Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation

Abstract

This research examines the transformative potential of artificial intelligence (AI) in general and Generative AI (GAI) in particular in supply chain and operations management (SCOM). Through the lens of the resource-based view and based on key AI capabilities such as learning, perception, prediction, interaction, adaptation, and reasoning, we explore how AI and GAI can impact 13 distinct SCOM decision-making areas. These areas include but are not limited to demand forecasting, inventory management, supply chain design, and risk management. With its outcomes, this study provides a comprehensive understanding of AI and GAI's functionality and applications in the SCOM context, offering a practical framework for both practitioners and researchers. The proposed framework systematically identifies where and how AI and GAI can be applied in SCOM, focussing on decision-making enhancement, process optimisation, investment prioritisation, and skills development. Managers can use it as a guidance to evaluate their operational processes and identify areas where AI and GAI can deliver improved efficiency, accuracy, resilience, and overall effectiveness. The research underscores that AI and GAI, with their multifaceted capabilities and applications, open a revolutionary potential and substantial implications for future SCOM practices, innovations, and research.

KEYWORDS:

• Generative artificial intelligence
• GAI
• artificial intelligence
• supply chain
• operations management

Acknowledgements

The first author of this paper wants to dedicate this work to the cherished memory of his Father and Grandfather. Their unwavering support, motivation, and encouragement have been the cornerstone of his perseverance and success. They continue to inspire beyond their time on this earth.

We would also like to express our gratitude to the two anonymous reviewers and the editors of this manuscript. Their insightful and critical comments were instrumental in enhancing the quality of this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available.

Additional information

Notes on contributors

Ilya Jackson

Dr. Ilya Jackson is a Postdoctoral Associate at MIT Center for Transportation & Logistics. He earned his PhD in Civil Engineering and Transportation from the Transport and Telecommunication Institute, where he spent one year as an Assistant Professor shortly after that. The main ideas of his PhD thesis have been summarised in the paper ‘Neuroevolutionary approach to metamodel-based optimisation in production and logistics’, which received the Young Researcher Award in 2020. Dr. Ilya Jackson currently focuses on Machine Learning and AI for Supply Chain Management.

Dmitry Ivanov

Dmitry Ivanov is a professor of supply chain and operations management at Berlin School of Economics and Law. He serves at the school as an Academic director of M.A. Global Supply Chain and Operations Management and B.Sc. International Sustainability Management as well as a Deputy Director of Institute for Logistics. His publication list includes around 400 publications, including over 150 papers in international academic journals and leading textbooks Global Supply Chain and Operations Management and Introduction to Supply Chain Resilience. His main research interests and results span resilience, viability and ripple effect in supply chains, risk analytics, and digital twins. Author of the Viable Supply Chain Model and founder of the ripple effect research in supply chains. Recipient of IISE Transactions Best Paper Award 2021, Best Paper and Most Cited Paper Awards of IJPR (2018,2019, 2020, 2021, 2022), OMEGA Best Paper Award 2022, Clarivate Highly Cited Researcher Award (2021, 2022, 2023). He co-edits IJISM and is an associate editor of the IJPR and OMEGA. He is Chairman of IFAC CC 5 ‘Cyber-Physical Manufacturing Enterprise’.

Alexandre Dolgui

Alexandre Dolgui is an IISE Fellow, Distinguished Professor and the Head of Automation, Production and Computer Sciences Department at the IMT Atlantique, Nantes, France. His research and teaching activities focuse on manufacturing line design, production planning and supply chain optimisation. He is the co-author of 5 books, the co-editor of 32 books or conference proceedings, the author of over 310 refereed papers in international journals. He is the Editor-in-Chief of the International Journal of Production Research, an Area Editor of Computers & Industrial Engineering. Member of Board for 27 international journals, including INternational Journal of Production Economics. Former Associate Editor for IEEE Transactions in Industrial Informatics and Omega. He is an Active Fellow of the European Academy for Industrial Management, Member of the Board of the International Foundation for Production Research, former Chair (Vice-Chair now) of IFAC TC 5.2 Manufacturing Modelling for Management and Control, Member of IFIP WG 5.7 Advances in Production Management Systems, and IEEE System Council Analytics and Risk Technical Committee, he has been Scientific Chair of many leading scientific conferences and received several international awards for his research.

Jafar Namdar

Jafar Namdar is a postdoctoral associate at Massachusetts Institute of Technology (MIT), having earned his Ph.D. in Business Analytics from the Tippie College of Business, University of Iowa. His research focuses on applying business analytics techniques, including Applied Econometrics, Machine Learning (ML), Simulation, and Optimization techniques to address business problems, focussing on supply chain risk management, supply chain digitalisation, policy uncertainty, and political instability. For this purpose, he employs data science tools like web scraping and text analytics to leverage unstructured and distributed data sources, including news, web, conference earning calls, and social media platforms. His work has received interest from professionals and obtained financial support from the corporate and public sectors. Furthermore, he has been invited to participate as a guest speaker at the MIT Industry Liaison Programme (ILP) and several schools to give presentations on supply chain risk management.