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The design of complex social systems, such as online communities, requires the consideration of many parameters, a practice at odds with social science research that focuses on the effects of a small set of variables. In this article, we show how synthesizing insights from multiple, narrowly focused social science theories in an agent-based model helps us understand factors that lead to the success of online communities. The agent-based model combines insights from theories related to collective effort, information overload, social identity, and interpersonal attraction to predict motivations for online community participation. We conducted virtual experiments to develop hypotheses around three design decisions about how to orchestrate an online community—topical breadth, message volume, and discussion moderation—and the trade-offs involved in making these decisions. The simulation experiments suggest that broad topics and high message volume can lead to higher member commitment. Personalized moderation outperforms other types of moderation in increasing members' commitment and contribution, especially in topically broad communities and those with high message volume. In comparison, community-level moderation increases commitment but not contribution, and only in topically narrow communities. These simulation results suggest a critical trade-off between informational and relational benefits. This research illustrates that there are many interactions among the design decisions that are important to consider; the particulars of the community's goals often determine the effectiveness of some decisions. It also demonstrates the value of agent-based modeling in synthesizing simple social science theories to describe and prescribe behaviors in a complex system, generating novel insights that inform the design of online communities. [ABSTRACT FROM PUBLISHER]

Objective: The objective of the paper is to understand leadership in an online community, specifically, Wikipedia. Background: Wikipedia successfully aggregates millions of volunteers’ efforts to create the largest encyclopedia in human history. Without formal employment contracts and monetary incentives, one significant question for Wikipedia is how it organizes individual members with differing goals, experience, and commitment to achieve a collective outcome. Rather than focusing on the role of the small set of people occupying a core leadership position, we propose a shared leadership model to explain the leadership in Wikipedia. Members mutually influence one another by exercising leadership behaviors, including rewarding, regulating, directing, and socializing one another. Method: We conducted a two-phase study to investigate how distinct types of leadership behaviors (transactional, aversive, directive, and person-focused), the legitimacy of the people who deliver the leadership, and the experience of the people who receive the leadership influence the effectiveness of shared leadership in Wikipedia. Results: Our results highlight the importance of shared leadership in Wikipedia and identify trade-offs in the effectiveness of different types of leadership behaviors. Aversive and directive leadership increased contribution to the focal task, whereas transactional and person-focused leadership increased general motivation. We also found important differences in how newcomers and experienced members responded to leadership behaviors from peers. Application: These findings extend shared leadership theories, contribute new insight into the important underlying mechanisms in Wikipedia, and have implications for practitioners who wish to design more effective and successful online communities. [ABSTRACT FROM AUTHOR]

Online communities are increasingly important to organizations and the general public, but there is little theoretically based research on what makes some online communities more successful than others. In this article, we apply theory from the field of social psychology to understand how online communities develop member attachment, an important dimension of community success. We implemented and empirically tested two sets of community features for building member attachment by strengthening either group identity or interpersonal bonds. To increase identity-based attachment, we gave members information about group activities and intergroup competition, and tools for group-level communication. To increase bond-based attachment, we gave members information about the activities of individual members and interpersonal similarity, and tools for interpersonal communication. Results from a six-month field experiment show that participants' visit frequency and self-reported attachment increased in both conditions. Community features intended to foster identity-based attachment had stronger effects than features intended to foster bond-based attachment. Participants in the identity condition with access to group profiles and repeated exposure to their group's activities visited their community twice as frequently as participants in other conditions. The new features also had stronger effects on newcomers than on old-timers. This research illustrates how theory from the social science literature can be applied to gain a more systematic understanding of online communities and how theory-inspired features can improve their success. [ABSTRACT FROM AUTHOR]