拥抱人工智能:智能转型如何影响新能源企业的技术创新?

IF 4.6 3区 管理学 Q1 BUSINESS
Chongchong Xu;Boqiang Lin
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引用次数: 0

摘要

人工智能(AI)技术正在深刻重塑新能源领域,在优化决策、提高运营效率和提高生产力方面显示出巨大潜力。然而,现有文献对人工智能如何促进新能源企业的创新提供了有限的见解。本研究利用2011 - 2022年145家中国a股上市公司的数据,采用交错差分模型研究智能转型对新能源企业技术创新的影响。结果表明:1)智能转型显著推动新能源企业技术创新,数字金融发展和具有信息技术背景高管的存在是正向调节因素;2)吸引政府补贴、提升内控质量、促进人力资本升级是新能源企业智能转型产生创新激励效应的重要渠道;3)智能转型对周边企业的技术创新产生了不利的空间溢出效应,主要是通过对创新资源的虹吸。同一子行业内相邻的新能源企业负外溢效应较强,而市场势力较大的企业受影响较小。这些见解为解决这些动态提供了有针对性的政策建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Embracing Artificial Intelligence: How Does Intelligent Transformation Affect the Technological Innovation of New Energy Enterprises?
Artificial intelligence (AI) technology is profoundly reshaping the new energy sector, demonstrating significant potential in optimizing decision-making, enhancing operational efficiency, and boosting productivity. However, existing literature offers limited insight into how AI facilitates innovation within new energy enterprises. Using data from 145 Chinese A-share listed companies from 2011 to 2022, this study employs a staggered difference-in-differences model to investigate the impact of intelligent transformation on technological innovation in new energy enterprises. The results show that: 1) Intelligent transformation significantly drives technological innovation in new energy enterprises, with digital financial development and the presence of senior executives with information technology backgrounds serving as positive moderating factors; 2) Attracting government subsidies, improving internal control quality, and promoting human capital upgrades serve as critical channels through which intelligent transformation in new energy enterprises generates innovation incentive effects; and 3) Intelligent transformation generates adverse spatial spillover effects on the technological innovation of neighboring enterprises, mainly through the siphoning of innovation resources. Neighboring new energy enterprises within the same subindustry face stronger negative spillovers, while enterprises with greater market power are less affected. These insights inform targeted policy recommendations to address these dynamics.
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来源期刊
IEEE Transactions on Engineering Management
IEEE Transactions on Engineering Management 管理科学-工程:工业
CiteScore
10.30
自引率
19.00%
发文量
604
审稿时长
5.3 months
期刊介绍: Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.
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