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Optimal Rebate Strategies Under Dynamic Pricing

Author

Listed:
  • Shanshan Hu

    (School of International Business Administration, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Xing Hu

    (Lundquist College of Business, University of Oregon, Eugene, Oregon 97403)

  • Qing Ye

    (School of Economics and Management, Tsinghua University, Beijing 100084, China)

Abstract

Instant discounts and mail-in rebates are two common pricing tools in retail, but they are not simple substitutes. On the one hand, consumers discount the face value of a mail-in rebate, making it less effective than an instant discount in inducing consumers’ purchase. On the other hand, a portion of consumers with mail-in rebates fail to redeem them, resulting in savings for the retailer. We study how retailers, under pressure to move inventory, should use these two pricing tools to maximize revenue by determining the optimal use of mail-in rebates together with dynamic pricing of limited inventory. In a base model that allows frequent adjustment of product price and rebate face value, the optimal policy takes the form of “discount only,” “rebate only,” or a combination of the two. For useful heuristics with infrequent policy adjustment, we analyze the deterministic approximation of the base model. Interestingly, the deterministic solution splits the selling season into two segments, and it suggests using different pricing-rebate policies in each segment. Finally, we study a scenario in which the retailer has only one opportunity to introduce a static rebate, and we find that for any inventory level there is a cutoff time before which rebates should not be used. Our numerical studies show that such an optimal one-time static rebate policy performs well compared with the optimal revenue in the benchmark model.

Suggested Citation

  • Shanshan Hu & Xing Hu & Qing Ye, 2017. "Optimal Rebate Strategies Under Dynamic Pricing," Operations Research, INFORMS, vol. 65(6), pages 1546-1561, December.
  • Handle: RePEc:inm:oropre:v:65:y:2017:i:6:p:1546-1561
    DOI: 10.1287/opre.2017.1642
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    References listed on IDEAS

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    1. Chen, Pengyu & Liu, Xu & Wang, Qin & Zhou, Pin, 2022. "The Implications of Competition on Strategic Inventories Considering Manufacturer-to-Consumer Rebates," Omega, Elsevier, vol. 107(C).
    2. Kartick Dey & Debajyoti Chatterjee & Subrata Saha & Ilkyeong Moon, 2019. "Dynamic versus static rebates: an investigation on price, displayed stock level, and rebate-induced demand using a hybrid bat algorithm," Annals of Operations Research, Springer, vol. 279(1), pages 187-219, August.
    3. Khouja, Moutaz & Subramaniam, Chandra & Vasudev, Vinay, 2020. "A comparative analysis of marketing promotions and implications for data analytics," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 151-174.
    4. Aika Monden & Yusuke Zennyo, 2022. "Consumer rebates from e‐commerce platforms and multichannel management of third‐party sellers," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 3059-3071, October.
    5. 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.
    6. Mahmoud Dehghan Nayeri & Amir-Nader Haghbin & Abdolkarim Mohammadi-Balani & Karim Bayat, 2020. "A multi-objective mean–variance mathematical programming approach to combined phase-out and clearance pricing strategy for seasonal products: case study of a Jeans retailer," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(3), pages 210-217, June.
    7. Yu, Niu & Wang, Shumei & Liu, Zhixin, 2022. "Managing brand competition with consumer fairness concern via manufacturer incentive," European Journal of Operational Research, Elsevier, vol. 300(2), pages 661-675.
    8. Yan Liu & Ningyuan Chen, 2022. "Dynamic Pricing with Money‐Back Guarantees," Production and Operations Management, Production and Operations Management Society, vol. 31(3), pages 941-962, March.
    9. Guillermo Gallego & Michael Z. F. Li & Yan Liu, 2020. "Dynamic Nonlinear Pricing of Inventories over Finite Sales Horizons," Operations Research, INFORMS, vol. 68(3), pages 655-670, May.
    10. Oggioni, Giorgia & Schwartz, Alexandra & Wiertz, Ann-Kathrin & Zöttl, Gregor, 2024. "Dynamic pricing and strategic retailers in the energy sector: A multi-leader-follower approach," European Journal of Operational Research, Elsevier, vol. 312(1), pages 255-272.
    11. Chen, Pingping & Chen, Huiru & Zhao, Ruiqing, 2022. "Price promotions in vertically-related market: Instant discount vs. gift card," Omega, Elsevier, vol. 108(C).

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