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A Comparison of Return Rate Calculation Methods: Evidence from 16 Retailers

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  • El Kihal, Siham
  • Nurullayev, Namig
  • Schulze, Christian
  • Skiera, Bernd

Abstract

The product return rate (RR) is an important metric for retailers; even small RR changes can significantly impact retailers’ profit. Companies and researchers typically favor and employ one of three methods to calculate the RR: based on the number of returned items, these items’ revenue, or their profit contribution. Interviews with 24 managers and industry experts reveal that two methods, item-based and revenue-based, are often used. However, little is known about how much the interpretation of RRs depends on the calculation method. In this article, the authors rely on extensive datasets to investigate these potential differences empirically. Analyzing more than 8 million transactions at sixteen different retailers, the authors find that RRs calculated via the three methods differ on average by 24.3%. The size of these differences makes cross-sectional comparisons of RRs calculated via different methods difficult. In contrast, the authors find that the developments of the RRs over time are similar, which allows for a meaningful time-series comparison of RR developments, regardless of the method. Finally, this research shows that all three calculation methods result in RRs that are equally insightful (leading) indicators of relevant retailer performance metrics.

Suggested Citation

  • El Kihal, Siham & Nurullayev, Namig & Schulze, Christian & Skiera, Bernd, 2021. "A Comparison of Return Rate Calculation Methods: Evidence from 16 Retailers," Journal of Retailing, Elsevier, vol. 97(4), pages 676-696.
    • Handle: RePEc:eee:jouret:v:97:y:2021:i:4:p:676-696
    DOI: 10.1016/j.jretai.2021.04.001
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    References listed on IDEAS

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    Cited by:

    1. El Kihal, Siham & Shehu, Edlira, 2022. "It's not only what they buy, it's also what they keep: Linking marketing instruments to product returns," Journal of Retailing, Elsevier, vol. 98(3), pages 558-571.
    2. Maier, Erik & Bornschein, Rico & Manss, Rico & Hesse, Damian, 2023. "Financial consequences of adding bricks to clicks," International Journal of Research in Marketing, Elsevier, vol. 40(3), pages 609-628.
    3. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).
    4. Krallman, Alexandra & Barnes, Donald C. & Lastner, Matthew M. & Collier, Joel E., 2023. "You can’t touch this: Driving purchase justification for hedonic online purchases," Journal of Business Research, Elsevier, vol. 155(PB).

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    More about this item

    Keywords

    Retailing; Product return rate; Product returns; Marketing metrics; Electronic commerce;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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