Policy-driven assessment and dynamic optimization of the resilience of returns in the green R&D industry: Empirical study from China

Against the dual backdrop of intensifying global technological innovation competition and the deepening of China's innovation-driven development strategy, the resilience of returns in the green R&D industry has emerged as a core indicator for evaluating national innovation capability and sustainable development. This study draws on panel data from Chinese green R&D projects between 2018 and 2023, encompassing both the pre- and post-policy phases of pilot incentive implementation. The geographic detector, fuzzy-set qualitative comparative analysis (fsQCA), and multiple linear regression models are employed to explore the dynamic evolution and underlying mechanisms of resilience under policy intervention. The findings reveal that: (1) transformations in the policy environment reconfigure the synergistic relationships among regional economies, corporate operations, and ecological governance, significantly altering the intensity and interaction patterns of key influencing factors; (2) the fsQCA identifies two typical configurational pathways: a fiscal–ecological dual-drive model in the pre-policy phase and an economic–technological collaboration model in the post-policy phase, revealing distinct path dependencies in the resilience enhancement process across different stages of development; (3) resilience is primarily driven by regional economic collaboration and firms' R&D capacity, moderated by an inverted U-shaped effect of environmental governance intensity, with R&D investment requiring adjustment to regional conditions. The theoretical framework of policy-driven factor synergy and resilience response developed in this study provides interdisciplinary methodological guidance for optimizing innovation ecosystems and offers valuable theoretical and practical implications for resilience governance.