Artificial intelligence and green transformation of manufacturing enterprises

IF 7.5 1区经济学 Q1 BUSINESS, FINANCE

International Review of Financial Analysis Pub Date : 2025-05-10 DOI:10.1016/j.irfa.2025.104330

Chaobo Zhou , Haikuo Zhang , Jinhuika Ying , Shouchao He , Chong Zhang , Jiale Yan

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引用次数: 0

Abstract

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.

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人工智能与制造企业绿色转型

人工智能的快速发展和广泛应用对经济和社会产生了深远的影响。但是，我们需要确保人工智能技术的使用能够为企业的绿色转型（GT）注入活力。本研究基于2013年至2022年中国制造业上市公司的面板数据，以中国新一代人工智能创新发展试验区的建立为准自然实验，在制造业领域提出了这个问题。采用多周期差分模型，我们发现人工智能的采用显著促进了制造企业的GT。当通过广义随机森林（GRF）模型进行验证时，这一结论仍然是稳健的。机制检验表明，企业环境、社会和治理绩效的改善以及信息透明度的提高是人工智能对GT产生积极影响的关键驱动因素。此外，媒体关注度和具有研发背景的高管进一步增强了人工智能对GT的促进作用。利用GRF模型进行异质性分析，发现托宾Q、企业年龄和治疗效果之间存在倒u型关系。因此，我们揭示了人工智能对GT影响的潜在机制，并为政策制定者积极审慎地推进人工智能发展提供了见解，支持数字经济和实体经济的融合。

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来源期刊

International Review of Financial Analysis BUSINESS, FINANCE-

CiteScore

10.30

自引率

9.80%

发文量

366

期刊介绍： The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.