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

  • Linlin Zhang
  • Zhong YaoEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 184)


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.


Dual-channel supply chain Risk-averse Mean-variance Pricing decision 



This paper is supported by the Natural Science Foundation of China (71071006; 71271012;71332003).


  1. 1.
    Chiang, W.Y.K., Chhajed, D., Hess, J.D.: Direct marketing, indirect profits: a strategic analysis of dual-channel supply chain design. Manage. Sci. 49, 1–20 (2003)CrossRefzbMATHGoogle Scholar
  2. 2.
  3. 3.
    Lau, H.S., Lau, A.H.L.: Manufacturer’s pricing strategy and returns policy for a single-period commodity. Eur. J. Oper. Res. 116, 291–304 (1999)CrossRefzbMATHGoogle Scholar
  4. 4.
    Gan, X.H., Sethi, S.P., Yan, H.M.: Coordination of supply chains with risk-averse agents. Prod. Oper. Manage. 13, 135–149 (2004)CrossRefGoogle Scholar
  5. 5.
    Choi, T.M., Li, D., Yan, H.M., Chiu, C.H.: Channel coordination in supply chains with agents having mean-variance objectives. Omega: Int. J. Manage. Sci. 36, 565–576 (2008)CrossRefGoogle Scholar
  6. 6.
    Choi, T.M., Chow, P.Z.: Mean-variance analysis of quick response program. Int. J. Prod. Econ. 114, 456–475 (2008)CrossRefGoogle Scholar
  7. 7.
    Chen, X., Sim, X., Simchi-Levi, D., Sun, P.: Risk aversion in inventory management. Oper. Res. 55, 828–842 (2007)CrossRefzbMATHGoogle Scholar
  8. 8.
    Chen, Y.F., Xu, M.H., Zhang, Z.: Technical note: a risk-averse newsvendor model under CVaR criterion. Oper. Res. 57, 1040–1044 (2009)CrossRefzbMATHGoogle Scholar
  9. 9.
    Wu, M., Zhu, S.X., Teunter, R.H.: The Risk-averse Newsvendor problem with random capacity. Eur. J. Oper. Res. 231, 328–336 (2013)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Chiu, C.H., Choi, T.M.: Supply chain risk analysis with mean-variance models: a technical review. Annals of Operations Research, published on line (2013) Google Scholar
  11. 11.
    Hess, J., Mayhew, G.: Modeling merchandise returns in direct marketing. J. Direct Mark. 11, 20–35 (1997)CrossRefGoogle Scholar
  12. 12.
    Anderson, E.T., Hansen, K., Simester, D., Wang L.K.: How are demand and returns related? Theory and empirical evidence. Working paper, Kellogg School of Management, Northwestern University (2006)Google Scholar
  13. 13.
    Mostard, J., Teunter, R.: The newsboy problem with resalable returns: a single period model and case study. Eur. J. Oper. Res. 169, 81–96 (2006)CrossRefzbMATHMathSciNetGoogle Scholar
  14. 14.
    Chen, J., Bell, P.C.: The impact of customer returns on pricing and order decision. Eur. J. Oper. Res. 195, 280–295 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
  15. 15.
    Ghoreishi, M., Arshsadi khamseh A., Mirzazadeh, A.: Joint optimal pricing and inventory control for deteriorating items under inflation and customer returns. J. Ind. Eng. (2013, in press)Google Scholar
  16. 16.
    Audimoolam S., Dutta R.: Decision Support System for Supply Chain Management. United States Patent, Pub. No.: US 2005/0209732 A1 (2005)Google Scholar
  17. 17.
    Biswas, S., Narahari, Y.: Object oriented modeling and decision support for supply chains. Eur. J. Oper. Res. 153, 704–726 (2004)CrossRefzbMATHGoogle Scholar
  18. 18.
    Blackhursta, J., Wu, T., Grady, P.O.: PCDM: a decision support modeling methodology for supply chain, product and process design decisions. J. Oper. Manage. 23, 325–343 (2005)CrossRefGoogle Scholar
  19. 19.
    Sarkis, J.: A strategic decision framework for green supply chain management. J. Clean. Prod. 11, 397–409 (2003)CrossRefGoogle Scholar
  20. 20.
    Ingene, C., Parry, M.: Bilateral monopoly, identical competitors/distributors and game-theoretic analyses of distribution channels. J. Acad. Mark. Sci. 35, 586–602 (2007)CrossRefGoogle Scholar
  21. 21.
    Petruzzi, N.C., Dada, M.: Pricing and the newsvendor problem: a review with extensions. Oper. Res. 47, 183–194 (1999)CrossRefzbMATHGoogle Scholar
  22. 22.
    Lau, H.S.: The newsboy problem under alternative optimization objectives. J. Oper. Res. Soc. 31, 525–535 (1980)CrossRefzbMATHMathSciNetGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of Economics and ManagementBeiHang UniversityBeijingChina

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