The AI-sustainability Nexus: How does intelligent transformation affect corporate green innovation?

IF 9.8 1区 经济学 Q1 BUSINESS, FINANCE International Review of Financial Analysis Pub Date : 2025-06-01 Epub Date: 2025-03-12 DOI:10.1016/j.irfa.2025.104107
Chongchong Xu , Boqiang Lin
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Abstract

The deep integration of the digital economy and sustainable development has emerged as a critical theme in the current socio-economic transformation. However, existing research lacks a comprehensive exploration of how enterprise intelligent transformation empowers green innovation. This study employs intelligent manufacturing demonstration projects as a quasi-experiment, utilizing a staggered difference-in-differences model to examine the impact of enterprise intelligent transformation on green innovation. We analyze data from Chinese manufacturing A-share listed companies from 2011 to 2022. The findings reveal that: (1) Intelligent transformation significantly enhances both the quantity and quality of corporate green innovation. (2) This effect is realized through channels such as attracting on-site investigations by institutional investors, increasing media attention, improving internal control quality, and promoting human capital upgrading. (3) Heterogeneity analysis indicates that intelligent transformation exerts a more pronounced influence on green innovation in large-scale firms, high-tech industry firms, and firms located in regions with stringent environmental regulations. Based on these findings, we propose targeted recommendations for refining policies on enterprise intelligent transformation and green innovation.
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人工智能与可持续发展的关系:智能转型如何影响企业绿色创新?
数字经济与可持续发展的深度融合已成为当前社会经济转型的重要主题。然而,现有研究缺乏对企业智能转型如何促进绿色创新的全面探索。本研究以智能制造示范项目为准实验,采用交错差中差模型考察企业智能化转型对绿色创新的影响。我们分析了2011年至2022年中国制造业a股上市公司的数据。研究结果表明:(1)智能化转型显著提高了企业绿色创新的数量和质量。(2)通过吸引机构投资者现场调研、增加媒体关注度、提高内部控制质量、促进人力资本升级等渠道实现。(3)异质性分析表明,智能转型对大型企业、高技术产业企业和环境规制较严地区企业绿色创新的影响更为显著。在此基础上,提出了完善企业智能化转型和绿色创新政策的针对性建议。
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来源期刊
CiteScore
10.30
自引率
9.80%
发文量
366
期刊介绍: The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.
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