Buy-One-Get-One Promotions in a Two-Echelon Supply Chain

库存 利润(经济学) 业务 商业 微观经济学 经济 物理 核物理学
作者
Yuefeng Li,Moutaz Khouja,Jingming Pan,Jing Zhou
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
卷期号:69 (9): 5234-5255 被引量:16
标识
DOI:10.1287/mnsc.2022.4638
摘要

Buy-one-get-one (BOGO) promotions have become popular. With BOGO, the first unit is sold for the regular price, and the second unit is discounted. We analyze BOGO in manufacturer–retailer supply chains. We identify conditions under which BOGO outperforms price reduction (PR) and everyday low price (EDLP) policies. We find that, for some products, whether consumers stockpile or not, if BOGO and PR have the same market size, BOGO has a larger retailer profit and the same or larger manufacturer profit because BOGO induces more consumers to buy and consume two units. When consumers stockpile, the retailer sets prices to prevent such behavior, and the retailer’s share of supply chain profits is largest under BOGO, whereas consumer surplus with BOGO is smaller than PR. We also find that BOGO reduces double marginalization. When PR expands market size more than BOGO, BOGO’s effectiveness diminishes. When consumers stockpile without increasing consumption and/or production cost is high, EDLP is best. Our results are robust to multiperiod with single-promotion-period settings. A large number of regular-price periods following a promotion period increases stockpiling, which erodes the retailer’s profit and favors EDLP. If promotions are offered for consecutive periods, a larger number of promotion periods increases PR’s efficacy relative to BOGO. Time-inconsistent consumers increase stockpiling and make PR outperform BOGO. Heterogeneous consumers’ holding cost and marginal utility prevent retailers from perfectly discriminating among consumers who make profit-reducing choices. Compared with retailers’ BOGO, manufacturers’ BOGO increases double marginalization and decreases retailers’ and manufacturers’ profits and consumer surplus. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: This work was partially supported by the National Science Foundation of China [Grants 71972026, 72101102]. Y. Li’s work was supported by the China Scholarship Council [Grant 201806070094]. Supplemental Material: The online companion and data are available at https://doi.org/10.1287/mnsc.2022.4638 .
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