Proceedings of the 3rd European Conference on Intellectual Capital

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Nicolae Al. Pop et al. <strong>the</strong> studies at <strong>the</strong> same university or <strong>the</strong> recommendation potential. In fig. 1 we can observe <strong>the</strong> absolute satisfaction <strong>of</strong> <strong>the</strong>se items, on a scale from 1 to 7, where 7 means very satisfied and 1 means totally dissatisfied. 5.2 5 4.8 4.6 4.4 4.2 4 3.8 Competences 5.06 Teaching Style 4.4 Pedagogical Skills 4.67 Implication 4.38 Satisfaction Attitude 4.42 Communication 4.24 Availability Figure 1: Satisfaction with <strong>the</strong> competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors at a university (on a scale <strong>of</strong> 1 to 7, where 7=very satisfied and 1=totally dissatisfied) As we can observe in fig. 1 <strong>the</strong> satisfaction <strong>of</strong> <strong>the</strong> students with <strong>the</strong> competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors have values between 4 (average satisfaction) and 5 (ra<strong>the</strong>r satisfied). Although <strong>the</strong>re is no high variation between <strong>the</strong> items, we can observe that <strong>the</strong> students are most satisfied with <strong>the</strong> competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors (5.06) and with <strong>the</strong> pedagogical skills (4.67) and least satisfied with <strong>the</strong> communication between <strong>the</strong> pr<strong>of</strong>essors and <strong>the</strong> students (4.24) and <strong>the</strong> availability <strong>of</strong> pr<strong>of</strong>essors for discussions (4.32). The values presented correspond to <strong>the</strong> average item “satisfied that you chose this university”, which has a value <strong>of</strong> 4.83. It is interesting to observe that <strong>the</strong> value <strong>of</strong> this item, asked at <strong>the</strong> end <strong>of</strong> <strong>the</strong> questionnaire is higher than <strong>the</strong> overall satisfaction, asked at <strong>the</strong> beginning <strong>of</strong> <strong>the</strong> questionnaire, which has a value <strong>of</strong> 3.16. This indicates that <strong>the</strong> cognitive satisfaction (after taking in consideration all aspects regarding <strong>the</strong> university) is higher than <strong>the</strong> emotional satisfaction (a value given, without taking in consideration all items). The university should take this result in consideration and improve its image by marketing more several positive aspects. Because <strong>of</strong> this result we will take in consideration in <strong>the</strong> fur<strong>the</strong>r analysis <strong>the</strong> item “satisfied that you chose this university”. In order to see <strong>the</strong> influence <strong>of</strong> all <strong>the</strong>se factors on <strong>the</strong> satisfaction with <strong>the</strong> university, we have done a regression analysis with <strong>the</strong> help <strong>of</strong> <strong>the</strong> SPSS. In this analysis we had as dependent variable <strong>the</strong> item “satisfied that you chose this university” and <strong>the</strong> independent variables <strong>the</strong> items presented in fig. 1. The results <strong>of</strong> <strong>the</strong> regression analysis are presented in fig. 2. According to <strong>the</strong> value <strong>of</strong> <strong>the</strong> R-Square obtained in <strong>the</strong> regression analysis we can state that 26% <strong>of</strong> <strong>the</strong> dependent variable can be explained by <strong>the</strong> analyzed factors. Although at <strong>the</strong> first glance this value is not very high, if we take in consideration <strong>the</strong> fact that in <strong>the</strong> study, <strong>the</strong>re have been considered 80 satisfaction items, this value is a significant one. This value is also confirmed by <strong>the</strong> R- Square change. Also <strong>the</strong> F-Test in <strong>the</strong> ANOVA Table shows a significance <strong>of</strong> <strong>the</strong> regression <strong>of</strong> 99%. According to <strong>the</strong> results <strong>of</strong> <strong>the</strong> Regression analysis and assuming that all o<strong>the</strong>r factors are constant we have <strong>the</strong> following regression function: Satisfaction = 1.66 + 0.21*competences + 0.12*teaching_style – 0.28*pedagogical_skills + 0.12*implication + 0.03*attitude + 0.12*communication + 0.08*availability So we can observe that <strong>the</strong> highest influence on <strong>the</strong> overall satisfaction has <strong>the</strong> competences <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors and <strong>the</strong> least influence has <strong>the</strong> attitude <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors towards <strong>the</strong> students. The next highest influence has <strong>the</strong> teaching style, <strong>the</strong> implication and <strong>the</strong> communication <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors towards <strong>the</strong> students. The BETA-test in <strong>the</strong> SPSS analysis shows also <strong>the</strong> highest influence for <strong>the</strong> item competences <strong>of</strong> pr<strong>of</strong>essors. With <strong>the</strong> exception <strong>of</strong> <strong>the</strong> items “pedagogical skills” and “attitude”, for all o<strong>the</strong>r factors <strong>the</strong> significance has a value close to “0” so that we can reject <strong>the</strong> Zero-Hypo<strong>the</strong>sis. 346 4.32
Nicolae Al. Pop et al. Consequently, with <strong>the</strong> exception <strong>of</strong> <strong>the</strong> two mentioned factors, all o<strong>the</strong>r factors have a significant influence on <strong>the</strong> dependent variable. Ano<strong>the</strong>r aspect which confirms this relation is <strong>the</strong> t-test, which also shows an influence <strong>of</strong> all factors on <strong>the</strong> dependent variable, with <strong>the</strong> exception <strong>of</strong> “pedagogical skills” and “attitude” <strong>of</strong> pr<strong>of</strong>essors towards students. The correlation table between <strong>the</strong> independent variables shows no significant dependence between <strong>the</strong> analyzed items. Model R 1 R Square Adjusted R Square Model Summary b Change Statistics Std. Error <strong>of</strong> R Square <strong>the</strong> Estimate Change F Change df1 df2 Sig. F Change Durbin- Watson 1 .515 a .265 .261 1.18156 .265 59.411 7 1152 .000 1.566 a. Predictors: (Constant), availability pr<strong>of</strong>essors, competences pr<strong>of</strong>essors, pedagogical skills, attitude pr<strong>of</strong>essors, teaching style, implication, communication b. Dependent Variable: satisfied that you chose ASE 1 ANOVA b Model Sum <strong>of</strong> Squares df Mean Square F Sig. Regression 580.603 7 82.943 59.411 .000 a Residual 1608.286 1152 1.396 Total 2188.889 1159 a. Predictors: (Constant), availability pr<strong>of</strong>essors, competences pr<strong>of</strong>essors, pedagogical skills, attitude pr<strong>of</strong>essors, teaching style, implication, communication b. Dependent Variable: satisfied that you chose ASE Coefficients a Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. (Constant) 1.663 .168 9.878 .000 competences pr<strong>of</strong>essors .219 .035 .193 6.221 .000 teaching style .129 .039 .118 3.314 .001 pedagogical skills -.028 .038 -.027 -.740 .459 implication .127 .037 .126 3.397 .001 attitude .038 .037 .039 1.038 .299 communication .127 .037 .133 3.482 .001 availability .084 .033 .088 2.563 .010 a. Dependent Variable: satisfied that you chose ASE Figure 2: Results <strong>of</strong> <strong>the</strong> regression analysis If we analyze <strong>the</strong> willingness <strong>of</strong> <strong>the</strong> students to continue <strong>the</strong>ir studies within <strong>the</strong> same university, we can observe that more satisfied students ra<strong>the</strong>r want to continue <strong>the</strong>ir studies. As fig. 3 shows only 50% <strong>of</strong> <strong>the</strong> dissatisfied students want to continue <strong>the</strong>ir studies within <strong>the</strong> same university, while over 62% <strong>of</strong> <strong>the</strong> students from <strong>the</strong> ra<strong>the</strong>r satisfied students have <strong>the</strong> intention to remain <strong>the</strong> same university. As this study shows, <strong>the</strong> human capital and <strong>the</strong> relational capital <strong>of</strong> a university are very important for its image and success on <strong>the</strong> higher education services market. Since <strong>the</strong> delivered services rely on <strong>the</strong> human capital, <strong>the</strong> quality <strong>of</strong> <strong>the</strong> pr<strong>of</strong>essors performing teaching activities represents a core asset <strong>of</strong> a university. By <strong>the</strong>ir knowledge and competence <strong>the</strong>y contribute directly to <strong>the</strong> improvement <strong>of</strong> <strong>the</strong> relationship with <strong>the</strong> students. The findings point out that <strong>the</strong> perceived competence, <strong>the</strong> teaching style and <strong>the</strong> implication have <strong>the</strong> most influence on <strong>the</strong> students’ overall satisfaction level. So does <strong>the</strong> communication between <strong>the</strong> pr<strong>of</strong>essors and <strong>the</strong> students, which scored <strong>the</strong> lowest specific satisfaction level. Two main ideas for fur<strong>the</strong>r consideration arise: The positive aspect is that <strong>the</strong> factor with most influence on <strong>the</strong> overall 347
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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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Page 330 and 331: Bongani Ngwenya late adopters respo
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Page 388 and 389: 2.1 Study measures Kent Rondeau and
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Page 394 and 395: Intellectual Capital and a Firm’s
Page 396 and 397: Figure 1: Hypothes
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Page 404 and 405: Factors Influencing the</st
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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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562
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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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582
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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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Proceedings of the 3rd European Conference on Intellectual Capital

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