The innovation effects of science and technology finance spatial networks: Evidence from China

Amid the accelerating convergence of the knowledge economy and technological advancement, science and technology finance spatial correlation networks (STFN) have emerged as transformative drivers of innovation resource allocation and collaboration. This study leverages provincial-level relational data from China (2012–2021) to construct STFN. It employs exploratory spatiotemporal data analysis methods to uncover the spatial distribution and dynamic evolution of science and technology finance (STF) and its networks. Network centralities are extracted to quantify structural characteristics, and a Tobit model is applied to examine their impact on urban innovation systematically. The findings reveal that China’s STFN have progressively transcended spatial barriers, fostering a synergistic and networked development pattern. More importantly, this study identifies that the key mechanism driving urban innovation within STFN lies in their ability to enhance urban capacity to capture and share the value embedded in innovation resources. We define this phenomenon as the “innovation resource value effects” of STFN. In addition, the innovation effects of network structures present obvious heterogeneous characteristics in terms of financial agglomeration density, regional absorptive capacity, and digital economy maturity, which may lead to regional innovation unbalanced development. These findings underscore the need for policymakers to prioritize the refinement of STFN as a strategic conduit for unlocking innovation resource value effects, strengthening urban network hubs, and fostering urban innovation balanced development.