Online discussion communities play an important role in the development of relationships and the transfer of knowledge within and across organizations. Their underlying technologies enhance these processes by providing infrastructures through which group-based communication can occur. Community administrators often make decisions about technologies with the goal of enhancing the user experience, but the impact of such decisions on how a community develops must also be considered. To shed light on this complex and under-researched phenomenon, we offer a model of key latent constructs influenced by technology choices and possible causal paths by which they have dynamic effects on communities. Two important community characteristics that can be impacted are community size (number of members) and community resilience (membership that is willing to remain involved with the community in spite of variability and change in the topics discussed). To model community development, we build on attraction–selection–attrition (ASA) theory, introducing two new concepts: participation costs (how much time and effort are required to engage with content provided in a community) and topic consistency cues (how strongly a community signals that topics that may appear in the future will be consistent with what it has hosted in the past). We use the proposed ASA theory of online communities (OCASA) to develop a simulation model of community size and resilience that affirms some conventional wisdom and also has novel and counterintuitive implications. Analysis of the model leads to testable new propositions about the causal paths by which technology choices affect the emergence of community size and community resilience, and associated implications for community sustainability.
Theory suggests that coworkers may influence individuals' technology use behaviors, but there is limited research in the technology diffusion literature that explicates how such social influence processes operate after initial adoption. We investigate how two key social influence mechanisms (identification and internalization) may explain the growth over time in individuals' use of knowledge management systems (KMS)-a technology that because of its publicly visible use provides a rich context for investigating social influence. We test our hypotheses using longitudinal KMS usage data on over 80,000 employees of a management consulting firm. Our approach infers the presence of identification and internalization from associations between actual system use behaviors by a focal individual and prior system use by a range of reference groups. Evidence of these kinds of associations between system use behaviors helps construct a more complete picture of social influence mechanisms, and is to our knowledge novel to the technology diffusion literature. Our results confirm the utility of this approach for understanding social influence effects and reveal a fine-grained pattern of influence across different social groups: we found strong support for bottom-up social influence across hierarchical levels, limited support for peer-level influence within levels, and no support for top-down influence.
Online discussion communities have become a widely used medium for interaction, enabling conversations across a broad range of topics and contexts. Their success, however, depends on participants' willingness to invest their time and attention in the absence of formal role and control structures. Why, then, would individuals choose to return repeatedly to a particular community and engage in the various behaviors that are necessary to keep conversation within the community going? Some studies of online communities argue that individuals are driven by self-interest, while others emphasize more altruistic motivations. To get beyond these inconsistent explanations, we offer a model that brings dissimilar rationales into a single conceptual framework and shows the validity of each rationale in explaining different online behaviors. Drawing on typologies of organizational commitment, we argue that members may have psychological bonds to a particular online community based on (a) need, (b) affect, and/or (c) obligation. We develop hypotheses that explain how each form of commitment to a community affects the likelihood that a member will engage in particular behaviors (reading threads, posting replies, moderating the discussion). Our results indicate that each form of community commitment has a unique impact on each behavior, with need-based commitment predicting thread reading, affect-based commitment predicting reply posting and moderating behaviors, and obligation-based commitment predicting only moderating behavior. Researchers seeking to understand how discussion-based communities function will benefit from this more precise theorizing of how each form of member commitment relates to different kinds of online behaviors. Community managers who seek to encourage particular behaviors may use our results to target the underlying form of commitment most likely to encourage the activities they wish to promote.
Many organizational innovations can be explained by the movement of ideas and information from one social context to another, "from where they are known to where they are not" (Hargadon 2002, p. 41). A relatively new technology, social bookmarking, is increasingly being used in many organizations (McAfee 2006), and may enhance employee innovativeness by providing a new, socially mediated channel for discovering information. Users of such systems create publicly viewable lists of bookmarks (each being a hyperlink to an information resource) and often assign searchable keywords ("tags") to these bookmarks. We explore two different perspectives on how accessing others' bookmarks could enhance how innovative an individual is at work. First, we develop two hypotheses around the idea that quantity may be a proxy for diversity, following a well established literature that holds that the more information obtained and the larger the number of sources consulted, the higher the likelihood an individual will come across novel ideas. Next, we offer two hypotheses adapted from social network research that argue that the shape of the network of connections that is created when individuals access each others' bookmarks can reflect information novelty, and that individuals whose networks bridge more structural holes and have greater effective reach are likely to be more innovative. An analysis of bookmarking system use in a global professional services firm provides strong support for the social diversity of information sources as a predictor of employee innovativeness, but no support that the number of bookmarks accessed matters. By extending the social networks literature to theorize the functionalities offered by social bookmarking systems, this research establishes structural holes theory as a valuable lens through which social technologies may be understood.
In a world where information technology is both important and imperfect, organizations and individuals are faced with the ongoing challenge of determining how to use complex, fragile systems in dynamic contexts to achieve reliable outcomes. While reliability is a central concern of information systems practitioners at many levels, there has been limited consideration in information systems scholarship of how firms and individuals create, manage, and use technology to attain reliability. We propose that examining how individuals and organizations use information systems to reliably perform work will increase both the richness and relevance of IS research. Drawing from studies of individual and organizational cognition, we examine the concept of mindfulness as a theoretical foundation for explaining efforts to achieve individual and organizational reliability in the face of complex technologies and surprising environments. We then consider a variety of implications of mindfulness theories of reliability in the form of alternative interpretations of existing knowledge and new directions for inquiry in the areas of IS operations, design, and management.
Knowledge repositories are commonly used by technical support analysts in call center environments as a way of capturing and reusing solutions to common problems, and are generally expected to improve service quality, reduce costs, and enhance analyst learning. This study investigates why technical support analysts seek out and access knowledge from these repositories, as opposed to more traditional sources of such knowledge—colleagues and manuals. Focusing on the demand for—rather than supply of—knowledge in organizations, our research elaborates the role played by analysts' learning orientation, perceived work demands, and risk aversion in predicting their knowledge sourcing behavior. Our results include several counterintuitive findings that suggest there is not very much learning going on via technical support knowledge repositories. Analysts seem to be focused on finding recipes for solving customers' problems rather than building a better understanding of the products they support. Implications for research and practice highlight the need for more effective technologies to speed searches, the utility of a formal and visible mechanism for validating knowledge, and the inherent tension between efficiency and learning in these environments.