管理评论 ›› 2026, Vol. 38 ›› Issue (9): 130-143.

• 创新与创业管理 • 上一篇    

TOE框架下企业持续绿色创新研究——基于可解释性机器学习算法

麻翼凡, 陈怀超, 马靖, 范建红   

  1. 太原理工大学经济与管理学院, 太原 030024
  • 收稿日期:2024-09-19 发布日期:2026-10-09
  • 作者简介:麻翼凡(通讯作者),太原理工大学经济与管理学院博士研究生;陈怀超,太原理工大学经济与管理学院教授,博士生导师,博士;马靖,太原理工大学经济与管理学院博士研究生;范建红,太原理工大学经济与管理学院副教授,博士生导师,博士。
  • 基金资助:
    国家社会科学基金一般项目(20BGL049)。

Research on Sustainable Green Innovation of Enterprises under TOE Framework -Based on Interpretable Machine Learning Algorithm

Ma Yifan, Chen Huaichao, Ma Jing, Fan Jianhong   

  1. College of Economics and Management, Taiyuan University of Technology, Taiyuan 030024
  • Received:2024-09-19 Published:2026-10-09

摘要: 随着可持续发展的深入,企业持续绿色创新已成为实现经济增长与环境保护双赢的关键手段。本文依据TOE框架采用可解释性机器学习模型全面考察企业持续绿色创新驱动因素的重要度及作用效果。研究结果表明,所建立的梯度提升树在探究企业持续绿色创新的驱动因素方面具有较高的预测精度和稳健性;技术层面的工业机器人应用和研发强度,组织层面的沉淀性冗余资源、非沉淀性冗余资源和企业规模,以及环境层面的ESG评级,是企业持续绿色创新的关键驱动因素,且与企业持续绿色创新之间存在非线性的正相关关系;工业机器人应用、研发强度、沉淀性冗余资源和企业规模之间存在正向交互效应,能够助力企业进行持续绿色创新。本文明晰了企业持续绿色创新的驱动因素,丰富了企业持续绿色创新的相关研究,为企业持续绿色创新决策提供了理论指导。

关键词: 持续绿色创新, TOE框架, 可解释性机器学习

Abstract: With the deepening of sustainable development, sustainable green innovation of enterprises has become a key means to realize the win-win situation of economic growth and environmental protection. Based on the TOE framework, this paper uses interpretable machine learning models to comprehensively examine the importance and effect of the driving factors of sustainable green innovation of enterprises. The research results are as follows: The established gradient boosting tree has high prediction accuracy and robustness in exploring the driving factors of sustainable green innovation of enterprises; industrial robot application and R&D intensity at the technology level, absorbed slack resources, unabsorbed slack resources, and enterprise size at the organizational level, and ESG ratings at the environmental level are the key drivers of sustainable green innovation of enterprises, and there is a non-linear relationship with sustainable green innovation of enterprises; there are positive interaction effects among industrial robot application, R&D intensity, absorbed slack resources and enterprise size, which can promote sustainable green innovation of enterprises. This paper clarifies the driving factors of sustainable green innovation of enterprises, enriches the related research on sustainable green innovation of enterprises, and provides theoretical guidance for enterprises to make decisions on sustainable green innovation.

Key words: sustainable green innovation, TOE framework, interpretable machine learning