Multi-network embeddedness and innovation quality: A panel data analysis based on fsQCA

Abstract

Organizations’ embeddedness in networks pertaining to collaboration and knowledge exerts a significant impact on their innovation. This study utilizes patent data from the field of 5 G (the fifth generation of cellular network technology) to examine the effects of organizations’ network embeddedness characteristics—specifically, collaboration breadth and depth, knowledge breadth and depth, and combination breadth and depth—on innovation quality. Furthermore, we utilize panel data fsQCA to explore paths (i.e., configurations of the six specified conditions) that can lead to high innovation quality. The analysis yields four sustainable configurations, which can be categorized as either a collaboration-knowledge dual-driven strategy (with collaboration breadth, collaboration depth, and combination depth as core conditions) or a deep knowledge-driven strategy (with knowledge depth and combination depth as core conditions). These findings provide a comprehensive understanding of the mechanisms influencing innovation quality within the framework of multi-network embeddedness.