转化(遗传学)
人工智能
计算机科学
能量(信号处理)
算法
机器学习
数学
生物
生物化学
统计
基因
作者
Meiying Huang,Quan Li,Bowen Li
标识
DOI:10.1016/j.eap.2025.02.029
摘要
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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