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.
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Notes
- 1.
VaR: Abbreviation for value at risk, which is a widely used risk measure of the risk of loss for a specific portfolio of financial assets in financial mathematics and financial risk management. CVaR: Abbreviation for conditional value at risk, also called Expected Shortfall (ES), which is an alternative to VaR that is more sensitive to the shape of the loss distribution in the tail of the distribution. ——Wikipedia. Both of them are also now used in supply chain risk management.
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This paper is supported by the Natural Science Foundation of China (71071006; 71271012;71332003).
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Zhang, L., Yao, Z. (2014). Decision Making for a Risk-Averse Dual-Channel Supply Chain with Customer Returns. In: Dargam, F., et al. Decision Support Systems III - Impact of Decision Support Systems for Global Environments. EWG-DSS EWG-DSS 2013 2013. Lecture Notes in Business Information Processing, vol 184. Springer, Cham. https://doi.org/10.1007/978-3-319-11364-7_11
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