Proceedings of the 3rd European Conference on Intellectual Capital

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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). 270
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]. 271
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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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Page 238 and 239: Eliciting Tacit Knowledge From a Do
Page 240 and 241: Peter Marshall and Damian Gordon MM
Page 242 and 243: Peter Marshall and Damian Gordon re
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Page 248 and 249: Maurizio Massaro et al. crucial fac
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Page 252 and 253: Maurizio Massaro et al. autonomy <s
Page 254 and 255: Maurizio Massaro et al. Chennal (20
Page 256 and 257: Intellectual Capital Management: Ca
Page 258 and 259: Florinda Matos et al. These models
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Page 262 and 263: Florinda Matos et al. Finally, <str
Page 264 and 265: Florinda Matos et al. The training
Page 266 and 267: Florinda Matos et al. 47. Opinion
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Page 272 and 273: Florinda Matos et al. Integrated te
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Page 276 and 277: Knowledge Management for Knowledge
Page 278 and 279: 3. Our research Ludmila Mládková
Page 280 and 281: Ludmila Mládková organizational s
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Page 284 and 285: Applying the VAIC
Page 288 and 289: Maria Molodchik and Anna Bykova 2.
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Page 292 and 293: Maria Molodchik and Anna Bykova The
Page 294 and 295: Perspectives on the</strong
Page 296 and 297: Maria Cristina Morariu as we consid
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Page 300 and 301: Maria Cristina Morariu for determin
Page 302 and 303: The Structural Model of</st
Page 304 and 305: Fattah Nazem Ackerley (2006) reveal
Page 306 and 307: Fattah Nazem The research instrumen
Page 308 and 309: Fattah Nazem intellectual capital m
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Page 312 and 313: Andrei Stefan Nestian organization.
Page 314 and 315: Andrei Stefan Nestian Chaordic syst
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Page 318 and 319: Increasing Knowledge Management Mat
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Page 326 and 327: 5. Discussion and summary Theodora
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Page 330 and 331: Bongani Ngwenya late adopters respo
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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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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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Nargiza Abdullaeva and Campbell War
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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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