Proceedings of the 8th International Conference on Intellectual ...

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Maria Cristina Morariu accordance with our expectations, <strong>the</strong>se findings appear to entirely support H1b, H1c, H2c, H3b, H3c, H4a and H4b, while rejecting, at least partially <strong>the</strong> rest <strong>of</strong> <strong>the</strong> hypo<strong>the</strong>ses. Table 7: Pearson correlation matrix VAHU_LnVA SCVA_Rec VAIN_Rec VACA_rec VAICTM_rec ROE_rec ATO_Rec MB_Rec LN_SALES INDUSTRY VAHU_LnVA Pearson Correlation 1 .844** .991** -.382 .910** .307 -.746** -.197 -.571* -.513 Sig. (2-tailed) .000 .000 .178 .000 .285 .002 .499 .033 .061 SCVA_Rec Pearson Correlation .844** 1 .908** -.098 .924** .563* -.570* .074 -.486 -.410 Sig. (2-tailed) .000 .000 .739 .000 .036 .033 .801 .078 .146 VAIN_Rec Pearson Correlation .991** .908** 1 -.323 .941** .379 -.724** -.136 -.567* -.502 Sig. (2-tailed) .000 .000 .260 .000 .181 .003 .642 .035 .067 VACA_rec Pearson Correlation -.382 -.098 -.323 1 .018 .615* .278 .858** .542* -.180 Sig. (2-tailed) .178 .739 .260 .952 .019 .336 .000 .045 .538 VAICTM_rec Pearson Correlation .910** .924** .941** .018 1 .621* -.666** .164 -.404 -.595* Sig. (2-tailed) .000 .000 .000 .952 .018 .009 .575 .152 .025 ROE_rec Pearson Correlation .307 .563* .379 .615* .621* 1 -.342 .731** .008 -.527 Sig. (2-tailed) .285 .036 .181 .019 .018 .232 .003 .980 .053 ATO_Rec Pearson Correlation -.746** -.570* -.724** .278 -.666** -.342 1 -.085 .321 .603* Sig. (2-tailed) .002 .033 .003 .336 .009 .232 .772 .264 .023 MB_Rec Pearson Correlation -.197 .074 -.136 .858** .164 .731** -.085 1 .368 -.459 Sig. (2-tailed) .499 .801 .642 .000 .575 .003 .772 .195 .099 LN_SALES Pearson Correlation -.571* -.486 -.567* .542* -.404 .008 .321 .368 1 .465 Sig. (2-tailed) .033 .078 .035 .045 .152 .980 .264 .195 .094 INDUSTRY Pearson Correlation -.513 -.410 -.502 -.180 -.595* -.527 .603* -.459 .465 1 Sig. (2-tailed) .061 .146 .067 .538 .025 .053 .023 .099 .094 **. Correlation is significant at <strong>the</strong> 0.01 level (2-tailed). Correlations a 390 *. Correlation is significant at <strong>the</strong> 0.05 level (2-tailed). a. Listwise N=14
4.3 Regression analysis Maria Cristina Morariu Table 8 exhibits <strong>the</strong> results <strong>of</strong> <strong>the</strong> regression coefficients for general explanatory variables using MB as <strong>the</strong> dependent variable. The model is statistically significant (F (3, 10) = 5.994, p < 0.05). However, contrary to <strong>the</strong>oretical expectations, <strong>the</strong> results indicate a non significant association between <strong>the</strong> VAIC and MB and. The adjusted R 2 is .535 indicating that 54% <strong>of</strong> <strong>the</strong> variance in MB was explained by <strong>the</strong> model. Table 9 below shows <strong>the</strong> results <strong>of</strong> regression coefficients for general explanatory variables, using pr<strong>of</strong>itability as <strong>the</strong> dependent variable. The model is statistically significant (F (3, 10) = 4.141, p < 0.05). However, contrary to <strong>the</strong>oretical expectations, <strong>the</strong> results indicate a non significant association between <strong>the</strong> VAIC, company size and industry type and companies’ pr<strong>of</strong>itability. The adjusted R 2 is .420 indicating that 42% <strong>of</strong> <strong>the</strong> variance in pr<strong>of</strong>itability was explained by <strong>the</strong> model. Table 10 exhibits <strong>the</strong> results <strong>of</strong> <strong>the</strong> regression coefficients for general explanatory variables, using productivity as <strong>the</strong> dependent variable. The model is not statistically significant (F (3, 10) = 3.465, p > .05).The results analysed up to this point partially confirm <strong>the</strong> findings <strong>of</strong> Firer and Williams (2003), Ghosh and Mondal (2009) and appear to reject H1a, H1b and H1c. Table 8: Regression analysis_M1 Coefficients a Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) .836 .340 2.460 .034 VAICTM_rec -.009 .095 -.024 -.099 .923 LN_SALES .018 .005 .739 3.403 .007 INDUSTRY -.070 .021 -.816 -3.304 .008 a. Dependent Variable: MB_Rec; R Square = .643; F (3,10) = 5.994, p < 0.05 Table 9: Regression analysis_M2 Coefficients a Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) -.333 .589 -.566 .584 VAICTM_rec .342 .164 .558 2.087 .063 LN_SALES .015 .009 .413 1.704 .119 INDUSTRY -.051 .037 -.388 -1.404 .191 a. Dependent Variable: ROE_rec; R Square = .554; F (3,10) = 4.141, p < 0.05 Table 10: Regression analysis_M3 Coefficients a Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 1.287 .256 5.034 .001 VAICTM_rec -.122 .071 -.481 -1.716 .117 LN_SALES .000 .004 -.027 -.105 .918 INDUSTRY .018 .016 .329 1.136 .282 a. Dependent Variable: ATO_Rec; R Squared = .510; F (3,10) = 3.465, p .059 Table 11 exhibits <strong>the</strong> results <strong>of</strong> <strong>the</strong> regression coefficients for all explanatory variables using MB as <strong>the</strong> dependent variable. The model is significant (F (5,8) = 28.037, p < 0.05) and explains 91.2% <strong>of</strong> 391
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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. Main
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Paper Title Author(s) Page No. Know
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Preface These proceedings represent
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TU Dortmund, Germany, ); Wing Bun L
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William Halal is Prof</stro
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Evgeny Blagov has obtained a specia
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science and mathem
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George Majdalany is a PhD candidate
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Joyce Nesamani Simson is a PhD cand
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Manpower Discipline Based on Knowle
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Peyman Akhavan et al. brains, knowl
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Peyman Akhavan et al. showed that o
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Peyman Akhavan et al. appropriate l
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Peyman Akhavan et al. sources for c
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Attitudes Towards Changes and Organ
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Ruth Alas et al. During the
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Professional inter
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Ruth Alas et al. Table 4: Correlati
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Research was supported by ETF Grant
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Rivadávia Correa Drummond de Alvar
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5. Conclusions Rivadávia Correa Dr
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Toward a Meta-Synthe</stron
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Xiaomi An et al 2.3 Reasons for dev
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Xiaomi An et al PTC works closely w
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Xiaomi An et al The first is an adm
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Xiaomi An et al policy reflections
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Figure 1: Transmission gear Marko A
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Marko Anzelak et al. knowledge basi
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Marko Anzelak et al. 72% recognise
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Marko Anzelak et al. virtually all
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Gabriel Prananingrum Aryanindita an
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Rita Babiliūtė and Kęstutis Kri
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Knowledge Management, Cultural Know
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Leonard Barnett and Edward Carter 2
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Leonard Barnett and Edward Carter p
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Leonard Barnett and Edward Carter p
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Leonard Barnett and Edward Carter d
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Impact of Knowledg
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Bob Barrett shorter product life-cy
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Bob Barrett 6. Concept of</
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Bob Barrett Brown, J.S. and Duguid
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Aurilla Aurelie Bechina and Eli Hus
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Lorne Booker et al. Knowledge is us
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Figure 1: Business Valuation Knowle
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3.4 Practitioner knowledge market L
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4. Implications Lorne Booker et al.
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Strategic Thinking Dimensions in Em
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Constantin Bratianu et al. shows <s
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Constantin Bratianu et al. Academy
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Constantin Bratianu et al. cases wi
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Constantin Bratianu et al. Pinker,
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Delio Ignacio Castañeda and Sandra
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Quality in Teacher Education: A Sys
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Rajendra Chetty The mechanism <stro
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Academic leadership Rajendra Chetty
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Rajendra Chetty There must be a re-
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Developing Personal Knowledge Manag
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Thirathep Chonmait
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Thirathep Chonmait
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The Relationship Between Knowledge
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Samuel Kai Wah Chu et al. A knowled
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Samuel Kai Wah Chu et al. negative
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Samuel Kai Wah Chu et al. Questionn
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Samuel Kai Wah Chu et al. few done
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Value Creation Through Collaborativ
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Ridha Derrouiche et al. level for e
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Ridha Derrouiche et al. best, <stro
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Ridha Derrouiche et al. experience
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Ridha Derrouiche et al. Of course,
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Organizational Learning and Transfo
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Irra Chrisyanti Dewi was carried ou
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Irra Chrisyanti Dewi Table 2: Valid
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Irra Chrisyanti Dewi Library is exp
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Knowledge Acquisition and Sharing:
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Ikechukwu Diugwu articulated and st
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Ikechukwu Diugwu establishing setti
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Ikechukwu Diugwu Mentzer, J. T., Mi
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Eva Eckenhofer cou
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Eva Eckenhofer The
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Eva Eckenhofer The
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Eva Eckenhofer Bur
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1.2 Intellectual capital and innova
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3.2.2 Reliability Irene Y.H. Fan an
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Figure 4: latent variable coefficie
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Irene Y.H. Fan and Rongbin W.B. Lee
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Irene Y.H. Fan and Rongbin W.B. Lee
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2.1 Appropriation Ronny Gey From a
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Ronny Gey Table 1: Characterization
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Ronny Gey The developers feel that
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Ronny Gey A first limitation we wer
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Kenneth Grant part of</stro
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Kenneth Grant The diffusion was stu
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Kenneth Grant A detailed computer-s
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Kenneth Grant did not come to <stro
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Kenneth Grant of m
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Michel Grundstein although hundred
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Michel Grundstein Figure 1: DITEK p
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Michel Grundstein 4.1.1 Knowledge i
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Michel Grundstein share. However <s
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6. Conclusions and perspectives Mic
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Intellectual Property Valuation Dec
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Hezlin Harris et al. (Burrone and S
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Hezlin Harris et al. The need for s
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Acknowledgements Hezlin Harris et a
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Managing an Assessment Process <str
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Table 1: List of N
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Shaheed Hartley Table 3: OEQ respon
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Shaheed Hartley It is very difficul
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A Community Framework for Knowledge
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Igor Hawryszkiewycz between communi
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Figure 4: Modeling knowledge subsys
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Igor Hawryszkiewycz Prahalad, C.K.,
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Eli Hustad and Aurilla Aurelie Bech
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Does Knowledge Stickiness Affect a
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Nurul Indarti knowledge (Nelson and
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3. Research methods 3.1 Research in
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Coded knowledge Nurul Indarti The f
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Nurul Indarti Arrow, K. J. (1969).
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Organizational Learning in Pr<stron
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Brigita Janiunaite et al. learn and
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Brigita Janiunaite et al. given dif
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Brigita Janiunaite et al. empowered
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Brigita Janiunaite et al. A statist
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Brigita Janiunaite et al. learning
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Balancing the Ince
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Giedrius Jucevičius safeguard and
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Giedrius Jucevičius nature <strong
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Giedrius Jucevičius motivating fac
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Giedrius Jucevičius Ghosh, T. (200
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Palmira Juceviciene and Vyda Mozuri
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Robertas Jucevicius relations shoul
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Robertas Jucevicius do not know whe
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Robertas Jucevicius and innovation
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Robertas Jucevicius Lawton Smith, H
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Annukka Jyrämä et al. knowledge c
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Annukka Jyrämä et al. Respondents
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Annukka Jyrämä et al. various cit
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Annukka Jyrämä et al. example hea
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Managing Information Overload - Tea
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Harri Ketamo conceptual structure a
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Harri Ketamo limited to YouTube, Fl
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Harri Ketamo Figure 8: Visualizatio
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Farmers’ Knowledge Management in
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2.1 Farmer knowledge Le Nguyen Doan
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Le Nguyen Doan Khoi days needed for
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Le Nguyen Doan Khoi dosage. Moreove
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Le Nguyen Doan Khoi use homemade in
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Developing Human Capital through Ne
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Eric Kong organisation as individua
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Eric Kong As described by Tosey and
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Eric Kong Craft, A. (2001) "Neuro-l
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Sophie Le Bellu and Benoit Le Blanc
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Results Sophie Le Bellu and Benoit
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Pornpen Lertthasanawong and Nopasit
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Page 367 and 368: 2. Literature review Ya-Hui Ling 2.
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Page 375 and 376: Maksim Maksimovic et al paper prese
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Page 405 and 406: Maria Cristina Morariu economy and
Page 407 and 408: Table 1: Literature review summary
Page 409 and 410: Maria Cristina Morariu ATO = Turnov
Page 411: 4.2 Correlation analysis Maria Cris
Page 415 and 416: Table 13: Regression analysis_M6 Mo
Page 417 and 418: The Arrival of <st
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Page 427 and 428: Wannapa Pipattanawong et al. cannot
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Page 433 and 434: The Dark Side of S
Page 435 and 436: Siwarit Pongsakornrungsilp vans, ro
Page 437 and 438: Siwarit Pongsakornrungsilp Kreng Ja
Page 439: Siwarit Pongsakornrungsilp Lave, J.
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