Knowledge sharing intention among employees in small and medium sized enterprises a case in ho chi minh city viet nam

UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Ta Tran Trung KNOWLEDGE SHARING INTENTION AMONG EMPLOYEES IN SMALL AND MEDIUM SIZED ENTERPRISES: A CASE IN HO CHI MINH CITY, VIETNAM MASTER OF BUSINESS ADMINISTRATION Ho Chi Minh City – Year 2018 UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Ta Tran Trung KNOWLEDGE SHARING INTENTION AMONG EMPLOYEES IN SMALL AND MEDIUM SIZED ENTERPRISES: A CASE IN HO CHI MINH CITY, VIETNAM MASTER OF BUSINESS ADMINISTRATION SUPERVISOR: Dr TRAN PHUONG THAO Ho Chi Minh City – Year 2018 ACKNOWLEDGEMENT I would like to express my deep gratitude to my supervisor, Dr Tran Phuong Thao for het patient attitude, valuable comment, helpful advice and continuous encouragement during the time of research and writing this research work My grateful thanks are also extended to my friends, my lecturers and Research Committee for their valuable time as their insightful comments and meaningful suggestions were contributed significantly for my completion of this research LIST OF ABBREVIATION WORDS CEO: Chief Executive Officer CFA: Confirmatory Factor Analysis EFA Exploratory Factor Analysis GDP: Gross Domestic Product ITC: Information and communication technology SEM: Structural Equation Modeling SMEs: Small and medium sized enterprises TRA: The Theory of Reasoned Action VND: Vietnamese Dong LIST OF TABLES Table A summary of prior studies on knowledge sharing 16 Table Measurement Scale 19 Table Descriptive statistics 21 Table Means and Cronbach alpha of items after deleting items results 25 Table Pattern matrix 27 Table KMO and Bartlett's Test 28 Table SEM Hypothesis testing results 32 Table Multi-group analysis results 34 LIST OF FIGURES Figure Conceptual model 17 Figure CFA model 29 Figure SEM Results 31 Figure Multi-group analysis model 33 TABLE OF CONTENTS Introduction 2 Literature review and hypothesis development 2.1 Foundational theory Social Exchange Theory Theory of Reasoned Action 2.2 Related review and hypothesis Research methodology 17 3.1 Research procedure 17 3.2 Measurements 18 3.3 Sampling and methods 20 3.3.1 Sampling 20 3.3.2 Methods 22 Data analysis and results 23 4.1 Reliability analysis 23 4.2 Exploratory Factor Analysis 26 4.3 Confirmatory Factor Analysis 28 4.4 SEM modeling 30 4.5 Hypothesis testing 31 4.6 Multi-group analysis results (The moderating effect results) 32 Conclusions and implications 35 5.1 Conclusions 35 5.2 Implications 35 5.3 Limitations and directions for future research 38 References 40 Appendix Questionnaire English version 49 Appendix Bảng câu hỏi khảo sát (Questionnaire Vietnamese version) 53 Appendix Cronbach’s alpha results 57 Appendix EFA results 59 KMO and Bartlett's Test 59 Appendix CFA results 62 Appendix SEM results 66 Appendix Multi-group analysis results 70 Abstract Knowledge is a valuable asset, a creativity, innovation, and potential contribution for the development of business That is the reason why knowledge sharing is researched to find out the way to promote knowledge sharing, to take advantage of this core competency A survey with a convenience sample of about 450 SMEs employees in Ho Chi Minh City was conducted with 18 variables and 429 observations valid samples in order to assess an overview of the opinions of all employees in SMEs on intend to share knowledge The data were analyzed by Reliability Analysis, EFA, CFA, SEM method and the results indicated factors Image, Subjective norms and Rewards have positive influence on the intention to share knowledge and Individual culture has a significant moderating effect on the relationship between both Image and Subjective norms toward intention to share knowledge Based on the finding of the research, the organization should respect and listen to the opinions of the employees and create the awareness of knowledge sharing as a must As majority of prior researches on enterprise knowledge sharing focus mainly on the public sector, large private companies, these new findings can be investigated in further research, because sharing knowledge in SMEs is still a new concept in developing country as Vietnam Keywords knowledge sharing intention, small and medium sized enterprises, Subjective norms, Image, Rewards, Intention to share knowledge, Individual culture 1 Introduction Managing knowledge effectively is believed to be crucial to the achievement of the organization, specifically in those companies that want to maintain their dominance through creativity (Dieng, 2000) As more companies try to increase benefit by widen their knowledge assets, a lot of enterprises have considered knowledge sharing as part of their strategy It is believed that knowledge sharing has been concerned by many academics and professionals globally Zakaria, Amelinckx and Wilemon (2004) confirm that the role of knowledge sharing within a team should be emphasized Blair (2002) believes that when employees in the organization gain a lot of knowledge in their organization, the organization has something far more valuable than data and information Many prior studies show that collaboration and knowledge sharing are important factors that organization should applied so as to attain continued competitive advantage (Tapscott & Williams, 2006) Cyril Eze, Guan Gan Goh, Yih Goh and Ling Tan (2013) state that a number of SMEs are manipulate knowledge management program to keep up with or stay ahead of their competitors as a business leader In Vietnamese organizations, it is easy to see that the tendency to approach new things in knowledge has evolved since the "Doi Moi" era to adapt to the globalized economy Although the sharing of knowledge is often seen as something new and meaningful in the context of Vietnam (Dong, Gia Liem, & Grossman, 2010), Dong et al., (2010) reveal that this is in fact only strongly empower individuals to access organizational knowledge instead of sharing their knowledge to other members Beside the practicality of knowledge sharing in companies, there are existing elements restraint knowledge sharing culture, including the lack of organizational structures, unfriendly sharing working environment, and denominational segregation (Davenport & Prusak, 1998; as cited in Hendriks, 1999) Additionally, the fact is that SME enterprises occupy most of the companies in Vietnam and contribute most of the domestic work (Swierczek & Ha, 2003; Dan, 2008) In general, the ineffective knowledge sharing system can make employees in a company unable to improve their knowledge and transfer their experience to other members On the other hand, a rich and effective knowledge sharing system can help employees save time and effort to solve problems that arise in the workplace Witherspoon, Bergner, Cockrell and Stone (2013) believe that the future success of the organization will depend on sharing knowledge and this will be a vital strategy in the new era It is understood that an organization will create a better working environment for development and innovation as it builds a better and more effective knowledge sharing system In addition, Desouza and Awazu (2006) state that common knowledge of employees of SMEs is deep and broad, and it can actively support small business in knowledge sharing Prior studies also indicate some of the factors that impact the knowledge sharing intension such as company rewards, reciprocity, ICT use, knowledge self-efficacy and top management support (Chang, Hsu, Shiau, & Tsai, 2015; Dong et al., 2010; Kanzler, Niedergassel, & Leker, 2012; Tohidinia & Mosakhani, 2010) However, as given by Tohidinia and Mosakhani (2010) almost studies take into account determinants of knowledge sharing intention in a specific group of people or a whole population Notably, studies by Fathi, Eze and Goh (2011) and also Chong, Chong and Wong (2007) indicate that the majority of prior researches on enterprise knowledge sharing focus on the public sector, large private companies, while very few focus on knowledge management conducted in SMEs Additionally, according to Yu (2014), individual culture in different countries may affect the knowledge sharing intention, but there are not many studies investigating the influence of this factor on knowledge sharing intention In SMEs the knowledge management model which is basically based upon knowledge sharing – through constant and open communication (often SME strength) – the making explicit of often buried or tacit knowledge held by all employees (Gray, 2006) Gold, Malhotra and Segars (2001) emphasize that knowledge infrastructures such as technology, structure and culture along with knowledge acquisition, conversion, application and protection are essential organizational capabilities for higher organizational performance Therefore, SMEs need to identify the influence of personal culture on the sharing of knowledge to bring more valuable benefits to their organization It is believed that large firm with large customer base tent to perceive a Knowledge management system more useful and have a better chance to apply Knowledge management system to build sustain competitive advantage Besides, SMEs are known of lacking of knowledge management practices even though they have a strong communication links and social networks in the organization It is said that knowledge sharing especially tacit knowledge, is highly and actively interacted in SMEs As more Appendix EFA results KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Approx Chi-Square Bartlett's Test of Sphericity 793 2935.889 df 105 Sig .000 Communalities Initial Extraction KSI1 561 699 KSI3 542 750 REW1 448 506 REW2 489 560 REW3 537 612 REW4 524 611 REW5 458 531 SNO1 498 648 SNO2 459 576 SNO3 440 531 IMG1 545 577 IMG2 571 619 IMG3 635 698 IMG4 566 587 IMG5 560 630 Extraction Method: Principal Axis Factoring Factor Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Total 10 11 12 3.727 3.137 2.454 1.309 570 538 476 461 436 387 363 352 % of Cumulati Variance ve % 24.848 24.848 20.914 45.762 16.363 62.124 8.728 70.853 3.799 74.652 3.589 78.241 3.175 81.417 3.070 84.487 2.905 87.392 2.580 89.972 2.419 92.391 2.348 94.738 Total 3.342 2.725 2.070 996 59 % of Variance 22.279 18.166 13.802 6.637 Rotation Sums of Squared Loadingsa Cumulati Total ve % 22.279 3.136 40.445 2.886 54.247 1.924 60.884 1.820 13 324 2.161 96.900 14 238 1.589 98.488 15 227 1.512 100.000 Extraction Method: Principal Axis Factoring a When factors are correlated, sums of squared loadings cannot be added to obtain a total variance Factor Matrixa Factor 698 -.435 671 -.407 652 -.431 613 -.448 599 -.464 418 601 474 595 482 579 388 575 416 548 IMG3 IMG5 IMG2 IMG4 IMG1 REW2 REW3 REW4 REW5 REW1 SNO1 698 381 SNO2 674 331 SNO3 666 KSI1 381 523 -.516 KSI3 316 471 -.621 Extraction Method: Principal Axis Factoring a Attempted to extract factors More than 25 iterations required (Convergence=.002) Extraction was terminated Pattern Matrixa Factor IMG3 834 IMG2 784 IMG5 780 IMG4 763 IMG1 761 REW3 781 REW4 768 REW2 746 REW5 740 REW1 708 SNO1 823 SNO2 766 SNO3 681 KSI3 885 KSI1 805 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization 60 a Rotation converged in iterations Structure Matrix Factor 832 786 782 763 758 782 778 747 725 711 IMG3 IMG2 IMG5 IMG4 IMG1 REW3 REW4 REW2 REW5 REW1 SNO1 802 SNO2 758 SNO3 719 342 KSI3 863 KSI1 323 832 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization Factor Correlation Matrix Factor 1.000 076 007 147 076 1.000 013 197 007 013 1.000 321 147 197 321 1.000 Extraction Method: Principal Axis Factoring Rotation Method: Promax with Kaiser Normalization 61 Appendix CFA results Regression Weights: (Group number - Default model) Estimate S.E C.R P IMG3 < - IMG 1.000 IMG2 < - IMG 915 051 17.865 *** IMG5 < - IMG 1.119 063 17.720 *** IMG4 < - IMG 935 053 17.671 *** IMG1 < - IMG 975 057 17.236 *** REW3 < - REW 1.000 REW4 < - REW 997 062 15.979 *** REW2 < - REW 879 057 15.340 *** REW5 < - REW 850 058 14.760 *** REW1 < - REW 795 055 14.515 *** SNO1 < - SNO 1.000 SNO2 < - SNO 965 073 13.252 *** SNO3 < - SNO 1.027 079 13.065 *** KSI3 < - KSI 1.000 KSI1 < - KSI 944 121 7.771 *** Label Standardized Regression Weights: (Group number - Default model) Estimate IMG3 < - IMG 831 IMG2 < - IMG 779 IMG5 < - IMG 774 IMG4 < - IMG 773 IMG1 < - IMG 758 REW3 < - REW 780 REW4 < - REW 778 REW2 < - REW 748 62 Estimate REW5 < - REW 722 REW1 < - REW 711 SNO1 < - SNO 783 SNO2 < - SNO 759 SNO3 < - SNO 732 KSI3 < - KSI 728 KSI1 < - KSI 978 Model Fit Summary CMIN Model Default model Saturated model Independence model RMR, GFI Model NPAR CMIN DF P CMIN/DF 36 198.851 84 000 2.367 120 000 15 2976.456 105 000 28.347 RMR GFI AGFI PGFI Default model 034 945 921 661 Saturated model 000 1.000 Independence model 227 450 371 394 NFI Delta1 RFI rho1 IFI Delta2 TLI rho2 CFI 933 916 960 950 960 Baseline Comparisons Model Default model Saturated model Independence model 1.000 000 Parsimony-Adjusted Measures Model PRATIO 1.000 000 000 PNFI PCFI Default model 800 747 768 Saturated model 000 000 000 1.000 000 63 000 Model Independence model NCP Model PRATIO PNFI PCFI 1.000 000 000 NCP LO 90 HI 90 114.851 77.449 159.963 000 000 000 Independence model 2871.456 2697.171 3053.066 FMIN Model FMIN F0 LO 90 HI 90 Default model 465 268 181 374 Saturated model 000 000 000 000 Independence model 6.954 6.709 6.302 7.133 RMSEA Model RMSEA LO 90 HI 90 PCLOSE Default model 057 046 067 140 Independence model 253 245 261 000 Default model Saturated model AIC Model AIC BCC BIC CAIC Default model 270.851 273.647 417.064 453.064 Saturated model 240.000 249.320 727.375 847.375 Independence model 3006.456 3007.621 3067.378 3082.378 ECVI Model ECVI LO 90 HI 90 MECVI Default model 633 545 738 639 Saturated model 561 561 561 583 7.024 6.617 7.449 7.027 Independence model HOELTER Model HOELTER 05 HOELTER 01 64 Model Default model Independence model HOELTER 05 HOELTER 01 230 252 19 21 65 Appendix SEM results Regression Weights: (iCU high - Default model) Estimate S.E C.R P KSI < - IMG 172 057 3.028 002 KSI < - REW 181 068 2.646 008 KSI < - SNO 422 086 4.898 *** IMG3 < - IMG 1.000 IMG2 < - IMG 915 051 17.865 *** IMG5 < - IMG 1.119 063 17.720 *** IMG4 < - IMG 935 053 17.671 *** IMG1 < - IMG 975 057 17.236 *** REW3 < - REW 1.000 REW4 < - REW 997 062 15.979 *** REW2 < - REW 879 057 15.340 *** REW5 < - REW 850 058 14.760 *** REW1 < - REW 795 055 14.515 *** SNO1 < - SNO 1.000 SNO2 < - SNO 965 073 13.252 *** SNO3 < - SNO 1.027 079 13.065 *** KSI3 < - KSI 1.000 KSI1 < - KSI 944 121 7.771 *** Label Standardized Regression Weights: (iCU high - Default model) Estimate KSI < - IMG 162 KSI < - REW 141 KSI < - SNO 329 IMG3 < - IMG 831 IMG2 < - IMG 779 66 Estimate IMG5 < - IMG 774 IMG4 < - IMG 773 IMG1 < - IMG 758 REW3 < - REW 780 REW4 < - REW 778 REW2 < - REW 748 REW5 < - REW 722 REW1 < - REW 711 SNO1 < - SNO 783 SNO2 < - SNO 759 SNO3 < - SNO 732 KSI3 < - KSI 728 KSI1 < - KSI 978 Model Fit Summary CMIN Model Default model Saturated model Independence model RMR, GFI Model NPAR CMIN DF P CMIN/DF 36 198.851 84 000 2.367 120 000 15 2976.456 105 000 28.347 RMR GFI AGFI PGFI Default model 034 945 921 661 Saturated model 000 1.000 Independence model 227 450 371 394 NFI Delta1 RFI rho1 IFI Delta2 TLI rho2 CFI 933 916 960 950 960 Baseline Comparisons Model Default model 67 Model Saturated model Independence model NFI Delta1 RFI rho1 IFI Delta2 1.000 000 Parsimony-Adjusted Measures Model PRATIO TLI rho2 1.000 000 1.000 000 000 PNFI PCFI Default model 800 747 768 Saturated model 000 000 000 1.000 000 000 Independence model NCP Model CFI 000 NCP LO 90 HI 90 114.851 77.449 159.963 000 000 000 Independence model 2871.456 2697.171 3053.066 FMIN Model FMIN F0 LO 90 HI 90 Default model 465 268 181 374 Saturated model 000 000 000 000 Independence model 6.954 6.709 6.302 7.133 RMSEA Model RMSEA LO 90 HI 90 PCLOSE Default model 057 046 067 140 Independence model 253 245 261 000 Default model Saturated model AIC Model AIC BCC BIC CAIC Default model 270.851 273.647 417.064 453.064 Saturated model 240.000 249.320 727.375 847.375 3006.456 3007.621 3067.378 3082.378 Independence model 68 ECVI Model ECVI LO 90 HI 90 MECVI Default model 633 545 738 639 Saturated model 561 561 561 583 7.024 6.617 7.449 7.027 Independence model 69 Appendix Multi-group analysis results Regression Weights: (high - Default model) Estimate S.E C.R P KSI < - IMG 512 065 7.906 *** KSI < - REW 219 096 2.289 022 KSI < - SNO 446 169 2.638 008 IMG3 < - IMG 1.000 IMG2 < - IMG 794 063 12.572 *** IMG5 < - IMG 853 065 13.165 *** IMG4 < - IMG 932 043 21.536 *** IMG1 < - IMG 752 062 12.058 *** REW3 < - REW 1.000 REW4 < - REW 1.060 093 11.413 *** REW2 < - REW 934 084 11.089 *** REW5 < - REW 828 085 9.703 *** 70 Label Estimate S.E C.R P REW1 < - REW 773 077 10.032 *** SNO1 < - SNO 1.000 SNO2 < - SNO 1.286 194 6.618 *** SNO3 < - SNO 1.149 171 6.712 *** KSI3 < - KSI 1.000 KSI1 < - KSI 602 080 7.487 *** Standardized Regression Weights: (high - Default model) Estimate KSI < - IMG 557 KSI < - REW 167 KSI < - SNO 208 IMG3 < - IMG 966 IMG2 < - IMG 708 IMG5 < - IMG 726 IMG4 < - IMG 897 IMG1 < - IMG 692 REW3 < - REW 812 REW4 < - REW 794 REW2 < - REW 775 REW5 < - REW 693 REW1 < - REW 712 SNO1 < - SNO 634 SNO2 < - SNO 820 SNO3 < - SNO 659 KSI3 < - KSI 895 KSI1 < - KSI 686 71 Label Model Fit Summary CMIN Model Default model Saturated model Independence model RMR, GFI Model NPAR CMIN DF P CMIN/DF 72 405.369 168 000 2.413 240 000 30 3039.937 210 000 14.476 RMR GFI AGFI PGFI Default model 048 893 848 625 Saturated model 000 1.000 Independence model 226 426 344 373 NFI Delta1 RFI rho1 IFI Delta2 TLI rho2 CFI 867 833 917 895 916 Baseline Comparisons Model Default model Saturated model Independence model 1.000 000 Parsimony-Adjusted Measures Model PRATIO 1.000 000 1.000 000 000 PNFI PCFI Default model 800 693 733 Saturated model 000 000 000 1.000 000 000 Independence model NCP Model NCP LO 90 HI 90 237.369 182.203 300.234 000 000 000 Independence model 2829.937 2655.324 3011.890 FMIN Model FMIN F0 Default model Saturated model LO 90 HI 90 72 000 Model FMIN F0 LO 90 HI 90 Default model 949 556 427 703 Saturated model 000 000 000 000 Independence model 7.119 6.627 6.219 7.054 RMSEA Model RMSEA LO 90 HI 90 PCLOSE Default model 058 050 065 041 Independence model 178 172 183 000 AIC Model AIC BCC BIC CAIC Default model 549.369 561.316 Saturated model 480.000 519.825 Independence model 3099.937 3104.915 ECVI Model ECVI LO 90 HI 90 MECVI Default model 1.287 1.157 1.434 1.315 Saturated model 1.124 1.124 1.124 1.217 Independence model 7.260 6.851 7.686 7.271 HOELTER Model Default model Independence model HOELTER 05 HOELTER 01 211 226 36 38 73 ... ECONOMICS HO CHI MINH CITY International School of Business Ta Tran Trung KNOWLEDGE SHARING INTENTION AMONG EMPLOYEES IN SMALL AND MEDIUM SIZED ENTERPRISES: A CASE IN HO CHI MINH CITY, ... has something far more valuable than data and information Many prior studies show that collaboration and knowledge sharing are important factors that organization should applied so as to attain... share knowledge among employees in SMEs Reward Researchers define organizational rewards as both financial and non-financial benefits that a worker achieves while working in an company (Malhotra,