Proceedings of the 3rd European Conference on Intellectual Capital

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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. 305
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Proceedings <stron
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Contents Paper Title Author(s) Page
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Paper Title Author(s) Page No. Hier
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Preface These proceedings represent
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educating through ‘hands on’ co
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Ibrahim Elbeltagi is a Senior lectu
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Theodora Ngosi has a PhD in Compute
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José Vale is an invited assistant
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Social Knowledge: Are you Ready? 1
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John Girard don’t know.” (Benne
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John Girard The real question becom
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John Girard our belief that many le
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John Girard organizations to gain k
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Intellectual Capital Accounting - H
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Academic Research Papers 15
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Khodayar Abili and Mahyar Abili The
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Khodayar Abili and Mahyar Abili Nah
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Khodayar Abili and Mahyar Abili Tim
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Knowledge Transfer in Romanian Univ
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Simona Agoston et al. Table 1: Know
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Simona Agoston et al. homoscedastic
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Simona Agoston et al. included in <
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A Modeling Approach to Intellectual
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Eckhard Ammann (referring to <stron
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Eckhard Ammann Figure 2: The IC spa
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Eckhard Ammann section 2. They are
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Eckhard Ammann From an overall pers
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Sorin Anagnoste and Gabriela Dumitr
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Gabriela Atanasiu and Florin Leon T
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Gabriela Atanasiu and Florin Leon B
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Gabriela Atanasiu and Florin Leon a
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Developing and Implementing Strateg
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2. Technology, faculty, and staff B
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Learning programs Individual poten
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Bob Barrett facts with the<
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Intellectual Capital Dynamics withi
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Ruxandra Bejinaru and Stefan Iordac
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Education and Training Practice Str
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Andrea Bencsik et al. We wanted to
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Andrea Bencsik et al. In this sampl
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Table 4: Types of
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References Andrea Bencsik et al. An
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Ayşen Berberoğlu and Emine Ünar
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Ayşen Berberoğlu and Emine Ünar
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Table 7: Descriptive statistics Ay
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Knowledge Dynamics Modeling Using A
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Constantin Bratianu et al. will hav
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Constantin Bratianu et al. 5. a) Gi
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Constantin Bratianu et al. 5. Data
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Constantin Bratianu et al. Nissen,
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2. Technology and infrastructure Sh
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Sheryl Buckley and Apostolos Gianna
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Donley Carrington and Mike Tayles t
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Donley Carrington and Mike Tayles G
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John Dumay and Jim Rooney on a more
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John Dumay and Jim Rooney Taking <s
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John Dumay and Jim Rooney “For ex
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John Dumay and Jim Rooney Mouritsen
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Marziye Ehrami et al. 1. Creation
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Marziye Ehrami et al. Note: In 2005
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Earnings Quality and Othe</
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Magdi El-Bannany resource-based per
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Magdi El-Bannany Based on this argu
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Magdi El-Bannany Table 2: Descripti
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Magdi El-Bannany variable equal to
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Magdi El-Bannany Edvinsson, L. & Ma
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Ahmed Elsetouhi and Ibrahim Elbelta
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Albrecht Fritzsche and Rebecca Geig
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Table 4: Applicability of</
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S&P 500 Market Cap ($ billions) 14,
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Tatiana Garanina and Yana Pavlova T
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Tatiana Garanina and Yana Pavlova I
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Impact of Investme
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Lidia García-Zambrano et al. 2003;
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Lidia García-Zambrano et al. 4.2 P
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Table 7: Goodness of</stron
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Lidia García-Zambrano et al. reaso
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Lidia García-Zambrano et al. Rodri
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Víctor Raúl López Ruiz et al. co
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EI c k i 1 w PC i ic Víctor Raúl
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Maria de Lourdes Machado and Odíli
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Intellectual Capital and Corporate
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Agnes Maciocha when objects in a da
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Agnes Maciocha 4. Presentation <str
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Agnes Maciocha while in the
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Agnes Maciocha Choong K., “Intell
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The Influence of H
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Anca Mândruleanu From the<
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Anca Mândruleanu In Table 2, <stro
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Eliciting Tacit Knowledge From a Do
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Peter Marshall and Damian Gordon MM
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Peter Marshall and Damian Gordon re
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Peter Marshall and Damian Gordon ar
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Peter Marshall and Damian Gordon Th
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Maurizio Massaro et al. crucial fac
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Maurizio Massaro et al. exclusive (
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Maurizio Massaro et al. autonomy <s
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Maurizio Massaro et al. Chennal (20
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Intellectual Capital Management: Ca
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Florinda Matos et al. These models
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Complaints System dos clients New
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Florinda Matos et al. Finally, <str
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Florinda Matos et al. The training
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Florinda Matos et al. 47. Opinion
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Florinda Matos et al. In th
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Page 278 and 279: 3. Our research Ludmila Mládková
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Page 284 and 285: Applying the VAIC
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3. The empirical study 3.1 Methodol
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Table 3: Smart cities - application
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4.3 Suggestions to future work Kati
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Anna Romiti and Daria Sarti 2. Orga
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Anna Romiti and Daria Sarti based o
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Anna Romiti and Daria Sarti Governa
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Anna Romiti and Daria Sarti Therefo
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Anna Romiti and Daria Sarti Valkoka
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Kent Rondeau and Terry Wagar planne
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2.1 Study measures Kent Rondeau and
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Kent Rondeau and Terry Wagar contri
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Kent Rondeau and Terry Wagar Our re
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Intellectual Capital and a Firm’s
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Figure 1: Hypothes
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Helena Santos-Rodrigues et al. Norm
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Helena Santos-Rodrigues et al. To s
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Helena Santos-Rodrigues et al. Our
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Factors Influencing the</st
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Thanaletchumi Sathasivam et al. 2.3
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Thanaletchumi Sathasivam et al. The
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Thanaletchumi Sathasivam et al. gro
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Thanaletchumi Sathasivam et al. The
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Thanaletchumi Sathasivam et al. 11.
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Enhancing IC Formation by Evoking H
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Klaus Bruno Schebesch to portray <s
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Klaus Bruno Schebesch 4. Leaning an
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Klaus Bruno Schebesch We argue in f
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Klaus Bruno Schebesch come
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In Search of key F
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Karen Smits et al. contribution, wi
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Karen Smits et al. Table 1: Correla
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Karen Smits et al. staff feel that
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Marta-Christina Suciu et al. This p
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Marta-Christina Suciu et al. The qu
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Marta-Christina Suciu et al. This t
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Information and Communication Techn
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Jukka Surakka et al. The participan
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Jukka Surakka et al. people. Commun
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Personal Knowledge Management (PKM)
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Marzena Świgoń provide th
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Marzena Świgoń (number and type <
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Marzena Świgoń measure self-perce
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Eduardo Tomé what we consider to b
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Eduardo Tomé IC. The intervention
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Eduardo Tomé In the</stro
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Eduardo Tomé to stress that <stron
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Eleni Magdalini Vasileiadou et al.
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José María Viedma Marti products
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Sustainable competitive advantage T
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José María Viedma Marti knowledge
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José María Viedma Marti pr<strong
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José María Viedma Marti All <stro
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ICBS I CBS José María Viedma Mart
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José María Viedma Marti Sullivan,
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2. Balanced scorecard framework Ang
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Angelos Vouldis and Angelica Kokkin
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Unclear benefits of</strong
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Angelos Vouldis and Angelica Kokkin
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9. Discussion and conclusions Angel
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The Global Position of</str
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Piotr Wisniewski safeguarding IC vi
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Piotr Wisniewski Figure 2: Ten larg
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Piotr Wisniewski suspected
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Piotr Wisniewski 2) Slow growth in
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Piotr Wisniewski US 3.8 3.8 3.9 4.3
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2. Hypothesis deve
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3.2 Control variables Deborah Brans
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Deborah Branswijck and Patricia Eve
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Deborah Branswijck and Patricia Eve
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Korosh Gholami et al. Durkheim beli
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Korosh Gholami et al. The effect <s
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Measure the Unmeas
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Knowledge Capital 5. Efforts for de
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Exclusive use of L
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Emmanouil Gkinoglou from th
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Project Assets Need for synergies Q
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Table 5: Sustainability checklist E
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Emmanouil Gkinoglou The next challe
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Kai Mertins and Ronald Orth generat
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Kai Mertins and Ronald Orth Never<s
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Kai Mertins and Ronald Orth <strong
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Ad 2 Structure of
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Kai Mertins and Ronald Orth Hauff,
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Maria Simonova “Concept o
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Maria Simonova The concept regardin
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Maria Simonova Becker, G. S. (1983)
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2. The aim of appl
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Nellija Titova W+I+DP+D+T+M+R (equa
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Nellija Titova performing better. I
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5. Conclusions and furthe</
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Nellija Titova Annex 2: Summary on
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Meaning in the tab
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Krishanthi Ganga Vithana et al. for
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Krishanthi Ganga Vithana et al. sti
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5. Conclusion Krishanthi Ganga Vith
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The Tobing Knowledge Management Arc
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Paul Lumbantobing et al. user, know
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Paul Lumbantobing et al. people con
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Paul Lumbantobing et al. influence
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Develop KM Strategy Description Dev
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Paul Lumbantobing et al. In <strong
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Yuli Purwanti et al. Figure 1: Imag
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Yuli Purwanti et al. Table below is
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Andreea Feraru and Nicoleta Ciucesc
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Roxana Mironescu This could be <str
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Roxana Mironescu Daft, R.L. (2002)
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Paloma Sánchez and Oihana Basilio
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Evaluating Intellectual Capital Usi
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Table 1. CRS input efficiency score
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Stelian Stancu and Anca Domnica Lup
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José Vale et al. However, it is im
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José Vale et al. Pöyhönen, A. an
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