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Price, rebate and order quantity decisions in a newsvendor framework with rebate-dependent recapture of lost sales

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  • Arcelus, F.J.
  • Gor, Ravi
  • Srinivasan, G.

Abstract

This paper analyses a single-period decision of a retailer facing uncertain and price dependent demand. The typical modeling of the problem in a newsvendor framework assumes the unfulfilled demand to be lost once and for all. However, in reality, there may be an opportunity to backlog the lost sales, by offering some incentive for waiting. Nevertheless, the retailer's procurement price may be higher, due to the likely cost increase of the emergency purchase. Further, not all the customers that could not buy in the first instance may avail the rebate offer and buy. The backlog fill rate is modeled as a function of the proportion of the rebate to the price. Then the retailer has to decide ahead of the realization of the demand the quantity to be ordered, the price and the rebate to be offered for backlogged sales that will maximize its expected profit. Numerical examples are presented to highlight model sensitivities to parametric changes.

Suggested Citation

  • Arcelus, F.J. & Gor, Ravi & Srinivasan, G., 2012. "Price, rebate and order quantity decisions in a newsvendor framework with rebate-dependent recapture of lost sales," International Journal of Production Economics, Elsevier, vol. 140(1), pages 473-482.
  • Handle: RePEc:eee:proeco:v:140:y:2012:i:1:p:473-482
    DOI: 10.1016/j.ijpe.2012.06.031
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    References listed on IDEAS

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    Cited by:

    1. Ata Allah Taleizadeh & Alireza Mahmoudzade Varzi & Alireza Amjadian & Mahsa Noori-daryan & Ioannis Konstantaras, 2023. "How cash-back strategy affect sale rate under refund and customers’ credit," Operational Research, Springer, vol. 23(1), pages 1-69, March.
    2. B.C. Giri & S. Bardhan & T. Maiti, 2016. "Coordinating a three-layer supply chain with uncertain demand and random yield," International Journal of Production Research, Taylor & Francis Journals, vol. 54(8), pages 2499-2518, April.
    3. Lifeng Mu & Xin Tang & Vijayan Sugumaran & Wei Xu & Xiangyang Sun, 2023. "Optimal rebate strategy for an online retailer with a cashback platform: commission-driven or marketing-based?," Electronic Commerce Research, Springer, vol. 23(1), pages 475-510, March.
    4. Jadidi, Omid & Taghipour, Sharareh & Zolfaghari, Saeed, 2016. "A two-price policy for a newsvendor product supply chain with time and price sensitive demand," European Journal of Operational Research, Elsevier, vol. 253(1), pages 132-143.
    5. Zhou, Yong-Wu & Cao, Bin & Tang, Qinshen & Zhou, Wenhui, 2017. "Pricing and rebate strategies for an e-shop with a cashback website," European Journal of Operational Research, Elsevier, vol. 262(1), pages 108-122.
    6. Liang, Donghan & Li, Gang & Sun, Linyan & Chen, Yubao, 2013. "The role of rebates in the hybrid competition between a national brand and a private label with present-biased consumers," International Journal of Production Economics, Elsevier, vol. 145(1), pages 208-219.
    7. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.

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