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204人工智能技术与ESG理念的融合推动企业以透明和数据驱动的方式满足利益相关者多样化需求。文章结合利益相关者理论和成本收入分析方法构建了一个多期动态博弈模型，从而系统地分析了人工智能技术与企业ESG表现的关系。文章基于2011—2021年A股上市公司人工智能专利数据与ESG新闻数据，实证检验了人工智能技术对企业ESG表现的影响，并且进一步讨论了媒体ESG舆情在此过程中的作用。文章研究发现：人工智能技术能够显著改善企业ESG表现，并且该积极效应在较大规模、非重污染行业与较高数字经济发展水平地区的企业中更为明显。机制分析表明，人工智能技术主要通过促进企业ESG投资和提升企业的信息透明度两条渠道来影响其ESG表现。基于媒体ESG舆情的分析表明，ESG“新闻情绪”在人工智能技术提升企业ESG表现的过程中发挥了显著的调节作用。文章的结论为帮助新一代人工智能推动企业高质量发展提供了有益的参考。
人工智能技术能提高企业ESG表现吗？——基于动态博弈的成本收入分析
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3 陈彦斌,林晨,陈小亮. 人工智能、老龄化与经济增长[J]. 经济研究,2019,(7):47−63.
10 戚聿东,肖旭. 数字经济时代的企业管理变革[J]. 管理世界,2020,(6):135−152.
16 王永钦,董雯. 机器人的兴起如何影响中国劳动力市场?——来自制造业上市公司的证据[J]. 经济研究,2020,(10):159−175.
17 王禹,王浩宇,薛爽. 税制绿色化与企业ESG表现——基于《环境保护税法》的准自然实验[J]. 财经研究,2022,(9):47−62.
18 谢红军,吕雪. 负责任的国际投资:ESG与中国OFDI[J]. 经济研究,2022,(3):83−99.
19 姚加权,张锟澎,郭李鹏,等. 人工智能如何提升企业生产效率?——基于劳动力技能结构调整的视角[J]. 管理世界,2024,(2):101−116. DOI:10.3969/j.issn.1002-5502.2024.02.006
20 于蔚,汪淼军,金祥荣. 政治关联和融资约束:信息效应与资源效应[J]. 经济研究,2012,(9):125−139.
21 张琦,郑瑶,孔东民. 地区环境治理压力、高管经历与企业环保投资——一项基于《环境空气质量标准(2012)》的准自然实验[J]. 经济研究,2019,(6):183−198.
22 张宗新,吴钊颖. 媒体情绪传染与分析师乐观偏差——基于机器学习文本分析方法的经验证据[J]. 管理世界,2021,(1):170−185. DOI:10.3969/j.issn.1002-5502.2021.01.011
23 赵涛,张智,梁上坤. 数字经济、创业活跃度与高质量发展——来自中国城市的经验证据[J]. 管理世界,2020,(10):65−75. DOI:10.3969/j.issn.1002-5502.2020.10.006
24 郑建东,吕晓亮,吕斌,等. 社交媒体平台信息交互与资本市场定价效率——基于股吧论坛亿级大数据的证据[J]. 数量经济技术经济研究,2022,(11):91−112.
25 Acemoglu D,Restrepo P. Robots and jobs:Evidence from US labor markets[J]. Journal of Political Economy,2020,128(6):2188−2244. DOI:10.1086/705716
26 Asif M,Searcy C,Castka P. ESG and Industry 5.0:The role of technologies in enhancing ESG disclosure[J]. Technological Forecasting and Social Change,2023,195:122806. DOI:10.1016/j.techfore.2023.122806
27 Azar J,Duro M,Kadach I,et al. The big three and corporate carbon emissions around the world[J]. Journal of Financial Economics,2021,142(2):674−696. DOI:10.1016/j.jfineco.2021.05.007
28 Babina T,Fedyk A,He A,et al. Artificial intelligence,firm growth,and product innovation[J]. Journal of Financial Economics,2024,151:103745. DOI:10.1016/j.jfineco.2023.103745
29 Bosse D,Thompson S,Ekman P. In consilium apparatus:Artificial intelligence,stakeholder reciprocity,and firm performance[J]. Journal of Business Research,2023,155:113402. DOI:10.1016/j.jbusres.2022.113402
30 Chen P Y,Chu Z Z,Zhao M. The Road to corporate sustainability:The importance of artificial intelligence[J]. Technology in Society,2024,76:102440. DOI:10.1016/j.techsoc.2023.102440
31 Chen Z F,Xie G X. ESG disclosure and financial performance:Moderating role of ESG investors[J]. International Review of Financial Analysis,2022,83:102291. DOI:10.1016/j.irfa.2022.102291
32 Chowdhury S,Budhwar P,Dey P K,et al. AI-employee collaboration and business performance:Integrating knowledge-based view,socio-technical systems and organisational socialisation framework[J]. Journal of Business Research,2022,144:31−49. DOI:10.1016/j.jbusres.2022.01.069
33 DasGupta R. Financial performance shortfall,ESG controversies,and ESG performance:Evidence from firms around the world[J]. Finance Research Letters,2022,46:102487. DOI:10.1016/j.frl.2021.102487
34 Deng X,Li W H,Ren X H. More sustainable,more productive:Evidence from ESG ratings and total factor productivity among listed Chinese firms[J]. Finance Research Letters,2023,51:103439. DOI:10.1016/j.frl.2022.103439
35 Drempetic S,Klein C,Zwergel B. The influence of firm size on the ESG score:Corporate sustainability ratings under review[J]. Journal of Business Ethics,2020,167(2):333−360. DOI:10.1007/s10551-019-04164-1
36 Fang M Y,Nie H H,Shen X Y. Can enterprise digitization improve ESG performance?[J]. Economic Modelling,2023,118:106101. DOI:10.1016/j.econmod.2022.106101
37 Freudenreich B,Lüdeke-Freund F,Schaltegger S. A stakeholder theory perspective on business models:Value creation for sustainability[J]. Journal of Business Ethics,2020,166(1):3−18. DOI:10.1007/s10551-019-04112-z
38 Kaginalkar A,Kumar S,Gargava P,et al. Review of urban computing in air quality management as smart city service:An integrated IoT,AI,and cloud technology perspective[J]. Urban Climate,2021,39:100972. DOI:10.1016/j.uclim.2021.100972
39 Liu J C,Xiong X,Gao Y,et al. The impact of institutional investors on ESG:Evidence from China[J]. Accounting & Finance,2023,63(S2):2801−2826.
40 Stahl B C,Andreou A,Brey P,et al. Artificial intelligence for human flourishing–Beyond principles for machine learning[J]. Journal of Business Research,2021,124:374−388. DOI:10.1016/j.jbusres.2020.11.030
41 Vinuesa R,Azizpour H,Leite I,et al. The role of artificial intelligence in achieving the Sustainable Development Goals[J]. Nature Communications,2020,11(1):233. DOI:10.1038/s41467-019-14108-y
42 Wang L,Yang H Y. Digital technology innovation and corporate ESG performance:Evidence from China[J]. Economic Change and Restructuring,2024,57(6):207. DOI:10.1007/s10644-024-09791-x
43 Yin Z H,Zeng W P. The effects of industrial intelligence on China's energy intensity:The role of technology absorptive capacity[J]. Technological Forecasting and Social Change,2023,191:122506. DOI:10.1016/j.techfore.2023.122506
44 Zhu Y J,Wu Z Y,Zhang H,et al. Media sentiment,institutional investors and probability of stock price crash:Evidence from Chinese stock markets[J]. Accounting & Finance,2017,57(5):1635−1670.
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唐秋雨, 谭伟杰, 申明浩, 等. 人工智能技术能提高企业ESG表现吗？——基于动态博弈的成本收入分析[J]. 财经研究, 2025, 51(2): 94-108.
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