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Article Excerpt
Abstract
Organizations are attempting to leverage their knowledge resources by employing knowledge management (KM) systems, a key form of which are electronic knowledge repositories (EKRs). A large number of KM initiatives fail due to the reluctance of employees to share knowledge through these systems. Motivated by such concerns, this study formulates and tests a theoretical model to explain EKR usage by knowledge contributors. The model employs social exchange theory to identify cost and benefit factors affecting EKR usage, and social capital theory to account for the moderating influence of contextual factors. The model is validated through a large-scale survey of public sector organizations. The results reveal that knowledge self-efficacy and enjoyment in helping others significantly impact EKR usage by knowledge contributors. Contextual factors (generalized trust, pro-sharing norms, and identification) moderate the impact of codification effort, reciprocity, and organizational reward on EKR usage, respectively. It can be seen that extrinsic benefits (reciprocity and organizational reward) impact EKR usage contingent on particular contextual factors whereas the effects of intrinsic benefits (knowledge self-efficacy and enjoyment in helping others) on EKR usage are not moderated by contextual factors. The loss of knowledge power and image do not appear to impact EKR usage by knowledge contributors. Besides contributing to theory building in KM, the results of this study inform KM practice.
Keywords: Knowledge management, electronic knowledge repositories, knowledge contribution, social exchange, social capital
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Introduction
The strategic management of organizational knowledge is a key factor that can help organizations to sustain competitive advantage in volatile environments. Organizations are turning to knowledge management (KM) initiatives and technologies to leverage their knowledge resources. According to the analyst firm IDC, business spending on KM could rise from $2.7 billion in 2002 to $4.8 billion in 2007 (Babcock 2004). Concurrent with the organizational interest in KM, a large number of academic papers have been published on KM (Schultze and Leidner 2002). These developments reflect the significance of KM among scholars and practitioners.
Knowledge management is defined as "a systemic and organizationally specified process for acquiring, organizing, and communicating both tacit and explicit knowledge of employees so that other employees may make use of it to be more effective and productive in their work" (Alavi and Leidner 1999, p. 6). KM systems are "a class of information systems applied to managing organizational knowledge. That is, they are IT-based systems developed to support and enhance the organizational processes of knowledge creation, storage/retrieval, transfer, and application" (Alavi and Leidner 2001, p. 114). Two models of KM systems have been identified in the information systems literature: the repository model and the network model (Alavi 2000). (2) The repository model corresponds to the codification approach to KM (Hansen et al. 1999). This approach emphasizes codification and storage of knowledge so as to facilitate knowledge reuse through access to the codified expertise. A key technological component of this approach is electronic knowledge repositories (EKRs) (Grover and Davenport 2001). The network model corresponds to the personalization approach to KM (Hansen et al. 1999). This approach emphasizes linkage among people for the purpose of knowledge exchange. Important technological components of this approach are knowledge directories that provide location of expertise (Ruggles 1998) and electronic forum software that allows people to interact within communities of practice (Brown and Duguid 1991).
While technological capabilities are important, having sophisticated KM systems does not guarantee success in KM initiatives (Cross and Baird 2000; McDermott 1999). This is because social issues appear to be significant in ensuring knowledge sharing success (Ruppel and Harrington 2001). Both social and technical barriers to usage of KM systems have been listed and calls have been made to simultaneously address both sets of issues (McDermott 1999; Zack 1999) in order to be able to reap the benefits of KM that have been experienced by some organizations (Davenport et al. 1998; O'Dell and Grayson 1998).
This study focuses on EKRs since they are fundamental to organizational knowledge capture and dissemination, yet the factors affecting EKR usage are not well understood (Markus 2001). EKRs are electronic stores of content acquired about all subjects for which the organization has decided to maintain knowledge (Liebowitz and Beckman 1998). EKRs can comprise multiple knowledge bases as well as the mechanisms for acquisition, control, and publication of the knowledge. (3) The process of knowledge sharing through EKRs involves people contributing knowledge to populate EKRs (e.g., customer and supplier knowledge, industry best practices, and product expertise) and people seeking knowledge from EKRs for reuse. Success of EKRs requires that knowledge contributors be willing to part with their knowledge and knowledge seekers be willing to reuse the codified knowledge (Ba et al. 2001). The distinction between contributors and seekers is conceptual in that the same individual can be a contributor or a seeker at different points in time. This study examines EKR usage from the perspective of knowledge contributors as this is the first step toward knowledge leverage through EKRs. Unless knowledge contributors are willing to provide content to EKRs, knowledge reuse through EKRs cannot take place.
Several prior studies have adopted a conceptual (Kollock 1999; Markus 2001) or qualitative approach (Goodman and Darr 1998; Orlikowski 1993; Wasko and Faraj 2000) in attempts to understand the behavior of knowledge contributors. Other studies have conducted experiments (Constant et al. 1994) or surveys (Bock et al. 2005; Constant et al. 1996; Jarvenpaa and Staples 2000; Wasko and Faraj 2005) to model and explain contributor behavior with varying success. Existing empirical studies focus on the benefits (acting as motivators) rather than the costs (acting as inhibitors) of knowledge contribution, despite suggestions from practitioner literature (O'Dell and Grayson 1998) and conceptual literature (Ba et al. 2001) that cost factors can be important in determining knowledge-sharing behavior. This study advances theoretical development on knowledge contribution in two important ways. First, it simultaneously investigates both cost and benefit factors affecting EKR usage. Second, it incorporates contextual factors to illustrate how these may moderate the relationships between cost and benefit factors and EKR usage. The results suggest organizational interventions and technology design considerations that can promote knowledge contribution to EKRs, thereby facilitating reuse of organizational knowledge.
Theoretical Background
The dependent variable we are interested in investigating is the degree of EKR usage by knowledge contributors. In investigating the usage of EKRs, the first choice of theoretical bases would appear to be theories such as the technology acceptance model (Davis 1989) which have been successful in explaining the usage of information systems (e.g., Venkatesh and Davis 2000). Although the technology acceptance model may partially explain the behavior of knowledge contributors, (4) this model does not directly account for the social cost and benefit factors experienced by knowledge contributors that may affect their usage of collective technologies such as EKRs. However, the social and individual cost and benefit factors in knowledge sharing can be accounted for by social exchange theory. The impact of cost and benefit factors on EKR usage by knowledge contributors is likely to be contingent upon contextual factors (Constant et al. 1996; Goodman and Darr 1998; Jarvenpaa and Staples 2000; Orlikowski 1993). Social capital theory accounts for several important contextual factors in knowledge exchange. Therefore, this study uses the social exchange theory and the social capital theory as its theoretical bases.
Cost and Benefit Factors
Cost and benefit factors in our study are derived based on social exchange theory. Social exchange theory explains human behavior in social exchanges (Blau 1964), which differ from economic exchanges in that obligations are not clearly specified. In such exchanges, people do others a favor with a general expectation of some future return but no clear expectation of exact future return. Therefore, social exchange assumes the existence of relatively long-term relationships of interest as opposed to one-off exchanges (Molm 1997). Knowledge sharing through EKRs can be seen as a form of generalized social exchange (Fulk et al 1996) where more than two people participate and reciprocal dependence is indirect, with the EKR serving as the intermediary between knowledge contributors and seekers. Knowledge contributors share their knowledge with no exact expectation of future return. The quantity and value of knowledge contributed is difficult to specify and so is the return obtained. Hence, knowledge contributors are likely to work on the assumption of relatively longer-term relationships of interest.
Resources (tangible and intangible) are the currency of social exchange. Resources given away during social exchange or negative outcomes of exchange can be seen as costs. Resources received as a result of social exchange or positive outcomes of exchange can be seen as benefits. Social exchange theory posits that people behave in ways that maximize their benefits and minimize their costs (Molm 1997). In agreement with this theory, researchers have suggested that increasing the benefits and reducing the costs for contributing knowledge can help to encourage knowledge sharing using KM systems (Markus 2001; Wasko and Faraj 2000), including EKRs.
During social exchange, costs can be incurred in the form of opportunity costs and actual loss of resources (Molm 1997). Opportunity costs are rewards foregone from alternative behavior not chosen. For example, the time and effort required to codify and input knowledge into EKRs (Ba et al. 2001; Markus 2001) can act as an opportunity cost that precludes knowledge contributors from performing alternative tasks at that time and accruing the corresponding rewards. Also, knowledge contributors may perceive a loss of power and unique value within the organization associated with the knowledge they transfer to EKRs (Davenport and Prusak 1998; Gray 2001). Such loss of knowledge power can be considered as an actual loss of resource during knowledge contribution.
During social exchange, benefits acting as motivators of human behavior can be extrinsic or intrinsic in nature (Deci and Ryan 1980; Vallerand 1997). Extrinsic benefits are sought after as means to ends desired by people. For example, knowledge contributors may receive organizational rewards for their contributions (Beer and Nohria 2000; Hall 2001) through which they can obtain a better lifestyle. As a result of contribution, knowledge contributors may also enhance their image or reputation in the organization (Ba et al. 2001; Constant et al. 1994; Constant et al. 1996), which can serve to increase their self-concept. By sharing their knowledge, contributors may receive reciprocal benefits, i.e., their future requests for knowledge being met by others (Connolly and Thorn 1990; Kollock 1999; Wasko and Faraj 2000), which can facilitate their work. Intrinsic benefits are sought after as ends by themselves. For example, through contribution, knowledge contributors can be satisfied by enhancing their knowledge self-efficacy or confidence in their ability to provide valuable knowledge that is useful to the organization (Constant et al. 1994; Constant et al. 1996). Also, by contributing knowledge to EKRs, knowledge contributors have the opportunity to help others (Ba et al. 2001; Wasko and Faraj 2000). Previous studies on altruism have shown that people enjoy and derive pleasure from such acts of helping others (Baumeister 1982; Krebs 1975). Research has established extrinsic and intrinsic benefits as motivators of human behavior in several domains (Vallerand 1997), including knowledge sharing (Osterloh and Frey 2000).
Contextual Factors
Contextual factors in our study are derived from social capital theory. Social capital refers to the resources embedded within networks of human relationships (Nahapiet and Ghoshal 1998). These networks include proximate as well as virtual communities (Rheingold 2000). Social capital theory posits that social capital provides the conditions necessary for knowledge exchange to occur. Three key aspects of social capital that can define the context for knowledge exchange are trust, norms, and identification (Nahapiet and Ghoshal 1998). Trust, norms, and identification can be considered as social capital since they are organizational resources or assets rooted within social relationships that can improve the efficiency of coordinated action. Practitioner literature has described the impacts of these factors without considering whether their effects are direct or moderating. However, several prior academic studies (e.g., Constant et al. 1994; Jarvenpaa and Staples 2000) have hinted at the moderating role of these aspects of social capital in knowledge-sharing situations. Specifically, these three factors are believed to be able to amplify or dampen the effects of particular cost and benefit factors on knowledge-sharing behavior.
Trust is the belief that the intended action of others would be appropriate from our point of view (Mistzal 1996). It indicates a willingness of people to be vulnerable to others due to beliefs in their good intent and concern, competence and capability, and reliability (Mishra 1996). McKnight et al. (1998) term these trusting beliefs as benevolence belief, competence belief, and predictability belief, respectively. Generalized trust is an impersonal form of trust that does not rest with a specific individual but rests on behavior that is generalized to a social unit as a whole (e.g., a community of knowledge workers exchanging knowledge through EKRs) (Putnam 1993). In the context of our study, generalized trust refers to the belief in the good intent, competence, and reliability of employees with respect to contributing and reusing knowledge through EKRs. With strong generalized trust, people may trust each other without having much personal knowledge about each other. Generalized trust has been viewed as a key factor that provides a context for cooperation (Tsai and Ghoshal 1998) and effective knowledge exchange (Adler 2001). When generalized trust is strong, the effort required for knowledge sharing may not be salient to knowledge contributors because they believe that knowledge shared is not likely to be misused by reusers (Davenport and Prusak 1998). Conversely, when...
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