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Customization and Returns

Author

Listed:
  • Gökçe Esenduran

    (Krannert School of Management, Purdue University, West Lafayette, Indiana 47907)

  • Paolo Letizia

    (Stokely Management Center, University of Tennessee, Knoxville, Tennessee 37996)

  • Anton Ovchinnikov

    (Smith School of Business, Queen’s University, Kingston, Ontario K7L 3N6, Canada; INSEAD, Fontainebleau 77300, France)

Abstract

Recent advances in information technology, advanced manufacturing (robotics, 3D printing, etc.), and logistics have allowed firms to customize their products to the specifications of individual consumers, who, in turn, prefer these products to standard ones. In the unlikely event that customized products do not match expectations, however, consumers often feel entitled to a return. Should firms offer returns on customized products? We examine this question via a Stackelberg game model, in which the firm (leader) decides the prices and returns policies for its customized and standard products; consumers (followers) decide which product to buy, given the initial noisy valuations and, upon experiencing the product, whether to return it. Both parties act strategically: Forward-looking consumers incorporate the real option value of possible returns into their initial purchasing decisions, and the firm incorporates consumers’ best purchase and return response into its pricing and returns policy decisions. Our model produces three key insights. First, firms can use customized products to induce some consumers who otherwise would buy and return a standard product to switch to lower-return-rate customized products. Second, it may be optimal to offer returns on customized products, despite their lower salvage value. Third, firms can increase profits and reduce (total) returns by offering returnable customized products.

Suggested Citation

  • Gökçe Esenduran & Paolo Letizia & Anton Ovchinnikov, 2022. "Customization and Returns," Management Science, INFORMS, vol. 68(6), pages 4517-4526, June.
  • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:6:p:4517-4526
    DOI: 10.1287/mnsc.2022.4305
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    References listed on IDEAS

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    1. Dmitri Kuksov & Yuanfang Lin, 2010. "Information Provision in a Vertically Differentiated Competitive Marketplace," Marketing Science, INFORMS, vol. 29(1), pages 122-138, 01-02.
    2. Niladri B. Syam & Nanda Kumar, 2006. "On Customized Goods, Standard Goods, and Competition," Marketing Science, INFORMS, vol. 25(5), pages 525-537, September.
    3. Ayd{i}n Alptekinou{g}lu & Charles J. Corbett, 2008. "Mass Customization vs. Mass Production: Variety and Price Competition," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 204-217, August.
    4. Elie Ofek & Zsolt Katona & Miklos Sarvary, 2011. ""Bricks and Clicks": The Impact of Product Returns on the Strategies of Multichannel Retailers," Marketing Science, INFORMS, vol. 30(1), pages 42-60, 01-02.
    5. Keith J. Crocker & Paolo Letizia, 2014. "Optimal Policies for Recovering the Value of Consumer Returns," Production and Operations Management, Production and Operations Management Society, vol. 23(10), pages 1667-1680, October.
    6. 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.
    7. Robert Swinney, 2011. "Selling to Strategic Consumers When Product Value Is Uncertain: The Value of Matching Supply and Demand," Management Science, INFORMS, vol. 57(10), pages 1737-1751, October.
    8. Tingliang Huang & Hang Ren & Ying‐Ju Chen, 2018. "Consumer return policies in competitive markets: An operations perspective," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(6-7), pages 462-476, September.
    9. Eric T. Anderson & Karsten Hansen & Duncan Simester, 2009. "The Option Value of Returns: Theory and Empirical Evidence," Marketing Science, INFORMS, vol. 28(3), pages 405-423, 05-06.
    10. Nan Xia & S. Rajagopalan, 2009. "Standard vs. Custom Products: Variety, Lead Time, and Price Competition," Marketing Science, INFORMS, vol. 28(5), pages 887-900, 09-10.
    11. Jeffrey D. Shulman & Anne T. Coughlan & R. Canan Savaskan, 2010. "Optimal Reverse Channel Structure for Consumer Product Returns," Marketing Science, INFORMS, vol. 29(6), pages 1071-1085, 11-12.
    12. Paolo Letizia & Morteza Pourakbar & Terry Harrison, 2018. "The Impact of Consumer Returns on the Multichannel Sales Strategies of Manufacturers," Production and Operations Management, Production and Operations Management Society, vol. 27(2), pages 323-349, February.
    13. Hailong Cui & Sampath Rajagopalan & Amy R. Ward, 2021. "Impact of Task-Level Worker Specialization, Workload, and Product Personalization on Consumer Returns," Manufacturing & Service Operations Management, INFORMS, vol. 23(2), pages 346-366, March.
    14. Ayd{i}n Alptekinou{g}lu & Charles J. Corbett, 2010. "Leadtime-Variety Tradeoff in Product Differentiation," Manufacturing & Service Operations Management, INFORMS, vol. 12(4), pages 569-582, January.
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    Cited by:

    1. He, Bo & Mirchandani, Prakash & Yang, Guang, 2023. "Offering custom products using a C2M model: Collaborating with an E-commerce platform," International Journal of Production Economics, Elsevier, vol. 262(C).

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