Are both generative AI and ChatGPT game changers for 21st-Century operations and supply chain excellence?

Samuel Fosso Wamba, Maciel M. Queiroz, Charbel Jose Chiappetta Jabbour and Shi, Chunming (Victor)

International Journal of Production Economics, 2023, vol. 265, issue C

Abstract: The remarkable growth of ChatGPT, a Generative Artificial Intelligence (Gen-AI), has triggered a significant debate in society. It has the potential to radically transform the business landscape, with consequences for operations and supply chain management (O&SCM). However, empirical evidence on Gen-AI's effects in O&SCM remains limited. This study investigates the benefits, challenges, and trends associated with Gen-AI/ChatGPT in O&SCM. We collected data from O&SCM practitioners in the UK (N = 154) and the USA (N = 161). As we used the organizational learning theory for the research, our findings reveal increased efficiency as a significant benefit for both adopters and non-adopters in both countries, while indicating security, risks, and ethical as prominent concerns. In particular, it appeared that the integration of Gen-AI/ChatGPT leads to the enhancement of the overall supply chain performance. Moreover, organizational learning can speed up the results of Gen-AI/ChatGPT in O&SCM. No wonders that adopters express their satisfaction about the post-implementation benefits of the technology, which include reduced perceived challenges for pre-implementation, and greater optimism about future Gen-AI/ChatGPT utilization compared to non-adopters. Adopters also display diverse behavioral patterns toward efficiency, agility, responsiveness, etc. This study provides valuable insights for scholars, practitioners, and policymakers interested in comprehending Gen-AI/ChatGPT's implications in O&SCM for both adopters and non-adopters. Additionally, it underscores the importance of organizational learning processes in facilitating successful Gen-AI/ChatGPT adoption in O&SCM.

Keywords: ChatGPT; Generative artificial intelligence; Operations and supply chain management; Disruptive technology; Emerging technologies; Organizational learning (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:265:y:2023:i:c:s0925527323002475

DOI: 10.1016/j.ijpe.2023.109015

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