The Impact of Artificial Intelligence on Corporate Environmental Investment

IF 4.6 3区 管理学 Q1 BUSINESS
Junkai Wang;Haowen Tian;Penghao Zheng
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Abstract

As an important driving force for a new round of scientific and technological revolution and industrial transformation, artificial intelligence has great potential in improving corporate investment in environmental protection and promoting economic growth. However, due to data bottlenecks, there is no clear conclusion on how AI impact environmental investment at the enterprise level. Based on the annual report data of Chinese listed companies, we use machine learning methods to generate an artificial intelligence dictionary, and then constructs enterprise-level artificial intelligence indicators. Through empirical research, we find that AI can significantly improve enterprises' environmental investment. After the robustness tests such as the instrumental variable method and the propensity score matching method, the conclusion remains unchanged. Mechanism analysis shows that AI can improve firms' investment in environmental protection by alleviating financing constraints and improving information transparency. Heterogeneity analysis shows that the state-owned attributes, high tax burden and high environmental regulation of enterprises can enhance the correlation between AI and environmental protection investment. Further research finds that the increase in environmental protection investment caused by artificial intelligence can significantly reduce environmental pollution, rather than for the sake of greenwashing behavior. This article not only enriches the relevant research on the impact of corporate environmental protection investment, but also provides a theoretical basis for enterprises to further promote the development of artificial intelligence technology.
人工智能对企业环境投资的影响
人工智能作为新一轮科技革命和产业变革的重要推动力,在提高企业环保投入、促进经济增长方面具有巨大潜力。然而,由于数据瓶颈,人工智能如何影响企业层面的环境投资并没有明确的结论。基于中国上市公司年报数据,利用机器学习方法生成人工智能词典,进而构建企业级人工智能指标。通过实证研究,我们发现人工智能可以显著提高企业的环境投资。经过工具变量法、倾向得分匹配法等稳健性检验,结论保持不变。机制分析表明,人工智能可以通过缓解融资约束和提高信息透明度来提高企业的环保投资。异质性分析表明,企业的国有属性、高税负和高环境监管可以增强人工智能与环保投资的相关性。进一步研究发现,人工智能导致的环保投资的增加可以显著减少环境污染,而不是为了洗绿行为。本文不仅丰富了企业环保投资影响的相关研究,也为企业进一步推动人工智能技术的发展提供了理论依据。
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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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