The impact of artificial intelligence on green innovation efficiency: Moderating role of dynamic capability

Fangfang Feng, Junjun Li, Feng Zhang and Jinghuan Sun

International Review of Economics & Finance, 2024, vol. 96, issue PB

Abstract: Environmental concerns have intensified the focus on sustainable innovation, with artificial intelligence (AI) emerging as a potential driver. However, the relationship between AI adoption and green innovation efficiency, particularly in emerging economies, remains unclear. This gap is crucial to address as it could reveal pathways to enhance sustainable development in rapidly growing markets. Here, we investigate how AI impacts green innovation efficiency in Chinese firms and examine the moderating effects of dynamic capabilities. Using panel data from 26,117 firm-year observations of Chinese A-share listed companies (2008–2022), we employ a novel text-based measure of AI adoption and assess green innovation efficiency through patent applications and R&D expenditure. Our findings reveal a significant positive relationship between AI adoption and green innovation efficiency, with dynamic capabilities enhancing this effect. The impact is stronger in non-state-owned and high-tech firms. These results demonstrate AI's potential as a catalyst for sustainable development and highlight the importance of organizational capabilities in realizing these benefits. Our study contributes to the evolving discourse on technology-driven sustainability, providing insights for both theory and practice in leveraging AI for green innovation in diverse economic contexts.

Keywords: Artificial intelligence; Green innovation; Dynamic capability; Absorptive capability; Innovative capability; Adaptive capability (search for similar items in EconPapers)
JEL-codes: M15 O32 O33 Q55 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:96:y:2024:i:pb:s1059056024006415

DOI: 10.1016/j.iref.2024.103649

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