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

Abstract

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

Ma Yifan, Chen Huaichao, Ma Jing, Fan Jianhong. Research on Sustainable Green Innovation of Enterprises under TOE Framework -Based on Interpretable Machine Learning Algorithm[J]. Management Review, 2026, 38(9): 130-143.

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