Title: Have your cake and eat it too: AI adoption on green innovation efficiency and persistence under industry dynamism

Authors: Ximing Yin; Tailun Chen; Jun Jin

Addresses: School of Management, Beijing Institute of Technology, Beijing, 100081, China ' School of Management, Zhejiang University, Hangzhou, 310058, China ' School of Management, Zhejiang University, Hangzhou, 310058, China

Abstract: Under the uncertain environment featured with geopolitical bifurcation and climate change, manufacturing companies are urged to enhance green innovation process performance towards sustainable growth. As a disruptive technology, artificial intelligence (AI) is introducing great potential in empowering manufacturing companies to conduct green innovation. However, the mechanisms and features of this process are still a subject of debate and warrant deeper exploration. Therefore, this study draws from the knowledge-based view and dynamic capability theory to investigate the effects of AI adoption on the efficiency and persistence of green innovation by employing a dataset consisting of 3,047 listed Chinese manufacturing companies from 2017 to 2021. Empirical findings indicate that corporate strategies comprising AI adoption can significantly enhance the efficiency and persistence of green innovation. Moreover, the effect on green innovation efficiency is more pronounced in industries with higher levels of dynamism. Furthermore, we discovered green innovation efficiency of high-tech manufacturing companies and green innovation persistence of low-tech manufacturing companies are benefited more from AI adoption. The results emphasise the importance for manufacturing companies, for both in high-tech and low-tech industries with significant environmental dynamism, to actively employ AI technologies to develop dynamic capabilities essential for achieving sustainable development.

Keywords: artificial intelligence; dynamic capability; green innovation efficiency; green innovation persistence; industry dynamism.

DOI: 10.1504/IJTM.2025.151671

International Journal of Technology Management, 2025 Vol.98 No.2/3/4, pp.298 - 328

Received: 30 Mar 2024
Accepted: 13 Feb 2025
Published online: 13 Feb 2026 *

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