Artificial Intelligence Adoption and Corporate ESG Performance

被引:0
作者
Tian, Haowen [1 ,2 ]
Wang, Junkai [3 ]
Cai, Yue [4 ]
机构
[1] Northwestern Polytech Univ, Sch Management, Xian, Peoples R China
[2] Northwestern Polytech Univ, Shenzhen Res Inst, Shenzhen, Peoples R China
[3] Sichuan Univ, Business Sch, Chengdu, Peoples R China
[4] Australian Natl Univ, Res Sch Accounting, Canberra, ACT, Australia
关键词
artificial intelligence; corporate innovation; ESG performance; financing constraints; information transparency; SOCIAL-RESPONSIBILITY; FIRM VALUE; INVESTMENT;
D O I
10.1002/bse.70032
中图分类号
F [经济];
学科分类号
02 ;
摘要
Based on the annual report of Chinese listed companies, we use machine learning methods to generate an artificial intelligence (AI) dictionary, and then construct firm-level AI measurements. Our empirical findings suggest that the use of AI by companies can significantly improve their environmental, social, and governance (ESG) performance by alleviating the financing constraints, improving information transparency, and improving corporate innovation. Further, our heterogeneity analysis shows that the impact of the use of AI on firms' ESG performance is more pronounced in regions with highly developed factor markets, in asset-intensive industries, and in industries characterized by high levels of competition. This paper contributes to the existing research on corporate ESG performance and provides a theoretical foundation for companies to advance the development and application of AI technology.
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页数:24
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共 83 条
[41]   Availability and reliability of information transmission for supply chain coordination with demand information sharing [J].
Huang, Yeu-Shiang ;
Ho, Jyh-Wen ;
Kao, Wei-Yu .
COMPUTERS & INDUSTRIAL ENGINEERING, 2022, 172
[42]   The Causal Effect of Corporate Governance on Corporate Social Responsibility [J].
Jo, Hoje ;
Harjoto, Maretno A. .
JOURNAL OF BUSINESS ETHICS, 2012, 106 (01) :53-72
[43]   The link between green innovations, corporate performance, ESG activities, and sharing economy [J].
Khan, Umair ;
Liu, Weili .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (32) :78763-78775
[44]   Recent applications of AI to environmental disciplines: A review [J].
Konya, Aniko ;
Nematzadeh, Peyman .
SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 906
[45]  
Kumar S., 2023, Academy of Marketing Studies Journal, V27, P1
[46]   Digital finance and enterprise financing constraints: Structural characteristics and mechanism identification [J].
Li, Chengming ;
Wang, Yilin ;
Zhou, Zhihan ;
Wang, Zeyu ;
Mardani, Abbas .
JOURNAL OF BUSINESS RESEARCH, 2023, 165
[47]   Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies [J].
Li, Chengming ;
Xu, Yang ;
Zheng, Hao ;
Wang, Zeyu ;
Han, Haiting ;
Zeng, Liangen .
RESOURCES POLICY, 2023, 81
[48]   Artificial intelligence and corporate ESG performance [J].
Li, Junjun ;
Wu, Tong ;
Hu, Boqiang ;
Pan, Dongliang ;
Zhou, Yaqiong .
INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 2025, 102
[49]   Impact of AI adoption on ESG performance: Evidence from Chinese firms [J].
Li, Shuangyan ;
Younas, Muhammad Waleed ;
Maqsood, Umer Sahil ;
Zahid, R. M. Ammar .
ENERGY & ENVIRONMENT, 2024,
[50]   Textual Analysis in Accounting and Finance: A Survey [J].
Loughran, Tim ;
Mcdonald, Bill .
JOURNAL OF ACCOUNTING RESEARCH, 2016, 54 (04) :1187-1230