Abstract
Global supply chains have vulnerabilities, and these escalate in crisis times like pandemics or wars. Digital twinning of supply chains can provide early alerts and timely interventions. We examined three companies in different industries using Digital Twin (DT) technology to improve their supply chain performance. We found that while DT successfully enhanced performance indicators, the dollar and time costs were significant, creating barriers to wider DT adoption. We conclude by outlining the positives and negatives of implementing Digital Twins in global supply chains.
Date Received
September 26, 2024
Date Revised
September 29, 2024
Date Accepted
October 5, 2024
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Yun, Gawon; Hales, Douglas N.; and Hong, Leo
(2024)
"Digital Twinning for Resilient Global Supply chains: Three Case Studies,"
Markets, Globalization & Development Review:
Vol. 9:
No.
1, Article 4.
Available at:
https://digitalcommons.uri.edu/mgdr/vol9/iss1/4
Included in
Anthropology Commons, Economics Commons, Management Information Systems Commons, Marketing Commons, Other Business Commons, Sociology Commons, Urban, Community and Regional Planning Commons
Author Bio
Gawon Yun is Assistant Professor of Logistics and Supply Chain Management at Missouri State University. She earned her Ph.D, with emphasis on Supply Chain Management from the University of Rhode Island. Her research focuses on economic, environmental, and social sustainability in the operations and supply chain context. Her research has appeared in International Journal of Logistics Management, Transportation Journal, and Benchmarking: An International Journal.
Douglas N. Hales is a Professor of Operations & Supply Chain Management and former Associate Dean in the College of Business at the University of Rhode Island. He earned his PhD in 2005 from Clemson University. His research and expertise includes Global Supply Chain Management, Sustainability, Lean Six Sigma and Digital Twins. He has published in European Journal of Operational Research, International Journal of Production Economics, International Journal of Production Research, Journal of Business Research, and Transportation Journal, among others.
Leo Hong, Ph,D,, is an Assistant Professor of Management at Millersville University of Pennsylvania. He specializes in teaching operations management, data analytics, and business statistics. His scholarly focus includes blockchain, machine learning, and supply chain management.