Journal of Intelligent Manufacturing

, Volume 28, Issue 1, pp 51–64 | Cite as

Research on closed loop supply chain with reference price effect



This paper considers a closed loop supply chain with the manufacturer as the Stackelberg leader. The manufacturer faces three different reverse channels, i.e., (1) manufacturer-managed, (2) retailer-managed, or (3) third party-managed channels. The reference price affects the purchase decision of consumers. Based on game theory, we discuss the reference price effect on the performances across three decentralized reverse channels, and examine the impact of reference price parameter (i.e., reference price coefficient in this paper) on optimal strategies. We conclude that higher reference price coefficient results in lower manufacturer and retailer profits. However, the profit of the third party increases in the reference price coefficient. In addition, some meaningful insights can be derived by comparison without the reference price effect in our models. We found that the scenario without reference price effect is generally superior to that with reference price effect.


Reverse channel Remanufacturing Reference price effect Game theory CLSC 


  1. Atasu, A., Sarvary, M., & Van Wassenhove, L. N. (2008). Remanufacturing as a marketing strategy. Management Science, 54(10), 1731–1746.CrossRefGoogle Scholar
  2. Atasu, A., Toktay, L. B., & Van Wassenhove, L. N. (2013). How collection cost structure drives a manufacturer’s reverse channel choice. Production and Operations Management, 22(5), 1089–1102.Google Scholar
  3. Benchekroun, H., Martín-Herrán, G., & Taboubi, S. (2009). Could myopic pricing be a strategic choice in marketing channels? A game theoretic analysis. Journal of Economic Dynamics and Control, 33(9), 1699–1718.CrossRefGoogle Scholar
  4. Cheng, C. Y., & Prabhu, V. (2013). An approach for research and training in enterprise information system with RFID technology. Journal of Intelligent Manufacturing, 24(3), 527–540.CrossRefGoogle Scholar
  5. Dickson, P. R., & Sawyer, A. G. (1990). The price knowledge and search of supermarket shoppers. The Journal of Marketing, 54(3), 42–53.CrossRefGoogle Scholar
  6. Feng, Y. D. (2010). Caterpillar: Remanufacturing can be self-promotive. Business Watch Magazine, 14(8), 80–81.Google Scholar
  7. Ferguson, M. E., & Toktay, L. B. (2006). The effect of competition on recovery strategies. Production and Operations Management, 15(3), 351–368.CrossRefGoogle Scholar
  8. Ferrer, G., & Swaminathan, J. M. (2006). Managing new and remanufactured products. Management Science, 52(1), 15–26.Google Scholar
  9. Ferrer, G., & Swaminathan, J. M. (2010). Managing new and differentiated remanufactured products. European Journal of Operational Research, 203(2), 370–379.Google Scholar
  10. Fibich, G., Gavious, A., & Lowengart, O. (2003). Explicit solutions of optimization models and differential games with nonsmooth (asymmetric) reference-price effects. Operations Research, 51(5), 721–734.CrossRefGoogle Scholar
  11. Fine, C. H., & Porteus, E. L. (1989). Dynamic process improvement. Operations Research, 37(4), 580–591.CrossRefGoogle Scholar
  12. Fleischmann, M., Beullens, P., Bloemhof-Ruwaard, J. M., & Van Wassenhove, L. N. (2001). The impact of product recovery on logistics network design. Production and Operations Management, 10(2), 156–173.CrossRefGoogle Scholar
  13. Fleischmann, M., Bloemhof-Ruwaard, J. M., Dekker, R., van der Laan, E., Van Nunen, J. A. E. E., & Van Wassenhove, L. N. (1997). Quantitative models for reverse logistics: A review. European Journal of Operational Research, 103(1), 1–17.CrossRefGoogle Scholar
  14. Fleischmann, M., Krikke, H. R., Dekker, R., & Flapper, S. D. P. (2000). A characterization of logistics networks for product recovery. Omega, 28(6), 653–666.CrossRefGoogle Scholar
  15. Greenleaf, P. K., & Winer, R. S. (1996). A dynamic model of reference price and expected quality. Marketing Letters, 7(1), 41–52.CrossRefGoogle Scholar
  16. Guide, V. R. D., Jayaraman, V., Srivastava, R., & Benton, W. C. (2000). Supply chain management for recoverable manufacturing systems. Interfaces, 30(3), 125–142.CrossRefGoogle Scholar
  17. Huang, C. C., Liang, W. Y., Tseng, T. L., & Chen, P. H. (2014). The rough set based approach to generic routing problems: Case of reverse logistics supplier selection. Journal of Intelligent Manufacturing. doi: 10.1007/s10845-014-0913-8.
  18. Huang, M., Song, M., Lee, L. H., & Ching, W. K. (2013). Analysis for strategy of closed-loop supply chain with dual recycling channel. International Journal of Production Economics, 144(2), 510–520.CrossRefGoogle Scholar
  19. Inderfurth, K., de Kok, A. G., & Flapper, S. D. P. (2001). Product recovery in stochastic remanufacturing systems with multiple reuse options. European Journal of Operational Research, 133(1), 130–152. Google Scholar
  20. Jung, K. S., & Hwang, H. (2011). Competition and cooperation in a remanufacturing system with take-back requirement. Journal of Intelligent Manufacturing, 22(3), 427–433.CrossRefGoogle Scholar
  21. Kalwani, M. U., Yim, C. K., Rinne, H. J., & Sugita, Y. A. (1990). Price expectations model of customer brand choice. Journal of Marketing Research, 27(3), 251–262.CrossRefGoogle Scholar
  22. Kopalle, P. K., Rao, A. G., & Assuncao, J. L. (1996). Asymmetric reference price effects and dynamic pricing policies. Marketing Science, 15(1), 60–85.CrossRefGoogle Scholar
  23. Kumar, V. V., Liou, F. W., Balakrishnan, S. N., & Kumar, V. (2013). Economical impact of RFID implementation in remanufacturing: A chaos-based interactive artificial bee colony approach. Journal of Intelligent Manufacturing. doi: 10.1007/s10845-013-0836-9.
  24. Majumder, P., & Groenevelt, H. (2001). Competition in remanufacturing. Production and Operations Management, 10(2), 125–141.CrossRefGoogle Scholar
  25. Naeem, M. A., Dias, D. J., Tibrewal, R., Chang, P. C., & Tiwari, M. K. (2013). Production planning optimization for manufacturing and remanufacturing system in stochastic environment. Journal of Intelligent Manufacturing, 24(4), 717–728.CrossRefGoogle Scholar
  26. Popesu, I., & Wu, Y. (2007). Dynamic pricing strategies with reference price effects. Operations Research, 55(3), 413–429.CrossRefGoogle Scholar
  27. Qiang, Q., Ke, K., Anderson, T., & Dong, J. (2013). The closed-loop supply chain network with competition, distribution channel investment, and uncertainties. Omega, 41(2), 186–194.CrossRefGoogle Scholar
  28. Savaskan, R. C., Bhattacharya, S., & Van Wassenhove, L. N. (2004). Closed-loop supply chain models with product remanufacturing. Management Science, 50(2), 239–252.CrossRefGoogle Scholar
  29. Shi, Y., Nie, J., Qu, T., Chu, L. K., & Sculli, D. (2013). Choosing reverse channels under collection responsibility sharing in a closed-loop supply chain with remanufacturing. Journal of Intelligent Manufacturing,. doi: 10.1007/s10845-013-0797-z.Google Scholar
  30. Souza, G. C. (2013). Closed-loop supply chains. In L. S. Gass & C. M. Fu (Eds.), Encyclopedia of operations research and management science (pp. 169–176). New York: Springer.Google Scholar
  31. Subramanian, P., Ramkumar, N., Narendran, T. T., & Ganesh, K. (2013). PRISM: PRIority based SiMulated annealing for a closed loop supply chain network design problem. Applied Soft Computing, 13(2), 1121–1135.CrossRefGoogle Scholar
  32. Takahashi, K., Doi, Y., Hirotani, D., et al. (2012). An adaptive pull strategy for remanufacturing systems. Journal of Intelligent Manufacturing,. doi: 10.1007/s10845-012-0710-1.Google Scholar
  33. Wang, J. (2006). Lenovo company has used-computer recycling service. (Accessed December 26, 2006).
  34. Xin, W. (2011). ArvinMeritor: The leader of global commercial vehicle parts remanufacturing industry. Automobile & Parts, 30(25), 22.Google Scholar
  35. Zhang, J., Chiang, W. Y. K., & Liang, L. (2014). Strategic pricing with reference effects in a competitive supply chain. Omega, 44, 126–135.CrossRefGoogle Scholar
  36. Zhang, J., Gou, Q., Liang, L., & Huang, Z. (2013). Supply chain coordination through cooperative advertising with reference price effect. Omega, 41(2), 345–353.CrossRefGoogle Scholar
  37. Zhang, Y., Jiang, P., Huang, G., Qu, T., Zhou, G., & Hong, J. (2012). RFID-enabled real-time manufacturing information tracking infrastructure for extended enterprises. Journal of Intelligent Manufacturing, 23(6), 2357–2366.CrossRefGoogle Scholar
  38. Zied, H., Sofiene, D., & Nidhal, R. (2014). Joint optimization of maintenance and production policies with subcontracting and product returns. Journal of Intelligent Manufacturing, 25(3), 589–602.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Management Science and Engineering, School of ManagementZhejiang UniversityHangzhouChina

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