Proceedings of the 3rd European Conference on Intellectual Capital

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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
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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
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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 f
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Donley Carrington and Mike Tayles l
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Donley Carrington and Mike Tayles i
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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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Víctor Raúl López Ruiz et al. NI
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EI c k i 1 w PC i ic Víctor Raúl
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Víctor Raúl López Ruiz et al. Ta
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Víctor Raúl López Ruiz et al. Co
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Víctor Raúl López Ruiz et al. At
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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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Florinda Matos et al. The Quadrant
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Florinda Matos et al. Integrated te
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Florinda Matos et al. The networks
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Knowledge Management for Knowledge
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3. Our research Ludmila Mládková
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Ludmila Mládková organizational s
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Ludmila Mládková mentioned only b
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Applying the VAIC
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Maria Molodchik and Anna Bykova pro
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Maria Molodchik and Anna Bykova 2.
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Maria Molodchik and Anna Bykova Let
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Maria Molodchik and Anna Bykova The
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Perspectives on the</strong
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Maria Cristina Morariu as we consid
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Maria Cristina Morariu Tobin’s q
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Maria Cristina Morariu for determin
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The Structural Model of</st
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Fattah Nazem Ackerley (2006) reveal
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Fattah Nazem The research instrumen
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Fattah Nazem intellectual capital m
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Fattah Nazem Johnson, M.J. (1986) T
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Andrei Stefan Nestian organization.
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Andrei Stefan Nestian Chaordic syst
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Andrei Stefan Nestian environment,
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Increasing Knowledge Management Mat
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Theodora Ngosi et al. 2.2 Dominatin
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Theodora Ngosi et al. Figure 1: Del
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Theodora Ngosi et al. IT systems, a
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5. Discussion and summary Theodora
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Theodora Ngosi et al. Weill, P., an
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Bongani Ngwenya late adopters respo
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Bongani Ngwenya This paper extends
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Bongani Ngwenya argument, t
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Bongani Ngwenya DiMaggio, P. J., an
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The Quality of Kno
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5.2 5 4.8 4.6 4.4 4.2 4 3.8 Compete
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Corina Pelau et al. In order to imp
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Hierarchy and Tacit Knowledge in <s
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Ulrica Pettersson and James Nyce in
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Ulrica Pettersson and James Nyce mi
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Katja Pook and Campbell Warden time
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Katja Pook and Campbell Warden futu
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5. Commonalities of</strong
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Katja Pook and Campbell Warden <str
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Katja Pook and Campbell Warden Lazl
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Nicolae Al. Pop et al. satisfaction
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Nicolae Al. Pop et al. the<
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Nicolae Al. Pop et al. satisfaction
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Knowledge Cities: A Portuguese Case
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Katia Rodrigues and Eduardo Tomé
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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. <stron
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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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498
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500
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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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Page 614 and 615: Roxana Mironescu This could be <str
Page 616 and 617: Roxana Mironescu Daft, R.L. (2002)
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Page 620 and 621: Evaluating Intellectual Capital Usi
Page 622 and 623: Table 1. CRS input efficiency score
Page 624 and 625: Stelian Stancu and Anca Domnica Lup
Page 626 and 627: José Vale et al. However, it is im
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