ArticleCarbon balance and management2025
How does industry-university-research collaborative green innovation affect regional carbon emissions? -nonlinear effects and multi-mechanism analysis.
Article in Carbon balance and management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Urban-scale and urban cluster-scale: how population agglomeration shapes carbon emission intensity.Carbon balance and management · 2026Article
- Carbon mitigation effect of service trade innovation: quasi-experimental evidence from China.Carbon balance and management · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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