Abstract
Based on empirical analysis of 113 climate disasters affecting 3563 listed firms across 31 provinces in China from 2010 to 2022, as documented in the Emergency Events Database (EM-DAT), this study employs event study and multiple regression to explore the impact of proactive green innovation on firm climate resilience. By categorizing proactive green innovation into process and product innovation and climate resilience into short-term and long-term resilience, a proactive green innovation-firm climate resilience 2 × 2 matrix is constructed to provide innovative insights. This study reveals that proactive green innovation enhances firm climate resilience. Specifically, proactive green process innovation both enhances short-term and long-term climate resilience, while proactive green product innovation only enhances long-term rather than short-term climate resilience. Furthermore, climate disaster has inverted U-shaped interaction effect on the relationship between proactive green innovation and short-term climate resilience and U-shaped interaction effect on the relationship between proactive green innovation and long-term climate resilience. Additionally, this study also investigates the heterogeneous mechanisms of proactive green innovation enhancing short-term and long-term climate resilience based on network embeddedness theory and legitimacy theory.
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This work was supported by the Young Fund of National Social Science Foundation of China (Grant numbers: 19CGL023).
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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Xinyi Gao and Cheng Liu. The first draft of the manuscript was written by Xinyi Gao. Writing—reviewing and editing were performed by Siyuan Dong and Hanying Wang. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Gao, X., Dong, S., Liu, C. et al. Proactive green innovation and firm climate resilience: the nonlinear interaction effect of climate risk. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-33576-4
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DOI: https://doi.org/10.1007/s11356-024-33576-4