An Interactive Decision Support Method for Measuring Risk in a Complex Supply Chain under Uncertainty

Content Provider	IEEE Xplore Digital Library
Author	Zhang, A.N. Goh, Mark Terhorst, M. Lee, A.J.L. Pham, M.T.
Copyright Year	2013
Description	Supply chains are becoming more vulnerable because of harsher and more frequent natural and man-made disasters. Supply chain disruptions now seem to occur more frequently and with more serious consequences. During and after supply chain disruptions, companies may lose revenue and incur high recovery costs. Therefore, if supply chain managers were able to better measure and manage supply chain vulnerability, they might be able to reduce the number of disruptions and their impacts. However, how to measure such risk is still an emerging topic for both research and practice. This paper presents a new interactive decision support method for measuring such risk using Value at Risk (VaR) and Conditional Value at Risk (CVaR). The proposed method, based on a disruption recovery model consisting of abrupt, linear and exponential modes, aims to help supply chain managers conduct "what-if" analyses, in order to tackle such vulnerability and other risk factors that would affect their business continuity.
Starting Page	633
Ending Page	638
File Size	849257
Page Count	6
File Format	PDF
ISBN	9781479906529
DOI	10.1109/SMC.2013.113
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-13
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	risk based decision support Supply chain risk management supply chain risk measurement
Content Type	Text
Resource Type	Article