Proceedings of the 12th European Conference on Knowledge ...

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Elena Shakina and Anna Bykova Table 3: Regression results for <strong>European</strong> companies: qualitative factors 1 Notes: 1 – The model where Q-Tobin coefficient was seen as dependent variable is statistical insignificant. * Significant at p
Elena Shakina and Anna Bykova Table 4 provides key results and evidence for two findings <strong>of</strong> this model. First, according to <strong>the</strong> Hypo<strong>the</strong>sis 3 confirmation, <strong>the</strong>re are three intellectual component inputs’ indicators that can be used in determination <strong>of</strong> <strong>the</strong> company’s intellectual capital configuration:' Earnings per employee (human capital). Intangible assets (structural capital). Well-known brand (relational capital). Second, both industry-(manufacture) and country- (Germany) specific features are associated with higher intellectual capital outcomes. Testing <strong>of</strong> Hypo<strong>the</strong>sis 4 both for Russian and <strong>European</strong> companies is <strong>the</strong> final stage <strong>of</strong> our research. We assume that <strong>the</strong> IC components are interconnected not additively but multiplicatively. As a result <strong>of</strong> testing <strong>of</strong> this assumption we have constructed <strong>the</strong> following model: Perf = α *β1HC* δ1SC * λ1RC * ε or (after logarithmic procedure) lnPerf = α + β1lnHC + δ1lnSC + λ1lnRC + ε where Perf is an indicator <strong>of</strong> <strong>the</strong> performance <strong>of</strong> companies (EVA; Q- Tobin; FGV as independent variables); HC is a variable responsible for human capital component; SC is a variable responsible for structural capital component; RC is a variable responsible for relational capital component. We have used intellectual component inputs obtained in <strong>the</strong> previous model as independent variables for human and structural capital except for <strong>the</strong> relation component. We had to replace <strong>the</strong> well-known brand variable with commercial expenses share due to its nominal scale. The results are shown in Table 5: Table 5: Complementarity for <strong>the</strong> IC components for Russian and <strong>European</strong> companies Notes: * Significant at p
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Proceedings <stron
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Contents Title Author(s) Picture <s
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Title Author(s) Picture of<
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Volume Two The Influence of
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The Symbolic Innovation of<
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Biographies of <st
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Jan Pawlowski works as Prof
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in academia. He holds the</
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Biomedical Engineering Research Cen
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Mathematics and Ph
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Thi Hai Hang Nguyen is a lecturer a
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Dan Savescu graduate TCM Faculty, p
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Teaches Business Computing and Stat
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Inocencia Mª Martínez-León and I
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5.2 Measures Inocencia Mª Martíne
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Maurizio Massaro and Roland Bardy p
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Maurizio Massaro and Roland Bardy T
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Maurizio Massaro and Roland Bardy i
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Maurizio Massaro and Roland Bardy T
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Florian Matthes an
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Florian Matthes an
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Florian Matthes an
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Florian Matthes an
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Germany - Towards a Knowledge-Based
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Kai Mertins, Sven Wuscher and Marku
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Sandra Moffett, Ro
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Sandra Moffett, Ro
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Sandra Moffett, Ro
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Sandra Moffett, Ro
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References Sandra Mof</stro
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Syed Moneeb Ali, Mark Woodman and A
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5. Evaluation Syed Moneeb Ali, Mark
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Mohammad Mirkazemi Mood, Farhad Dan
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RI = w k j Mohammad Mirkazemi Mood,
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References Mohammad Mirkazemi Mood,
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Knowledge Mapping Based on EFQM Exc
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Mahmoud Moradi, Mohammad Rahim Rama
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The University Institution’s Impr
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Oliver Moravcik, Dagmar Caganova an
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Figure 9: Researchers at th
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Martina Mullally et al A self-learn
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Martina Mullally et al In t
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Martina Mullally et al contacted, <
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Martina Mullally et al Choo, C. W (
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Fattah Nazem Organizational level
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3. Method of <stro
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Fattah Nazem strengthe</str
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Fattah Nazem Miller, R. (1996). Lea
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Fattah Nazem 1991). Intellectual ca
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Fattah Nazem Table 1: Rotated Compo
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Fattah Nazem Intellectual capital i
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The Knowledge Clinic: Concepts, Met
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Gaby Neumann and Eduardo Tomé capi
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Gaby Neumann and Eduardo Tomé impr
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Gaby Neumann and Eduardo Tomé inst
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A Tenth Anniversary Assessment <str
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Company discussed in Working Knowle
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Gary R Oliver The difficulty with u
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Gary R Oliver accounting precedent
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Gary R Oliver Grant, R. M. (1996).
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Kaspars Osis and Janis Grundspenkis
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Taha Osman, Dhavalkumar Thakker and
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Getting Ready for Knowledge Managem
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Paul Parboteeah, Thomas Jackson and
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Figure 1 Information Management Str
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Knowledge Transfer, Knowledge Shari
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2.2 KBs Dan Paulin and Kaj Suneson
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Dan Paulin and Kaj Suneson Organiz
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Dan Paulin and Kaj Suneson The R&D
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Dan Paulin and Kaj Suneson Paulin,
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Jan Pawlowski and Markus Bick frame
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3.1 Methodology Jan Pawlowski and M
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Jan Pawlowski and Markus Bick aware
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Jan Pawlowski and Markus Bick This
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Jan Pawlowski and Markus Bick Dawes
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Understanding inter-firm networks a
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3.1 Structural properties 3.1.1 Bet
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Meysam Poorkavoos, Yanqing Duan and
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Meysam Poorkavoos, Yanqing Duan and
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Institutional Matrix of</st
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Evgeny Popov, Maxim Vlasov and Anna
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References Evgeny Popov, Maxim Vlas
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Evgeny Popov, Maxim Vlasov and Mari
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Farnaz Rahimi and Mohamad Ebrahim M
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4. Research design Farnaz Rahimi an
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An Intelligent Model to Asses Organ
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Kamaladdin Rahmani Youshanloui et a
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Kamaladdin Rahmani Youshanloui et a
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4. Conclusion Kamaladdin Rahmani Yo
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Risk Analysis for Knowledge Managem
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4. Risk management Lila Rajabion an
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Lila Rajabion and Jafar Zanganeh po
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Lila Rajabion and Jafar Zanganeh D
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Lila Rajabion and Jafar Zanganeh th
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References Lila Rajabion and Jafar
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Anna Maria Costanza Rinaldi state t
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Anna Maria Costanza Rinaldi single
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Anna Maria Costanza Rinaldi With ho
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Figure 3 : Group k - Leathe
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Anna Maria Costanza Rinaldi determi
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Country Strategic Risk and Knowledg
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Eduardo Rodriguez, John Edwards and
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Max Erik Rohde and David Sundaram i
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Max Erik Rohde and David Sundaram
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Max Erik Rohde and David Sundaram S
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Max Erik Rohde and David Sundaram 6
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A Ranking Method for Identification
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Inès Saad criteria are decomposed
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Inès Saad K3 (Crucial knowledge)
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Josune Sáenz, Nekane Aramburu and
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Social Media Mindset and Knowledge
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Risto Säntti social media mindset
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Page 308 and 309: Dan Săvescu, Mihaela-Georgia Sima
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Page 328 and 329: 2.1 Web analytics evolution Alexand
Page 330 and 331: Alexander Schneider and Alexander S
Page 336 and 337: Camilo Augusto Sequeira and Eloi Fe
Page 344 and 345: 9. Conclusions Camilo Augusto Seque
Page 346 and 347: Elena Shakina and Anna Bykova P. Ra
Page 348 and 349: Elena Shakina and Anna Bykova Accor
Page 350 and 351: Elena Shakina and Anna Bykova Figur
Page 352 and 353: Table 1: The sample descriptive sta
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Page 358 and 359: The Major Challenges of</st
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Page 364 and 365: Evangelia Siachou, Sof</str
Page 372 and 373: Relevance of Intel
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Page 388 and 389: Universities as Knowledge Creation
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Infrastructure of
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Natalia Tikhomirova et al global c
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Natalia Tikhomirova et al developm
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Measurement of cus
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Kamila Tislerova and customers, ra<
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Kamila Tislerova as pretty poor (45
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Multi Perspective Framework to Impr
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Choon-Bae Yoo, Igor Hawryszkiewycz
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6.4.1 Content Analysis Choon-Bae Yo
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2. Research objective John T Young
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Figure 2: Exploring and expressing
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John T Young municipal services. Th
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4.1.4 The Customers C John T Young
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6.3 Procedural changes John T Young
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8. The CATWOE Components 8.1 Transf
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John T Young orders could be airfre
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Alexander K. Kofin
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Alexander K. Kofin
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4 : Mobilization of</strong
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Alexander K. Kofin
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Alexander K. Kofin
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1022
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Nadine Amende Figure 1 shows an exa
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Nadine Amende they
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Figure 3: Classification of
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Nadine Amende such as “What are y
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Nadine Amende Davis, F. D. (1986) A
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Evgeny Blagov internal and external
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Evgeny Blagov oriented on t
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Evgeny Blagov (0 - absolutely unimp
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References Evgeny Blagov Arrow, K.J
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Roman Kislov This research looks at
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Roman Kislov role boundary blurring
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Roman Kislov The following methods
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Roman Kislov Lave, J. and Wenger, E
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Tony K. M. Lo and Patrick S.W. Fong
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Type P=A=L P=A, L P, A=L P=L, A P,
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6. Case analysis Tony K. M. Lo and
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Tony K. M. Lo and Patrick S.W. Fong
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KM as a Solution for the</s
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Thi Hai Hang Nguyen et al competiti
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Thi Hai Hang Nguyen et al The varia
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Thi Hai Hang Nguyen et al The resul
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Knowledge Base Development
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2. Literature review 2.1 AC: Theore
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2.3 The inter-relations between SC
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Omid Omidvar Jansen, J. J. P., Van
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Sakura Shimada and that of<
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Sakura Shimada Figure 1: Strategic
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Sakura Shimada broader repercussion
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Sakura Shimada Excousseau, J-L. (20
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Simon Woll The research topic can b
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Simon Woll UI research projects are
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Figure 2: Research design and metho
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1088
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1090
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Chris Blodgett leadership journey t
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Figure 2: Needleman’s Knowledge P
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Chris Blodgett Analysts turn inform
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Figure 8: Cynefin Framework Chris B
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Chris Blodgett IKM Level 1: Inform
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7. Conclusion Chris Blodgett Given
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Stefanie Dannemann However, what wo
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Stefanie Dannemann In modern econom
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2. Research design and methodology
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3.4 KM Applications in IDSC Mohamed
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Mohamed Farid 3.5 Problems with <st
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Mohamed Farid “Enterprise collabo
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Mohamed Farid The design of
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Mohamed Farid For the</stro
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Susan McIntyre and Kate Kaminska re
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Susan McIntyre and Kate Kaminska C
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Susan McIntyre and Kate Kaminska Th
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Susan McIntyre and Kate Kaminska il
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1128
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Óscar Arias Londoño mention that
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5.4 Tacit Knowledge Óscar Arias Lo
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Proposal For A 2.0 Knowledge Manage
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Lillyana María Giraldo Marín et a
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Similarity and Accuracy of<
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Nina Groß et al reporting and cont
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Ravinder Singh Kahlon and Man-Chie
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Figure 3: Non-IT and IT Kiviat Diag
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Appendix B Ravinder Singh Kahlon an
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Pushkal Pandey, Sandra Mof<
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Pushkal Pandey, Sandra Mof<
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José Vásquez Paniagua According t
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José Vásquez Paniagua the
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