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Extracting Maximum Value from Consumer Returns: Allocating Between Remarketing and Refurbishing for Warranty Claims

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  • Çerağ Pinçe

    (Kühne Logistics University, 20457 Hamburg, Germany)

  • Mark Ferguson

    (Moore School of Business, University of South Carolina, Columbia, South Carolina 29208)

  • Beril Toktay

    (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 31200)

Abstract

The high cost of lenient return policies force consumer electronics original equipment manufacturers (OEMs) to look for ways to recover value from lightly used consumer returns, which constitute a substantial fraction of sales and cannot be resold as new products. Refurbishing to remarket or to fulfill warranty claims are the two common disposition options considered to unlock the value in consumer returns, which present the OEM with a challenging problem: How should an OEM dynamically allocate consumer returns between fulfilling warranty claims and remarketing refurbished products over the product’s life cycle? We analyze this dynamic allocation problem and find that when warranty claims and consumer returns are jointly taken into account, the remarketing option is generally dominated by the option of refurbishing and earmarking consumer returns to fulfill warranty claims. Over the product’s life cycle, the OEM should strategically emphasize earmarking of consumer returns at the early stages of the life cycle to build up earmarked inventory for the future warranty demand, whereas it should consider remarketing at the later stages of the life cycle after enough earmarked inventory is accumulated or most of the warranty demand uncertainty is resolved. These findings show that, for product categories with significant warranty coverage and refund costs, remarketing may not be the most profitable disposition option even if the product has strong remarketing potential and the OEM has the pricing leverage to tap into this market. We also show that the optimal dynamic disposition policy is a price-dependent base-stock policy where the earmarked quantity is capacitated by the new and refurbished product sales quantities. We compare with the myopic policy and show that it is a good heuristic for the optimal dynamic disposition policy.

Suggested Citation

  • Çerağ Pinçe & Mark Ferguson & Beril Toktay, 2016. "Extracting Maximum Value from Consumer Returns: Allocating Between Remarketing and Refurbishing for Warranty Claims," Manufacturing & Service Operations Management, INFORMS, vol. 18(4), pages 475-492, October.
  • Handle: RePEc:inm:ormsom:v:18:y:2016:i:4:p:475-492
    DOI: 10.1287/msom.2016.0584
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    17. Cui, Hailong & Rajagopalan, Sampath & Ward, Amy R., 2020. "Predicting product return volume using machine learning methods," European Journal of Operational Research, Elsevier, vol. 281(3), pages 612-627.

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