The effects of perceived network characteristics on knowledge exchange in virtual communities

Understanding virtual community (VC) networks is essential because the characteristics of these networks play a fundamental role in knowledge exchange. This survey-based study proposes two network-related antecedents: perceived closeness with VC members (PCL) and perceived connectedness with VC members (PCN). Using a structural equation modeling approach, we examined the two antecedents' associations with the knowledge-exchange drivers that, in turn, are related to two endogenous variables: intention to acquire knowledge and intention to share knowledge. The results of our bootstrapping mediation tests suggest that the perceived network characteristics indirectly influence members' knowledge-exchange intentions through mediators such as identification, knowledge self-efficacy, reputation, and shared vision. We conclude that PCN can positively influence the four mediators and is a key network characteristic that facilitates knowledge exchange in virtual spaces. By studying the antecedents of users' intentions to share and acquire knowledge, this research provides a holistic view of information exchange on VCs. © 2023 Decision Sciences Institute.