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When to carry eccentric products? Optimal retail assortment under consumer returns


  • Aydm Alptekinoglu
  • Alex Grasas León


To understand whether retailers should consider consumer returns when merchandising, we study how the optimal assortment of a price-taking retailer is influenced by its return policy. The retailer selects its assortment from an exogenous set of horizontally differentiated products. Consumers make purchase and keep/return decisions in nested multinomial logit fashion. Our main finding is that the optimal assortment has a counterintuitive structure for relatively strict return policies: It is optimal to offer a mix of the most popular and most eccentric products when the refund amount is sufficiently low, which can be viewed as a form of risk sharing between the retailer and consumers. In contrast, if the refund is sufficiently high, or when returns are disallowed, optimal assortment is composed of only the most popular products (a common finding in the literature). We provide preliminary empirical evidence for one of the key drivers of our results: more eccentric products have higher probability of return – conditional on purchase. In light of our analytical findings and managerial insights, we conclude that retailers should take their return policies into account when merchandising.

Suggested Citation

  • Aydm Alptekinoglu & Alex Grasas León, 2011. "When to carry eccentric products? Optimal retail assortment under consumer returns," Economics Working Papers 1272, Department of Economics and Business, Universitat Pompeu Fabra, revised Nov 2012.
  • Handle: RePEc:upf:upfgen:1272

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    References listed on IDEAS

    1. Jeffrey D. Shulman & Anne T. Coughlan & R. Canan Savaskan, 2009. "Optimal Restocking Fees and Information Provision in an Integrated Demand-Supply Model of Product Returns," Manufacturing & Service Operations Management, INFORMS, vol. 11(4), pages 577-594, December.
    2. V. Daniel R. Guide , Jr. & Gilvan C. Souza & Luk N. Van Wassenhove & Joseph D. Blackburn, 2006. "Time Value of Commercial Product Returns," Management Science, INFORMS, vol. 52(8), pages 1200-1214, August.
    3. Gérard P. Cachon & A. Gürhan Kök, 2007. "Category Management and Coordination in Retail Assortment Planning in the Presence of Basket Shopping Consumers," Management Science, INFORMS, vol. 53(6), pages 934-951, June.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, March.
    5. A. Gürhan Kök & Yi Xu, 2011. "Optimal and Competitive Assortments with Endogenous Pricing Under Hierarchical Consumer Choice Models," Management Science, INFORMS, vol. 57(9), pages 1546-1563, February.
    6. Dorothée Honhon & Vishal Gaur & Sridhar Seshadri, 2010. "Assortment Planning and Inventory Decisions Under Stockout-Based Substitution," Operations Research, INFORMS, vol. 58(5), pages 1364-1379, October.
    7. Wallace J. Hopp & Xiaowei Xu, 2005. "Product Line Selection and Pricing with Modularity in Design," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 172-187, August.
    8. Sridhar Moorthy & Kannan Srinivasan, 1995. "Signaling Quality with a Money-Back Guarantee: The Role of Transaction Costs," Marketing Science, INFORMS, vol. 14(4), pages 442-466.
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    More about this item


    assortment planning; product variety management; product returns; nested logit;

    JEL classification:

    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce


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