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

Shaofeng Wang and Hao Zhang

International Journal of Production Research, 2025, vol. 63, issue 18, 6732-6757

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

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2025.2485318 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:63:y:2025:i:18:p:6732-6757

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2025.2485318

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().