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Returns Freight Insurance Policy and the Impact from a BOPS Retailer

Author

Listed:
  • Junxia He

    (Nanjing University of Finance and Economics)

  • Jian Liu

    (Nanjing University of Finance and Economics)

  • Fan Yang

    (Nanjing University of Finance and Economics)

  • Xia Zhao

    (Nanjing University of Finance and Economics)

Abstract

This paper studies the “returns freight insurance” (RFI) policy for an e-retailer who faces consumer returns. Under the monopoly case, we find that if the product can satisfy consumers’ tastes with a high possibility (we call it a low mismatch rate in this paper), then the e-retailer inclines to provide a RFI policy for consumers even when the consumer can make a voluntary RFI purchase decision. Under the competition case, we find that the e-retailer’s RFI strategy is not only dependent on the mismatch rate but also on the consumer’s preference for the e-retailer’s RFI policy. When the mismatch rate is sufficiently high, there exists a counterintuitive strategy for the e-retailer regarding the consumer’s preference for RFI. That is, the e-retailer may not offer RFI policy even when the consumer’s preference for such policy is high. Moreover, when the mismatch rate is within a lower range, then the e-retailer can always hold a profit advantage by adopting a RFI policy that conflicts with his rival’s benefit. We also find that the cross-sales effect in the buy-online-pick-up-in-store channel has a negative impact on the e-retailer’s equilibrium price and profit, and the returns handling cost of the e-retiler always hurts his profit under the monopoly situation while makes it possible to increase the profit when the return handling cost is relatively low under the competition situation. Lastly, when the BOPS retailer extends to the omni-channel mode, the proportion of offline consumers influences the e-retailer’s RFI strategy.

Suggested Citation

  • Junxia He & Jian Liu & Fan Yang & Xia Zhao, 2022. "Returns Freight Insurance Policy and the Impact from a BOPS Retailer," SN Operations Research Forum, Springer, vol. 3(1), pages 1-36, March.
  • Handle: RePEc:spr:snopef:v:3:y:2022:i:1:d:10.1007_s43069-022-00120-4
    DOI: 10.1007/s43069-022-00120-4
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    References listed on IDEAS

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    Cited by:

    1. Qiu, Ruozhen & Ma, Lin & Sun, Minghe, 2023. "A robust omnichannel pricing and ordering optimization approach with return policies based on data-driven support vector clustering," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1337-1354.
    2. Liu, Jiqiong & Yuan, Rui & Feng, Shuai, 2023. "Whether to offer return-freight insurance or open a physical showroom: A strategic analysis of an online retailer’s decisions," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).

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