What kind of research network configurations lead to high academic productivity for young management scholars?—A fuzzy-set qualitative comparative analysis (fsQCA)

The existing body of research predominantly focuses on distinguished scholars, while early-career scholars, as an emerging force in academia, warrant comparable attention. However, current studies on young scholars are limited to their academic performance across three dimensions—research productivity, collaborative networks, and social media engagement—leaving a gap in multidimensional investigations. This study centers on early-career scholars in the management field in China, adopting a research network perspective and employing a mixed-method approach integrating Necessary Condition Analysis and Qualitative Comparative Analysis to explore the configurational effects of network characteristics on academic productivity. The findings reveal that network scale and network strength constitute necessary conditions for enhancing academic productivity. Through configurational analysis, six distinct research network configurations associated with high academic productivity were identified. Breaking the constraints of single-variable analyses, this research highlights that early-career scholars can optimize combinations of network elements to construct personalized research networks, thereby offering diverse pathways for academic innovation. The data analysis further underscores that, in the information age, young scholars should prioritize structural design of academic networks and strategies for resource integration to maximize their scholarly impact.