School of Politics and Public Administration, Qingdao U., China
Previous network research has focused on studying scientists’ network embeddedness and knowledge creation at the individual level, but ignored the impact of network embeddedness variance among scientists within a team. In this study, we examine how network variance of scientific team contributes to knowledge creation from a network embeddedness perspective. Specifically, we explore how team relational embeddedness variance and team structural embeddedness variance influence team knowledge creation. Furthermore, team average relational embeddedness and team average structural embeddedness serve as moderators. We conduct empirical tests, using a negative binomial regression model and several robustness tests, on bibliographic data from scientific articles in the field of new energy vehicles. The data was provided by Web of Science Core Collection and covered the period from 2008 to 2020. We find that both team relational embeddedness variance and team structural embeddedness variance have inverted U-shaped impacts on team knowledge creation. The results also provide original evidence on an overlooked phenomenon: team average relational embeddedness and team average structural embeddedness moderate the effect of team relational embeddedness variance and team structural embeddedness variance on knowledge creation, respectively. Overall, these findings suggest important implications for understanding the relationship between network variance of scientific team and knowledge creation.