Decision Making for a Risk-Averse Dual-Channel Supply Chain with Customer Returns

Abstract

An optimal mathematic model is presented in consideration of customers' returns in a dual-channel supply chain consisting of a risk-averse manufacturer and a risk-averse retailer under the stochastic market requirement which supports the decision-making process for participants. Closed-form decisions are achieved in the centralized scenario. In the decentralized scenario, mean-variance analysis is used to conduct risk analysis. This study also delves into the influence of the degree of risk aversion, demand fluctuation and return rates on optimal decisions with the help of sensitivity analysis and numerical experimentation. Sensitivity analysis also indicates that the optimal solutions are robust. The model is a real expansion of the model library in the decision support system for dual-channel supply chains. © Springer International Publishing Switzerland 2014.