The spillover effect serves as the basis of regional collaborative innovation. Existing research on innovation spillover focuses on the overall impact of a region's innovation factors on local and other regions' innovation activities. However, re-spillover may occur since the flow of innovation factors between any two regions may influence the innovation in third-party regions. This study quantifies labor flow, capital flow, and institutional learning between regions in China using a gravity model and a social network analysis model, and then applies a spatial econometric model to investigate innovation spillover and re-spillover. The results show that re-spillover can better explain levels of regional innovation. Capital, government support, labour flow, capital flow, and institutional learning have a positive spillover effect on local innovation, while labour flow also has positive spillover effects to other regions.
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