Industry-university-research digital innovation collaboration and AI-driven green innovation: An innovation resource perspective

Artificial intelligence (AI)-driven green innovation has become a central topic in the green transition of contemporary economies. However, extant literature lacks a comprehensive examination of how firms overcome innovation resource constraints when leveraging AI to drive green innovation. Utilizing patent data and financial metrics from Chinese A-share listed firms during 2007–2023, this study probes the identified issue through an empirical lens. Empirical results show that industry-university-research (IUR) digital innovation collaboration significantly enhances firms' AI-driven green innovation, with the supplementation of the firm's innovation resources acting as a crucial channel. The absence of regional incentive-based environmental policies amplifies this positive effect, whereas a lack of incentive-based digital policies and insufficiently stringent mandatory environmental regulations tend to attenuate it. This study broadens the firm-level comprehension of AI-driven green innovation and offers practical implications for firms pursuing technology-driven sustainability. • IUR digital innovation collaboration promotes AI-driven green innovation. • The supplementation of firms' innovation resources is a key mechanism. • Absent environmental incentives amplify IUR digital innovation synergy. • Absent digital incentives attenuate IUR digital innovation synergy. • Weak environmental mandates attenuate IUR digital innovation synergy.

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Publication Details

Journal
International Review of Economics & Finance
Published
2026-04-12
DOI
https://doi.org/10.1016/j.iref.2026.105253
Primary Topic
University-Industry-Government Innovation Models
Type
article
Field-Weighted Citation Impact
0.00

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article

Industry-university-research digital innovation collaboration and AI-driven green innovation: An innovation resource perspective

Jun Shao, Zhen Ju
International Review of Economics & Finance
University-Industry-Government Innovation Models
article

Industry-university-research digital innovation collaboration and AI-driven green innovation: An innovation resource perspective

Jun Shao, Zhen Ju
article en

Abstract

Artificial intelligence (AI)-driven green innovation has become a central topic in the green transition of contemporary economies. However, extant literature lacks a comprehensive examination of how firms overcome innovation resource constraints when leveraging AI to drive green innovation. Utilizing patent data and financial metrics from Chinese A-share listed firms during 2007–2023, this study probes the identified issue through an empirical lens. Empirical results show that industry-university-research (IUR) digital innovation collaboration significantly enhances firms' AI-driven green innovation, with the supplementation of the firm's innovation resources acting as a crucial channel. The absence of regional incentive-based environmental policies amplifies this positive effect, whereas a lack of incentive-based digital policies and insufficiently stringent mandatory environmental regulations tend to attenuate it. This study broadens the firm-level comprehension of AI-driven green innovation and offers practical implications for firms pursuing technology-driven sustainability. • IUR digital innovation collaboration promotes AI-driven green innovation. • The supplementation of firms' innovation resources is a key mechanism. • Absent environmental incentives amplify IUR digital innovation synergy. • Absent digital incentives attenuate IUR digital innovation synergy. • Weak environmental mandates attenuate IUR digital innovation synergy.

International Review of Economics & FinanceVol. 108
Southeast University (CN)
Major Program of National Fund of Philosophy and Social Science of China
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
University-Industry-Government Innovation Models
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