Abstract
Amid the deepening implementation of the "dual carbon" strategy, elucidating the multidimensional dynamics of industry-university-research (IUR) collaborative green innovation on regional carbon emissions holds critical significance for reconciling environmental governance with economic development. Leveraging panel data from 30 Chinese provinces (2010-2022), this study employs parametric and non-parametric approaches to decode the nonlinear impact of IUR collaborative green innovation on carbon emissions. Through moderated mediation models and spatial lag analysis, it systematically reveals operational mechanisms. Key findings include: (1) An inverted U-shaped relationship emerges-initial collaboration phases may elevate emissions, but sustained efforts progressively manifest emission reduction effects. (2) Technological substitution drives low-carbon transitions in polluting industries. While restructuring triggers transient carbon pulse peaks from cost surges, long-term trajectories follow inverted U-shaped patterns moderated by industrial composition and structural upgrading. (3) Initial U-shaped suppression effects stem from resource misallocation and adaptation costs, yet enhanced technological absorptive capacity elevates green total factor productivity (GTFP), enabling a 9.57% emission reduction through industrial transformation. (4) Spatiotemporal interactions evolve from short-term U-shaped spatial spillovers to long-term inverted U-shaped synergies, necessitating optimized policy coordination for dynamic emission reduction dividends. (5) Regional heterogeneity persists-eastern China demonstrates stable impacts through industrial maturity, contrasting with volatile central/western regions constrained by fragmented innovation ecosystems. This research advances understanding of collaborative innovation's nonlinear carbon governance effects, offering actionable insights for regionalized decarbonization strategies and cross-regional innovation alliances.