管理评论 ›› 2025, Vol. 37 ›› Issue (7): 115-126.

• 创新与创业管理 • 上一篇    下一篇

数字化能否赋能绿色工艺创新?

郑航, 叶阿忠   

  1. 福州大学经济与管理学院, 福州 350116
  • 收稿日期:2023-02-13 发布日期:2025-07-30
  • 作者简介:郑航,福州大学经济与管理学院博士研究生;叶阿忠,福州大学经济与管理学院教授,博士生导师,博士。
  • 基金资助:
    国家自然科学基金面上项目(72073030)。

Can Digitalization Empower Green Process Innovation

Zheng Hang, Ye Azhong   

  1. School of Economics and Management, Fuzhou University, Fuzhou 350116
  • Received:2023-02-13 Published:2025-07-30

摘要: 以2010—2020年我国A股制造业上市企业作为研究样本,探究企业数字化赋能绿色工艺创新的微观效应。为更好地缓解内生性问题,本文在传统因果识别模型的基础上引入机器学习技术,将机器学习的思维方式与经济学的经典方法融合,进而提高因果推断的准确性。研究表明:制造业企业数字化水平的提升对于绿色工艺创新具有积极的驱动作用,且在经过内生性和稳健性检验后这一作用仍然显著。同时,数字化赋能绿色工艺创新的影响效应在企业生命周期、所有制和网络中心性差异下表现出一定的异质性。具体而言,数字化赋能绿色工艺创新的影响效应在国有企业、成长期企业和处于网络中心的企业更为显著。上述分析扩展了植根于自然资源基础观的研究范畴,为理解绿色创新过程中存在的潜在决策动机和驱动机制提供了新的微观解释。

关键词: 绿色工艺创新, 数字化, 机器学习, 因果推断

Abstract: Taking China’s A-share manufacturing listed companies in 2010-2020 as research samples, this paper explores the micro-effect of enterprise digitalization enabling green process innovation. In order to better alleviate the endogenous problem, this paper introduces machine learning technology on the basis of the traditional causal identification model, and integrates the thinking mode of machine learning with the classical methods of economics, so as to improve the accuracy of causal inference. The research shows that the improvement of digital level of manufacturing enterprises has a positive driving effect on green process innovation, and this effect is still significant after a series of endogenous and robust tests. In the meantime, the influence effect of digitalization empowering green process innovation shows certain heterogeneity under the differences of enterprise life cycle, ownership and network centrality. Specifically, the impact of digitalization empowering green process innovation is more significant for state-owned enterprises, growth-stage enterprises, and enterprises in the center of the network. The above analysis expands the research scope rooted in the natural resource-based view and provides a new micro-explanation for understanding the potential decision-making motivation and driving mechanism in the process of green innovation.

Key words: green process innovation, digitalization, machine learning, causal inference