation <strong>of</strong> IC on sustainable economic development are presented. At <strong>the</strong> end <strong>the</strong> short
results <strong>of</strong> <strong>the</strong> ongoing research are given, as well as a list <strong>of</strong> fur<strong>the</strong>r questions to be investigated.
Definition and dynamics <strong>of</strong> IC
There is no single definition <strong>of</strong> “Intellectual Capital” and its components among scientists. The
shortest and <strong>the</strong> most capacious IC definition was given by Stewart (1997, p. 67), which identify IC as
"packaged useful knowledge."
Intellectual Capital includes, toge<strong>the</strong>r with Human Capital, Relational and Organizational Capitals,
which are <strong>the</strong> necessary factors for <strong>the</strong> economic performance <strong>of</strong> a company and <strong>the</strong> economy as a
whole. IC includes personal experiences, skills, education and training, information technologies,
research and development, innovation, organizational intelligence, and etc. While significant research
has been done on HC starting from <strong>the</strong> 1960s, relational and organizational capitals have been less
investigated by economists due to <strong>the</strong>ir more interdisciplinary and complex character.
It should be noted that not only IC <strong>the</strong>ory is still in <strong>the</strong> process <strong>of</strong> development, but also <strong>the</strong> main
object <strong>of</strong> <strong>the</strong> <strong>the</strong>ory – Intellectual Capital itself – is going through significant changes. One <strong>of</strong> <strong>the</strong>se
changes is related to <strong>the</strong> focus shifting <strong>of</strong> IC according to time needs dynamics. According to Scandia
Navigator, <strong>the</strong> focus on financial elements as a basis <strong>of</strong> past IC had been shifted to customer, human
and process focuses, and in <strong>the</strong> future <strong>the</strong>se focuses will be shifted towards renewal and
development, i.e. more related to innovation activities.
Figure 1: Dynamics <strong>of</strong> intellectual capital focus (Scandia Navigator)
Source: Edvinsson, L.and M. S. Malone (1997), Intellectual Capital: Realizing Your Company's True
Value by Finding Its Hidden Roots. - HarperCollins Publishers, Inc., New York.
IC Components and Measurement Issues
Several difficulties arise while measuring <strong>the</strong> interrelationship between IC and economic
development.
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Nargiza Abdullaeva and Campbell Warden
First, while HC can be more clearly measured through <strong>the</strong> indicators <strong>of</strong> education, training, labour
productivity, <strong>the</strong> Structural and Relational Capitals have more abstract and qualitative characters,
which complicates <strong>the</strong> quantitative measurement procedure.
Second, due to <strong>the</strong> differences in determining <strong>the</strong> composition elements <strong>of</strong> Intellectual Capital 1 , it is
difficult to find an agreement on <strong>the</strong> common indicator <strong>of</strong> National Intellectual Capital, which is vital in
calculating <strong>the</strong> impact <strong>of</strong> IC on economic development (see Figure 2, table 1).
Figure 2: Model composition by Edvinsson and Malone (1997)
Table 1: Components <strong>of</strong> intellectual capital
Market assets
Service brands
Product brands
Corporate brands
Champions
Customers
Evangelists
Customer loyalty
Repeat business
Company name
Backlog
Distribution channels
Business collaborations
Franchise agreements
Licensing agreements
Favorable contracts
Intellectual
property assets
Patent
Copyright
Design rights
Trade secrets
Know-how
Trade marks
Service marks
Human-centered assets Infrastructure assets
Education
Vocational qualifications
Work-related knowledge
Occupational assessments
and psychometrics
Work-related competencies
Management philosophy
Corporate culture
Management processes
Information technology
systems
Networking systems
Financial relations
Source: Brooking A. Intellectual Capital: Core Asset for <strong>the</strong> Third Millennium Enterprise by Annie
Brooking, International Thomson Business Press, New York, 1996.
Preconditions, Factors and Assessment Issues <strong>of</strong> IC Impact on sustainable economic development
In <strong>the</strong> proposed methodology Organizational and Relational Capitals are supposed to be supportive
capitals, closely related to and created by Human Capital. All <strong>the</strong>se components <strong>of</strong> IC are dependent
on <strong>the</strong> quality <strong>of</strong> human capital and its development.
1 See for ex., Adriessen and Stam (2004), Bontis (2004), Malhotra (2000) are giving different composition <strong>of</strong> Structural, Process
and Organizational Capital.
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Nargiza Abdullaeva and Campbell Warden
In <strong>the</strong> impact chain below are shown <strong>the</strong> development <strong>of</strong> <strong>the</strong> basic factors/driving forces <strong>of</strong> IC and
<strong>the</strong>ir impact on <strong>the</strong> main goal (ED) through economic growth, which is <strong>the</strong> main factor <strong>of</strong> ED (see
Figure 3).
Education and Training help to create, to develop and to transfer knowledge and skills, which, in <strong>the</strong>ir
turn, are <strong>the</strong> main preconditions and factors <strong>of</strong> economic growth. And economic growth is <strong>the</strong> main
component <strong>of</strong> economic development.
Training and Skills have a more applicable character than education and knowledge and are directly
related to <strong>the</strong> value-added creation and economic growth. Training and Skills development are one <strong>of</strong>
<strong>the</strong> main driving forces <strong>of</strong> “evolutional economic growth”, or steady economic growth. At <strong>the</strong> same
time, new knowledge (innovation), based on proper education, can be <strong>the</strong> cause <strong>of</strong> “revolutionary
economic growth”, which can lead to faster economic development. This supports <strong>the</strong> significance <strong>of</strong>
both government and public R&D investments.
Education/Training and Knowledge/Skills are interrelated to each o<strong>the</strong>r, without one it is difficult to
produce <strong>the</strong> o<strong>the</strong>r.
Figure 3: Basic impact <strong>of</strong> intellectual capital on economic development through <strong>the</strong>ir driving forces
Source: Composed by authors
While assessing <strong>the</strong> impact <strong>of</strong> Intellectual Capital on economic development, it is important to take
into account that <strong>the</strong>re should be certain preconditions for <strong>the</strong> fullest implementation <strong>of</strong> <strong>the</strong> results <strong>of</strong>
IC development in economic development.
Firstly, knowledge creation is closely related to <strong>the</strong> quality, relevance and accessibility <strong>of</strong> education.
By quality <strong>the</strong> level <strong>of</strong> teaching and research undertaken at <strong>the</strong> educational institutions are implied, as
well as <strong>the</strong> relevance and compliance with <strong>the</strong> demands <strong>of</strong> <strong>the</strong> current market. At least two questions
are arising regarding this issue: Does education always lead to increased value-added, and is it
always connected to <strong>the</strong> creation <strong>of</strong> necessary for current market needs knowledge? The main
problem <strong>of</strong> <strong>the</strong> low-income developing countries is “brain-drain”, despite high budget expenditures on
education, because <strong>of</strong> low reflection <strong>of</strong> education to market requirements. In order to maintain <strong>the</strong> IC
development in <strong>the</strong>se countries, and especially, to support <strong>the</strong> conversion <strong>of</strong> its results into economic
growth and development, it is necessary to ensure <strong>the</strong> balance between supply and demand in <strong>the</strong>
education-knowledge-skills- market structure.
Secondly, <strong>the</strong> role <strong>of</strong> <strong>the</strong> government is significant in <strong>the</strong> whole “IC-ED” chain. Support <strong>of</strong> education,
knowledge and skills transfer across regional, national and international borders suppose efficient
functioning <strong>of</strong> rules and motivations, clearly defined in <strong>the</strong> legislation.
Thirdly, <strong>the</strong> level <strong>of</strong> absorption capacity <strong>of</strong> <strong>the</strong> new knowledge <strong>of</strong> <strong>the</strong> country plays an important role in
providing <strong>the</strong> base for fostering <strong>the</strong> impact <strong>of</strong> IC on ED. It is natural that <strong>the</strong> countries with
conservative mentality, low literacy/education rate, low democracy presence, have less potential in
absorption, implementation and development <strong>of</strong> new knowledge.
Fourthly, in order to enhance economic growth it is vital to provide a favourable environment for
IC/business functioning and development in <strong>the</strong> country, which is impossible without efficient
government regulation.
588

Nargiza Abdullaeva and Campbell Warden
Fifthly, it is significant to ensure and maximize <strong>the</strong> input <strong>of</strong> IC to economic development by providing
efficient social, demographic and environmental policies.
Sixthly, sustainability <strong>of</strong> economic development supposes that its main drivers should be renewable
factors, and <strong>the</strong> role <strong>of</strong> <strong>the</strong> government and society in achieving this is in maintaining <strong>the</strong> prevailing
usage and development <strong>of</strong> IC as a main factor <strong>of</strong> ED.
The assessment <strong>of</strong> <strong>the</strong> impact <strong>of</strong> IC to economic development can be done by using <strong>the</strong> National
Intellectual Capital <strong>of</strong> Andriessen and Stam (2004, see table 2) and HDI dynamics for ED. Although,
HDI dynamics do not give us <strong>the</strong> whole notion <strong>of</strong> economic development, it can show <strong>the</strong> main
changing direction <strong>of</strong> <strong>the</strong> human well-being in <strong>the</strong> country.
Table 2: Indicators for <strong>the</strong> effects <strong>of</strong> IC
Effects Human Capital Organizational Capital Relational Capital
GDP per hour worked
(as % <strong>of</strong> US)
Source: Andriessen and Stam, 2004, p.14
-Percentage <strong>of</strong>
businesses using <strong>the</strong>
Internet for purchasing
and selling
-value-added <strong>of</strong> hightech
industry, relative to
GDP
- birth rate <strong>of</strong> enterprises
The share <strong>of</strong> persons
with an equalised
disposable income below
<strong>the</strong> risk-<strong>of</strong>-poverty
threshold
-life expectancy at birth
- breadth <strong>of</strong> international
scientific collaboration
- percentage <strong>of</strong> patents
with foreign co-inventors
- export <strong>of</strong> loyalty and
license fees
- export <strong>of</strong> services
- high-tech export
Implementation <strong>of</strong> IC approaches for sustainable economic development – Practical overview
Significant research has been done on <strong>the</strong> IC impact on economic performance on <strong>the</strong> micro level.
Firer and Stainbank (2003) investigated <strong>the</strong> relationship between <strong>the</strong> IC on company’s performance
through pr<strong>of</strong>itability, productivity and market valuation variables in South Africa. The research
revealed <strong>the</strong> relationship between IC and pr<strong>of</strong>itability and productivity. Bonis et al (2000) found out
that human and customer capitals are important for <strong>the</strong> way that businesses are run, and that
structural capital positively influences a company’s performance. Riahi-Belcaoui’s (2003) research
supported <strong>the</strong> hypo<strong>the</strong>sis that IC is positively related to <strong>the</strong> company’s financial performance, through
investigation <strong>of</strong> MNCs performance in <strong>the</strong> US.
Vicious and virtuous cycles between IC investments and ED were found by EEC (1991). Barro and
Lee (1993), United Nations (2001) and World Bank (2001) found a positive relationship between IC
standards and ED levels.
At <strong>the</strong> same time, IC impact measurement on ED is related above all to overcoming <strong>the</strong> barriers <strong>of</strong>
measurement on <strong>the</strong> conception level, which were described in <strong>the</strong> <strong>the</strong>oretical part.
2. Conclusion and <strong>the</strong> questions for fur<strong>the</strong>r research
It is clear that IC is at <strong>the</strong> same time <strong>the</strong> precondition and consequence <strong>of</strong> economic development,
and HC and is created by human capital, where <strong>the</strong> structural and relational capitals are <strong>the</strong> main
drivers and receivers <strong>of</strong> economic development. Good governance, which consists <strong>of</strong> both efficient
human and organizational capitals, supports <strong>the</strong> interrelationship between IC and sustainable ED,
through development policies for IC and smoo<strong>the</strong>ning and facilitating <strong>the</strong> process <strong>of</strong> contribution <strong>of</strong> IC
to ED, through social, demographic and environmental policies.
Maintenance <strong>of</strong> <strong>the</strong> contribution <strong>of</strong> IC to ED is related to quality, relevance and accessibility <strong>of</strong>
education and training; education, knowledge and skills transfer/mobility freedom; <strong>the</strong> level <strong>of</strong>
absorption capacity <strong>of</strong> <strong>the</strong> new knowledge <strong>of</strong> <strong>the</strong> country; provision <strong>of</strong> favourable environment for
IC/business functioning and development in <strong>the</strong> country; and o<strong>the</strong>rs.
589

Nargiza Abdullaeva and Campbell Warden
Sustainability <strong>of</strong> economic development suppose that its main drivers should be renewable factors,
and <strong>the</strong> role <strong>of</strong> <strong>the</strong> government and society in achieving this is in maintaining <strong>the</strong> prevailing usage and
development <strong>of</strong> IC as a main factor <strong>of</strong> ED
For development <strong>of</strong> assessment <strong>the</strong> impact <strong>of</strong> IC to sustainable ED, it is necessary to work out <strong>the</strong>
unified IC components conception, which will help to give <strong>the</strong> common ground for <strong>the</strong> fur<strong>the</strong>r research
on calculations <strong>of</strong> National IC indicator. It would be challenging to use HDI in <strong>the</strong> calculations <strong>of</strong> IC-ED
impact in order to observe not only economic, but also social consequences <strong>of</strong> IC development.
References
Andriessen D., Stam C. (2004). The Intellectual Capital and <strong>the</strong> <strong>European</strong> Union/ Measuring <strong>the</strong> Lisbon Agenda.
Available at http://www.intellectualcapital.nl/artikelen/IC<strong>of</strong>EU_2004.pdf
Barro J. and Lee J. (1993). International Comparisons <strong>of</strong> Educational Attainment – How do national policies affect
long run growth? – <strong>Conference</strong>, Bank <strong>of</strong> Portugal – World Bank, January.
Brooking A. (1996). Intellectual Capital: Core Asset for <strong>the</strong> Third Millennium Enterprise by Annie Brooking.
International Thomson Business Press, New York.
Bontis, N., Keow W., Richardson S. (2000). Intellectual Capital and Business Performance in Malaysian
Industries. Journal <strong>of</strong> Intellectual Capital. Vol 1, #1, pp.85-100.
EEC (1991). Employment in Europe. – EEC Publishing Services. Luxemburg.
Elwood F. Holton III, B. Yamkovenko (2008). Strategic Intellectual Capital Development: A defining Paradigm for
HRD? – Human Research Development Review, Vol.7, #3, September, pp. 270-291.
Edvinsson, L., Malone M. S. (1997). Intellectual Capital: Realizing Your Company's True Value by Finding Its
Hidden Roots. HarperCollins Publishers, Inc., New York.
Firer S., Williams S.M.. Intellectual Capital and Traditional Measures <strong>of</strong> Corporate Performance. – Singapore
Management University Research Papers. Available at:
http://www.research.smu.edu.sg/faculty/cgic/Research/Research_Papers/CGICResearchPaper6.pdf
Firer S., Stainbank L. (2003). Testing <strong>the</strong> Relationship between Intellectual Capital and a Company’s
Performance: Evidence from South Africa. – Meditari Accountancy Research, Vol.11, pp.25-44. Available
at: http://www.meditari.org.za/docs/2003/25_44.pdf
Makarov P. (2010). – Intellectual Capital as an Indicator <strong>of</strong> a Sustainable Development Journal <strong>of</strong> Sustainable
Development. Vol.3, #3, September.
Malhorta, Y. (2000). Knowledge Assets in <strong>the</strong> Global Economy: Assessment <strong>of</strong> National Intellectual Capital.
Journal <strong>of</strong> Global Information Management. Vol.8, #3, pp.5-15.
Malhorta, Y. (2003). Measuring Knowledge Assets <strong>of</strong> <strong>the</strong> Nation: Knowledge Systems for Development.
UNDESA, UN. Available at: http://km.brint.com/KnowledgeManagementMeasurementResearch.pdf
Riahi-Belkaoui A. (2003). Intellectual Capital and Firm Performance <strong>of</strong> US multinational firms. Journal <strong>of</strong>
Intellectual Capital. Vol4, #2, pp.215-226.
Stewart T.A. (1997). Intellectual Capital, The New Wealth <strong>of</strong> <strong>the</strong> Nations. First edition, Nicholas Brealy
Publishing, London.
Shaffer D. F., Wright D. J. (2010). A New Paradigm for Economic Development. How Higher Education Institutes
are Working to Revitalize Their Regional and State Economies. Rockefeller Institute, March.
http://www.rockinst.org/pdf/education/2010-03-18-A_New_Paradigm.pdf
Tome E. (2004). Intellectual Capital, Social Policy, Economic Development and The World Evolution. Journal <strong>of</strong>
Intellectual Capital, 5 (4), pp.648-665
United Nations (2001). Human Development Report. – New York.
World Bank (2001). World Development Report. – New York.
590

Diagnostic Analysis <strong>of</strong> Human Capital in <strong>the</strong> University -
<strong>the</strong> Premise <strong>of</strong> Organizational Development
Andreea Feraru and Nicoleta Ciucescu
Vasile Alecsandri University <strong>of</strong> Bacau, Romania
andreea_feraru26@yahoo.com
ciucnico@yahoo.com
Abstract: Human capital development, namely, <strong>the</strong> investment in education and health, primarily aims to train
<strong>the</strong> available scientific and human resources and <strong>the</strong>n, to adapt human resources to structural changes <strong>of</strong> <strong>the</strong>
current economy. The investment in human capital in order to ensure, maintain, develop and motivate human
resources is <strong>the</strong> main premise that organizations (and universities) must capitalize. Empirical studies conducted
within <strong>the</strong> organizations have revealed a direct relationship between human capital and organizational
productivity: high-educated employees have a better health and are <strong>the</strong> unique and direct source <strong>of</strong> innovation,
creativity, and hence competitiveness. The purpose <strong>of</strong> this article is to conduct a diagnostic analysis <strong>of</strong> human
capital development and competitiveness in <strong>the</strong> universities and faculties. Thus, <strong>the</strong> present research focuses on
a quantitative and qualitative empirical approach to <strong>the</strong> issue under consideration. The present paper analyzed
<strong>the</strong> human capital in universities taking in consideration <strong>the</strong> links between education, lifelong learning and
employment and <strong>the</strong> training <strong>of</strong> scientific and human resources.
Keywords: human capital, institutional development, intellectual investments, universities, turbulent environment
1. Introduction
The issue <strong>of</strong> transition from school to work is a burden issue in <strong>the</strong> current economic restructuring
process in Romania, where a big number <strong>of</strong> young people is facing <strong>the</strong> unemployment. Therefore, <strong>the</strong>
transition from school to <strong>the</strong> labour market is governed by a new vision, called „education centered on
<strong>the</strong> labor market needs”. Graduates <strong>of</strong> higher education are those young people who have <strong>the</strong> highest
creative potential and who are expected to contribute <strong>the</strong> most to <strong>the</strong> development <strong>of</strong> <strong>the</strong> knowledge
economy.
The development <strong>of</strong> <strong>the</strong> knowledge economy where <strong>the</strong> investment in human capital is a priority and
human resources become an important asset will create prerequisites for <strong>the</strong> employment policy to
build a close relationship between education and training.
Globalization and knowledge economy expansion creates a competitive environment defined by <strong>the</strong>
criteria <strong>of</strong> efficiency, competitiveness and economic performance where <strong>the</strong> human capital develops.
Human capital consists <strong>of</strong> <strong>the</strong> characteristic abilities <strong>of</strong> individuals that remain <strong>the</strong> same in any social
environment and can be exploited on <strong>the</strong> labour market in exchange for any kind <strong>of</strong> economic
resources.
Within <strong>the</strong> higher education system <strong>the</strong> human capital refers to all <strong>the</strong> academics (in terms <strong>of</strong>
knowledge, experience, skills and <strong>the</strong>ir individual talent) and <strong>the</strong> number <strong>of</strong> students involved in <strong>the</strong>
educational process. Students’ education is done through <strong>the</strong> transmission and <strong>the</strong> development <strong>of</strong>
basic and specialized <strong>the</strong>oretical knowledge.
Human capital concept reflects <strong>the</strong> investment in education and <strong>the</strong> development <strong>of</strong> competencies
and skills necessary to perform certain economic activities. Basically, human capital consists <strong>of</strong>
educational capital (skills acquired by individuals while <strong>the</strong>y are enrolled in a school but also <strong>the</strong> skills
acquired outside <strong>the</strong> school) and biological capital (physical abilities <strong>of</strong> individuals, most <strong>of</strong>ten
syn<strong>the</strong>sized as <strong>the</strong> health status). Universities distinguish from o<strong>the</strong>r education and training
institutions because <strong>the</strong>y increase knowledge and generate graduates and researchers with creative
and innovative potential.
The research on <strong>the</strong> relationship between <strong>the</strong> education and <strong>the</strong> development <strong>of</strong> human capital is
included in social and organizational research. Our paper has <strong>the</strong> following structure:
Defining scope, objectives, identification <strong>of</strong> expected results;
Defining <strong>the</strong> main concepts <strong>of</strong> human capital, investment in education, training, labor market
insertion
591

Andreea Feraru and Nicoleta Ciucescu
Making a diagnostic analysis <strong>of</strong> academic human capital.
2. Analysis <strong>of</strong> human capital development in university
The term human capital reflects <strong>the</strong> investment in education and <strong>the</strong> development <strong>of</strong> adequate
aptitudes for <strong>the</strong> labour process. (Bratianu C., page 19)
Economists consider that investment in education produces human capital, by analogy with <strong>the</strong>
investment in physical capital used in industrial enterprises. Human capital develops progressively
within <strong>the</strong> formal frame <strong>of</strong> <strong>the</strong> school, in <strong>the</strong> family, within <strong>the</strong> organization, and through individual
efforts <strong>of</strong> study and reflection.
An analysis <strong>of</strong> human capital development in universities is <strong>of</strong> interest in <strong>the</strong> context <strong>of</strong> dynamic
changes <strong>the</strong> Romanian higher education goes through. The analysis focused on <strong>the</strong> educational
capital and on two main categories <strong>of</strong> human involved in <strong>the</strong> educational process such as: students /
graduates and academic staff. Human capital development contributes to increase competitiveness
by linking education and lifelong learning with <strong>the</strong> labor market and providing higher opportunities to
participate in a modern and flexible labor market.
Experts believe that qualitative education systems develop students’ creativity, innovation and <strong>the</strong>ir
ability to apply knowledge in various practical situations. Graduates who will miss such skills are at
risk <strong>of</strong> unemployment, social exclusion and poverty. Human capital and hence investment in human
capital - particularly <strong>the</strong> investment in education - determines <strong>the</strong> employees’ wages and <strong>the</strong>
employment prospects.
2.1 Lifelong learning-education-labor market
The creation <strong>of</strong> links between higher education and employment is a prerequisite for human capital
development in order to achieve economic performance and competitiveness. The present paper
analyzed a University from <strong>the</strong> North-East <strong>of</strong> Romania which is characterized as a mixed and flexible
organization, focused on students and labor market developments. It aims to train pr<strong>of</strong>essionals
according to current requirements <strong>of</strong> <strong>the</strong> Romanian and <strong>European</strong> Union labour market. The main
objectives <strong>of</strong> <strong>the</strong> university teaching staff are:
To train specialists for research, education and socio-economic and cultural activities;
To train <strong>the</strong> graduates in order to provide continuous education programs
To integrate into <strong>the</strong> national and international academic community
To create and develop competitive research teams.
Therefore, a major goal is to balance <strong>the</strong> University's educational <strong>of</strong>fer and <strong>the</strong> requirements <strong>of</strong> <strong>the</strong>
labor market.
A class <strong>of</strong> students enrolled for Bologna bachelor’s degree (3 years study programs) was analyzed in
order to highlight <strong>the</strong>se objectives. The data are presented in table 1 and <strong>the</strong> interpretation <strong>of</strong>
graphical results is presented in figure 1.
Table 1: Students enrolled in college degree programs in <strong>the</strong> 2005-2006 academic year compared to
students who have graduated license program in 2008-2009
University Structure Students enrolled in college degree
programs in <strong>the</strong> 2005-2006 academic
year
Number <strong>of</strong> graduates from public
education, <strong>the</strong> faculty in 2008-2009
Faculty 1 (F1) 196 133
Faculty 2 (F2) 790 684
Faculty 3 (F3) 334 222
Faculty 4 (F4) 163 99
Faculty 5 (F5) 472 394
Faculty 6 (F6) 61 45
Total 2016 1577
592

number
900
800
700
600
500
400
300
200
100
0
196
133
Andreea Feraru and Nicoleta Ciucescu
790
684
334
222
F1 F2 F3 F4 F5 F6
faculty
Figure 1: Students enrolled in college degree programs in <strong>the</strong> 2005-2006 academic year compared to
students who have graduated license program in 2008-2009
The total number <strong>of</strong> graduates in 2009 was <strong>the</strong> 1577, a decrease <strong>of</strong> 21.8% compared with 2016
students enrolled at <strong>the</strong> beginning <strong>of</strong> <strong>the</strong> academic year 2005-2006, (-439 students).
This decrease was due to numerous reasons such as:
Abandoning <strong>the</strong> Bachelor studies for various reasons;
Expelling students due to <strong>the</strong> non-payment <strong>of</strong> education fees, not signing study contracts/
addendum in due time, to failing <strong>the</strong> didactic activities.
The table no. 2 reflects <strong>the</strong> number <strong>of</strong> graduates <strong>of</strong> <strong>the</strong> Bachelor degree in <strong>the</strong> year 2008-2009 at <strong>the</strong>
analyzed University and indirectly, <strong>the</strong> importance <strong>of</strong> academic education for acquiring <strong>the</strong> necessary
skills for <strong>the</strong> integration into <strong>the</strong> labor market.
Table 2: Number <strong>of</strong> graduates integrated into <strong>the</strong> labor market according to <strong>the</strong> specialty obtained
after completion <strong>of</strong> Bachelor studies
University Structure Number <strong>of</strong> integrated graduates into <strong>the</strong> labour market
163
Faculty 1 (F1) 31
99
472
Faculty 2 (F2) 261
Faculty 3 (F3) 42
Faculty 4 (F4) 21
Faculty 5 (F5) 181
Faculty 6 (F6) 15
Total 551
University aims to train students who become tolerant graduates, able to keep pace with <strong>the</strong> changes
produced in <strong>the</strong> world economy system and able to work in interdisciplinary areas. From <strong>the</strong> total
number <strong>of</strong> 2008-2009 graduates, namely 1577, only 551 <strong>of</strong> <strong>the</strong>m managed to integrate into <strong>the</strong> labor
market, in accordance with <strong>the</strong> specialization <strong>the</strong>y obtained after passing <strong>the</strong> license examination.
The graduates’ difficulties in finding a proper and convenient job can be explained by <strong>the</strong> successive
reforms <strong>of</strong> <strong>the</strong> higher education system and <strong>the</strong> changes in <strong>the</strong> labour market. The slow pace <strong>of</strong>
economic growth and <strong>the</strong> difficulty <strong>of</strong> generate new jobs lead to a low demand <strong>of</strong> work force and
<strong>the</strong>refore <strong>of</strong> human capital.
593
394
61
45

Andreea Feraru and Nicoleta Ciucescu
2.2 Pr<strong>of</strong>essional and scientific training <strong>of</strong> human capital in <strong>the</strong> University
Ano<strong>the</strong>r topic <strong>of</strong> analyze is <strong>the</strong> quality <strong>of</strong> human capital as a key element in organizational
development.
Insert number <strong>of</strong> graduates in <strong>the</strong> labor market
300
250
200
150
100
50
0
31
261
42
F1 F2 F3 F4 F5 F6
faculty
Figure 2: Number <strong>of</strong> integrated graduates into <strong>the</strong> labor market in accordance with <strong>the</strong> specialty
obtained after completion <strong>of</strong> Bachelor studies
Pr<strong>of</strong>essional training is a process <strong>of</strong> learning by which people acquire new <strong>the</strong>oretical and practical
knowledge but also skills and techniques which contribute to <strong>the</strong> efficiency <strong>of</strong> <strong>the</strong>ir work. (Mathis R.,
Jackson H.J., 1994)
Pr<strong>of</strong>essional training, besides o<strong>the</strong>r activities, is part <strong>of</strong> a comprehensive and long- lasting process,
namely, <strong>the</strong> continuing education. Continuing education takes place during all <strong>the</strong> active life and
consists <strong>of</strong> all training programs aiming <strong>the</strong> carrying on <strong>of</strong> a job in good conditions.
The university's teaching staff is represented by doctors and doctoral students in a variety <strong>of</strong> fields
such as engineering, ma<strong>the</strong>matics, economics, marketing, movement sciences, accounting, economic
informatics, law, humanities, foreign languages, psychopedagogy. The structure <strong>of</strong> permanent
teaching staff in <strong>the</strong> university, distributed on faculties according to <strong>the</strong> academic rank is represented
in <strong>the</strong> following table.
Table 3: Structure <strong>of</strong> permanent teachers in <strong>the</strong> university distributed on faculties according to
academic rank
University Structure
Faculty 1 (F1)
Faculty 2 (F2)
Faculty 3 (F3)
Faculty 4 (F4)
Faculty 5 (F5)
Faculty 6 (F6)
Total
Pr<strong>of</strong>essors Lecturers
Assistant
pr<strong>of</strong>essors
21
181
15
Junior
Lecturer Instructors Total
3 9 15 15 1 43
18 11 13 15 8 65
9 6 10 9 12 46
4 7 6 10 3 30
3 7 10 10 2 32
1 2 2 2 1 8
38 42 56 61 27 224
Figure 3 represents <strong>the</strong> number <strong>of</strong> <strong>the</strong> university teaching staff (224 people) distributed according to
<strong>the</strong> academic rank in <strong>the</strong> academic year 2009-2010.
594

Andreea Feraru and Nicoleta Ciucescu
The percentage (35%) <strong>of</strong> pr<strong>of</strong>essors and lecturers from <strong>the</strong> total university teaching staff represents
an acceptable percentage <strong>of</strong> specialized teaching staff. The teaching staff also conducts scientific
research activities which are published in foreign and Romanian specialty journals.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
The structure <strong>of</strong> teachers teaching in <strong>the</strong> university between
2009-2010
1
15
15
9
3
8
15
13
11
18
12
9
10
6 7
9
3
10
2
10
6 10
7
1
2
2
2
4 3 1
F1 F2 F3 F4 F5 F6
faculty
Instructors 27
Junior Lecturer 61
Assistant pr<strong>of</strong>essors 56
Lectures 42
Pr<strong>of</strong>essors 38
Figure 3: Structure <strong>of</strong> university teaching staff according to academic rank distributed on faculties
3. Conclusions
Universities educate and train future graduates in <strong>the</strong> spirit <strong>of</strong> a modern vision, specific to <strong>the</strong> market
economy. The diagnosis <strong>of</strong> university human capital focuses on teaching staff (<strong>the</strong> size, <strong>the</strong>
qualification, <strong>the</strong> structure and <strong>the</strong> pr<strong>of</strong>essional training) and on graduates (percentage <strong>of</strong>graduates
that were inserted into <strong>the</strong> labor market in a position requiring <strong>the</strong> specific specialization obtained after
<strong>the</strong> completion <strong>of</strong> <strong>the</strong>ir Bachelor degree) from a university from <strong>the</strong> North-East <strong>of</strong> Romania. The higher
education system underwent many changes but it has to integrate <strong>European</strong> standards and
regulations as Romania is an EU member from 2007. Universities need a better knowledge <strong>of</strong> <strong>the</strong>
labour market realities in order to make an adequate coordination between <strong>the</strong>ir academic studies
and <strong>the</strong> occupations that require a higher level <strong>of</strong> education. In addition, <strong>the</strong> follow-up <strong>of</strong> <strong>the</strong> time <strong>of</strong>
<strong>the</strong> graduates’ insertion on <strong>the</strong> labour markets creates a good basis <strong>of</strong> information between
employment and tertiary education.
References
Bârgăoanu A., Negrea E., Călinescu L. (2007) - Project-oriented university - an emerging concept, Management
& Marketing, 4(4), pp 55-64.
Becker, G. (1997) - Capitalul uman. O analiză teoretică şi empirică cu referire specială la educaţie, Editura All,
Bucureşti.
Brătianu, C. (2005b) - Schimbarea de paradigmă în managementul universitar românesc, Revista de
Management şi Inginerie Economică, 4 (3):7-23.
Brătianu, C. (2008) - Leadership and management in <strong>the</strong> transition romanian higher education system,
Management & Marketing, 4(2), pp. 21-36.
Brătianu, C. (2006) - Un model de analiză a capitalului intelectual organizaţional, Management & Marketing, 1(3),
pp. 17-32.
Brătianu, C., Jianu I. (2007) - The vision and mission <strong>of</strong> <strong>the</strong> university. Case study, Management & Marketing,
4(2), pp 37-46.
Brătianu, C., Lefter, V. (2001) - Managementul strategic universitar. Bucureşti: Rao.
Brătianu, C., Vasilache S. (2009) - Implementing innovation and knowledge management in <strong>the</strong> romanian
economy, Management & Marketing, Vol. 4, No. 4, pp. 3-14.
Brătianu, C., Vasilache S. (2009) - Evaluating linear-nonlinear thinking style. For knowledge management
education, Management & Marketing, Vol. 4, No. 3, pp. 3-18.
Bouchardy I. (2010) - Quality strategies: what are french universities. Looking for?, Management & Marketing,
Vol. 5, No. 1, pp. 39-56.
Feraru A. (2009) - The concept <strong>of</strong> knowledge and knowledge <strong>the</strong> management in <strong>the</strong> Romanian business field,
Studies and Scientific Researches - Economic Edition, Issue 14, pp. 137-141.
Feraru A. (2010) - Knowledge management within organisations, Annals <strong>of</strong> <strong>the</strong> Oradea University. Fascicle <strong>of</strong>
Management and Technological Engineering, Volume IX (XIX), NR1, pp 157-160.
Leitner K-H. (2002) - Intellectual capital reporting for universities: Conceptual background and application within
<strong>the</strong> reorganization <strong>of</strong> Austrian universities.
595

Andreea Feraru and Nicoleta Ciucescu
Mathis L.R., Jackson H.J. (1994) -Human resource management, West Publishing Corporation.
Nicolescu O., Nicolescu L. (2005), - Economia, firma şi managementul bazate pe cunostinţe,Bucureşti, Editura
Economică.
Nonaka, I., Takeuchi, H. (1995) - The Knowledge Creating Company: How Japanese Companies Create <strong>the</strong>
Dynamics <strong>of</strong> Innovation. Oxford University Press, New York.
Petrash G. (2002) - KnowledgeManagement. Classic and Contemporary works, Masschusetts Institute <strong>of</strong>
Tehnology.
Roşca Ion Gh., Păunescu C., Pârvan C. (2010) - Shaping <strong>the</strong> future <strong>of</strong> higher education in Romania: Challenges
and driving factors, Management & Marketing, Vol. 5, No. 1, pp. 57-70.
596

The Contribution <strong>of</strong> <strong>the</strong> Organizational Culture for <strong>the</strong>
Development <strong>of</strong> Human Capital in Non-Pr<strong>of</strong>it System
Roxana Mironescu
Vasile Alecsandri University <strong>of</strong> Bacau, Romania
roxy_mironescu58@yahoo.com
Abstract: This paper comes to meet <strong>the</strong> need to streng<strong>the</strong>n a new type <strong>of</strong> organizational culture, corresponding
to <strong>the</strong> current stage <strong>of</strong> <strong>the</strong> Romanian development in <strong>the</strong> non-pr<strong>of</strong>it system. The goal is to find and to dedicate
new values and components <strong>of</strong> an organizational culture,based on <strong>the</strong> relationship between managers and
employees which have new opportunitiesfor work and prosperity. The work is framed in <strong>the</strong> context <strong>of</strong> new
concerns for <strong>the</strong> foundation <strong>the</strong> corporate culture <strong>of</strong> academia, and o<strong>the</strong>r non-pr<strong>of</strong>it organizations as part <strong>of</strong> <strong>the</strong>
need to adapt corporate culture in Romania. New mutations occurred in <strong>the</strong> economics and social field after <strong>the</strong>
integration <strong>of</strong> our country in <strong>the</strong> <strong>European</strong> Union and in <strong>the</strong> globalized world, <strong>the</strong>re were new approaches in <strong>the</strong>
educational, health, social, cultural missions, which are claiming from <strong>the</strong> people involved in <strong>the</strong>se fields
unificated efforts, coordination <strong>of</strong> <strong>the</strong> creation <strong>of</strong> new corporate culture in which managers and employees regain
<strong>the</strong>ir moral values and benchmarks. To complete <strong>the</strong> study, <strong>the</strong> most suitable methods are <strong>the</strong> systematic
observation and a quantitative and qualitative analysis which may furnish specific data necessary to extract some
relevant findings. The main results obtained from empirical observations are partial and require fur<strong>the</strong>r verification
by extending <strong>the</strong> search in a scientific method. <strong>the</strong> most suitable methods are and systematic observation and a
quantitative and qualitative analysis which may furnish specific data necessary to extract some relevant findings.
The main results obtained from empirical observations are partial and require fur<strong>the</strong>r verification by extending <strong>the</strong>
search in a scientific method. A successful organizational culture may pay particular attention to ethics. The main
purpose <strong>of</strong> an activity, includes values such as honor, honesty, fairness, which must be placed in top <strong>of</strong>
managerial preoccupations. They provide security and safe business, reliabil organization, stable business
relationships and trust income (possibly less, but more secure), so <strong>the</strong> ethical management may be pr<strong>of</strong>itable in
<strong>the</strong> long term. The relationship between an organizational culture and <strong>the</strong> economic performance is done by
motivation, loyalty and creativity. Successful team leadership, will be partially, induced by <strong>the</strong> individual ability to
ethically determine different people and develop trust between <strong>the</strong> leader and <strong>the</strong> o<strong>the</strong>r team members, among
all <strong>the</strong> crew. In this context, <strong>the</strong> cultural change within organizations is indissolubly linked or complete <strong>the</strong>
conservation <strong>of</strong> cultures and traditional values. Managers and leaders face major issues within organizations,
ei<strong>the</strong>r multicultural both local ones, linked to <strong>the</strong> cultural adaptation to deeper or superficial changes.
Keywords: corporate culture, non-pr<strong>of</strong>it organization, human capital, successful team, ethical management
1. Introduction
Currently, Romania is going through a complex set <strong>of</strong> turbulent and <strong>of</strong>ten paradoxical transformations,
at all <strong>the</strong> levels <strong>of</strong> society, including all types <strong>of</strong> organizations. The confusion between <strong>the</strong> desire for
stability and change, simultaneously manifested, <strong>the</strong> lack <strong>of</strong> stable hierarchy <strong>of</strong> values, which should
fill a gap <strong>of</strong> 50 years, <strong>the</strong> need to discover new meanings and new directions for work and life, <strong>the</strong>
desire to copy Western democracies mechanisms are some <strong>of</strong> <strong>the</strong> most important characteristics <strong>of</strong>
<strong>the</strong> Romanian society. At <strong>the</strong> national level, in <strong>the</strong> organizational culture, people still retain <strong>the</strong>ir
conservative rustic essence, which is based on basic assumptions and beliefs manifested in legends,
myths, heroes, symbols and superstitions more than 2,000 years old. Romanian society has
experienced that cultural change is nei<strong>the</strong>r easy nor quick, both at <strong>the</strong> national and at <strong>the</strong>
microeconomic level <strong>the</strong>re are critical factors that makes <strong>the</strong>ir mark on <strong>the</strong> way <strong>of</strong> developing <strong>the</strong>
economy and society. Today, in Romania, we can identify two distinct types <strong>of</strong> organizational culture -
bureaucratic culture and entrepreneurial culture, supporting <strong>the</strong> hypo<strong>the</strong>sis that <strong>the</strong>se two categories
are <strong>the</strong> extremes <strong>of</strong> a present time, with a wide variety <strong>of</strong> expression. Bureaucratic culture is typical
for state-owned companies, companies undergoing privatization, <strong>the</strong> former state companies during
privatization, autonomous companies, educational institutions and state sponsored health, or public
institutions, military institutions. It still can be characterized as strong, inertial, focussed to extreme
consequences within <strong>the</strong> system and <strong>the</strong> country's political life. Entrepreneurial culture, is typical for
private firms, founded since 1989. Cultural immobility is a characteristic for <strong>the</strong> bureaucratic
organizations which decrease <strong>the</strong>ir performance, with negative effects for <strong>the</strong> entire Romanian
economy - a high rate <strong>of</strong> inflation and unemployment, high level <strong>of</strong> taxes, higher rate <strong>of</strong> prices /
wages, In <strong>the</strong> bureaucratic nature <strong>of</strong> cultures, <strong>the</strong>re is no significant difference between proclaimed
real values and actions. This is not only leading to more confusion, distrust and lack <strong>of</strong> respect within
organizations and it is creating a communicative gap between management and lower echelons, but
also it is an extremely dangerous phenomenon, because any positive cultural change, any activity can
not develop performance than in a communicative framework based on respect, openness and trust.
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Roxana Mironescu
This could be <strong>the</strong> cause <strong>of</strong> hostile relations between members <strong>of</strong> <strong>the</strong> organizations, between
employees and managers especially, when <strong>the</strong> management does not prove pr<strong>of</strong>essionalism and
employees have an apathic attitude towards work, <strong>the</strong> latter having a disastrous impact on labour
productivity. Today, entrepreneurial culture is crystallized in private firms, in nonpr<strong>of</strong>it
organizations,such as associations or foundations, placed in education, health, social services
culture, religion, environmental protection, founded after <strong>the</strong> creation <strong>of</strong> free market mechanisms in
Romania. The effort shows <strong>the</strong> great importance <strong>of</strong> building a new significance, by promoting values
such as respect and consideration for customers, employees and communities, concern for <strong>the</strong> quality
<strong>of</strong> <strong>the</strong> <strong>of</strong>fered products and services, creativity, contribution and involvement, ethical management,
courage, openness and personal development . In <strong>the</strong> new entrepreneurial culture, feelings such as
helplessness and lack <strong>of</strong> control over <strong>the</strong>ir actions are replaced with more confidence and
participation, and fear begins to disappear due to <strong>the</strong> open recognition <strong>of</strong> <strong>the</strong> fact that errors are part
<strong>of</strong> human nature and facilitate opportunities to decide, to take risks and responsibilities.
2. Research utility
This study may be useful for members <strong>of</strong> <strong>the</strong> academic community ,nonpr<strong>of</strong>it organizations managers,
o<strong>the</strong>r private entities managers, awareness <strong>of</strong> new aspects <strong>of</strong> <strong>the</strong> corporate life and <strong>the</strong> changes in
<strong>the</strong> value system and <strong>the</strong> mentality <strong>of</strong> young or elder employees. Work methodology reveales <strong>the</strong>
relationship and communication between managers and <strong>the</strong> executive staff.This work aims to enrich
<strong>the</strong> practice <strong>of</strong> leaders and managers from nonpr<strong>of</strong>it organizations by furnishing important conclusions
and topics about performance, motivation, communications within <strong>the</strong> organizations. We also intend
to generate a modern view about <strong>the</strong> conditions where <strong>the</strong> Romanian nonpr<strong>of</strong>it actors work and <strong>the</strong>ir
problems linked to <strong>the</strong> old organizational culture.
3. Methodology
Taking into account <strong>the</strong> requirements <strong>of</strong> <strong>the</strong> research paper we used a series <strong>of</strong> tools and techniques,
as follows: SWOT analysis, benchmarking, document analysis, questionnaire-based survey. The
research methodology <strong>of</strong> this work was based also on <strong>the</strong> implementation <strong>of</strong> different projects
between 2003-2009.
4. Content
Human capital is a key aspect <strong>of</strong> social capital, involving <strong>the</strong> existence and development <strong>of</strong> human
capacity at all levels <strong>of</strong> society in order to define and achieve development and a proper
organizational culture. The creative processes <strong>of</strong> <strong>the</strong> necessary human capacity for development can
be grouped into several generic rules. Development depends on:
The ability to have perceptions <strong>of</strong> <strong>the</strong> future and to understand <strong>the</strong> process <strong>of</strong> change;
The knowledge and skills to aplly change and development;
The existence <strong>of</strong> critical human capital able to produce change
The concept <strong>of</strong> leadership is set in many contexts and is sometimes used in its narrow meaning. We
accept <strong>the</strong> notion <strong>of</strong> leadership as having three interrelated dimensions: <strong>the</strong> leader, adherents and
situation / context. Often, organizations come to preconceived or imposed from outside solutions . In
most cases, <strong>the</strong> missing component <strong>of</strong> an analysis <strong>of</strong> markets <strong>the</strong>re are <strong>the</strong> economic forces which
produces a distorted picture <strong>of</strong> sustainable solutions. In many cases we see indifference or
misunderstanding <strong>of</strong> <strong>the</strong> various interests <strong>of</strong> different social actors in society, where <strong>the</strong> most
sustainable solutions are <strong>the</strong> result <strong>of</strong> <strong>the</strong> benefits created for <strong>the</strong>ir actors. Sometimes, <strong>the</strong>re is no
approach by seeking mutually beneficial solutions and policies. Ano<strong>the</strong>r important issue is <strong>the</strong> wording
<strong>of</strong> several goals that are not achievable in <strong>the</strong> absence <strong>of</strong> resources, <strong>the</strong> lack <strong>of</strong> understanding and
consistent implementation <strong>of</strong> concrete steps related to internal resources and external opportunities.
Knowledge and skills needed to exercise a pr<strong>of</strong>ession that will produce <strong>the</strong> long-term results and will
change <strong>the</strong> community and <strong>the</strong> society <strong>the</strong>re are considered to be: identifying and understanding <strong>the</strong>
problem (s) facing <strong>the</strong> community , understanding <strong>the</strong> (social, economic, cultural)causes and <strong>the</strong>
ability to formulate solutions (alternative solutions). The lack <strong>of</strong> <strong>the</strong> leadership qualities can generate
<strong>the</strong> existence <strong>of</strong> toxic negative traits <strong>of</strong> leadership and bad leadership (bad leadership). Both forms
are deficiencies in <strong>the</strong> manifestation <strong>of</strong> its content Training and educational programmes can help
minimizing <strong>the</strong> toxic and bad leadership:
Civic Leadership-Business-Politics-Public;
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Roxana Mironescu
Individual capacities (values, principles, ethics, confidence, self-awareness, personality, skills,
personal SWOT);
Pr<strong>of</strong>essional skills (decision making, communication and active listening, creative and strategic
thinking, pr<strong>of</strong>essional SWOT, cultivating relations with adherents);
Democratic Leadership (Relationship and relationship development, educating <strong>the</strong> stakeholders
and <strong>the</strong> shareholders);
Training and encouraging new leaders by coaching and mentoring;
Leadership in <strong>the</strong> organizational context.
Ano<strong>the</strong>r way to solve <strong>the</strong> problem <strong>of</strong> toxic/bad leadership may be <strong>the</strong> cultivation <strong>of</strong> local strategic
human capital able to promote change. Local human capital is <strong>the</strong> best investment to generate and
regenerate society's capacity to address problems and seek solutions to development. In <strong>the</strong> effort to
attract and retain <strong>the</strong> best definition <strong>of</strong> <strong>the</strong> organization's core , <strong>the</strong> basic values are essential. These
principles should clearly and concisely show <strong>the</strong> organization's mission and how it wants to fulfill it.
Even if <strong>the</strong> organization's attitude towards its employees is not stipulated in <strong>the</strong> declaration <strong>of</strong>
principles, it should, however, implicitly be present at <strong>the</strong> same time, it must be easily distinguished.
This includes care for employees, <strong>the</strong> only “full-time clients” <strong>of</strong> <strong>the</strong> organization. Putting into practice
<strong>the</strong>se ideas can not be achieved without an effective internal communication that take into account
<strong>the</strong> interests and <strong>the</strong> points <strong>of</strong> views <strong>of</strong> all <strong>the</strong> involved parts This may encourage an atmosphere <strong>of</strong>
confidence, which, in <strong>the</strong> medium and long period <strong>of</strong> time can shape a deeper motivation <strong>of</strong>
employees. Last but not least, <strong>the</strong> feeling <strong>of</strong> belonging to a community (common organizational
culture) has a significant impact on employees' attitudes towards current work. One <strong>of</strong> <strong>the</strong> basic
needs <strong>of</strong> <strong>the</strong> individual is recognition, being a social necessity, by definition. Because one spends
considerable time at work, recognizing his role at <strong>the</strong> workplace, <strong>the</strong> pr<strong>of</strong>essional accomplishments,
his skills and his moral and emotional qualities may built <strong>the</strong> foundation <strong>of</strong> a deep and long- lasting
relationship with <strong>the</strong> employer. Therefore, <strong>the</strong> relationship "trade" between employee and employer
must be imbued with a moral component: mutual respect.
The practitioners suggestions and ideas that could meet <strong>the</strong> challenge <strong>of</strong> forming human capital to
express and enforce organizational policies can be:
a. to communicate to "internal customers", to <strong>the</strong>ir views on providing products and services;
b. to evaluate <strong>the</strong>"culture" in <strong>the</strong>ir own organizations It is useful to examine <strong>the</strong> organizational
culture, whe<strong>the</strong>r it is based on values such as trust, quality, respect, integrity, teamwork and if
<strong>the</strong>se values are accepted and promoted within organization ;
c. to analyse <strong>the</strong> customers’ messages through <strong>the</strong>ir employees ;
d. to select <strong>the</strong> staff provided with "quality to deal with <strong>the</strong> customer" A selection <strong>of</strong> human capital
performance standards and current employees involved in recruitment and selection process can
clarify if potential employees will fit with <strong>the</strong> existing team and organizational values. Certain skills
can be acquired by employees through training programs on workplace, but attitudes and
personality may not be "assimilated" directly through such programs;
e. to recognize and to reward. Results give <strong>the</strong> positive feedback and encourage <strong>the</strong> employees
so <strong>the</strong>y have extra motivation to perform. Involved in innovation and finding new solutions to solve
direct work tasks, <strong>the</strong>y will have a positive attitude towards <strong>the</strong>ir work and organization. perfect
performance by <strong>the</strong> standards / objectives imposed.
5. Conclusions
The basis for future development <strong>of</strong> a strong culture, strategically adequate and adaptive, it was
created, especially for <strong>the</strong> nonpr<strong>of</strong>it organizations, it demonstrates that <strong>the</strong> phenomenon is possible in
Romania, stimulating and strengthing joint efforts to create confidence for <strong>the</strong> future.
References
Aghion, Ph.and Tirole, J.,(1997) Formal and Real Authority in Organizations, Journal <strong>of</strong> Political Economy. 105:
1.
Bennis, W.and Benne K.D., Holt, R. C.(1969) The Planning <strong>of</strong> Change, Rinehart and Winston, New York.
Bratianu, C.(2006), Management si marketing. Concepte fundamentale, Editura Comunicare.ro, Bucuresti;
Business management.
Burns, J. M. (1978), Leadership, New York: Harper & Row, Publishers.
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Roxana Mironescu
Daft, R.L. (2002) The leadership experience, Mason, Ohio: South-Western.
Drucker, P. (1988) The coming <strong>of</strong> <strong>the</strong> new organization, Harvard Business Review.
Hersey, P.and Blanchard, K. H. (1996) The management <strong>of</strong> organizational behavior, Englewood
Cliffs, NJ: Prentice-Hall.
Marin, D.and Verdier,Th.(2001) Power inside <strong>the</strong> Firm and <strong>the</strong> Market: A General Equilibrium Approach,
University <strong>of</strong> Munich and DELTA,Paris, Mimeo.
Nicolescu, O.and Verboncu, I.(2008) Fundamentele managementului organizatiei, Editura Universitara,
Bucuresti.
Schuster, J. (1994) Transforming your leadership style, Association Management 46 (1).
Steers, R. (1988) Introduction on Organizational Behavior, Scott, Foresman and Co, Glenview.
Vlasceanu ,M. (2003) Organizatii si comportament organizational, Polirom, Iasi.
Zlate. M. (2004) Leadership si management, Polirom, Iasi.
*** (2002) Managementul resurselor umane, “Înţelegerea schimbării”, CODECS.
*** (2002) Putere, conducere şi schimbare, “Managementul schimbării”, CODECS.
http://www.agero-stuttgart.de/REVISTA-AGERO, Analiza strategică SWOT a unei întreprinderi/organizaţii,
Filipaş, T.
http://www.bloombiz.ro/cariere ,Repr<strong>of</strong>ilarea pr<strong>of</strong>esională, Popa, T.
http://www.humansynergics.ro/index.php?id=23, Human Synergics International(2006), Cultura organizationala in
companiile romanesti- analize si tendinte.
http://en.wikipedia.org./wiki/Change Management.
600

Building an IC Based Model for <strong>the</strong> Evaluation <strong>of</strong> <strong>the</strong>
Innovation Capacity <strong>of</strong> KIBS
Paloma Sánchez and Oihana Basilio
Autonomous University <strong>of</strong> Madrid, Spain
mpaloma.sanchez@uam.es
oihana.basilio@uam.es
Abstract: This research in progress aims to elaborate a model to assess <strong>the</strong> innovation capacity <strong>of</strong> knowledge
intensive business services (KIBS), testing it by evaluating a large service company in Spain and later revisiting it
with additional KIBS. Based on a thorough literature review, a first Model has been elaborated and a
questionnaire designed to provide qualitative and quantitative information about intellectual capital related to
innovation. The <strong>the</strong>oretical background lies on <strong>the</strong> resource-based view <strong>of</strong> <strong>the</strong> firm (RBV) and its outgrowth, <strong>the</strong>
knowledge-based view (KBV). The Model has been applied to a large service company, by conducting structured
interviews with a broad range <strong>of</strong> employees, and complementing it with documentary analysis. In future steps, <strong>the</strong>
result <strong>of</strong> <strong>the</strong> interviews will be tested by a large survey directed at <strong>the</strong> company employees and, after analyzing
<strong>the</strong> results <strong>of</strong> this main case study, <strong>the</strong> Model and <strong>the</strong> questionnaire will be revisited and applied to o<strong>the</strong>r KIBS
companies. The results <strong>of</strong> this research will eventually shed new light on <strong>the</strong> relationships between IC, KM
practices and innovation and also on <strong>the</strong> understanding <strong>of</strong> innovation dynamics in KIBS. It will be valuable for
advancing in <strong>the</strong> definition <strong>of</strong> IC and innovation capacity management and measurement methods. It will also be
useful at micro level, for those service companies aiming to assess and improve <strong>the</strong>ir innovative capacity. The
expected end result <strong>of</strong> this long process, is an innovation capacity autoevaluation model, based on <strong>the</strong> analysis
<strong>of</strong> <strong>the</strong> IC management <strong>of</strong> service companies. Since <strong>the</strong> present research is a work-in-progress, we will present
here <strong>the</strong> qualitative part <strong>of</strong> <strong>the</strong> main case study, describing <strong>the</strong> developed Model, <strong>the</strong> main insights gained
through interviews and documentary analysis, and <strong>the</strong> main limitations found so far.
Keywords: intellectual capital; innovation; knowledge management; services
1. Introduction
This research in progress will be part <strong>of</strong> <strong>the</strong> doctoral <strong>the</strong>sis <strong>of</strong> Oihana Basilio
The capacity to systematically innovate is essential for companies aiming to remain competitive, so it
is critical to identify <strong>the</strong> variables that will help <strong>the</strong>m develop that capacity and to understand <strong>the</strong>ir
proper working. Knowledge and o<strong>the</strong>r intangibles have been recognized to be major sources <strong>of</strong>
innovation (Swan et al 1999: 264; Sánchez et al. 2000: 3; Guthrie et al. 2003: 429) and literature on
<strong>the</strong>se issues has increased notoriously over <strong>the</strong> last decades (Sánchez et al. 2009), but <strong>the</strong>re is still
much work to do, developing methodologies that help organizations identify, measure and manage
relevant knowledge and IC for innovation. Moreover, <strong>the</strong> majority <strong>of</strong> studies that analyse <strong>the</strong> influence
<strong>of</strong> knowledge management (KM) and IC management (ICM) on innovation focus on a few intangibles
and <strong>the</strong>ir effects, such as networking (e.g. Capaldo 2007; Swan et al. 1999), knowledge protection
(e.g. Bader 2008; Hurmelinna-Laukkanen and Ritala 2010), creativity (e.g. Henard and McFadyen
2008; Rosa et al. 2008), etc. There are relatively few studies that <strong>of</strong>fer a general perspective,
analysing <strong>the</strong> effects <strong>of</strong> a broader set <strong>of</strong> key variables (e.g. Hull et al. 2000).
In this sense, this research in progress aims to elaborate a broad model to evaluate <strong>the</strong> innovation
capacity <strong>of</strong> knowledge intensive business services (KIBS), based on <strong>the</strong> assessment <strong>of</strong> <strong>the</strong>ir key KM
and ICM activities. In order to become a practical tool for auto-evaluation purposes, we aim to a) test
<strong>the</strong> model by assessing <strong>the</strong> innovation capacity <strong>of</strong> a service company in Spain, and c) re-test it, after
<strong>the</strong> necessary revision, with additional KIBS.
The following sections <strong>of</strong>fer an overview <strong>of</strong> <strong>the</strong> <strong>the</strong>oretical framework and research questions (section
1), <strong>the</strong> methodology that is being applied and that is planned for next steps (section 2), some interim
results and limitations (section 3), and finally a conclusion with <strong>the</strong> expected value <strong>of</strong> <strong>the</strong> research.
2. Theoretical background and research questions
Contrasting with <strong>the</strong> paradigms that locate <strong>the</strong> sources <strong>of</strong> competitive advantage outside <strong>the</strong> company
or on a privileged market position, we believe that it lies within firm resources and capabilities (Teece
et al. 1997: 510). Many scholars are increasingly focusing on <strong>the</strong> role <strong>of</strong> intangibles and knowledge
(e.g. Becker and Zirpoli 2003; Daneels 2002; Collinson and Wilson 2006; Knight and Cavusgil 2004),
addressing issues such as internal coordination, organizational structure, <strong>the</strong> role <strong>of</strong> management,
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Paloma Sánchez and Oihana Basilio
and <strong>the</strong> allocation <strong>of</strong> decision-making rights (Grant 1996: 110). Following <strong>the</strong>ir example, our model
aims to assess <strong>the</strong> core resources, capabilities and routines that both enable and hamper innovation
in <strong>the</strong> company.
For that purpose, we aim to answer <strong>the</strong> following questions: Which IC resources and activities
increase/decrease <strong>the</strong> company’s innovative capacity? How does <strong>the</strong> innovative capacity building
effort reflect on effective innovation and o<strong>the</strong>r results? We hypo<strong>the</strong>size that: (h1) KM and ICM
positively affect innovation capacity, (h2) KIBS need a specific Innovation Capacity Evaluation Model
(ICEM), (h3) innovation capacity building efforts are reflected in effective innovation and o<strong>the</strong>r
financial and non-financial results, and (h4) some <strong>of</strong> <strong>the</strong> introduced organizational innovations (e.g.
new ICTs or Human Resource Management practices) may lead to unintended and undesirable
effects on employees.
3. Methodology
Within <strong>the</strong> long-term research project (2-3 years), both qualitative and quantitative research methods
are used:
First: Literature related to <strong>the</strong> effects <strong>of</strong> IC and KM on innovation, services innovation and innovation
capacity building has been reviewed, identifying <strong>the</strong> main intangible and knowledge resources that
affect innovative capacity.
Second: Supported on <strong>the</strong> literature, a first Model has been elaborated and a semi-structured
questionnaire for interviews has been designed to provide qualitative and some quantitative
information about intangibles related to innovation. This questionnaire is partly based on <strong>the</strong>
methodology applied by Hull et al. 2000 to manufacturing, in which he analyzed five groups <strong>of</strong> KM
practices (R&D management process, mapping <strong>of</strong> knowledge relationships, human resource
management, management <strong>of</strong> Intellectual Property, and R&D Information Technology management)
in companies with sophisticated units for innovation, i.e. R&D departments. We have modified and
adapted <strong>the</strong>ir model to <strong>the</strong> evaluation <strong>of</strong> services and <strong>the</strong> objectives <strong>of</strong> our project. The most
important changes are:
New sections, to evaluate a) <strong>the</strong> innovation strategy and <strong>the</strong> obtained innovative results, and b)
<strong>the</strong> unintended and undesirable effects that <strong>the</strong> introduction <strong>of</strong> KM practices for innovation and
<strong>the</strong> innovation per se can have on employees (e.g. work intensification, decrease <strong>of</strong> well-being).
Inclusion <strong>of</strong> variables such us trust, leadership, organizational structure, and culture, which have
been related to innovation (Merx-Chermin and Nijh<strong>of</strong>. 2005).
The focus on <strong>the</strong> R&D department as <strong>the</strong> source <strong>of</strong> innovation has been substituted by a focus on
both internal and external sources (e.g. acquisition <strong>of</strong> technology and cooperation), because
many service companies do not have such department.
Third: We are applying <strong>the</strong> model to a large firm supplying services to different areas, by conducting
structured interviews with a broad range <strong>of</strong> employees, and complementing it with documentary
analysis. 22 interviews have been already made and ano<strong>the</strong>r 20 to 30 will follow.
Fourth: The result <strong>of</strong> <strong>the</strong> interviews will be tested by a large survey that will allow to: a) validate <strong>the</strong>
correlation <strong>of</strong> selected variables with innovation, b) evaluate <strong>the</strong> current innovation capacity <strong>of</strong> <strong>the</strong>
company and detect <strong>the</strong> gap with <strong>the</strong> intended one, and c) assess <strong>the</strong> effective innovation <strong>of</strong> <strong>the</strong>
company and its effects on o<strong>the</strong>r results.
Fifth: After analyzing <strong>the</strong> results <strong>of</strong> <strong>the</strong> interviews and survey, <strong>the</strong> Model and <strong>the</strong> questionnaire will be
revisited and applied to o<strong>the</strong>r KIBS companies.
4. Interim results and limitations
The initial interviews have allowed us to detect <strong>the</strong> importance that employees give to each <strong>of</strong> <strong>the</strong>
analyzed issues, for <strong>the</strong> innovation in <strong>the</strong> company, and <strong>the</strong>ir level <strong>of</strong> satisfaction with <strong>the</strong> current
situation (Likert skale: from 1 to 6). All <strong>the</strong> variables have been rated as being <strong>of</strong> very high importance
(mode: 5 or 6) and satisfaction is also generally high (rarely lower than 4). The qualitative part <strong>of</strong> <strong>the</strong>
questionnaire, based in interviewees’ commentaries, has allowed us to detect strengths and
weaknesses for <strong>the</strong> analyzed variables, and some uncoherences between existing formal initiatives
and <strong>the</strong>ir implementation (Table 1).
602

Table 1: Examples <strong>of</strong> uncoherences
Paloma Sánchez and Oihana Basilio
Formal initiative Implementation and coherence
Strong <strong>of</strong>fer <strong>of</strong> information and knowledge sources
and o<strong>the</strong>r facilties (e.g. communication technologies,
management methodologies, training <strong>of</strong>fer, KM
systems)
Strong innovation strategy (e.g. specific programme,
innovation department, innovative ideas repository
etc.)
Not recognized time for employees to learn about <strong>the</strong>
exising facilities and technologies, and to assimilate
and exploit all <strong>the</strong> opportunities <strong>the</strong>y have avalable
Time devoted to innovation (not chargeable)
diminishes <strong>the</strong> key performance indicator <strong>of</strong>
employees
Little value <strong>of</strong> innovation results in <strong>the</strong> rewarding and
appraisal system
The main limitations <strong>of</strong> our analysis so far are that it: a) <strong>of</strong>fers a partial picture <strong>of</strong> <strong>the</strong> company,
because all areas have not yet been covered; and b) is mainly based on qualitative information and
very basic quantitative data (meda, variance and mode).
5. Conclusions and interest <strong>of</strong> <strong>the</strong> research
Since <strong>the</strong> present research is a work-in-progress, we will present here <strong>the</strong> qualitative part <strong>of</strong> <strong>the</strong> main
case study, describing <strong>the</strong> developed Model, <strong>the</strong> main insights gained through interviews and
documentary analysis, and <strong>the</strong> main limitations found until that point (steps one to three). Steps four
and five are expected to start around June 2011.The results <strong>of</strong> this research will eventually shed new
light on <strong>the</strong> relationships between IC, KM practices and innovation and also on <strong>the</strong> understanding <strong>of</strong>
innovation dynamics in KIBS. It will be valuable for advancing in <strong>the</strong> definition <strong>of</strong> IC and innovation
capacity management and measurement methods. It will also be useful at micro level, for those
service companies aiming to assess and improve <strong>the</strong>ir innovative capacity. The expected end result
<strong>of</strong> this long process, is an innovation capacity autoevaluation model, based on <strong>the</strong> analysis <strong>of</strong> <strong>the</strong> IC
management <strong>of</strong> service companies.
6. References
Bader, M.A. (2008) Managing intellectual property in inter-firm R&D collaborations in knowledge-intensive
industries. International Journal <strong>of</strong> Technology Management, 41(3-4), 311-35.
Becker, M. and F. Zirpoli. (2003) Organizing new product development: knowledge hollowing-our and knowledge
integration: <strong>the</strong> FIAT Auto case. International Journal <strong>of</strong> Operations and Production Management 23(9):
1033-61.
Capaldo, A. (2007) Network structure and innovation: <strong>the</strong> leveraging <strong>of</strong> a dual network as a distinctive relational
capability. Strategic Management Journal, 28(6), 585-608.
Collinson, S. and D.C. Wilson. (2006) Inertia in Japanese organizations: knowledge management routines and
failure to innovate. Organization Studies, 27(9), 1359-87.
Daneels, E. (2002) The dynamics <strong>of</strong> product innovation and firm competences. Strategic Management Journal,
23, 1095-1121.
Grant, R.M. (1996) Toward a knowledge-based <strong>the</strong>ory <strong>of</strong> <strong>the</strong> firm. Strategic Management Journal 17, 109-22.
Guthrie, J., U. Johanson, P.N. Bukh, and M.P. Sánchez. (2003) Intangibles and <strong>the</strong> transparent enterprise: new
strands <strong>of</strong> knowledge. Journal <strong>of</strong> Intellectual Capital, 4(4), 429-40.
Henard, D.H. and M.A. McFadyen (2008) Making knowledge workers more creative. Research-Technology
Management, 51(2), 40-46.
Hull, R., R. Coombs, and M. Peltu. (2000) Knowledge management practices for innovation: an audit tool for
improvement. International Journal <strong>of</strong> Technology Management, 20(5-8), 633-56.
Hurmelinna-Laukkanen, P. and P. Ritala. (2010) Protection for pr<strong>of</strong>iting from collaborative service innovation.
Journal <strong>of</strong> Service Management, 21(1), 6-24.
Knight, G.A. and S.T. Cavusgil. (2004) Innovation, organizational capabilities, and <strong>the</strong> born-global firm. Journal <strong>of</strong>
International Business Studies, 35(2), 124-41.
Merx-Chermin, M. and W.J. Nijh<strong>of</strong>. (2005). Factors influencing knowledge creation and innovation in an
organization. Journal <strong>of</strong> <strong>European</strong> Industrial Training 29(2), 135-47.
Rosa, J. A., W. J. Qualls, et al. (2008). Involving mind, body, and friends: management that engenders creativity.
Journal <strong>of</strong> Business Research, 61(6), 631-39.
Sánchez, M.P., O. Basilio, C. Vivas. (2009). Knowledge management, intellectual capital and innovation:
Usefulness <strong>of</strong> a literature review for policy making. <strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> 2009 International Forum on
Knowledge Asset Dynamics held at <strong>the</strong> University <strong>of</strong> Glasgow. Glasgow
Sánchez, M.P, C. Chaminade and M. Olea. (2000) Management <strong>of</strong> intangibles: an attempt to build a <strong>the</strong>ory.
Journal <strong>of</strong> Intellectual Capital, 1(4), 312-27.
Swan, J., S. Newell, H. Scarbrough, and D. Hislop. (1999) Knowledge management and innovation: networks
and networking. Journal <strong>of</strong> Knowledge Management, 3(4), 262-75.
Teece, D.J., G. Pisano, and A. Shuen. (1997) Dynamic capabilities and strategic management. Strategic
Management Journal 18 (7): 509-33.
603

Evaluating Intellectual Capital Using DEA Envelopment
Techniques
Stelian Stancu and Anca Domnica Lupu
Academy Of Economic Studies, Romania
stelian_stancu@yahoo.com
lupu_anca@yahoo.com
Abstract: Managing and reporting Intellectual Capital is <strong>of</strong> great interest not only to <strong>the</strong> private sector but also to
<strong>the</strong> public one such as: public institutions, research organizations, regions and even countries. Although <strong>the</strong>re is
a great deal <strong>of</strong> literature concerning Intellectual Capital <strong>the</strong>re is still a lack <strong>of</strong> quantitative and financial methods
for evaluating it in practice. The present paper is trying to present a practical compared evaluation method for
intellectual capital with respect to <strong>the</strong> Romanian economy. The advantages <strong>of</strong> this method reside in <strong>the</strong> fact that
<strong>the</strong> variables that can be used can be presented on different scales and that this method includes multiple
ingoing and outgoing variables in contrast to <strong>the</strong> rest <strong>of</strong> <strong>the</strong>m that only allow one <strong>of</strong> each. DEA is a non
parametric model based o linear programming and not having to fix a parameter in advance is its main advantage
DEA also does a SWAT analysis <strong>of</strong> <strong>the</strong> unit, if previously identified as efficient. For all <strong>the</strong> inefficient units <strong>the</strong>
consultants can easily trace and quantify <strong>the</strong> potential <strong>of</strong> improvement, as follows: budget cuts, expanding
incomes, etc, for each Intellectual Capital part included in this analysis. This gives an exact idea to all <strong>the</strong>
manager not only how <strong>the</strong> future looks like but also what is to be done to change it. It traces <strong>the</strong> parts that need
more resource allocation and tracks where to get it from. In <strong>the</strong> same time DEA allows us to range <strong>the</strong> units as it
is an analysis compared to all <strong>the</strong> o<strong>the</strong>rs units in range. DEA deals with overall efficiency as it analyses <strong>the</strong>
relationship between inputs and outputs and does not divide it in pure, technical and allocative. In <strong>the</strong> end, DEA
analysis contains a sensitivity analysis , which is to prove that <strong>the</strong> given results are robust and are to be trusted
into practice.
Keywords: intellectual capital,DEA envelopment techniques, efficient units, rankings
1. Production frontier function
Let y be a production process with only one variable output, obtained by combining M variable inputs
x = ( x1,
x2
, K,
xm
) . We also assume that we have observed values for inputs and outputs for all K
companies taken into account, and that for a company, k , production process is described with <strong>the</strong>
k
help <strong>of</strong> a function f , as follows:
k k ( x ) ⋅
k k
y f ε
k
= for 1 ≤ k ≤ K cu(
y,
−x
) ∈ Z
that express, for each company, <strong>the</strong> maximum output that can be obtained with a given input.
This production frontier function, known as F, is a real function, defined on <strong>the</strong> input space through
<strong>the</strong> forumla given below:
k k
( x)
f ( x )
k k
F = max for ( y , −x
) ∈ Z (1)
k
that indicate, for each possible mix <strong>of</strong> given inputs, <strong>the</strong> maximum output that can be obtained for all
<strong>the</strong> companies.
2. Non-parametrical techniques (DEA) for measuring production efficency
We define an envelopment surface composed <strong>of</strong> portions <strong>of</strong> hyperplans <strong>of</strong> Z :
N
∑
r=
1
M
−∑
μr y r υi
xi
+ ϖ = 0 , where μ1, μ2
, K , μ N , − υ1,
−υ
2,
K,
−υ
M and ϖ are <strong>the</strong> coefficients
i=
1
<strong>of</strong> <strong>the</strong> hyperplane.
k
Such a hyperplane is a support one (it is part <strong>of</strong> <strong>the</strong> envelopment surface) if and only if all z points
<strong>of</strong> <strong>the</strong> surface are to be found on or under hyperplane and also, if <strong>the</strong> hyperplane passes through one
<strong>of</strong> <strong>the</strong>se points, that is:
604

N
∑
r=
1
N
∑
r=
1
Stelian Stancu and Anca Domnica Lupu
μ y − υ x + ϖ ≤ 0 for k = 1,
2,
K , K
r
μ y
r
rk
rs
−
M
∑
i=
1
M
∑
i=
1
i
υ x
i
ik
is
+ ϖ = 0
forsome
sunits.
For estimating <strong>the</strong> production frontier <strong>the</strong>re have to be solved K programming problems, each
decision unit being at a given time an evaluator.
2.1 Measures <strong>of</strong> productive efficency
The performance technical indicators <strong>of</strong> a company can be defined for a given time or in dynamics.
More useful is, however, comparing <strong>the</strong> activity <strong>of</strong> <strong>the</strong> company with <strong>the</strong> one <strong>of</strong> o<strong>the</strong>r companies
similarly from technological point <strong>of</strong> view, that are part <strong>of</strong> <strong>the</strong> same industry.Given inputs and outputs
are supposed to be known for <strong>the</strong>se k companies.
2.2 Envelopment techniques for estimating productive efficiency
2.2.1 Envelopment surfaces
It is known that, in classic microeconomic <strong>the</strong>ory, production function can be interpreted as being <strong>the</strong>
base for describing <strong>the</strong> input-output relation in a production unit. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> production
function represents a frontier for <strong>the</strong> production possibility.
DEA techniques assure a detailed analysis <strong>of</strong> efficiency in multi input/output situations, through
evaluation ef each decision unit, by measuring its performance compared to <strong>the</strong> envelopment surface
described by all <strong>the</strong> decision units. Those decision units that determine <strong>the</strong> envelopment surface are
considered, in DEA terms, as efficient.
The units that are not to be found on <strong>the</strong> envelopment surface are called unefficient and <strong>the</strong>se degree
<strong>of</strong> unefficiency can also be determined.
With regards to <strong>the</strong> production scale, <strong>the</strong>re are two types <strong>of</strong> envelopment surfaces:
Surfaces for <strong>the</strong> constant returns to scale-CRS
Surfaces for <strong>the</strong> variable returns to scale-VRS
3. Aplication in Romania’s case
3.1 Actual data
In this aplication we shall study efficiency and productivity in <strong>the</strong> case <strong>of</strong> 27 Romanian counties, first
places being taken by Bucharest.
The data used are from 2008 and 2009 and in <strong>the</strong> made analysis we have chosen two outputs-
Relative contribution to GDB (O1) and Net Added Value (O2) and 4 inputs: The number <strong>of</strong> emplied
persons(I1), <strong>the</strong> average number <strong>of</strong> emploied people(I2), <strong>the</strong> degree <strong>of</strong> education(I3) and <strong>the</strong> number
<strong>of</strong> brevets and inventions. (I4).
3.2 Non-parametric approach with <strong>the</strong> help <strong>of</strong> DEA models
We shall first consider input orientation. For <strong>the</strong> estimation <strong>of</strong> production frontier and efficiency
envelopment techniques have been used and <strong>the</strong> s<strong>of</strong>tware was also DEAP.
In <strong>the</strong> input orientation that describes a technology with constant returns, <strong>the</strong> efficiency scores
obtained for Industry, for <strong>the</strong> first 27 counties, are presented in Table 1 and 2:
605

Table 1. CRS input efficiency scores for 2009
Stelian Stancu and Anca Domnica Lupu
County Efficiency in 2009 County Efficiency în 2009
1 0.312 15 0.372
2 1.000 16 0.502
3 0.364 17 1.000
4 0.605 18 0.870
5 1.000 19 0.124
6 0.936 20 1.000
7 1.000 21 0.447
8 0.138 22 0.244
9 0.664 23 0.233
10 1.000 24 0.331
11 0.372 25 0.071
12 0.090 26 0.142
13 1.000 27 0.500
14 1.000 MEDIA 0.567
Table 2. CRS input efficiency scores for 2008 and 2009
County Efficiency in 2008 Efficiency in 2009
2 1.000 1.000
4 1.000 0.605
5 1.000 1.000
6 1.000 0.936
7 1.000 1.000
10 1.000 1.000
16 1.000 0.502
17 1.000 1.000
18 1.000 0.870
20 1.000 1.000
25 0.172 0.071
12 0.140 0.090
13 0.826 1
14 0.571 1
It can be concluded that counties 2, 5, 7, 10, 17 and 20 remained efficient. Generally, <strong>the</strong>re were no
spectacular increases or decreases in <strong>the</strong> efficiency scores <strong>of</strong> <strong>the</strong> o<strong>the</strong>r counties, <strong>the</strong> average for
2008 being <strong>of</strong> 0,655, a little bigger than in 2009. It also has to be said that in <strong>the</strong> case <strong>of</strong> constant
scale outputs , <strong>the</strong> scores are <strong>the</strong> same for output oriented DEA models.
3.2.1 DEA oriented VRS models
A)DEA input oriented VRS models
Constant return for CRS is an appropiate condition for <strong>the</strong> case in which all units operate on <strong>the</strong> same
optimum scale. Imperfect competition , financial restrictions, can though produce situations in which
<strong>the</strong> county may act in optimum scale. In this current situation we are talking about variable outputs:
increasing (irs) or decreasing (drs).
The following scores have been obtained for year 2009:
606

Stelian Stancu and Anca Domnica Lupu
Fur<strong>the</strong>r on,an envelopment model also informs about <strong>the</strong> reference counties for each analysed
county.In table 3 it is shown , for each individual county, <strong>the</strong> county <strong>the</strong>y should be compared to,
according to <strong>the</strong> size <strong>of</strong> <strong>the</strong> used inputs .
Table 3. CRS and VRS input efficiency scores for 2009
County Efficiency in CRS Efficiency in VRS Scale Type
1 0.312 0.331 0.941 Irs
2 1.000 1.000 1.000 -
3 0.364 0.371 0.980 Irs
4 0.605 0.605 0.999 -
5 1.000 1.000 1.000 -
6 0.936 1.000 0.936 Drs
7 1.000 1.000 1.000 -
8 0.138 1.000 0.136 Drs
9 0.664 0.678 0.979 Irs
10 1.000 1.000 1.000 -
11 0.372 0.494 0.753 Drs
12 0.090 0.094 0.954 Drs
13 1.000 1.000 1.000 -
14 1.000 1.000 1.000 -
15 0.372 0.534 0.695 Drs
16 0.502 0.695 0.722 Irs
17 1.000 1.000 1.000 -
18 0.870 1.000 0.870 Drs
19 0.124 0.228 0.545 Irs
20 1.000 1.000 1.000 -
21 0.447 0.565 0.792 Drs
22 0.244 0.244 0.999 -
23 0.233 0.244 0.957 Drs
24 0.331 0.436 0.759 Irs
25 0.071 0.075 0.949 Drs
26 0.142 0.153 0.926 Drs
27 0.500 1.000 0.500 Drs
Average 0.567 0.657 0.866
B) DEA output oriented VRS model
The same results have been obtained here also, but <strong>the</strong>re is no rule however regarding <strong>the</strong> dimension
<strong>of</strong> <strong>the</strong> scores, that is, <strong>the</strong>y should be higher/lower than in input oriented models.
A close analysis reveals that no county has increasing outputs to scale.
References
Anderson, L.J., Boget<strong>of</strong>t, P., Frost, H., 2003, “The Application Of Production Functions In Bioeconomic models”,
Danish Research Institute <strong>of</strong> Food Economics
Brunnermeier, Markus K, Andrew Crockett, Charles A Goodhart, Avinash Persaud, and Hyun Song Shin. 2009.
“The Fundamental Principles <strong>of</strong> Financial Regulation.” Geneva Reports on <strong>the</strong> World Economy. Geneva:
International Center for Monetary and Banking Studies.
Calvo, Guillermo A. 2009. “Financial Crises and Liquidity Shocks: A Bank-run Perspective.” NBER Working
Papers, National Bureau <strong>of</strong> Economic Research, Cambridge, MA.
Cambell, R., Rogers, K., Rezek, J., “Efficiency Frontier Estimation: A Maximum Entropy Approach”, Department
<strong>of</strong> Finance and Economics Mississippi State University
Casu, B., Girardone, C., Molyneux , P., “Productivity Change In <strong>European</strong> Banking: A Comparison Of Parametric
a Non-Parametric Approaches”, Essex Finance Centre, University <strong>of</strong> Essex, 6-8
607

Stelian Stancu and Anca Domnica Lupu
Cetorelli, Nicola, and Linda Goldberg. 2009. “Globalized Banks: Lending to Emerging Markets in <strong>the</strong> Crisis.” Staff
Report 377. Federal Reserve Bank <strong>of</strong> New York, New York.
Coelli, T., 1996, “A Guide To Deap Version 2.1: A Data Envelopment Analysis(Computer) Program”, Cepa
Working Paper 96/08 - Centre <strong>of</strong> Efficiency and Productivity Analysis, Department <strong>of</strong> Econometrics,
University <strong>of</strong> New England, Australia, 18-20-http://www.uq.edu.au/economics/cepa/
Coelli, T., Prasada Rao, D.S., Battese, E. G., 1998, “An Introduction To Efficiency An Productivity Analysis”,
Kluwer Academic Publishers, Boston, 133-134
Coelli, T.J., Prasada Rao, D.S., 2003, “Total Factor Productivity Growth In Agriculture: A Malmquist Index
Analysis <strong>of</strong> 93 countries, 1998-2000”, Centre for Efficiency and Productivity Analysis, Univeristy <strong>of</strong>
Queensland, Australia, 2-6
Cortavarria, Luis, Simon Gray, Barry Johnston, Laura Kodres, Aditya Narain, Mahmood Pradhan, and Ian Tower.
2009. Lessons <strong>of</strong> <strong>the</strong> Financial Crisis for Future Regulation <strong>of</strong> Financial Institutions and Markets and for
Liquidity Management. Washington, DC: International Monetary Fund.
Cowan, Kevin, Jose De Gregorio, Alejandro Micco, and Christopher Neilson. 2008. “FinancialDiverisification,
Sudden Stops and Sudden Starts.” In Current Account and External Financing, ed. Kevin Cowan, Sebastián
Edwards, and Rodrigo O. Valdés. Santiago: Central Bank <strong>of</strong> Chile.
Crotty, James. 2009. “Structural Causes <strong>of</strong> <strong>the</strong> Global Financial Crisis: A Critical Assessment <strong>of</strong> <strong>the</strong> ‘New
Financial Architecture.’” Cambridge Journal <strong>of</strong> Economics 33: 563–80.
Daouia, A.B., Aragon, Y., Thomas-Agnan, C., 2004, “Efficiency Measurement: A Nonparametric Approach”,
Universite Toulouse 1-2
Delhausse, B., Fecher, E., Perelman, S., Pestieau, P., 1995, “Measuring Productive Performance In <strong>the</strong> Non-Life
Insurance Industry: The Case <strong>of</strong> French and Belgian Markets”, Tijdschrift veor Economie on Management,
Vol.XI, 54-55
Edvinsson and Malone 1997]Edvinsson L. , Malone M. : “Intellectual Capital” , New York, Harper Business (1997)
Fandel P., 2003, “Technical And Scale Efficiency Of Corporate Farms In Slovakia”, Slovak University Of
Agriculture, Nitra, 377
FMEL 2004 Federal Ministry <strong>of</strong> Economics and Labour: “Intellectual Capital Statement-Made in Germany-
Guideline” , Harzdruckerei, Wernickerode (2004)
Kaplan and Norton 1996, Kaplan R. , Norton D. : “The Balanced Scorecard-Translating Strategy into Action” ,
Harvard Business School Press, Boston (1996)
Keat, P., Young, P., 2003, “ Theory And Estimation Of Production”, Managerial Economics, Tools For Today’s
Decision Makers, Prentice Hall Business Publishing, 2-6
Martellato, D., Tarancon Moran, M.-A., 2005, “Openness, Dependency And Productive Efficiency In Nine
<strong>European</strong> Countries”,Universita’ Ca’ Foscari Di Venezia
608

Intellectual Capital in a Seaport Context
José Vale 1 , João Ribeiro 2 and Manuel Branco 2
1 Institute <strong>of</strong> Accounting and Administration <strong>of</strong> Porto (ISCAP), Portugal
2 Porto University, Porto, Portugal
josevale@iscap.ipp.pt
joao.ribeiro@fep.up.pt
mcbranco@fep.up.pt
Abstract: This poster, which is <strong>the</strong> result <strong>of</strong> an ongoing PhD <strong>the</strong>sis project, illustrates how and why <strong>the</strong>
Intellectual Capital (IC) concept can be applied to a seaport. A seaport can be conceptualized as a cluster
composed by organisations interrelated in a complex and specific network system. In a knowledge-based
economy, where <strong>the</strong> competitiveness <strong>of</strong> an organisation is a consequence <strong>of</strong> its ability to create IC, <strong>the</strong> spatial
proximity can be an important factor because it facilitates interactions between organisations. Traditionally,
literature defends an IC composed by three dimensions: human, structural and relational capital. Also, <strong>the</strong>
interplay between <strong>the</strong>se dimensions is considered an important factor to improve performance and thus
competitiveness. As far as <strong>the</strong> authors are aware, most <strong>of</strong> <strong>the</strong> research in IC has been focused on individual
firms. Although some recent papers examine macro-level organizations, such as regions, none exist on seaports.
In addition, <strong>the</strong>re is a paucity <strong>of</strong> management sciences’ research on to maritime transportation and seaports.
Several research questions are thus pertinent attending to <strong>the</strong> specificity <strong>of</strong> <strong>the</strong> context: What are <strong>the</strong> main IC
dimensions in a seaport? How those dimensions relate with each o<strong>the</strong>r? How IC, in its different dimensions, is
created/destroyed within a seaport? Answers to <strong>the</strong>se questions can have important strategic and managerial
implications for <strong>the</strong> seaport and its stakeholders. We consider a case study methodology as an appropriate
approach to answer <strong>the</strong>se questions, given that this methodology is suited for exploratory research and for
dealing with situations in which creativity and innovation prevail. Early insights provided not only by <strong>the</strong> literature
review, but also by two informal interviews, suggest that we can find <strong>the</strong> three “main” dimensions <strong>of</strong> IC within a
seaport context and also two types <strong>of</strong> relational capital: an “internal” and an “external” one. They also suggest
that IC dimensions may be interrelated with each o<strong>the</strong>r within a seaport and that relational capital may be <strong>the</strong>
most important dimension in that particular context.
Keywords: Intangible assets, intellectual capital, network, case study, seaport
1. Introduction
Many authors claim that organisations are less dependent on traditional tangible resources (Alwis,
Hlupic and Fitzgerald, 2003), considering intangible resources as <strong>the</strong> most important and required
critical drivers <strong>of</strong> sustainable competitive advantages (Viedma, 2003; Palacios and Galván, 2006).
Thus, <strong>the</strong> new challenge for organisations is <strong>the</strong> ability to drive <strong>the</strong>ir transformation into intelligent
organisations (Schiuma and Lerro, 2008a). For that, organisations should not only rely on its IC but
also on <strong>the</strong> IC <strong>of</strong> o<strong>the</strong>rs. Therefore, a seaport, due to its contextual complexity, can provide us with
empirical evidence in order to illustrate how and why <strong>the</strong> Intellectual Capital (IC) concept can be
applied to a cluster composed by organisations interrelated in a complex and specific network system.
2. Literature review
2.1 Intellectual capital dimensions
Tan, Plowman and Hancock (2008) consider that <strong>the</strong>ories on intellectual capital are embedded in two
streams <strong>of</strong> research: <strong>the</strong> strategy stream, which is concerned with knowledge creation, acquisition,
management, diffusion, utilization, capitalization, conversion, transfer, and storage; and <strong>the</strong>
measurement stream, which is concerned with measuring and reporting IC.
Although <strong>the</strong>re have been various and discordant definitions <strong>of</strong> IC, many individuals have, in recent
years, tried to agree on a standard one (Nazari and Herremans, 2007; Tan, Plowman and Hancock,
2008). However, is difficult to achieve a consensus.
Also, <strong>the</strong>re are several models, decomposing IC in different ways. In this case, and although <strong>the</strong> use
<strong>of</strong> different terminology, <strong>the</strong>re has been some consensus regarding <strong>the</strong> IC’s dimensions (Verma and
Dewe, 2008).
Generally, <strong>the</strong> literature defends an IC composed by three dimensions: human capital, structural (or
organisational) capital and relational (or customer) capital (Roslender and Fincham, 2001; Liu, 2007).
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However, it is important to notice that performance improvement is enabled by, among o<strong>the</strong>rs, <strong>the</strong>
interplay between <strong>the</strong>se dimensions (Kujansivu, 2008).
2.2 IC in meso level organisations
Most <strong>of</strong> <strong>the</strong> research on intellectual capital has focused on individual companies instead <strong>of</strong> macrolevel
units (e.g. regions) (Pöyhönen and Smedlund, 2004). Thus, in <strong>the</strong> last decade, <strong>the</strong> importance <strong>of</strong>
knowledge resources as source <strong>of</strong> regional and local development dynamics have been inquired and
many researchers have now underlined <strong>the</strong> importance <strong>of</strong> IC trying to go beyond <strong>the</strong> study <strong>of</strong>
individual firms (Schiuma, Lerro and Carlucci, 2008b).
In a knowledge-based economy, where knowledge production, transmission and dissemination are
<strong>the</strong> main characteristics, intangible assets are considered crucial to create value and, thus, economic
wealth (Sánchez and Elena, 2006). Therefore, in this knowledge economy, organisations not only rely
on <strong>the</strong>ir IC but also on <strong>the</strong> IC <strong>of</strong> o<strong>the</strong>rs (namely on those <strong>of</strong> <strong>the</strong> cluster, microcluster or territory where
<strong>the</strong> organisation is located) in order to build sustainable competitive advantages (Viedma, 2003).
Hence, competitiveness <strong>of</strong> regions can be increased through <strong>the</strong> development <strong>of</strong> strong regional
clusters and networking (Smedlund and Toivonen, 2007) and, thus, IC should be studied at <strong>the</strong>se
meso levels.
The development <strong>of</strong> clusters located in a specific city, region or territory is very important because <strong>the</strong>
organisations’ ability to exchange or share knowledge develops new capacities, resulting in an
increase <strong>of</strong> <strong>the</strong>ir IC (Joia and Malheiros, 2009).
Networking improves <strong>the</strong> flow <strong>of</strong> information (Sporleder and Peterson, 2003), giving organizations <strong>the</strong>
knowledge that <strong>the</strong>y cannot obtain in-house and also giving <strong>the</strong>m external economies <strong>of</strong> cognitive
scope (Visser, 2009).
On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong>re is a lack <strong>of</strong> research related to “<strong>the</strong> ways in which intellectual capital is
created and maintained as a dynamic process” (Pöyhönen & Smedlund, 2004).
The dynamics capabilities and <strong>the</strong> relational approaches try to analyse how <strong>the</strong> network is operating
as a relational system and how this influences <strong>the</strong> network capability to create intellectual capital
(Pöyhönen & Smedlund, 2004).
2.3 Ports as clusters and networks
The current state <strong>of</strong> knowledge on maritime transport and ports related to business economics
research appears to be modest (Carbone and De Martino, 2003). Governance approaches have been
most successful in presenting <strong>the</strong> port as a place where synchronic forces are played out among a
pluralistic port community (multi-terminal ports may include several operators within <strong>the</strong> same port)
striving for common internal and external goals (Olivier and Slack, 2005). Thus, ports should continue
to be seen as a politically cohesive entity (as a stakeholders’ consensual space) (Olivier et al., 2005).
Several authors define <strong>the</strong> port as a cluster which includes several activities and actors. Therefore,
although ports’ roles have been changing and are now considered as nodes in global supply chains,
proximity continues to be an important factor (Hall and Jacobs, 2010). O<strong>the</strong>rs define it as a network,
arguing that while most clusters are simple co-located organizations, some are networks <strong>of</strong> strong
cooperation. Both <strong>the</strong>se cases may include not only private actors, but also public ones (Visser,
2009). Therefore, and according to <strong>the</strong> aforementioned explanations, it is our opinion that a port is a
cluster <strong>of</strong> organizations which are related in a network system.
3. Research questions
What are <strong>the</strong> main dimensions <strong>of</strong> <strong>the</strong> Seaport’s IC?
How do <strong>the</strong>se dimensions relate with each o<strong>the</strong>r?
How is IC, in its different dimensions, created and/or destroyed within a seaport?
4. Methodological approaches
We will do a case study due to <strong>the</strong> fact that we are exploring a complex reality. It is our opinion that a
Seaport, ra<strong>the</strong>r than an organisation, it is a network composed <strong>of</strong> many individual firms connected in a
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relatively complex way. On <strong>the</strong> o<strong>the</strong>r hand, by aiming to get a holistic view on potential determinants,
our case study focuses on <strong>the</strong> network (seaport) and, like Pöyhönen & Smedlund (2004), we will
analyse <strong>the</strong> inter-organisational network according to <strong>the</strong> socio-centric perspective, i.e. not from <strong>the</strong>
actor-centric perspective <strong>of</strong> an individual organisation, but from <strong>the</strong> viewpoint <strong>of</strong> <strong>the</strong> whole network.
Our case study will be based on a mix <strong>of</strong> qualitative as well as quantitative evidence (Yin, 2003),
resulting from interviews to representatives <strong>of</strong> <strong>the</strong> main actors <strong>of</strong> <strong>the</strong> network and from <strong>the</strong> analysis <strong>of</strong>
documents such as sustainability reports, annual reports and o<strong>the</strong>r financial reports, as well as
strategic plans and o<strong>the</strong>r documents that can provide us with information regarding investments in IC.
5. Early insights
We start this study trying to answer <strong>the</strong> two first research questions. In order to do that, we have
already made two informal interviews to one <strong>of</strong> <strong>the</strong> seaport administrators.
From <strong>the</strong>se interviews, we consider that we can find <strong>the</strong> three “main” dimensions <strong>of</strong> IC within a
seaport context. Also, we can find two types <strong>of</strong> relational capital: an “internal” one encompassing <strong>the</strong>
relationships between <strong>the</strong> actors belonging to <strong>the</strong> seaport and an “external” one encompassing <strong>the</strong>
relationships between <strong>the</strong> seaport and external entities, such as universities or municipalities.
These interviews suggested that <strong>the</strong> main IC dimension may be <strong>the</strong> relational capital because a
seaport is composed by several firms that collaborate with each o<strong>the</strong>r in order to achieve common
internal and external objectives. Firms within a seaport collaborate not only in order to create value for
<strong>the</strong> final client, but also to achieve some o<strong>the</strong>r goals, such as developing <strong>the</strong> region where <strong>the</strong> seaport
is located.
These interviews have also suggested that, in a seaport, <strong>the</strong> IC dimensions may be interrelated. For
example, frequently, when firms within a seaport implement new types <strong>of</strong> equipment (and new
processes <strong>of</strong> doing something), <strong>the</strong>y have to give formation to o<strong>the</strong>r firms’ human resources (in order
to handle it or knowing how to do it). This example can attest how human capital within a seaport can
increase in consequence <strong>of</strong> an investment in structural capital made by one actor, and also can attest
<strong>the</strong> importance <strong>of</strong> relational capital.
6. Constraints
Our two biggest constrains have been <strong>the</strong> lack <strong>of</strong> literature related to <strong>the</strong> treatment <strong>of</strong> IC within a
seaport context and <strong>the</strong> delimitation <strong>of</strong> <strong>the</strong> port’s network.
7. Expected contributions
To produce knowledge by making <strong>the</strong> connection between <strong>the</strong> IC <strong>the</strong>ory and networks <strong>the</strong>ory;
Transferability <strong>of</strong> <strong>the</strong> conceptualization (IC in networks);
Extend literature related to IC in a context <strong>of</strong> a network.
References
Alwis, D., Hlupic, V. and Fitzgerald, G. (2003) 25th Int. Conf. Information Technology Interfaces ITI 2003, June
16-19, 2003, Cavtat, Croatia.
Carbone, V. and De Martino, M. (2003) “The changing role <strong>of</strong> ports in supply-chain management: an empirical
analysis”, Maritime Policy & Management, 30:4, pp.305-320.
Hall, P. and Jacobs, W. (2010) “Shifting Proximities: The Maritime Ports Sector in an Era <strong>of</strong> Global Supply
Chains”, Regional Studies. First published on: 27 January 2010 (iFirst).
Joia, L. and Malheiros, R. (2009) “Strategic alliances and <strong>the</strong> intellectual capital <strong>of</strong> <strong>the</strong> firms. Journal <strong>of</strong>
Intellectual Capital”, Vol.10, No.4, pp.539-558.
Kujansivu, P. (2008) “Operationalising intellectual capital management: choosing a suitable approach”,
Measuring Business Excellence, Vol.12, No.2, pp.25-37.
LIU, C.C. (2007). Developing measures <strong>of</strong> value creation at private universities. International Journal <strong>of</strong>
Management in Education, 1, 86-99.
Nazari, J. and Herremans, I. (2007) “Extended VAIC model: Measuring intellectual capital components”, Journal
<strong>of</strong> Intellectual Capital, 8, 595-609.
Olivier, D. and Slack, B. (2005) Rethinking <strong>the</strong> port, forthcoming at Environment & Planning A.
Palacios, T. and Galván, R. (2006) “Intellectual capital within Iberian municipalities (network)”, Journal <strong>of</strong>
Knowledge Management, Vol.10, No.5, pp.55-64.
611

José Vale et al.
Pöyhönen, A. and Smedlund, A. (2004) “Assessing intellectual capital creation in regional clusters”, Journal <strong>of</strong>
Intellectual Capital, Vol.5, N.3., pp.351-365.
Roslender, R. and Fincham, R. (2001) “Thinking critically about intellectual capital accounting. Accounting”,
Auditing & Accountability Journal, Vol.14, No.4, pp.383-398.
Sánchez, M. and Elena, S. (2006) “Intellectual Capital in Universities – Improving Transparency and Internal
Management”, Journal <strong>of</strong> Intellectual Capital. Vol.7, No.4, pp.529-548
Schiuma, G. and Lerro, A. (2008a) “Intellectual capital and company's performance improvement”, Measuring
Business Excellence, 12, 3-9.
Schiuma, G., Lerro, A. and Carlucci, D. (2008b) “The Knoware Tree and <strong>the</strong> Regional Intellectual Capital Index –
An Assessment Within Italy”, Journal <strong>of</strong> Intellectual Capital. Vol.9, No.2, pp.283-300.
Smedlund, A. and Toivonen, M. (2007) “The role <strong>of</strong> KIBS in <strong>the</strong> IC development <strong>of</strong> regional clusters”, Journal <strong>of</strong>
Intellectual Capital, Vol.8, No.1, pp.159-170.
Sporleder, T. and Peterson, H. (2003) “Intellectual capital, learning, and knowledge management in agrifood
supply chains”, Chain and Network Science.
Tan, H., Plowman, D. and Hancock, P. (2008) “The Evolving Research on Intellectual Capital”, Journal <strong>of</strong>
Intellectual Capital, Vol.9, No.4, pp.1469-1930.
Verma, S. and Dewe, P. (2008) “Valuing Human Resources: Perceptions and Practices in UK Organisations”,
Journal <strong>of</strong> Human Resource Costing and Accounting. Vol.12, No.2, pp102-103.
Viedma, J. (2003) “SCBS social capital benchmarking system: pr<strong>of</strong>iting from social capital when building network
organisations”, Journal <strong>of</strong> Universal Computer Science, Vol.9, No.6, pp.501-509.
Visser, E. (2009) “The Complementary Dynamic Effects <strong>of</strong> Clusters and Networks”, Industry & Innovation, Vol.16,
No.2, pp.167-195.
Yin, R. (2003) Case Study Research: Design and Methods, Third Edition, Applied Social Research Methods
Series, Vol 5. Sage Publications, Inc, <strong>3rd</strong> edition, December 2002.
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