Abstract
This paper studies the inventory and price strategies of an omnichannel firm adopting the “Buy-Online-Return-to-Store” (BORS) policy. Taking the omnichannel participants’ rational expectation behavior and random demand into consideration, the optimal operation strategy is derived and the effectiveness of the BORS policy is explored. The results show that inventory and price display a positive relationship. The optimal inventory and price decrease with the return cost, consumers’ travel cost, and the proportion of low-value consumers, while they increase with consumers’ beliefs regarding the inventory availability rate. Online sales outperform store sales when there are more low-value consumers. Adopting a BORS policy may reduce price and inventory but increase profit when consumers’ store return cost is high or the firm’s store return cost is low. In addition, when the long-term additional favorable effect of the store return is large, the firm can derive more profit through BORS policy.
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This research was supported by the National Natural Science Foundation of China under Projects 71771122 and 71562006.
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All authors contributed to the study conception and design. Zonghuo Li and Wensheng Yang were involved in conceptualization; Zonghuo Li was involved in methodology and investigation; Zonghuo Li and Xintong Chen were involved in writing—review and editing; and Wensheng Yang was involved in supervision. All authors read and approved the final manuscript. We also appreciate the contributions of Dear Di Wang and Hyun Seung Jin.
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Li, Z., Yang, W. & Chen, X. Omnichannel inventory models accounting for Buy-Online–Return-to-Store service and random demand. Soft Comput 25, 11691–11710 (2021). https://doi.org/10.1007/s00500-021-06045-0
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DOI: https://doi.org/10.1007/s00500-021-06045-0