Article(id=1322240047739416700, tenantId=1146029695717560320, journalId=1146120045056339983, issueId=1322239982887096469, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1002-980X.J26031701, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1773676800000, receivedDateStr=2026-03-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793176193413, onlineDateStr=2026-10-28, pubDate=1787587200000, pubDateStr=2026-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793176193413, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793176193413, creator=13701087609, updateTime=1793176193413, updator=13701087609, issue=Issue{id=1322239982887096469, tenantId=1146029695717560320, journalId=1146120045056339983, year='2026', volume='45', issue='8', pageStart='1', pageEnd='149', issueExtLink='null', onlineDate='null', pubDate='1787587200000', pubDateStr='2026-08-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793176177951, creator='13701087609', updateTime=1793176177951, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=1, endPage=14, ext={EN=ArticleExt(id=1322240047953326205, articleId=1322240047739416700, tenantId=1146029695717560320, journalId=1146120045056339983, language=EN, title=How Can Artificial Intelligence Policy Enable Corporate Sustainable Development Performance?Evidence from the National New Generation Artificial Intelligence Innovation and Development Pilot Zones, columnId=1322239948326023513, journalTitle=Journal of Technology Economics, columnName=Financial and Accounting Issues in the AI Era: Perspectives from History, Institutions and Openness, runingTitle=null, highlight=null, articleAbstract=

As the new round of scientific and technological revolution advances in tandem with the green and low-carbon transition, how to leverage industrial intelligence policies to simultaneously improve economic performance and environmental performance has become a critical issue for the long-term high-quality sustainable development of enterprises. Based on data from Chinese A-share listed companies from 2013 to 2024, and treating the National New Generation Artificial Intelligence Innovation and Development Pilot Zones as a quasi-natural experiment, a multi-period difference-in-differences method was employed to examine the impact of artificial intelligence policies on corporate sustainable development performance. The findings indicate that artificial intelligence policies significantly enhance corporate sustainable development performance. Mechanism tests show that artificial intelligence policies promote corporate sustainable development performance through two channels: stimulating corporate green innovation and optimizing capital allocation efficiency. Human capital positively moderates the enabling effect of artificial intelligence policies on corporate sustainable development performance. Heterogeneity analyses reveal that the enhancing effect of artificial intelligence policies on corporate sustainable development performance is more pronounced in high-tech industries, non-heavily polluting industries, and regions with low environmental regulatory intensity. Further analyses indicate that artificial intelligence policies generate spillover effects, which contribute to the improvement of sustainable development performance among other firms within the same industry and the same city. These conclusions not only elucidate the micro-mechanisms through which artificial intelligence policies enhance corporate sustainable development performance, but also provide policy implications for optimizing the strategic layout of artificial intelligence and promoting high-quality development.

, authors=Zhengwei Ma^{1, 2}, Jinming Mo¹, authorsList=Zhengwei Ma, Jinming Mo, authorCompany=null, correspAuthors=Jinming Mo, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322240048213373054, articleId=1322240047739416700, tenantId=1146029695717560320, journalId=1146120045056339983, language=CN, title=人工智能政策何以赋能企业可持续发展绩效？——来自国家新一代人工智能创新发展试验区的证据, columnId=1322239948514767195, journalTitle=技术经济, columnName=AI时代的金融与会计问题研究：历史、制度与开放的视角, runingTitle=null, highlight=null, articleAbstract=

随着新一轮科技革命与绿色低碳转型深度推进，如何依托产业智能化政策协同提升经济效益与环境表现，已成为企业长期高质量可持续发展的重要命题。基于2013—2024年中国A股上市公司数据，以国家新一代人工智能创新发展试验区为准自然实验，采用多期双重差分法探讨人工智能政策对企业可持续发展绩效的影响。研究发现，人工智能政策提升了企业可持续发展绩效。机制检验表明，人工智能政策通过推动绿色创新、优化资本配置效率提升企业可持续发展绩效。人力资本水平正向调节人工智能政策对企业可持续发展绩效的赋能效应。异质性分析发现，在高科技行业、非重污染行业、低环境规制强度地区，人工智能政策提升企业可持续发展绩效的效应更为突出。拓展性分析发现，人工智能政策存在溢出效应，能够带动同行业、同城市内其他企业提升可持续发展绩效。研究结论不仅揭示了人工智能政策提升企业可持续发展绩效的微观机制，而且为优化人工智能战略布局、推动企业高质量发展提供了政策启示。

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^2.School of Economics and Management, China University of Petroleum-Beijing, Beijing 102249, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1322240054349639819, tenantId=1146029695717560320, journalId=1146120045056339983, articleId=1322240047739416700, authorId=1322240052638363783, language=CN, stringName=马郑玮, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=^1．中国石油大学（北京）克拉玛依校区工商管理学院，克拉玛依 834000
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马郑玮（1980—），博士，中国石油大学（北京）克拉玛依校区工商管理学院副院长，中国石油大学（北京）经济管理学院教授，博士研究生导师，研究方向：公司金融；

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马郑玮（1980—），博士，中国石油大学（北京）克拉玛依校区工商管理学院副院长，中国石油大学（北京）经济管理学院教授，博士研究生导师，研究方向：公司金融；

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