Collaborative innovation network and knowledge transfer performance: A fsQCA approach

Under the context of “open innovation”, scholars increasingly consider collaborative innovation network as an effective framework to enable firms' knowledge transfer. This study examines four factors of collaborative innovation network that affect the level of knowledge transfer performance of firms, viz., network size, network heterogeneity, network tie-strength, and network centrality. Based on a survey to high-tech firms in China, this study uses fuzzy-set Qualitative Comparative Analysis (fsQCA) to explore the relationships between collaborative innovation network and knowledge transfer performance. This study supports the argument that different causal paths explain knowledge transfer performance of firms. The findings reveal that the presence of network size, network tie-strength, and network centrality determines the level of knowledge transfer performance. However, network heterogeneity does not show significant impact on the knowledge transfer performance. The findings also identify theoretical and practical implications of collaborative innovation network and knowledge transfer research.