UNDERSTANDING KNOWLEDGE-SHARING BEHAVIOR IN VIRTUAL COMMUNITIES: THE ROLE OF TRUST, REPUTATION, AND RECIPROCITY

Abstract

This paper uses an agent-based model (ABM) to model a variety of participants with various preferences and tolerance for reputational signals. Knowledge sharing in virtual communities becomes more and more essential due to organizations that operate in the digital world through cooperation and innovation processes. Reputation and reciprocity have been commonly acknowledged as important mechanisms that may be at play to foster continued participation in community activities, but how these two operate together for achieving community outcomes has not yet been fully understood (Wasko & Faraj, 2005; Zhang & Wang, 2021). The goal is to see how reputation impacts exchanges driven by reciprocity and the aggregate outcomes that affect the spread of knowledge in communities (Resnick et al., 2000; Fiore et al., 2010). In simulation experiments, we adjusted the reputation weighting, reciprocity threshold and community diversity to account for various dynamics. Results show that the reputation enhances reciprocity, leading to more extended knowledge contribution when they are concerned about reputational rewards (Chen et al., 2018). From the other direction, reciprocity minimizes free-riding inclination, which is more pronounced in heterogeneous environments. In general, hybrid arrangements that employ the reputational mechanism and reciprocity are most conducive to the development of resilient and active VKMs (Ma & Agarwal, 2007). This study adds by presenting a computational model for the understanding of cooperative behaviors in digital communities and offers practical advice on how to design engagement strategies in online platforms.

Keywords: Knowledge-sharing, virtual communities, agent-based modeling, reputation, reciprocity, knowledge diffusion, collaboration