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Reverse Revenue Sharing Contract versus Two-Part Tariff Contract under a Closed-Loop Supply Chain System

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  • Zunya Shi
  • Nengmin Wang
  • Tao Jia
  • Haoxun Chen

Abstract

The importance of remanufacturing has been recognized in research and practice. The integrated system, combining the forward and reverse activities of supply chains, is called closed-loop supply chain (CLSC) system. By coordination in the CLSC system, players will get economic improvement. This paper studies different coordination performances of two types of contracts, two-part tariff (TTC) and reverse revenue sharing contract (RRSC), in a closed-loop system. Through mathematical analysis based on Stackelberg Game Theory, we find that it is easy for manufacturer to improve more profits and retailer’s collection effects by adjusting the ratio of transfer collection price through RRSC, and we also give the function to calculate the best ratio of transfer collection price, which may be a valuable reference for the decision maker in practice. Besides, our results also suggest that although the profits of the coordinated CLSC system are always higher than the contradictory scenario, the RRSC is more favorable to the manufacturer than to the retailer, as results show that the manufacturer will share more profits from the system through RRSC. Therefore, RRSC has attracted the manufacturers more to closing the supply chain for economic consideration.

Suggested Citation

  • Zunya Shi & Nengmin Wang & Tao Jia & Haoxun Chen, 2016. "Reverse Revenue Sharing Contract versus Two-Part Tariff Contract under a Closed-Loop Supply Chain System," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-15, May.
  • Handle: RePEc:hin:jnlmpe:5464570
    DOI: 10.1155/2016/5464570
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    Cited by:

    1. Ehsan Shekarian & Simme Douwe Flapper, 2021. "Analyzing the Structure of Closed-Loop Supply Chains: A Game Theory Perspective," Sustainability, MDPI, vol. 13(3), pages 1-32, January.
    2. Teymourifar, Aydin & Kaya, Onur & Ozturk, Gurkan, 2021. "Contracting models for pricing and capacity decisions in healthcare systems," Omega, Elsevier, vol. 100(C).

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