Why full refunds prevail: A product fit perspective

This paper studies how an online seller designs a menu of return contracts to manage consumer heterogeneity arising from product misfit risk. In the model, informed consumers know the product fits, whereas uninformed consumers face uncertainty about fit. We show that when only misfit risk exists, a single full-refund contract can implement the optimal menu. The return price insures consumers against misfit, and the selling price extracts full surplus. This finding aligns with the widespread adoption of lenient return policies and demonstrates that uniform contracts can emerge endogenously from incentive compatibility rather than as ad hoc assumptions. Introducing quality risk—an additional source of uncertainty in the valuation of fit products—fundamentally changes this outcome. The seller then shifts from full to partial refunds. Under high quality risk, the optimal menu becomes differentiated: A low-price, no-frills option for informed consumers and a high-price, insurance-heavy option for uninformed consumers. To induce self-selection, the seller distorts the return price upward for uninformed consumers to strengthen the insurance effect, trading off allocative efficiency for screening. Interestingly, when quality risk becomes extreme, refunds not only mitigate information rents but also enhance social surplus by preventing consumers from retaining low-quality products. Extensions incorporating misfit valuation, seller-side costs, and return hassle costs show that the uniform contract remains robust when only misfit risk is present, rationalizing diverse return policy practices in online markets.

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Publication Details

Journal
Production and Operations Management
Published
2026-03-31
DOI
https://doi.org/10.1177/10591478261442318
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Why full refunds prevail: A product fit perspective

Chuanshuai Ru, Wenqiang Xiao, Fangruo Chen, Weitao Ren
Production and Operations Management
Supply Chain and Inventory Management
article

Why full refunds prevail: A product fit perspective

Chuanshuai Ru, Wenqiang Xiao, Fangruo Chen, Weitao Ren
article en

Abstract

This paper studies how an online seller designs a menu of return contracts to manage consumer heterogeneity arising from product misfit risk. In the model, informed consumers know the product fits, whereas uninformed consumers face uncertainty about fit. We show that when only misfit risk exists, a single full-refund contract can implement the optimal menu. The return price insures consumers against misfit, and the selling price extracts full surplus. This finding aligns with the widespread adoption of lenient return policies and demonstrates that uniform contracts can emerge endogenously from incentive compatibility rather than as ad hoc assumptions. Introducing quality risk—an additional source of uncertainty in the valuation of fit products—fundamentally changes this outcome. The seller then shifts from full to partial refunds. Under high quality risk, the optimal menu becomes differentiated: A low-price, no-frills option for informed consumers and a high-price, insurance-heavy option for uninformed consumers. To induce self-selection, the seller distorts the return price upward for uninformed consumers to strengthen the insurance effect, trading off allocative efficiency for screening. Interestingly, when quality risk becomes extreme, refunds not only mitigate information rents but also enhance social surplus by preventing consumers from retaining low-quality products. Extensions incorporating misfit valuation, seller-side costs, and return hassle costs show that the uniform contract remains robust when only misfit risk is present, rationalizing diverse return policy practices in online markets.

Production and Operations Management
Shanghai Jiao Tong University (CN), New York University (US)
Openalex Percentile: Top 27%
Supply Chain and Inventory Management
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Why full refunds prevail: A product fit perspective — Chuanshuai Ru, Wenqiang Xiao, et al. · Production and Operations Management (2026) | TGRS Research Map | TGRS