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Knowledge sharing in virtual communities – a review of the empirical research Miia Kosonen School of Business Lappeenranta University of Technology P.O. Box 20, 53851 Lappeenranta, Finland E-mail: [email protected] Abstract: This study reviews the recent empirical studies on knowledge sharing in Virtual Communities (VCs). The paper begins with an analysis of the VC conceptualisation and the focal phenomenon of knowledge sharing. Secondly, the factors that seem to facilitate knowledge-sharing activities in VCs are identified and categorised as individual motivations, personal characteristics, technical attributes and community-level social capital. Overall, the results demonstrate a strong emphasis on why individuals engage in such activities, but less attention is given to what is being shared and how the processes of sharing are manifested in practice. The paper concludes with some suggestions for further research. Keywords: virtual community; knowledge sharing; contribution; participation; motivation; social capital. Reference to this paper should be made as follows: Kosonen, M. (2009) ‘Knowledge sharing in virtual communities – a review of the empirical research’, Int. J. Web Based Communities, Vol. 5, No. 2, pp.144–163. Biographical notes: Miia Kosonen (DrSc, Econ) is a Researcher at the Lappeenranta University of Technology, Finland. Her research interests include virtual communities, online communication, trust, social capital and open innovation. She has published in the International Journal of Knowledge and Learning and the International Journal of Web Based Communities.

1

Introduction

The internet has given rise to Virtual Communities (VCs) dedicated to a common interest, allowing members to share knowledge about a specific topic (Chiu et al., 2006; Ridings et al., 2002; Wasko and Faraj, 2000; Preece, 2000). As informal entities of social interaction, VCs imply change in how collaboration is organised within and across organisations. However, their value fundamentally depends on the levels of member involvement and engagement in knowledge-sharing activities (Hsu et al., 2007). Even if the relevance of VCs to knowledge management has been explicated by many authors (cf. Ardichvili et al., 2003; 2006; Wasko and Faraj, 2000; Powers, 2004), the amount of academic work about knowledge sharing in VCs is scarce. This may be due to the newness of VCs as objects of study: the pioneering work originates from the Copyright © 2009 Inderscience Enterprises Ltd.

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mid-1990s, while studies that take a more focused knowledge-sharing perspective have been published in the 2000s. The studies derive from different disciplines, such as computing and Information Systems (IS), management, e-commerce and marketing. The related theoretical bases are also disparate in nature. In order to provide a more coherent understanding and foundations for further research, this paper reviews the current empirical studies on knowledge sharing in VCs, tracks their conceptual strengths and shortcomings and identifies the factors that seem to facilitate knowledge sharing activities. Hence, by focusing on this specific form of virtual organising, it extends the work of Rafaeli and Raban (2005) in their review of the research on online information sharing in organisations. The paper continues as follows. First, there is a short review of the relevant literature, after which the methodology used in the study is clarified. Next, the various definitions of VCs are presented based on a content analysis of the selected studies. The factors that seem to facilitate knowledge sharing in VCs are then identified and the paper concludes with a discussion and suggestions for further research.

2

Key concepts: knowledge sharing and virtual communities

In general, knowledge sharing presumes a two-way relation between at least two parties (i.e., subjects capable of ‘knowing’, individuals or collectives), of which one communicates knowledge either consciously or not and the other should be able to perceive knowledge expressions and make sense of them (Hendriks, 1999). Kotlarsky and Oshri (2005) identified two basic approaches towards sharing, namely, transactive memory (implying knowledge about who knows what) and collective knowledge (invisible structures built on language and shared meanings and experiences). A VC refers specifically to an online social network in which people with common interests and needs interact repeatedly within certain boundaries (Chiu et al., 2006; Porter, 2004; Preece, 2000; Slevin, 2000). VCs take a variety of forms, ranging from interest-based open groups (cf. de Valck et al., 2007; Blanchard and Markus, 2004) to organisation-hosted groups of practitioners and professionals (cf. Ardichvili et al., 2006; Usoro et al., 2007). Their organisational benefits are various: they may facilitate personal learning (Wagner and Bolloju, 2005), enhance storytelling and the exchange of ideas (Röll, 2004), foster social relationships (Blanchard and Markus, 2004), enable ongoing dialogue with customers (Füller et al., 2006; Nambisan, 2002) and provide a context for developing products and services through collaboration with innovative users (Jeppesen and Frederiksen, 2006). Accordingly, knowledge sharing in VCs has attracted growing interest in the literature (Hsu et al., 2007); without such an activity, they are of limited value (Chiu et al., 2006). In order to understand knowledge-sharing activities in VCs, it is necessary to position knowledge sharing in line with related concepts such as contribution (Wasko and Faraj, 2005; Wang and Fesenmaier, 2003; Jeppesen and Frederiksen, 2006) and participation (Ardichvili et al., 2003; Yoo et al., 2002). Although all these deal with VC member activities, the level of involvement varies due to differing levels of individual interest and different personal goals and needs (Golder and Donath, 2004). For instance, participation may take the form of lurking (or quiet membership), which means that people simply read others’ posts on the weblogs or discussion forums but do not post themselves

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(Nonnecke and Preece, 2000; Hammond, 2000). At the other end of the continuum is communicative membership (Nonnecke and Preece, 2000; Hammond, 2000), which involves frequent interaction by members who Golder and Donath (2004) labelled ‘celebrities’ – people who spend a great deal of time and energy contributing to the community. Participation could thus be viewed as either active (giving information, i.e., contributing by producing an outcome valued by others) or passive (receiving information) (Ridings et al., 2002; Hsu et al., 2007). Knowledge sharing, in turn, implies active involvement from both givers and receivers – it promotes interaction and learning among the members who are capable of making sense of the provided information (Hendriks, 1999).

3

Method

The articles included in the review were screened from the international journal databases ABI and EBSCOHost. The terms used in the search were ‘knowledge sharing’, ‘information sharing’, ‘contribution’ and ‘participation’ combined with ‘virtual/online/ electronic community’. Conference papers and working papers were not included. The specific purpose of the review was to investigate the research papers focusing on the empirical realm of VCs. Thus, analytical and tentative work was excluded. Secondly, only the studies published in the 2000s were eligible. This fixed period of time was chosen because earlier studies on VCs and knowledge sharing were mainly tentative in nature and a reasonable number of studies could thus be included. Thirdly, in order to limit the scope of the review and make it manageable while still providing examples of different types of VCs, studies on Open-Source Software (OSS) projects as a specific set of online collaboration networks were excluded (see e.g., Kuk, 2006; Bagozzi and Dholakia, 2006; Hertel et al., 2003). A total of 14 articles were identified for further review. As mentioned above, the main focus was on capturing the factors that seem to facilitate knowledge sharing in VCs. Each article was content-analysed in order to identify: •

the conceptualisation of the VC



the assumptions regarding the nature of knowledge and knowledge sharing



the facilitators of knowledge sharing.

The reviewed articles were published in Organization Science, Organization Studies, MIS Quarterly, Decision Support Systems, the Journal of Strategic Information Systems, the Journal of Knowledge Management, Knowledge Management Research and Practice, the Journal of Global Information Management, Electronic Markets, the International Journal of Human-Computer Studies and Internet Research. The reviewed articles are briefly introduced below. Chiu et al. (2006) considered knowledge sharing based on social capital and social cognitive theories, while Hsu et al. (2007) focused more specifically on the role of trust, self-efficacy and outcome expectations. Wasko and Faraj (2000) reviewed the current knowledge management practices and the public-good approach in order to explain the knowledge-sharing activity in VCs. Their latter study (2005) discussed the role of the dimensions of social capital in relation to contributing knowledge in virtual networks. Wiertz and de Ruyter (2007) extended the social capital model developed by Wasko and Faraj in their examination of

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customer contributions to firm-hosted online communities. The articles by Ardichvili et al. (2003; 2006) illustrated the influence of cultural values on the motivation to share knowledge in VCs and the barriers against doing so. Ridings et al. (2002) measured the effect of trust on the individual willingness to give and receive information in interest-based VCs, while Usoro et al. (2007) investigated the role of trust in Virtual Communities of Practice (VCoP) in the organisational context. Wang and Fesenmaier (2003) captured and categorised the different motivations that drive individuals to share knowledge. Yoo et al. (2002) studied the roles of the management strategy, the quality of the information system and a sense of community in VC participation. Lee et al. (2006) reported an experiment carried out to investigate the factors that drive knowledge sharing among the users of web-based discussion boards. Jeppesen and Frederiksen (2006) focused on an innovative user community in order to identify individual motivations to contribute. Finally, Fahey et al. (2007) discussed the role of rewards within a VCoP. Table 1 provides an overview of the reviewed articles. It describes the research approach, the theoretical background, the research questions, the methodology and data and the key findings related to knowledge contribution, participation and knowledge sharing in VCs. Table 1

The research approach, theoretical background, research questions, methodology and data and key findings

Theoretical Research approach background Ardichvili et al. (2006): Qualitative study of members of VCoPs at Caterpillar Inc.

Cultural values

Research questions

Methodology and data

Key findings

How do differences in cultural values, assumptions and preferences affect the way employees in overseas offices access and share professional knowledge?

In-depth interviews with open-ended questions (36) in three different countries and the analysis of online participation records.

Perceived differences in power and hierarchy turned out to be less critical than assumed in all three collectivist cultures.

What are the employees’ perceptions of the preferred approaches to seeking and sharing knowledge?

There is also a strong in-group orientation. In China, modesty requirements and a high degree of competitiveness (the need to ‘own’ knowledge) are serious barriers to knowledge sharing in VCoPs.

What are the culture-specific knowledge-sharing barriers? Ardichvili et al. (2003): Qualitative study of members of VCoPs at Caterpillar Inc.

Motivation

What are the: 1) reasons for and 2) barriers against contributing knowledge in VCoPs? What are the: 1) reasons for and 2) barriers against using VCoPs as a source of new knowledge?

However, top and middle managers are less likely to participate in VCoPs.

Semistructured interviews (30), company documentation (presentations, manuals, community reports and statistics).

Sharing is enhanced by prior knowledge about members, being comfortable with Computer-Mediated Communication (CMC) and the need to gain status/reputation, solve problems and manage one’s own work. In addition, moral obligations and viewing knowledge as a public good (norms, culture of sharing) foster sharing. Face-to-face interactions may make online sharing redundant.

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M. Kosonen The research approach, theoretical background, research questions, methodology and data and key findings (continued)

Theoretical Research approach background Chiu et al. (2006): Quantitative study of one professional (IT) VC, BlueShop

Social capital Social cognitive theory – outcome expectations

Research questions

Methodology and data

Key findings

What is the influence of the outcome expectations and facets of the three dimensions of social capital on knowledge sharing in terms of quantity and quality?

Online survey, pretest and a pilot study, 310 respondents.

Personal outcome expectations have a negative but insignificant effect on the amount of knowledge sharing. Community-related outcome expectations enhance both the amount and quality of knowledge sharing. Social interaction ties and the norms of reciprocity and identification increase knowledge sharing quantitatively, but not qualitatively. The norms of reciprocity and identification exert a positive and strong effect on trust. Trust has a positive impact on the quality of knowledge sharing. Neither trust nor a shared language enhances the amount of sharing.

Fahey et al. (2007): Rewards Qualitative study of one VCoP by SAP

What kind of effects do rewards and incentives have on knowledge exchange and behaviour?

Ethnographic/Participant observation, together with the collection of postings from the community.

Hsu et al. (2007): Quantitative study of 39 societies from Yahoo! Groups and professional associations

What is the influence of outcome expectations, self-efficacy and trust (economy-based, information-based and identification-based) on an individual’s knowledge-sharing behaviour?

Self-efficacy has both direct Online survey, response rate of 28% of those who and indirect effects on browsed the survey (768), knowledge sharing. 274 respondents. Personal outcome expectations have a significant influence, while community-related expectations do not.

Trust Social cognitive theory – self-efficacy – outcome expectations

Tangible rewards have a negative effect on knowledge sharing. The motivation to exchange knowledge decreased, while the motivation to obtain an economic (tangible) reward increased.

Economy-based trust and information-based trust have to be established in order to develop identification-based trust, which is critical for knowledge sharing.

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The research approach, theoretical background, research questions, methodology and data and key findings (continued)

Theoretical Research approach background Jeppesen and Personal attributes Frederiksen (2006): Quantitative and qualitative study of one VCoP for music software developers hosted by Propellerhead

Research questions

Methodology and data

Key findings

Why do users contribute to firm-hosted user communities?

Online survey with 422 respondents, a follow-up survey with 13 respondents, observation, interviews and log data from the community.

Innovative users who share their knowledge among the community tend to be hobbyists, not professionals.

In particular, what are their personal attributes?

Recognition by the firm hosting the community is important for active contribution. Being a leading-edge user and satisfying one’s own product needs by contributing positively affects sharing. Professionals, in turn, cannot share freely because of their competitive position. Sharing is fostered by enjoyment: satisfaction, learning, reciprocal help.

What are the factors that drive knowledge sharing among customers in web-based discussion boards?

Online survey with open questions, 104 respondents.

Trust

How does members’ trust in other members affect knowledge sharing and what builds such trust?

Online survey, 663 respondents.

Trust has a direct effect on the willingness to exchange and, particularly, to receive information.

Usoro et al. (2007): Trust Quantitative study of one VCoP (Systems Thinking) from CSC, IT services organisation

What is the role of trust (in competence, integrity and benevolence) in the provision of knowledge?

Online survey, 75 respondents.

All three dimensions of trust positively relate to knowledge sharing, most significantly integrity-based trust.

Lee et al. (2006): Exploratory study of customers using web-based discussion boards

Personal interest – motivation – social exchange, reciprocity

Sharing is hindered when knowledge self-efficacy is lacking (competence, confidence), knowledge is considered useless, too much time and effort are required, a sense of community is lacking, people feel uncomfortable with the system or feel their privacy is being compromised and there are no rewards.

Social context – social identity – sense of community Technological attributes – usefulness – ease of use Ridings et al. (2002): Quantitative study of 36 online bulletin boards

Knowledge sharing was evaluated in terms of quantity, quality and individual engagement in sharing (i.e., focus); of these, focus exhibits the most significant relationship with trust.

150 Table 1

M. Kosonen The research approach, theoretical background, research questions, methodology and data and key findings (continued)

Theoretical Research approach background Wang and Fesenmaier (2003): Quantitative study of one VC (a travel community)

Motivation Ease of communication Member characteristics – personality – level of involvement

Research questions

Methodology and data

Online survey, Why do people freely give valuable information 322 respondents. and advice? What can explain the amount of cooperation in VCs? How can businesses get individuals to contribute to the provision of a public good?

Key findings Three major groups of knowledge-contribution determinants are identified: motivation (e.g., expectation of future reciprocation), ease of communication and members’ characteristics (level of involvement and personality, such as being expressive, high in self-esteem and competence, high in internal locus of control, low in the need for approval and high in moral development).

Why do people contribute time and effort to the provision of knowledge as a public good?

Collecting messages within a seven-week period for content analysis, an online survey with open questions, 342 participants.

Sharing is boosted by community interest, tangible returns (access to valuable knowledge, personal gain) and intangible returns (enjoyment, learning).

Wasko and Faraj Social capital (2005): Collective action Quantitative and qualitative study of Motivation one electronic network supporting a professional legal association

How do individual motivations and social capital influence knowledge contribution?

Observation of message postings (597 unique individuals) and a paper survey (173 respondents, 29%).

Sharing is encouraged by motivational factors (enhancing reputation and helping others), having experience of sharing and being structurally embedded in the network.

Wiertz and de Social capital Ruyter (2007): Collective action Quantitative study of one technical Personal attributes support community

What is the impact of Online survey, commitment (to the 216 respondents. community and the hosting firm) and reciprocity on the quantity and quality of knowledge contribution?

Wasko and Faraj (2000): Qualitative study of three technical Usenet newsgroups

Perceptions of knowledge (object, embedded in individuals, collective) Motivation Public good

Knowledge contribution is strongly influenced by online interaction propensity, commitment to the community and perceived informational value. Reciprocity only has an indirect effect on the amount of knowledge sharing, as it strengthens online interaction propensity. Being committed to the host firm leads customers to make lower-quality contributions. However, sportsmanship attenuates the negative relationship between commitment and quality.

Yoo et al. (2002): Managing strategy What are the factors Quantative study of that enhance member IS quality eight VCs participation? Sense of community

Online survey, 1887 respondents.

Member participation is affected by a sense of community. A sense of community may be enhanced by a valid management strategy and IS quality.

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Virtual communities as entities of knowledge sharing

The results of the review are discussed in this section. The first question relates to what VCs are and how they are defined in the current research. Table 2 captures the focal concepts of the reviewed articles. Table 2

The definitions of virtual communities

Authors

Focal concept

Definition

Ardichvili et al. (2006)

Online CoPs

A CoP is an activity system about which participants share their understanding concerning what they are doing and what that means in their lives and for their community (Lave and Wenger, 1991). Accordingly, online CoPs make use of online collaborative communication technologies for such exchanges (pp.95–96).

Ardichvili et al. (2003)

VCoPs

A CoP is an activity system that includes individuals who are united in action and in the meaning that action has for them and for the larger collective (Lave and Wenger, 1991). VCoPs are supported by internet technologies (p.65).

Chiu et al. (2006)

VCs

VCs are online social networks in which people with common interests, goals or practices interact to share information and knowledge and engage in social interactions (p.1873).

Fahey et al. (2007)

VCoPs

CoPs are groups of people who share a concern, a set of problems or a passion about a topic and who deepen their knowledge and expertise by interacting on an ongoing basis (Wenger, 1998); VCoPs add the online context (p.187).

Hsu et al. (2007)

VCs

A VC is a cyberspace supported by information technology. It is centred upon the communications and interactions that enable the participants to perform common functions and learn from, contribute to and collectively build upon that knowledge (Lee et al., 2003, p.153).

Jeppesen and Frederiksen (2006)

Firm-hosted user communities

Firm-hosted online user communities are peer-to-peer communities of common interest which employ internet communication technologies as vehicles to increase information sharing (p.45).

Lee et al. (2006)

Web-based discussion boards

A web-based discussion board is a sociotechnical system involving interactions among the characteristics of individual users, user groups and the system (p.291).

Ridings et al. (2002)

VCs

VCs can be defined as groups of people with common interests and practices that communicate regularly and, for some duration, in an organised way over the internet through a common location or mechanism (p.273).

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M. Kosonen The definitions of virtual communities (continued)

Authors

Focal concept

Definition

Usoro et al. (2007)

VCoPs

CoPs are groups of people “informally bound together by shared expertise and passion for a joint enterprise” (Wenger and Snyder, 2000); VCoPs extend their boundaries by enabling global asynchronous and real-time collaboration (p.200).

Wang and Fesenmaier (2003)

Online communities

Online communities are sustained and supported by group media and represent a long-term shift to communities organised according to shared interests rather than a shared place such as a neighbourhood or village (Wellman, 1998, p.34).

Wasko and Faraj (2000)

Electronic CoPs

Newsgroups are “self-organizing, electronic forums in which issues associated with the topic of the newsgroup are discussed” (p.162).

Wasko and Faraj (2005)

Electronic networks of practice

Networks of practice consist of a larger, loosely knit, geographically distributed group of individuals engaged in a shared practice, but who may not know each other nor necessarily expect to meet face-to-face (Brown and Duguid, 2001); in an electronic network of practice, sharing knowledge occurs primarily through computer-based communication technologies (p.37).

Wiertz and de Ruyter (2007)

Firm-hosted online communities

Commercial online communities are firm-hosted online aggregations of customers who collectively co-produce and consume content about a commercial activity that is central to their interest by exchanging intangible resources (such as information, knowledge or socio-emotional support) (p.349).

Yoo et al. (2002)

VCs

A VC has four requirements: cyberspace, commonness, interactivity and continuance (see Rheingold, 1993, p.57).

In sum, these definitions clearly imply the four requirements of VCs, as discussed by Yoo et al. (2002): cyberspace, commonness, interactivity and continuance. Firstly, VCs are rooted in cyberspace, at least to a certain degree; the supporting infrastructure is referred to as group media, online/electronic forums or collaboration and communication technology in a broader sense (Wang and Fesenmaier, 2003; Jeppesen and Frederiksen, 2006; Wasko and Faraj, 2005). Secondly, with regard to commonness, through these communities, people engage in activities of sharing (practices, interests, understanding or expertise, for instance, and deepening knowledge about a certain subject) based on a common need (Chiu et al., 2006; Ridings et al., 2002; Wiertz and de Ruyter, 2007; Fahey et al., 2007). Thirdly, in practice, VCs are maintained through social interaction – in other words, communicating and discussing (Ridings et al., 2002; Hsu et al., 2007). Finally, some definitions also imply the time range, identifying a community that operates “on an ongoing basis” (Fahey et al., 2007) or “regularly, for some duration” (Ridings et al., 2002), referring to the continuance of VCs in contrast to temporary online groups.

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Interestingly, only Wasko and Faraj (2005) explicitly differentiated between a community and a network of practice. The former refers to a tightly knit group of members engaged in a shared practice (Lave and Wenger, 1991; Wenger, 1998), whereas networks of practice consist of larger, loosely knit and geographically distributed groups of individuals sharing a practice, but not necessarily knowing each other or engaging in face-to-face interaction (Wasko and Faraj, 2005; Brown and Duguid, 2001). There is an underlying assumption that community membership incorporates the affective, emotional dimension manifested in social relationships (Blanchard and Markus, 2004), yet it seems that researchers willingly adopt the concept of a ‘VC’ regardless of whether such affective ties are involved or not (see Table 1). To conclude, the concept of VC refers to a technology-mediated virtual space supporting ongoing social interaction among people who share an interest in a certain subject or practice. Over time, members may build affective relationships and engage in more tightly knit social groups within the community.

4.1 The nature of knowledge in virtual communities The analysis now focuses on how the concept of knowledge was approached in the reviewed articles. In general, the core difference between information and knowledge is that the latter cannot be disseminated as such without shared practices or frames through which the involved subjects give meaning and value to their information environment (e.g., Brown and Duguid, 1991). Usoro et al. (2007), in turn, gave definitions for the concepts of data, information and knowledge, while Wasko and Faraj (2000) identified three types of knowledge – object, embedded and collective – and categorised the key characteristics related to them. In sum, the object type of knowledge implies the codified knowledge owned by organisations, embedded knowledge exists in the minds of individuals (know-that) and collective knowledge refers to the social practice of knowing among communities. Lee et al. (2006) identified two types of knowledge to be shared: knowledge about people and knowledge residing in people. Of all of the articles examined for the review, only these three provide some illustration of how knowledge and information are conceptually understood. The studies in question are empirical in nature and a detailed theoretical discussion is not appropriate. However, the scant reference to the basic assumptions behind the core concepts may also indicate a strong emphasis on why individuals engage in knowledge-sharing activities within VCs. Less attention is given to what is actually being shared and how the processes of sharing are manifested in practice. Wasko and Faraj (2000) and Fahey et al. (2007) aptly noted that it is impossible to separate knowledge from its context: all types of knowledge activities require general discussions, experimentations and joint experiences with others who share the same interest or practice. With the exception of their work, a common notion expressed in the reviewed studies is that even in the case of a VC with certain boundaries and underlying interests, knowledge is mostly seen as either an object (codified knowledge) that can be relatively easily identified, located and transferred, or as individual property to be extracted from individuals and made available to the collective (cf. Ridings et al., 2002; Usoro et al., 2007; Hsu et al., 2007). For Wiertz and de Ruyter, knowledge is the “main resource exchanged in online communities” (2007, p.347). Indeed, according to Usoro et al. (2007), such knowledge can only exist in the mind of an individual.

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The above contradicts the view of knowledge as a collective social practice that is enacted in a particular context, referred to as ‘collective knowledge’ that is sticky and, strategically, the most valuable (Spender, 1996; Orlikowski, 2002). It can be understood as an invisible structure or as collective wisdom built on language, shared meanings, routines and experiences (Kotlarsky and Oshri, 2005; Wasko and Faraj, 2000; Schultze, 1999). Individuals may not consciously identify the existence of collective knowledge, which is accessed and maintained through social interaction (Spender, 1996).

4.2 The nature of knowledge sharing in virtual communities Various forms of knowledge-sharing activity are discussed. Ardichvili et al. (2006) referred to knowledge sharing and seeking (supply and demand) and Ridings et al. (2002, see also Fahey et al., 2007), to giving and getting information. Communities involve contributing personal knowledge and operating as a source of new knowledge (Ardichvili et al., 2003; 2006). Knowledge sharing in VCs could be thought of as a form of generalised exchange among a group of people, involving indirect reciprocal dependence and a system (a set of communication technologies adopted by the VC) serving as the intermediary between the contributors to and seekers of individual knowledge (Lee et al., 2006; Ridings et al., 2002). According to Wasko and Faraj (2000), in conditions in which knowledge is embedded in the community, knowledge sharing is enabled through collaborative technologies that support posting and responding, sharing personal stories and debating issues relevant to the collective. Contributing to the VC thus involves asking questions, providing information and expertise and sharing ideas. The authors seem to have adopted the terms ‘sharing’, ‘exchange’, ‘contribution’ and ‘participation’ to refer to the same issue: individuals engage in community interaction to share their private knowledge or contribute to the public good (Wasko and Faraj, 2000). Wasko and Faraj (2005) referred in their later study to knowledge sharing as contributing one’s own knowledge to help others in the network (see also Wiertz and de Ruyter, 2007). Usoro et al. (2007, p.201) illustrated the two sides of the coin: “Knowledge sharing involves a process of communication, whereby two or more parties are involved in the transfer of knowledge.” More specifically, sharing is a process of communication between two or more participants involving both the provision and acquisition (interpretation) of knowledge (Usoro et al., 2007). According to Hsu et al. (2007, p.154), knowledge sharing is “the behavior when an individual disseminates his acquired knowledge to other members within an organization” (Ryu et al., 2003), while Chiu et al. (2006) considered sharing to be manifested in the form of supplying one’s own knowledge. Thus far, two differing views on knowledge sharing have emerged from the literature. While several of the reviewed studies consider it to be a two-way act (Ardichvili et al., 2006; Wasko and Faraj, 2005; Usoro et al., 2007), according to another stream, it operates in a unidirectional, ‘broadcasting’ mode, implying the supply of personal knowledge (Chiu et al., 2006). Finally, there are studies that do not explicitly refer to knowledge sharing as such. For instance, Jeppesen and Frederiksen (2006) mentioned revealing user innovations freely among the community (i.e., contributing to the public good; Wasko and Faraj, 2000) and Wang and Fesenmaier (2003) also considered the offering of free information. Yoo et al. (2002) labelled knowledge merely as one important asset that VCs may possess.

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The analysis now focuses on how the factors that appear to facilitate knowledge sharing within VCs are identified in the existing empirical studies.

5

Facilitators of knowledge sharing in virtual communities

Various knowledge-sharing facilitators are related to personal motivations (e.g., Wasko and Faraj, 2000; Wang and Fesenmaier, 2003; Ardichvili et al., 2003), both intrinsic (the enjoyment of helping, learning) and extrinsic (access to useful resources, reputation, status and rewards). In particular, sharing expertise is motivated by status, respect, compliance and obligation (see also Blau, 1964). Motivation is a psychological state, whereas actual behaviour is the outcome of that state (see Mitchell and Daniels, 2003). Hence, motivation is a necessary – but not sufficient – condition for active contribution to and participation in VCs (Wang and Fesenmaier, 2003). Both intrinsic and extrinsic rewards are considered important motivators of knowledge sharing. Individuals are more inclined to contribute when they expect rewards such as promotion and career advancement. Nevertheless, rewards remain a double-edged sword, as expectations of them seem to hinder the development of a positive attitude towards sharing (cf. Bock and Kim, 2002) and may outweigh internal motivations (Deci and Ryan, 1985; Fahey et al., 2007), thus destroying the public good. Indeed, as Lee et al. (2006) found, a lack of reward was interpreted to have a negative effect on knowledge-sharing activities, while in a real-life VC hosted by a firm (Fahey et al., 2007), the observed negative effect was a result of introducing a reward system. It is thus not easy to see how rewards affect knowledge sharing in VCs and which form of reward or incentive is appropriate (Chiu et al., 2006). According to Fahey et al. (2007), rewards may turn counterproductive in terms of social interaction by increasing opportunism and conflict. They suggested that specific attention should be given to linking rewards with the quality of contributions. Jeppesen and Frederiksen (2006) also found that innovative users were motivated by explicit recognition from the firm hosting the community, rather than by the idea of directly advancing their position and reputation among their peers. Of other motivating factors, self-efficacy refers to “a judgment of one’s ability to organize and execute given types of performances”, while outcome expectations are judgements of the likely consequences produced by such performances (Bandura, 1997, p.21). Community-related outcome expectations refer to an individual’s judgement about the likely consequences that his or her behaviour will produce for the community and personal outcome expectations accordingly refer to the anticipated consequences for him- or herself (Bandura, 1997, p.21). Self-efficacy is manifested in terms of having an impact on the surrounding collective (Bandura, 1997; Wang and Fesenmaier, 2003) and is also referred to as the feelings of influence that affect an individual’s sense of belonging (see Blanchard and Markus, 2004). For instance, autonomous workers perceive greater utility in engaging in VCoPs and identifying innovative working patterns than the employees who are monitored and receive detailed directions from managers (Hsu et al., 2007). Interestingly, the effects of personal and community outcome expectations turned out to be contradictory in the studies conducted by Chiu et al. (2006) and Hsu et al. (2007): in the former, community-related expectations strongly affected both the quantity and quality of knowledge sharing, while in the latter, only personal outcome expectations

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played a role. In explaining their finding, Chiu et al. (2006, p.1883) suggested that the salience of community-related outcome expectations may outweigh personal expectations in the sense that “knowledge contributors are more concerned about the successful functioning, survival, and growth of the virtual communities than the benefits they will produce to themselves”. It is also worth noting that Chiu et al. studied one established professional community, while the data from Hsu et al. covers 39 different online groups and associations. The interesting question of how and why community-related outcome expectations evolve remains. When they are lacking, VC members expect to share knowledge in terms of reaching personal (extrinsic) goals related to praise, image and social status (Hsu et al., 2007). According to the empirical work carried out so far, an individual’s knowledge-contributing activity is still strongly affected by network centrality (Wasko and Faraj, 2005), i.e., a focal position with connections to a large number of members. In particular, social-interaction ties increase the amount of knowledge (Chiu et al., 2006). Individual assumptions about the nature of knowledge also affect sharing in VCs (Wasko and Faraj, 2000): when knowledge is considered the property of a social collective and a public good, it is more ‘naturally shared’. According to Usoro et al. (2007), when the sense of belonging is strong and benevolence among the VC members is high, people more willingly contribute to the public good. Assumptions about knowledge are affected by cultural values to some extent (Ardichvili et al., 2006; 2003). An intention to share knowledge in VCs may develop more easily in individualistic cultures that favour the use of communications technology for collaboration and problem solving, whereas in collectivist cultures, modesty requirements and strong in-group orientation may hinder knowledge sharing among loose groupings such as VCoPs (Ardichvili et al., 2006). However, the effects of cultural values remain a complex and understudied phenomenon in the context of VCs (Ardichvili et al., 2006). Technical attributes have been identified as another relevant set of factors that facilitate knowledge sharing (Wang and Fesenmaier, 2003; Yoo et al., 2002). The study conducted by Yoo et al. (2002) refers to the quality of IS, which consists of system quality (users’ perceptions of the system) and the quality of the generated information. System quality includes aspects such as speed, reliability, user-friendliness, functionality and recovery. Lee et al. (2006), in turn, adopted the usability measures introduced by Preece (2000), including support for social interaction (such as feedback and prompts), information design (understandability), ease of navigation and access (response time, downloading speed). The community must also handle member data sensitively and maintain privacy (Lee et al., 2006). More generally, VC site management involves mutual decision making about the appropriate rules and policies, member roles and practices (Yoo et al., 2002) such as reward systems which, in turn, may have significant effects on member motivations and the patterns of social interaction (Fahey et al., 2007). Up to this point, the analysis has emphasised the individual motivations, personal characteristics and technical attributes that may facilitate knowledge sharing in VCs. However, there is a fourth category of knowledge-sharing facilitators, social capital, which essentially means that social relations may be productive resources. Social capital exists in relations between people and, thus, is collectively owned and maintained (Coleman, 1990). More specifically, it consists of structural, relational and cognitive dimensions (Nahapiet and Ghoshal, 1998; Wasko and Faraj, 2005). It could be

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considered ‘a theoretical umbrella’ covering a variety of VC issues such as online network ties, norms, identification, trust, commitment and a shared language (Chiu et al., 2006; Wasko and Faraj, 2005; Nahapiet and Ghoshal, 1998). Many studies on VCs focus on a technical infrastructure that easily allows individual users to find each other and communicate or cooperate through network ties. Nevertheless, the opportunity to do so is not enough to enable knowledge sharing: it requires not only structural social capital, but also the cognitive and relational dimensions (Nahapiet and Ghoshal, 1998; Wasko and Faraj, 2005; Chiu et al., 2006). The higher the cognitive ability in a social group (in other words, the ability to understand each other), the more its members are able to share. Relational social capital such as norms, trust and reciprocity, in turn, may stimulate people to engage in knowledge sharing if they have the ability and opportunity to do so (Wasko and Faraj, 2005; Huysman and Wulf, 2006). Within VCs, trusting relationships may emerge without any direct social interaction (Usoro et al., 2007), as communication is open and transparent in nature. Initially, trust may develop between an individual and a ‘group of strangers’ belonging to the community, thereby providing a positive knowledge-sharing outcome in the collective. Hence, knowledge sharing is encouraged by generalised trust in the community (Ridings et al., 2002). Over time, it becomes more interpersonal (see also Wilson et al., 2006). In particular, trust in the ability and benevolence of other members positively affects the willingness to acquire information among the community (Ridings et al., 2002). Hsu et al. (2007) found identification-based trust critical in terms of knowledge sharing in VCs. It consists of emotional bonds between individuals who understand and appreciate each other’s needs (McAllister, 1995). Hence, people trust due to emotional interaction (Hsu et al., 2007), and express care and concern for each other. Finally, the study conducted by Usoro et al. (2007) emphasises the role of integrity-based trust, which is rooted in past behaviour among the social collective: it derives from the perceptions of the trustee adhering to a set of acceptable principles. Integrity-based trust is manifested in VCs in the compatibility of the community’s cultural values with those of the trusting members, the credibility of the community’s reputation and the consistency in the behaviour of its members (Usoro et al., 2007). Identification refers to the individual’s sense of belonging and positive feelings towards the VC. It has been suggested that it explains the willingness to maintain social relationships among the community and, consequently, foster knowledge sharing: social unity and togetherness activate behaviour and positively affect the knowledge-sharing quality (Chiu et al., 2006). Together with membership, influence and a shared emotional connection, identification is a focal dimension of a sense of community (Blanchard and Markus, 2004), which has been found to enhance VC participation (Yoo et al., 2002; Lee et al., 2006). According to Chiu et al. (2006), identification positively affects the quantity of knowledge sharing while having an indirect effect on quality through trust. Finally, a strong norm of reciprocity has been identified in VCs (Wasko and Faraj, 2000). This justifies the expense of time and effort in sharing knowledge (Chiu et al., 2006) and implies commitment to the community which, in turn, conveys a sense of responsibility to help others based on shared membership (Wasko and Faraj, 2005). The norm of reciprocity has also been found to have indirect effects on the quantity of knowledge sharing through higher online interaction propensity (Wiertz and de Ruyter, 2007) and on its quality through higher levels of trust (Chiu et al., 2006). Table 3 summarises the results of the review in terms of the knowledge-sharing facilitators.

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Table 3

The facilitators of knowledge sharing in virtual communities

Category

Facilitators

Source

Individual motivations

Moral obligations

Wasko and Faraj (2000)

Enjoyment of helping

Wasko and Faraj (2000) and Lee et al. (2006)

Learning

Wasko and Faraj (2000)

Perceived informational value

Wiertz and de Ruyter (2007)

Information quality

Yoo et al. (2002)

Access to valuable resources

Wasko and Faraj (2000)

Recognition by the host firm

Jeppesen and Frederiksen (2006)

Enhancing reputation, status

Wasko and Faraj (2005)

Rewards (when appropriate)

Lee et al. (2003)

Self-efficacy

Hsu et al. (2007)

Community-related outcome expectations

Chiu et al. (2006)

Personal outcome expectations

Hsu et al. (2007)

Viewing knowledge as a public good

Wasko and Faraj (2000)

Active, helping personality

Wang and Fesenmaier (2003)

Central position within the network

Wasko and Faraj (2005)

Sportsmanship, toleration of failures

Wiertz and de Ruyter (2007)

Experience of sharing

Wasko and Faraj (2005)

Being comfortable with CMC

Ardichvili et al. (2003)

Cultural values that favour CMC

Ardichvili et al. (2006)

Being a leading-edge user

Jeppesen and Frederiksen (2006)

Lower position in the organisational hierarchy

Ardichvili et al. (2006)

IS quality

Yoo et al. (2002)

Usability

Lee et al. (2006)

Ease of communication

Wang and Fesenmaier (2003)

Privacy

Lee et al. (2006)

Site management

Yoo et al. (2002)

Social interaction ties

Chiu et al. (2006)

Prior knowledge about others

Ardichvili et al. (2003)

Sense of community

Yoo et al. (2002)

Trust

Ridings et al. (2002), Usoro et al. (2007) and Hsu et al. (2007)

Commitment

Wiertz and de Ruyter (2007)

Norm of reciprocity

Wasko and Faraj (2000)

Identification

Chiu et al. (2006)

Shared language

Chiu et al. (2006)

Personal characteristics

Technical attributes

Social capital

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159

To conclude, contribution on an individual’s part calls for motivation, certain personal attributes and an appropriate technical system (see Wang and Fesenmaier, 2003), whereas knowledge sharing is a social process involving complex structures, relational processes and cognitive frames. For instance, a shared language facilitates the community’s ability to engage in knowledge sharing and combine the knowledge gained through social exchange (Chiu et al., 2006). Hence, social capital may bridge the gap between personal and organisational levels of knowledge and, thus, facilitate knowledge sharing.

6

Discussion

This review explored knowledge sharing in VCs as depicted in prior empirical studies. It captured the varying definitions of the core concept of VC and illustrated the four underlying requirements: cyberspace, commonness, interactivity and continuance. Furthermore, it revealed how knowledge and knowledge sharing were approached in the selected studies and identified the facilitators of knowledge sharing within VCs, categorised as individual motivations, personal characteristics, technical attributes and community-level social capital. Much of the empirical research on facilitating knowledge sharing in VCs is related to individual motivations and personal characteristics, while the community-level facets have attracted less interest. However, while motivation explains why individuals contribute to the common good (i.e., supply their personal knowledge and expertise), knowledge-sharing processes require general conversational norms and practices and a shared language (Wasko and Faraj, 2000). Not every online network will “sharpen its practice” (Castells, 2001) in a way that eventually enables community-level sharing and the creation of knowledge. The important question of how to breed such an effort and foster community development remains. The small amount of work that has focused on the basic assumptions behind the core concept of knowledge indicates a strong emphasis on why individuals engage in knowledge-sharing activities within VCs. Less attention has been given to what is being shared and how the processes of sharing are manifested in practice, even if all three dimensions are highly interrelated (see Huysman and Wulf, 2006). It is often argued that Information and Communications Technologies (ICTs) cannot even support significant outcomes of valuable knowledge due to flaws in their ability to build social capital in the form of norms, obligations and trust (Cohen and Prusak, 2001; Putnam, 2000). On the other hand, a strong norm of reciprocity has been identified in VCs (Wellman and Gulia, 1999; Wasko and Faraj, 2000) and their members may express strong identification based on an underlying shared interest that gathers people together (Bagozzi and Dholakia, 2006; Spears et al., 2001). Overall, the analysis implied an important linkage between social capital and VCs in terms of knowledge sharing. Social capital has only recently attracted attention within this field (for empirical studies, see Chiu et al., 2006; Wasko and Faraj, 2005; Wiertz and de Ruyter, 2007; for analytical work, see Blanchard and Horan, 1998; Huysman and Wulf, 2006; Widén-Wulff and Ginman, 2004; von Wartburg et al., 2006; Kianto and Kosonen, 2007). Codified knowledge that is made collectively available within the VC (i.e., a public good such as a piece of software) could be considered an outcome of knowledge sharing, while collective knowledge (i.e., a shared context, language and common history)

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provides the enabling frame for such activities. In this sense, these types of knowledge are interrelated and inseparable: personal expertise and collective structures are intertwined. Collective knowledge is manifested in social interactions (Spender, 1996) which fundamentally determine the existence of VCs in the minds of their members (Chiu et al., 2006; Ardichvili et al., 2003; Slevin, 2000; Rheingold, 1993) and enable the processes of sharing. Indeed, each VC is considered unique in terms of its membership, norms and practices, language, history and acceptable communication culture (Porter, 2004; Hagel and Armstrong, 1997; Rheingold, 1993), implying community-level manifestations of ‘knowledge in action’. Identifying such community artefacts should not be reduced to a temporal investigation of personal motivations to contribute: understanding a VC ‘as it is’ with a distinct language, norms, practices and identity performance calls for a variety of research methods (typically grounded on the ethnographic approach and participant observation; see Hine, 2000; Kendall, 1999) and requires the time and effort of researchers. As Tsoukas (2005) argued, we need to strive to develop a better theory of knowledge and understand knowing in practice. As organisations increasingly aim at building VCs in order to enhance communication and collaboration both internally and externally, more in-depth understanding is needed on how – and to what extent – such practices could be supported by technology. Hence, it is important to make time for storytelling and negotiating meaning, through which collective sense making may become enabled (see Röll, 2004). As knowledge sharing and social capital inherently breed one another, important questions for further research include how social capital is built and maintained within VCs and the interplay between its different facets. The network structure of VCs also remains a focal concern, hence calling for the systematic social network analyses of the knowledge-sharing relations among them. On the personal level, the reasons for withdrawing and not sharing knowledge seem more diverse and complex than the reasons for sharing (Lee et al., 2006; see also Nonnecke and Preece, 2000) and deserve major research attention. To conclude, prior research demonstrates a strong focus on the question of “Why share?” However, researchers investigating knowledge sharing and contribution should take two steps forward and be aware of what is actually being shared and how such processes are manifested in practice. Hence, rich qualitative studies on knowledge sharing and social capital within VCs are called for.

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Knowledge sharing in virtual communities.pdf

Page 2 of 20. Knowledge sharing in virtual communities 145. mid-1990s, while studies that take a more focused knowledge-sharing perspective have. been published in the 2000s. The studies derive from different disciplines, such as. computing and Information Systems (IS), management, e-commerce and marketing. The.

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