| Title | Evaluating the mechanism of AI contribution to decarbonization for sustainable manufacturing in China |
|---|---|
| ID_Doc | 77429 |
| Authors | Wang, J; Wen, YM; Long, H |
| Title | Evaluating the mechanism of AI contribution to decarbonization for sustainable manufacturing in China |
| Year | 2024 |
| Published | |
| Abstract | While existing theories investigate the relationship between digital technologies and environmental, social responsibility, and governance (ESG) performance, this study formulates a distinct theoretical framework aimed at understanding of the role played by specific artificial intelligence (AI)-based technologies for decarbonization in the manufacturing processes. Drawing upon data sampled from 2607 manufacturing firms listed in Chinese stock markets spanning the years 2004-2020, this study employs an ordinary least squares regression model to investigate the mechanism in question. The findings demonstrate that AI applications facilitate carbon reduction through innovations in terms of production, technology, and management in manufacturing processes, particularly in large-scale enterprises, profitability, and state-owned entities. AI applications integrated into manufacturing processes contribute to ESG performance, especially in terms of environmental (E) considerations and governance (G). This contribution is manifested via improvements in total factor productivity, technological innovation, and information disclosure. Notably, the contributions are more pronounced in less-polluting firms and those located in the underdeveloped western regions of China than in their counterparts. These findings not only enhance the theoretical underpinnings of the ESG framework but also offer practical insights that can serve as a valuable reference for policymakers and governing bodies overseeing manufacturing economies. |
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