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Optimal Design of Return Policies

Author

Listed:
  • Thanh Tran

    (University of Central Oklahoma, Edmond, Oklahoma 73034)

  • Haresh Gurnani

    (Center for Retail Innovation, School of Business, Wake Forest University, Winston Salem, North Carolina 27106)

  • Ramarao Desiraju

    (University of Central Florida, Orlando, Florida 32816)

Abstract

Quota-based and partial-refund return policies abound in practice between manufacturers and their resellers. While the literature has provided insights into the design of the partial-refund policy, little attention has been directed at the design of the quota-based return policy. Accordingly, this paper explores the relative preference of a quota-based policy vis-à-vis a partial-refund policy. We do this, first, in the context of risk-neutral channel partners to identify the strategic decisions of each party and the effect of demand uncertainty on the variation of their respective profits. Our results reveal that the manufacturer faces higher profit variation (between the different demand realizations) under the quota policy. The variance in profits for the reseller is, however, higher under the partial-refund policy. We explain the source of profit variations by comparing it across different channel structures (centralized and decentralized). Next, we formally extend the model to include a disutility associated with profit variation and show that when the manufacturer has a variation-induced disutility, the partial-refund contract should be used, as it is the dominating contract. Similarly, when the retailer has a variation-induced disutility, the quota contract should be used. This is consistent with the pattern of profit variations in the risk-neutral case where the manufacturer has lower variation with the partial-refund contract while the reseller has lower variation with the quota contract. Finally, our analysis also shows how the manufacturer may employ a combination policy to better manage its own profit variation while providing adequate overstocking protection for the reseller.

Suggested Citation

  • Thanh Tran & Haresh Gurnani & Ramarao Desiraju, 2018. "Optimal Design of Return Policies," Marketing Science, INFORMS, vol. 37(4), pages 649-667, August.
  • Handle: RePEc:inm:ormksc:v:37:y:2018:i:4:p:649-667
    DOI: 10.1287/mksc.2018.1094
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    References listed on IDEAS

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    6. Chen, Hao-Wei, 2023. "Improving supply quality through the store-initiated returns in wholesale supply chains," International Journal of Production Economics, Elsevier, vol. 261(C).
    7. Priya, Bhawna & Biswas, Indranil & Agrawal, Anupam, 2023. "The over-ordering problem in trade credit: Role of return policies," European Journal of Operational Research, Elsevier, vol. 309(2), pages 731-744.
    8. Li, Ting & He, Shuguang & Zhao, Xiujie, 2022. "Optimal warranty policy design for deteriorating products with random failure threshold," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    9. Shouqiang Wang & Haresh Gurnani & Upender Subramanian, 2021. "The Informational Role of Buyback Contracts," Management Science, INFORMS, vol. 67(1), pages 279-296, January.
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    11. Jian Liu & Xinyue Sun & Yanyan Liu, 2022. "Products pricing and return strategies for the dual channel retailers," Operational Research, Springer, vol. 22(4), pages 3841-3867, September.

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