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

IF 8.7 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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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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从算法到绿色增长:人工智能能否推动企业能源转型?
随着全球优先事项转向可持续性和减缓气候变化,人工智能(AI)作为新兴技术力量对企业能源转型(EET)的影响仍未得到充分探索。本研究将“智能制造试点政策”作为准自然实验,采用2007 - 2022年a股上市公司数据,运用标准的异中差模型检验人工智能对企业绩效的影响。研究结果显示,人工智能的采用显著提高了EET,在国有企业、东部和沿海地区的企业以及数字化转型先进的企业中,效果更为明显。确定了四个关键机制:促进绿色技术创新、优化人力资本结构、改善环境信息披露和减少融资约束。总的来说,这项研究为人工智能的经济影响提供了新的见解,并提供了一个可持续、节能发展的框架,可应用于具有类似经济结构和发展轨迹的国家。
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来源期刊
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.
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