Artificial Intelligence and Green Collaborative Innovation: An Empirical Investigation Based on a High-Dimensional Fixed Effects Model

Guanyan Lu () and Bingxiang Li
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Guanyan Lu: School of Economics and Management, Xi’an University of Technology, Xi’an 710054, China
Bingxiang Li: School of Economics and Management, Xi’an University of Technology, Xi’an 710054, China

Sustainability, 2025, vol. 17, issue 9, 1-41

Abstract: This study focuses on the intrinsic mechanisms and sustainable value of artificial intelligence (AI)-driven green collaborative innovation in enterprises amid the global green low-carbon transition, revealing new pathways for digital technology-enabled green development. Based on the data of China’s A-share listed companies jointly applying for green patents with other entities from 2010 to 2023, this study used a high-dimensional fixed effect model to empirically find that artificial intelligence significantly promotes green collaborative innovation. This promoting effect proved more pronounced in the case of high macroeconomic uncertainty, large enterprises and SOEs. A mechanism test revealed that artificial intelligence drives green collaborative innovation primarily by reducing transaction costs and optimizing the labor structure. A moderating effect analysis showed that green investor entry and CEO openness can strengthen the facilitating effect of artificial intelligence on green collaborative innovation. In addition, the facilitating effect of artificial intelligence on green collaborative innovation helps companies reduce carbon emissions and improve ESG performance, driving the transformation of business ecosystems toward environmental sustainability. From a technology–organization–environment co-evolution perspective, this research clarifies the micro-level operational chain of AI-enabled green innovation, providing theoretical support for developing countries to achieve leapfrog low-carbon transitions through digital technologies. Practically, it offers actionable insights for advancing AI-enabled green industries, constructing collaborative green innovation ecosystems, and supporting the realization of the United Nations Sustainable Development Goals (SDGs).

Keywords: artificial intelligence; collaborative innovation; green innovation; transaction costs; labor force structure (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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