Department of Management


Date of this Version



Published in International Journal of Production Economics 114:2 (August 2008), pp. 646-655; Special Section on Logistics Management in Fashion Retail Supply Chains; doi 10.1016/j.ijpe.2008.02.013 Copyright © 2008 Elsevier B.V. Used by permission.


This paper considers three types of risk evaluation models within supply chains: chance constrained programming (CCP), data envelopment analysis (DEA), and multi-objective programming (MOP) models. Various risks are modeled in the form of probability and simulation of specific probability distribution in risk-embedded attributes is conducted in these three types of risk evaluation models. We model a supply chain consisting of three levels and use simulated data with representative distributions. Results from three models as well as simulation models are compared and analysis is conducted. The results show that the proposed approach allows decision makers to perform trade-off analysis among expected costs, quality acceptance levels, and on-time delivery distributions. It also provides alternative tools to evaluate and improve supplier selection decisions in an uncertain supply chain environment.