Artificial intelligence and green transformation of manufacturing enterprises
The rapid development and widespread application of artificial intelligence (AI) has had a profound impact on the economy and society. However, we need to be sure that the use of AI technology can inject vitality into the green transformation (GT) of enterprises . Based on panel data from Chinese listed manufacturing companies spanning 2013 to 2022, this study asks the question in the manufacturing sector , using the establishment of China's new-generation AI innovation and development pilot zones as a quasi-natural experiment. Employing a multiperiod difference-in-differences model, we find that AI adoption significantly promotes GT in manufacturing enterprises. This conclusion remains robust when validated through a generalized random forest (GRF) model. Mechanism testing shows that improvements in enterprise environmental, social, and governance performance and information transparency serve as key drivers of AI's positive influence on GT. Additionally, media attention and executives with research and development backgrounds further enhance AI's role in promoting GT. Heterogeneity analysis using the GRF model reveals an inverted U-shaped relationship between Tobin's Q , enterprise age, and the treatment effect . As such, we uncover the underlying mechanisms of AI's impact on GT and offer insights for policymakers to actively and prudently advance AI development, supporting the integration of digital and real economies. • Using generalized random forest for causal identification. • Artificial Intelligence (AI) can promote green transformation (GT) of enterprises. • AI can promote GT through enterprise ESG and information transparency. • Media attention can further amplify the role of AI in promoting GT.
Authors
- Jianjun Yan (ORCID: https://orcid.org/0000-0002-1233-1136)
- Shouchao He (ORCID: https://orcid.org/0000-0003-2094-5768)
- Chong Zhang (ORCID: https://orcid.org/0000-0001-6475-3659)
- Haikuo Zhang
- Ji Ying
- Chaobo Zhou (ORCID: https://orcid.org/0000-0001-5066-3003)
Institutions
- Ningbo University (CN)
- Berkeley College (US)
- University of Nottingham Ningbo China (CN)
- Wenzhou University (CN)
- Wenzhou University of Technology
- University of California, Berkeley (US)
Publication Details
- Journal
- International Review of Financial Analysis
- Published
- 2025-05-10
- DOI
- https://doi.org/10.1016/j.irfa.2025.104330
- Citations
- 30
- Primary Topic
- Innovation Policy and R&D
- Type
- article
- Field-Weighted Citation Impact
- 93.93