Fostering the determinants of knowledge sharing in professional virtual communities
Introduction
The internet has led to a proliferation of virtual communities (VCs) all over the world (Fernback, 1999, Hiltz and Wellman, 1997). Exchanging information and knowledge inside VCs has dramatically changed our lives. To be successful in today’s competitive workplace, more and more individuals proactively take part in different kinds of VC, especially in professional VCs (PVCs) for knowledge workers that enable them to seek, collect, or even contribute knowledge to improve their capabilities, to absorb advanced insights, and to resolve problems at work. Many organizations have also recognized PVCs as valuable systems for knowledge management and have begun to support the development and growth of PVCs to meet their business needs and objectives (Gongla & Rizzuto, 2001). The executives of organizations should consider PVCs as a new innovation or knowledge pool since members share knowledge (Nambisan & Sawhney, 2007).
Over the past decade, a number of researchers have suggested that VCs (Preece, 2000, Rothaermel and Sugiyama, 2001) and knowledge sharing behaviors are influential to knowledge management success (Chowdhury, 2005, Kankanhalli et al., 2005, Wasko and Faraj, 2005, Williams, 2001). This importance has led to the investigation of knowledge sharing in VCs by some scholars in an effort to determine what factors are significant to knowledge sharing and knowledge management success (Chiu et al., 2006, Hsu et al., 2007, Koh and Kim, 2004, Wasko and Faraj, 2005). Most previous studies have focused on either contextual factors and knowledge sharing (Bock and Kim, 2002, Bock et al., 2005, Kankanhalli et al., 2005, Purvis et al., 2001, Wasko and Faraj, 2005) or on personal factors and knowledge sharing (Bock and Kim, 2002, Chiu et al., 2006, Hsu et al., 2007, Kankanhalli et al., 2005, Wasko and Faraj, 2005). In this study, we propose an integrated framework to develop a more comprehensive perspective of the relationships between contextual factors, personal perceptions of knowledge sharing, knowledge sharing behavior, and community loyalty, and bring it up-to-date with empirical data from three PVCs.
We investigate how the contextual factors (norm of reciprocity and trust) and personal perceptions of knowledge sharing (knowledge sharing self-efficacy, perceived relative advantage, and perceived compatibility) can influence PVC members’ willingness to share knowledge with other members and their loyalty to their communities. To get a better understanding of knowledge sharing in PVCs, we examine the relationships between the following four pairs of concepts:
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Contextual factors and knowledge sharing behavior.
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Contextual factors and personal perceptions of knowledge sharing.
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Personal perceptions of knowledge sharing and knowledge sharing behavior.
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Knowledge sharing behavior and community loyalty.
Knowledge-based VCs or organizations need to increase the quality and quantity of new knowledge more rapidly to satisfy the expanding requirements of members. This research has been pursued to assist executives of VCs or organizations to solve some of the difficulties that occur in knowledge management (KM). A universally accepted definition of KM does not yet exist. Many definitions of KM have been proposed in the literature (Nonaka, 1991, Petrash, 1996, Wiig, 1997). Our comprehensive definition of KM is based on Corso, Martini, Paolucci, and Pellegrini (2003). KM in this context is the combination of management systems, organizational mechanisms, information, and communication technologies through which an organization fosters and focuses individual and group behaviors in terms of assimilation and generation, transfer and sharing, capitalization and reuse of knowledge, in tacit or explicit form, that is useful to the organization.
Even with the existence of information systems, knowledge sharing is a difficult challenge for organizations (Argote et al., 2000, Bakker et al., 2006, Szulanski, 1996). Researchers have noted that knowledge management often fails in fostering knowledge sharing efforts due to its neglect of the willingness of knowledge sharing and the knowledge required for successful knowledge sharing; the omission of important enhancing activities from their knowledge sharing mechanisms; and their often ineffective and inefficient performance of knowledge sharing tasks (Kankanhalli et al., 2005, Pfeffer and Sutton, 1999). In addition to these difficulties, the investigation of knowledge sharing relationships with “personal perceptions of knowledge sharing” such as knowledge sharing self-efficacy, perceived relative advantage, and perceived compatibility have not been closely scrutinized to ascertain members’ involvement with and contribution to knowledge sharing in VCs. The influence of contextual factors and personal perceptions of knowledge sharing on knowledge sharing behavior and community loyalty is a critical area on which very few studies have been performed. We attempt to illuminate some of KM areas.
Section snippets
Knowledge sharing and influencing factors
Knowledge sharing is the behavior of an individual dispersing his or her obtained knowledge and information to other colleagues within an organization (Ryu, Ho, & Han, 2003). Knowledge sharing involves a process of communication whereby two or more parties are involved in the transfer of knowledge. Hence, knowledge sharing is defined as a process of communication between two or more participants involving the provision and acquisition of knowledge (Usoro, Sharratt, Tsui, & Shekhar, 2007).
Research model
Based on SCT, we may reasonably assume that the contexts of PVCs shaped by the norm of reciprocity and trust should influence personal perceptions and a member’s behavior. Fig. 1 shows the research model for this study, which examines the effects that the norm of reciprocity has on knowledge sharing behavior through trust and three personal perceptions. We also examine the relationship knowledge sharing behavior and community loyalty. Each construct involved in the research model and hypotheses
Research methodology
We tested our hypotheses using data surveyed from three maybe famous in Taiwan PVCs. We describe the development of the survey instrument, the data collection procedures, and the validation of the measures in the following subsections.
Data analysis and results
The research model shown in Fig. 1 was analyzed primarily using SEM, supported by LISREL 8.7 software. Numerous researchers have proposed a two-stage model-building process (Anderson and Gerbing, 1988, Hair et al., 1998, Joreskog and Sorbom, 2001, Maruyama, 1998). The first step involves the analysis of the measurement model, while the second step tests the structural relationships among latent constructs. The aim of the two-step approach is to assess the reliability and validity of the
Summary of results
This study developed an integrated model designed to investigate and explain the relationships between contextual factors, personal perceptions of knowledge sharing, knowledge sharing behavior, and community loyalty. Our results provide support for the theoretical model and most of our hypotheses, and add to the existing research on the validation of knowledge sharing behavior on PVCs. This study produces four important findings that deserve considerable attention from executives of
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