Knowledge sharing in networked communities of practice: Computational network analysis of organizing dynamics in online crowdsourcing communities

This study examines the knowledge-sharing dynamics of crowdsourcing challenge communities (CCCs), conceptualized as possessing the hybrid features of both communities of practice (CoPs) and networks of practice (NoPs). A systematic review on CoPs and NoPs points toward the rarity of longitudinal network analysis within the area and the risks of overlooking the impact of external groups of the communities. Addressing these gaps, this research identifies several different types of reciprocity patterns in the communities using longitudinal network analyses (i.e., relational event modeling). Results suggest CCCs are competitive and temporary challenge communities. Idea innovators contribute until they receive communication ties from others. Their contribution is also dominated by direct reciprocity (which means favor is being directly returned to the original sender), reflecting the potentially self-interested culture of the communities. Visitors, temporary participants who do not directly compete in the challenges but share comments, were found to have a significant impact on encouraging the knowledge-exchange norms of the community members. Managers’ impact was also significant in improving knowledge sharing. In practice, the management of online CCCs should be aware that networked communities of practice are still egocentric, and community-oriented norms are largely lacking, which is nurturing because support is often conditional and self-serving and may risk the loss of community members over time. This paper contributes to the practice community (i.e., CoP and NoP) literature by recognizing the hybridity of CCCs. This paper also contributes to the synthesis and development of network reciprocity and the evolution of knowledge sharing networks. • Proposes Networked Communities of Practice framework via systematic literature review • Longitudinal network analysis shows self-interested knowledge exchange patterns. • Analyzes visitors’ and managers’ impact on knowledge contribution • Provides practical guidance for managing innovation challenge communities