管理评论

管理评论 ›› 2025, Vol. 37 ›› Issue (11): 206-218.

• • 上一篇    

人工智能如何影响企业颠覆性绿色创新——基于知识重组的视角

周源1, 代兴良1, 许冠南2   

  1. 1. 清华大学公共管理学院, 北京 100084;
    2. 北京邮电大学经济管理学院, 北京 100876
  • 收稿日期:2024-08-20 发布日期:2025-12-17
  • 作者简介:周源，清华大学公共管理学院副教授，博士生导师，博士；代兴良，清华大学公共管理学院博士研究生；许冠南（通讯作者），北京邮电大学经济管理学院教授，博士生导师，博士。
  • 基金资助:
    国家自然科学基金面上项目（72272017；71974107；L2424237；L2224059）；国家社会科学基金重点项目（22AZD125）；国家社会科学基金重大专项；中国工程院院士科技咨询紧急重点项目(2024-JZ-17)。

How Artificial Intelligence Affects Corporate Disruptive Green Innovation: A Knowledge Recombination Perspective

Zhou Yuan1, Dai Xingliang1, Xu Guannan2   

  1. 1. School of Public Management, Tsinghua University, Beijing 100084;
    2. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876
  • Received:2024-08-20 Published:2025-12-17

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摘要： 颠覆性绿色创新是实现碳中和目标的关键，而人工智能（AI）作为一种重要的赋能技术，如何影响颠覆性绿色创新，仍有待探究。为此，本文引入知识重组视角，构建AI技术促进企业颠覆性绿色创新的作用机制模型，并采用2007—2019年中国A股制造业上市公司的数据进行实证检验。为提高指标测度的准确性，本文利用机器学习模型BERT对公司年报文本进行深入分析来构建企业AI技术采用指标，并使用基于专利引用网络的CD指数来衡量颠覆性绿色创新水平。研究结果表明，AI技术可以显著促进企业颠覆性绿色创新，其效应主要通过增加知识搜索宽度和知识搜索深度两条路径实现。异质性分析表明，AI技术对颠覆性绿色创新的促进效应在数字基础设施水平更高、环境规制强度更弱地区的企业，以及研发补贴力度更高的企业中更为显著。本文从微观企业层面深化了AI对颠覆性绿色创新作用机制的理解，为推动企业智能化绿色化协同发展提供了经验证据。

关键词: 人工智能, 颠覆性绿色创新, 知识重组, 机器学习

Abstract: Disruptive green innovation (DGI) is essential for achieving carbon neutrality goals; however, its development is constrained by the dual challenges of externalities and substantial knowledge burdens. Artificial Intelligence (AI), with its potential to act as an “invention of a method of invention,” raises important yet underexplored questions concerning whether and how it influences firms’ DGI. Drawing on the knowledge recombination perspective, this study develops a theoretical framework to elucidate the mechanisms through which AI technologies can facilitate DGI at the firm level. To empirically validate this framework, we utilize panel data from China’s A-share listed manufacturing firms spanning 2007 to 2019. To improve measurement accuracy, we employ the BERT machine learning model to analyze corporate annual reports and construct firm-level AI adoption indicators, while the disruptiveness of green innovation is measured using the CD index derived from patent citation networks. The results reveal that AI significantly promotes DGI, primarily through dual pathways of expanding knowledge search breadth and deepening knowledge search depth. Heterogeneity analysis demonstrates that AI’s positive effects on DGI are more pronounced in regions with advanced digital infrastructure, weaker environmental regulation intensity, and firms receiving higher R&D subsidies. This study deepens the understanding of AI’s role in driving DGI at the micro-enterprise level, providing empirical evidence and theoretical insights for fostering synergistic development of intelligent and green transformation in corporations.

Key words: artificial intelligence, disruptive green innovation, knowledge recombination, machine learning