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Leveraging generative artificial intelligence for sustainable business model innovation in production systems

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  • Shaofeng Wang
  • Hao Zhang

Abstract

This study develops an integrated framework, termed the GAI&ABC model, to examine how manufacturing firms can leverage generative artificial intelligence (GAI) to achieve sustainable business model innovation (SBMI) in production systems. While prior research primarily focuses on the technical aspects of AI, we address the challenge of understanding the organisational learning mechanisms that underpin GAI's impact on SBMI. Drawing on the Antecedents-Behaviour-Consequences (ABC) model, we investigate the mediating roles of GAI-powered exploitative and exploratory learning, and consider international entrepreneurship orientation and GAI education as key moderators. Using survey data from 402 manufacturing start-ups in China and employing PLS-SEM analysis, we find that GAI adoption significantly enhances both exploitative learning (β = 0.439, p

Suggested Citation

  • Shaofeng Wang & Hao Zhang, 2025. "Leveraging generative artificial intelligence for sustainable business model innovation in production systems," International Journal of Production Research, Taylor & Francis Journals, vol. 63(18), pages 6732-6757, September.
    • Handle: RePEc:taf:tprsxx:v:63:y:2025:i:18:p:6732-6757
    DOI: 10.1080/00207543.2025.2485318
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