Artificial intelligence-driven energy technology innovation: Dynamic impact and mechanism exploration

IF 13.6 2区经济学 Q1 ECONOMICS

Energy Economics Pub Date : 2025-05-08 DOI:10.1016/j.eneco.2025.108541

Renbo Shi , Wei Shan , Richard Evans , Qingjin Wang

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引用次数: 0

Abstract

Energy Technology Innovation (ETI) has received considerable attention in recent decades as firms strive to comply with pollution regulations and advance green transformation. This study investigates the dynamic impact of Artificial Intelligence (AI) on firm-level ETI and the mechanisms driving this relationship. The results show that AI positively contributes to ETI, although its effects exhibit a time lag, with the long-term impact being more significant. Specifically, AI exerts a more pronounced positive impact on renewable ETI compared to traditional ETI, guiding firms' innovation towards cleaner energy sources. The promotion of ETI by AI is found to be stronger in heavily polluted industries and geographical regions with greater openness. In addition, mechanism analysis demonstrates that AI primarily promotes ETI through enhanced Research and Development (R&D) activities, factor allocation effects, and increased financial opportunities. Furthermore, these AI-driven advancements in ETI contribute to improved energy efficiency. This study provides valuable guidance for firms seeking to effectively integrate AI into their ETI strategies and holds significant theoretical and practical implications for accelerating energy transformation.

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人工智能驱动的能源技术创新：动态冲击与机制探索

近几十年来，随着企业努力遵守污染法规和推进绿色转型，能源技术创新（ETI）受到了相当大的关注。本研究探讨了人工智能（AI）对企业层面ETI的动态影响以及驱动这种关系的机制。结果表明，人工智能对ETI有正向贡献，但其效应存在时滞，且长期影响更为显著。具体而言，人工智能对可再生ETI的积极影响比传统ETI更明显，引导企业向更清洁的能源创新。研究发现，在污染严重的行业和开放程度较高的地理区域，人工智能对ETI的促进作用更强。此外，机制分析表明，人工智能主要通过增强研发活动、要素配置效应和增加金融机会来促进ETI。此外，这些人工智能驱动的ETI进步有助于提高能源效率。本研究为寻求将人工智能有效整合到其ETI战略中的企业提供了有价值的指导，并对加速能源转型具有重要的理论和实践意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Energy Economics ECONOMICS-

CiteScore

18.60

自引率

12.50%

发文量

524

期刊介绍： Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.