From algorithms to green growth: Can artificial intelligence drive enterprise energy transformation?

IF 7.9 2区经济学 Q1 ECONOMICS

Economic Analysis and Policy Pub Date : 2025-02-21 DOI:10.1016/j.eap.2025.02.029

Meiying Huang, Quan Li, Bowen Li

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引用次数: 0

Abstract

As global priorities shift towards sustainability and climate change mitigation, the impact of artificial intelligence (AI) as an emerging technological force on enterprise energy transformation (EET) remains insufficiently explored. This study treats the “Smart Manufacturing Pilot Policy” as a quasi-natural experiment, uses data from A-share listed companies between 2007 and 2022, and applies the standard Difference-in-Differences model to examine the impact of AI on EET. The findings reveal that AI adoption significantly enhances EET, with more pronounced effects observed in state-owned enterprises, firms in eastern and coastal regions, and those with advanced digital transformation. Four key mechanisms are identified: fostering green technology innovation, enhancing human capital structure, improving environmental information disclosure, and reducing financing constraints. Overall, this study provides novel insights into the economic impact of AI and offers a framework for sustainable, energy-efficient development that can be applied to countries with similar economic structures and development trajectories.

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来源期刊

Economic Analysis and Policy ECONOMICS-

CiteScore

9.80

自引率

9.20%

发文量

231

审稿时长

93 days

期刊介绍： Economic Analysis and Policy (established 1970) publishes articles from all branches of economics with a particular focus on research, theoretical and applied, which has strong policy relevance. The journal also publishes survey articles and empirical replications on key policy issues. Authors are expected to highlight the main insights in a non-technical introduction and in the conclusion.