Zhang, A. N., Wagner, S. M., Goh, M., & Asian, S. (2021). Quantifying supply chain disruption: a recovery time equivalent value at risk approach. International Journal of Logistics Research and Applications, 27(5), 667–687. https://doi.org/10.1080/13675567.2021.1990872
Abstract:
The global pandemic COVID-19 has disrupted many supply chains across numerous industries the world over. If not well contained and managed at an early stage, such unprecedented disruptions may lead to even more serious consequences in an era of supply chain re-globalization. The attendant challenge for research and practice is on how to readily measure and quantify the disruption risk. To address the plethora of concerns, this article presents a recovery time equivalent (RTE) disruption risk measurement model using Value at Risk (VaR). We consider a disruption recovery model comprising abrupt, normal, fast, and slow modes. To demonstrate the practical relevance of our study, we establish a case study with a multinational corporation from the IT sector. Decision makers and supply chain managers can use the model to conduct “what-if” analyses on their supply chain vulnerabilities and risks for a more proactive business continuity planning and contingency management.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the A*STAR - Logistics and Supply Chain Programme (TSRP)
Grant Reference no. : 1224204048
Social Research Platform Grant from La Trobe University, Australia.
Description:
This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Logistics Research and Applications on 25 October 2021, available online: http://www.tandfonline.com/doi.org/10.1080/13675567.2021.1990872