Key Success Factors that Influence Knowledge ... - Science Direct

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Procedia Economics and Finance 4 (2012) 23 – 32

International Conference on Small and Medium Enterprises Development with a Theme (ICSMED 2012)

Key Success Factors that Influence Knowledge Transfer Effectiveness: A Case Study of Garment Sentra at Kabupaten Sragen Aries Susantya*, Naniek Utami Handayanib, Mahardian Yugi Henrawanc a,b,c

Diponegoro University, Campus Tembalang 50275, Semarang, Indonesia

Abstract Through an effectiveness of knowledge transfer, organizations can improve their performance and gain competitive advantage. It is believed there are several factors influencing the knowledge transfer effectiveness, including optimum budget allocation, culture, leadership, etc and also, there are various frameworks, models, and analytical tools that can be used to study the causal relationships between some key success factor and effectiveness of knowledge transfer. Based on existing models, this study aims to identify and discuss the key success factors that determine knowledge transfer effectiveness in a Garment Sentra in Kabupaten Sragen, which in turn influence positively the total performance of the enterprise. The proposed research model is tested via a questionnaire sent to 75 respondents which is part of small and medium enterprise in the Garment Sentra in Kabupaten Sragen; of those only 74 answered the questionnaire correctly. After questionnaire collected, the Partial Least Squares (PLS) approach was used to analyze the research model of this study. The results of study showed that knowledge transfer effectiveness in a Garment Sentra in Sragen is influenced by two factors, i.e. organizational culture and organizational structure. The result of the study also proved that knowledge transfer effectiveness has impact on performance of enterprise through an increase in market share and profit. © 2012 The Authors. Authors. Published Published by by Elsevier Elsevier Ltd. Ltd.Open access under CC BY-NC-ND license. Selection and peer-review under responsibility of Parahyangan Catholic University. and/or peer-review under responsibility of Parahyangan Catholic University. Keywords: Knowledge Transfer Effectiveness; Factors; Perfomance; Garment Sentra

* Corresponding author. Tel.:+062-0811-220-5563; fax: +062-024-7460052. E-mail address: [email protected]

2212-5671 © 2012 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license. Selection and peer-review under responsibility of Parahyangan Catholic University. doi:10.1016/S2212-5671(12)00317-6

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Aries Susanty et al. / Procedia Economics and Finance 4 (2012) 23 – 32

1. 1. Introduction Knowledge, if properly harnessed and leveraged can propel organizations to become more adaptive, innovative, intelligent and sustainable (Wong, Aspinwall, 2004). Businesses that can efficiently capture the knowledge embedded in their organizations and deploy it into their operations, productions and services will have an edge over their competitors (Wong, Aspinwall, 2005). Besides large organizations, the success of a small business or an SME can be linked to how well they manage their knowledge. SMEs, in particular, must pay close attention to knowledge management for several reasons. SMEs compete on their know-how and hence have to use knowledge to their advantage, even more so than traditional resources. SMEs normally do not have deep pockets to spend on resources such as land, labor, and capital. They must do more with less. Knowledge housed in the SME, must be leveraged so that goals can be achieved in an effective and efficient manner. While an SME might be constrained by not enough capital or labor, their knowledge is bountiful and, in many cases, an unlimited resource. The only way an SME can limit this resource is by not using it effectively. Having knowledge is one thing, and using it effectively towards organizational ends are quite another. It will be useful for an SME owner to house knowledge in his/her mind, and not use it for business decision-making (Desouza, Awazu, 2006). Besides, using the knowledge directly, the owner of SMEs must also transfer knowledge to his/her employee. Knowledge transfer requires the willingness of a group or an individual to work with each others. Knowledge transfer is about connection not collection, and that connection ultimately depends on the choices made by individuals. It is worth noting tha between the transfer agent and transfer recipient. It is believed there are several factors influencing the knowledge transfer effectiveness, including optimum budget allocation, culture, leadership, etc and also, there are various frameworks, models, and analytical tools that can be used to study the causal relationships between some key success factor and effectiveness of knowledge transfer. Based on existing models, this study aims to identify and discuss the key success factors that determine knowledge transfer effectiveness in a Garment Sentra in Kabupaten Sragen, which in turn influence positively the total performance of the enterprise. This research chose the Garment Sentra at Kabupaten Sragen as an object of research because, although new, Garment Sentra at Kabupaten Sragen has big potential to be developed. This is evidenced by the values LQ = 1.791, which means that growth of garment sector at Kabupaten Sragen is above the average and greater than other sectors, and it is expected that the Garment Sentra at Kabupaten Sragen can help governments to improve the economy in Sragen. 2. Literature review 2.1. Knowledge Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it is often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms (Davenport, Prusak, 1998). Knowledge can be divided into two categories, namely explicit and tacit knowledge. Explicit knowledge can be formalized and represented, and thus articulated in formal languages. Tacit knowledge can be described as an experience that is embedded in an individual such as perspective and inferential knowledge. It includes insights, hunches, intuitions, and skills that are highly personal and difficult to formalize, and as a result are hard to communicate or share with others (Nunes, Annasigh, Eaglestone, 2005).


2.2. Knowledge transfer and conceptual model of knowledge transfer In whatever dimension knowledge exists, knowledge must be transferred or moving from one individual to another person. Knowledge transfer within an organization enables employees to work efficiently together. According to Dixon in the 2000, there are five main types of knowledge transfer/sharing. These include serial transfer, near transfer, far transfer, strategic transfer, and expert transfer. Each of these differs according to the purpose, method, and ways in which they are implemented (Pham, 2008). This study, using a research model from Gholipour, Jandaghi, and Hosseinzadeh (2010) as a basic conceptual model to describe some variations which have an impact on knowledge transfer effectiveness. Although that model not directly describe the relationship between any variable and knowledge transfer effectiveness but based on some literature, we found that all variable used by Gholipour, Jandaghi, and Hosseinzadeh (2010) in their research, have relationship with knowledge transfer effectiveness. 2.2.1. Culture It is not easy to transfer knowledge from one individual to others because there are some factors that can be a barrier to transfer of knowledge, i.e. the size and the nature of the gap of knowledge between source and recipient (Leornard, 2007). Organizational culture and structure are other factors influencing the knowledge transfer process. A knowledge oriented organizational culture is clearly one of the most influential factors of successful knowledge transfer (Davenport, De Long, and Beers, 1998), because a culture that promotes change and innovative behavior encourages the active exchange of ideas and increased knowledge transfers. According to Schein (1995), organizational culture refers to the values and view that are rooted in an organization, and how they influence attitudes and behavior there. Many of these attitudes are taken for granted, and people are hardly aware of them. But they can also represent more conscious views and values. Manifestations of these values and views can be the design of the workplace, personnel policy, advertising campaigns, organizational structure, product design, logo, jargon and so on. There are three important dimensions of organizational culture that have an impact on knowledge transfer, i.e. trust, learning culture, and collaboration. Trust is a foundation of organizational culture and the most important explicitly stated value essential for knowledge management. The importance of trust has been supported in a study by Connelly and Kelloway in the year 2000. In this study, respondents noted that they would only be willing to share knowledge in contexts where they trusted the recipient of the knowledge (Connelly, Kelloway, 2000). Besides trust, a learning culture opens up formal and informal channels of communication (Bhatt, 2000). Strong learning culture of firms is linked to creation, acquisition, and transfer of knowledge (Murray, Donegan, 2003). The last dimension of organizational culture that has impact on the effectiveness of knowledge transfer is collaboration culture. Lopez, Peon, and Ordas (2004) empirically identify collaborative culture as a means to leverage knowledge through organizational learning. A culture of collaboration helps in knowledge creation by increasing knowledge exchange. 2.2.2. Organizational structure Firms require some degree of structural organization (Buckley and Carter, 2002). Structures can formally indicate and facilitate connections, and communications between individuals both within and across these boundaries, although connections may also arise spontaneously and informally. Structures may also place limits on communications or create intentional or unintentional obstacles (Buckley and Carter, 2002). The impact of organizational structure dimensions (centralization and formalization) on the knowledge transfer process is revealed in the study of Tsai, 2002; Goh, 2002; Lee and Choi, 2003; Lucas, 2006; Chen and Huang, 2007; and Al-Alawi et al., 2007. Based on all that research, we can conclude that centralization gives negatively influence

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the flow of knowledge among individuals. High centralization prevents interaction and frequency of communication among individuals in different units. It also hinders the creativity and the need for sharing ideas between individuals since they are not required to do so by higher authorities. The more control the managers exercised on their subordinates, the less the subordinates were willing to share knowledge with others. Therefore, participation and active involvement in the decision making process are essential for successful knowledge transfer (Pham, 2008). 2.2.3. People Besides culture, successful knowledge management is mainly linked to people because learning and sharing knowledge is social activities that take place among people. To be effective, knowledge transfer needs a person who posses T-shaped skills because, according to Leonard Barton in the1995 and Madhaven and Grover in the year 1998, a person who posses T-shaped skills are able to integrate diverse knowledge assets, to combine theoretical and practical knowledge, and to see how their branch of knowledge interacts with other branches (Gholipour, Jandaghi, Hosseinzadeh, 2010). 2.2.4. Information technology Information technology has created new means of knowledge transfer as knowledge can now be transferred faster and between a larger number of organizational members. According to Phang and Foong (2010), effectiveness of information technology in supporting knowledge transfer might to a great deal depend on the type of knowledge that is to be transferred. Information technology is generally used for managing and codifying knowledge as well as creating networks. Most commonly, information technology is used to facilitate the capture, storage, retrieval and distribution of explicit knowledge, in order to make explicit knowledge even more accessible and more transferable. Thus, instead of codifying tacit knowledge, companies should utilize information technology to bring people together in sharing tacit knowledge without having to make it explicit. This can for example be achieved through various groupware applications and intranets that have features such as transferred databases, collaborative spaces, advanced communication features, electronic yellow pages, automated knowledge maps and expertise databases, through helping to locate and connect people who either seek or possess relevant or required knowledge. 2.2.5. Effectiveness of knowledge transfer Effectiveness of knowledge transfer in organizations can be assessed through measuring changes in the knowledge of the recipient unit (Argote, Ingram, 2000). Brachos, Konstantinos, Soderquist, and Prastacos (2007) use perceived knowledge usefulness as a proxy of knowledge transfer in organizations. It is not new in knowledge theory. Besides Brachos, Konstantinos, Soderquist, and Prastacos (2007), Levin and Cross (2004) also develop the construct receipt of useful knowledge as an outcome variable to denote the concept of knowledge transfer. 2.2.6. Organizational performance According to Toften and Olsen in the year 2003, an effective knowledge management implementation will add more value to the overall performance of the organization. Moreover, Gold et al. in the year 2001 states that the successful application of knowledge management enables a firm to become innovative, harmonize its efforts better, commercialize new products quickly, foresee surprises, and become more responsive to market change (Theriou, Maditinos, Theriou, 2010).

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3. Methodology 3.1. Conceptual model and hypothesis Based on the research model from Gholipour, Jandaghi, and Hosseinzadeh (2010) and some literature related to effective of knowledge transfer and knowledge management implementation, the conceptual model which is used in this research can be seen as in Fig 1. Collaboration Trust

Organizational Culture

Learning H1 Centralization

Organizational Structure

H2

Formalization H3 T-Shaped Skills

Market Share

H5 Effectiveness of Knowledge Transfer

Organizational Performance

People

Profitability H4

IT-Support

Information Technology

Changes in the knowledge

Perceived knowledge usefulness

Fig. 1. Conceptual model of knowledge transfer effectiveness and organizational performance

Based on that model, a number of hypotheses used in this research can be described as follows. Hypothesis 1 Hypothesis 2 Hypothesis 3 Hypothesis 4 Hypothesis 5

Organizational culture which consists of trust, learning and collaboration culture will have a positive impact on the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen Increasingly centralized organizational structure will have a negative impact on effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen People who posses T-shaped skills will have a positive impact on the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen Information technology will have a positive impact on the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen Effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen which is measured by changes in the knowledge and perceived knowledge usefulness will have a positive impact on organizational performance

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3.2. Sample of research and data collection The proposed research model is tested via a questionnaire sent to 75 respondents which is part of Small and Medium Enterprises (SMEs) in the Garment Sentra in Kabupaten Sragen; of those only 74 answered the questionnaire correctly. Besides questionnaire, the proposed research also uses structured interviews with the owner of SMEs or senior employee to obtain a more complete picture of the organizational context variables. A multiple-item method was used to construct the questionnaires. Each item was based on a 5 point scale, from "strongly disagree" to "strongly agree". 4. Result In this study, data were analyzed by using partial least squares (PLS). PLS is a structural equation model (SEM) based components or variants (variance). According PLS is an alternative approach that shifts from SEM-based approach covariance be based variant. General covariance-based SEM to test the causal relationship/ theory, while PLS is a more predictive model. PLS is a powerful Ghozali (2008) analytical method because it is not based on many assumptions. For example, data must be normally distributed; the sample is not necessarily in large quantities. Besides using to confirm the theory, PLS can also used to explain the relationship between latent variables. PLS can simultaneously analyze the constructs formed with reflective indicators and formative. This cannot be done by the covariance-based SEM because it will be unidentified model (Ghozali, 2008). In the analysis by PLS, there are three things to do. First, describes the path diagram of the conceptual model of research. Second, assessing the outer model or measurement model, and the third, assessing the inner model or structural model. Assessment of outer model is a test of reliability and validity of research variables. There are three criteria to assess the outer model, i.e.: the convergent validity, discriminant validity, and composite reliability. Assessment inner model or structural model made to look at the relationship between constructs, significance values, and R-square of the research model (Ghozali, 2008) 4.1. Path diagram of the conceptual model Path diagram for a model of effective knowledge transfer and organizational performance in a SMEs Garment Sentra at Kabupaten Sragen can be seen in Fig 2. 4.2. Assessing the outer model (test of reliability and validity) There are three criteria to assess the outer model, i.e.: the convergent validity, discriminant validity, and composite reliability. Convergent validity Convergent validity captures some of the aspects of the goodness of fit of the measurement model, i.e., How well the measurement items relate to the constructs. Convergent validity is shown when each measurement item correlates strongly with its assumed theoretical construct (Gefen, Straub, 2005). In convergent validity, we say that an item has good relation with the construct if a loading factor of an item is 0,500 or more (Ghozali, 2008). Results of data processing against SMEs in Garment Sentra in Kabupaten Sragen indicates that there are 7 (seven) items which had a loading factor less than 0.500. Two of those items were part of organizational culture construct, four of those items were part of organizational structure construct, and one of those items was part of information technology construct. After removing 7 items from three constructs, all items had a loading factor greater than 0.500.

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x12

x13

x14

x15

x16

x2

x3

x4

x5

x6

x11

x7

x10

x8

x1

x17 x18 x19

x9

Organizational Culture

Organizational Structure

x25

Organizational Performance

People

x26 x27

Effec. Knowledge Transfer

x20 x21 x22 x23 x24

x35 x36 x37 x38 x39

x28 x29 x30

x31

x32

x33

x34

Information Technology

Fig. 2. Path diagram for a model of effective knowledge transfer and organizational effectiveness in SMEs Garment Sentra at Kabupaten Sragen

Discriminant validity Discriminant validity also captures some of the aspects of the goodness of fit of the measurement model, i.e., how well the measurement items relate to the constructs. Discriminant validity is shown when each measurement item correlates weakly with all other constructs except for the one to which it is theoretically associated (Gefen, Straub, 2005). In this study, we tested the discriminant validity based on Fornell and Larcker criterion. This criterion points out that the discriminant validity is established if the square root of the average variance extracted from each construct is greater than the correlation between the construct and the other constructs (Liu, Hung, 2010). The final result of the discriminant validity test showed that each item from each construct can clearly be distinguished from other constructs. Composite Reliability used in measuring the internal consistency reliability, Henseler et al. in the year 2009 argued that composite account the different indicator loadings, which is consistent with a PLS algorithm (Rosnita, Roshayati, 2012). In the PLS analysis, it is required that the composite reliabilities of each construct had value above 0.600 (Ghozali, 2005). Construct organizational culture had composite reliability equal to 0.919 after removed two items belong to that construct. Construct organizational culture had composite reliability equal to 0.850 after removed four items belong to that construct. Construct information technology had composite reliability equal to 0.998 after removed one item belong to that construct. Construct effectiveness of knowledge transfer had composite reliability equal to 0.792, construct people (skill of the worker) had

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composite reliability equal to 0.852, and construct organizational performance had composite reliability equal to 0.840. We can conclude that all constructs have composite reliability more than 0.600. Overall, the results of the convergent validity, discriminant validity and composite reliability suggest that the measurement model meets the standard of having good explanatory power. 4.3. Assessing the inner model The inner model is assessed by examining the path coefficients, t-value, and R-square. T-value used as criterion to accept or reject the hypothesis which containing the statement about the correlation between second order construct. This study use alpha equal to 0.05, so the correlation between second order construct will be accepted (or the hypothesis will be accepted), if t-value is above 1.667. Path coefficient, t-value, and R-square between second orders construct from the model of effective knowledge transfer and organizational performance of SMEs Garment Sentra at Kabupaten Sragen can be seen in Table 1. Table 1. Path coefficient, t-value, and R-square between second orders construct from the model of effective knowledge transfer and organizational performance of SMEs Garment Sentra at Kabupaten Sragen Hyph.

Relationship between second order construct

Path coefficient

T-stat

R-square

1

Organizational culture (+) effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen

0.201

2.179

0.550

2

Centralized organizational structure (-) effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen

-0.546

4.101

3

People who posses T-shaped skills (+) effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen

0.024

0.226

4

Information technology (+) effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen

0.039

0.540

6

Effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen (+) organizational performance

0.700

17.976

0.491

Based on Table 1, there were two factors which have an impact on the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen, namely: organizational culture and centralized organizational structure. Organizational culture has a significant positive impact on the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen (coefficient value = 0.201, t-value = 2.179); but, increasingly centralized organizational structure have a negative impact on effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen (coefficient value = -0.546, t-value = 4.101). This research also found that the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen which is measured by changes in the knowledge and perceived knowledge usefulness have a significant positive impact on organizational performance through increased market share and profit (coefficient value = 0.700, t-value = 17.976). It can be concluded that, for SMEs Garment Sentra at Kabupaten Sragen, the results of this research support the hypothesis 1, hypothesis 2, and hypothesis 5. This research is failing to prove the contribution of people who posses T-skills and information technology on effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen. Table 1 also presents the R-square values. It demonstrated that organizational culture, organizational structure, people who posses T-shaped, and information technology have 55% effect on the effectiveness of


knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen; and the degree of effectiveness of knowledge transfer has 49.1% effect on organizational performance. There are some other factors outside of organizational culture, organizational structure, people who posses T-shaped, or information technology that have an effect on the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten. There are also some other factors outside of effective knowledge transfer that have an effect on organizational performance. 5. Result A number of conclusions from this study can be described as follows: 1. There were two factors that have significant impact on the effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen, i.e. organizational culture and centralized organizational structure. Organizational culture have a positive significant impact on effectiveness of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen, but centralized organizational structure have a negative significant impact on of knowledge transfer by SMEs Garment Sentra at Kabupaten Sragen. 2. Associated with the positive impact of organizational culture on effectiveness of knowledge transfer, the owner of the SMEs Garment Sentra at Kabupaten Sragen must give more intention to build trust, learning, and collaboration culture in their enterprise. The result of observation found the majority of SMEs Garment at Kabupaten Sragen already have three elements of those cultures. The workers in the SMEs Garment at Kabupaten Sragen have become accustomed to sharing their knowledge with the others and conducting informal open dialogue between the workers which aims to work together to solve a particular problem and take some decision. The workers also have a high desire for joining some training that conducted by government or educational institutional although, sometimes, the material of the training was difficult to implement due to limited capital and the level of their knowledge. 3. Associated with the negative impact of organizational structure on effectiveness of knowledge transfer, the owner of SMEs must begin to think how to delegate some part of his or her authority to the other workers and how to give freedom to the workers to realize their positive ideas. It was the important subject because the majority of SMEs tend to centralize their key strategic operations on the hand of the owner of SMEs. 4. There are some recommendations that can be given to increase the contribution of factor people and information technology on effectiveness of knowledge transfer. In the SMEs Garment Sentra at Kabupaten Sragen, people are not a main factor that has an impact on the effectiveness of knowledge transfer because most of the workers have similar skill, i.e. sewing. The absence of other knowledge possessed by workers of the SMEs Garment Sentra, except sewing, is showing a condition that no workers in SMEs Garment Sentra which have T-shaped posses. Based on that condition, owner of SMEs must encourage their workers to gain other skills and knowledge outside sewing, i.e. knowledge about design and marketing. Besides people, information technology is another factor that has no impact on the effectiveness of knowledge transfer because only a small proportion of SMEs Garment Sentra at Kabupaten Sragen have a computer and internet networks. Furthermore, lack of knowledge about how to use the internet to improve its business performance have led to the utilization of computer and internet networks are not maximal. Based on that condition, government should facilitate SMEs to have a computer and internet networks and provide support to SMEs to learn and use an internet that relevant to their business.

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Acknowledgements Many thanks to the Study Program Industrial Engineering that give me an opportunity and accommodation assistance to attend the International Conference on Small and Medium Enterprise Development: Innovation and Sustainability in SME Development on Bali, 14-16th June 2012. References Argote, L., Ingram, P., 2000. Knowledge Transfer: A Basis for Competitive Advantage in Firms, Journal of Organizational Behavior and Human Decision Processes 82, p. 150 169. Bhatt, G.D., 2000. Organizing Knowledge in The Knowledge Development Cycle, Journal of Knowledge Management 4, p. 15- 26. Brachos, D., Konstantinos, K., Soderquist, K. E., Prastacos, G., 2007. Knowledge Effectiveness, Social Context and Innovation, Journal of Knowledge Management 11, p. 31-44. Buckley, P., Carter, M. J., 2002. Process and Structure in Knowledge Management Practices of British and US Multinational Enterprises, Journal of International Marketing 8, p. 29- 48. Connelly, C., Kelloway, K., 2000. Predictors of Knowledge Sharing in Organizations, Thesis, University, Kingston. Davenport T.H., De Long D.W., Beers M.C., 1998. Successful Knowledge Management Projects, Sloan Management Review 39, p. 43 57. Davenport, T. H., Prusak, L., 1998. Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press: Boston, p. 5. Desouza C.K., Awazu,Y., 2006. Knowledge Management at SMEs: Five Peculiarities, Journal of Knowledge Management 10, p. 32-43. Gefen, D., Straub, D., 2005. A Practical Guide to Factorial Validity using PLS-Graph: Tutorial and Annotated Example, Journal of Communications of the AIS 16, p. 91-109. Gholipour R. Jandaghi Gh., Hosseinzadeh A. A., 2010. Explanation of Knowledge Management Enabler as a Latent Variable: A Case Study of SMEs in Iran, African Journal of Business Management 4, p. 1863-1872. Ghozali, I., 2005. Analysis Multivariat dengan Program SPSS. Badan Penerbit UNDIP, Semarang, Indonesia. Ghozali, I., 2008. Structural Equation Modeling: Metode Alternatif dengan Partial Least Square (PLS). Badan Penerbit UNDIP, Semarang, Indonesia. Knowledge Creation and Management: New Challenges For Ichijo, K., Nonaka, I. (eds.), Oxford University Press, p. 57-68. Levin, D., Cross, R., 2004. The Strength of Weak Ties you Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer, Management Science 50, p. 1477-1490. Liu, H.Y., Hung, W.T., 2010. of the Virtual Environment, Journal of Business Management 4, p. 2915-2920. Lopez, S.P., Peon, J.M.M., Ordas, C.J.V., 2004. Managing Knowledge: The Link Between Culture and Organizational Learning, Journal of Knowledge Management 8, p. 93-104. Murray, P., Donegan, K., 2003. Empirical Linkages Between Firm Competencies and Organizational Learning, Journal of The Learning Organization 10, p. 51-62. Nunes, M.B., Annansingh, F., Eaglestone, B., 2006. Knowledge Management Issues in Knowledge-Intensive SMEs, Journal of Documentation 62, p. 101-19. Pham, T. B.N., 2005. Intraof Economics and Social Sciences, University of Fribourg, Switzerland, p. 20, 59 61. Phang, M, Foong, S. Y., 2010. Information Communication Technologies (ICTs) and Knowledge Sharing: The Case of Professional Accountants in Malaysia, World Journal of Science, technology and Sustainable Development 7, p. 35-49. Rosniati, I., Roshayati, 2 application in journal of operation management: a r Supply Chain Management. Bandung, Indonesia, paper#188. Schein, 1985. Organizational Culture and Leadership. Jossey-Bass, San Francisco, p. 87-89 Ther management enabler factors and firm performance: an empirical research of the Greek medium and large firms", International Conference on Applied Business and Economics. Technological Educational Institute of Kavala, Kavala, Greece, paper#448. Wong, K. Y., Aspinwall, E. 2004. Characterizing Knowledge Management in the Small Business Environment, Journal of Knowledge Management 8, p. 44-61. Wong, K. Y., Aspinwall, E. 2005. An Empirical Study of the Important Factors for Knowledge Management Adoption in the SME Sector 9, p. 64-82.