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On the Profitability of Stacked Discounts: Identifying Revenue and Cost Effects of Discount Framing

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  • Necati Ertekin

    (Leavey School of Business, Santa Clara University, Santa Clara, California 95053)

  • Jeffrey D. Shulman

    (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195)

  • Haipeng (Allan) Chen

    (Gatton College of Business and Economics, University of Kentucky, Lexington, Kentucky 40506)

Abstract

Previous research demonstrates that stacked discounts increase retail revenue. For instance, a retailer should sell more products by offering “20% off, plus an extra 25% off” than by offering an economically equivalent single discount of “40% off.” We conduct multimethodology research to investigate a potential downside of offering stacked discounts: Can stacked discounts disproportionately increase retailer costs from product returns? We incorporate insights from prior behavioral work and develop an analytical model to generate predictions about how stacked discounts affect retail sales and return performance. Next, we conduct a laboratory experiment to provide evidence for our theory in a controlled environment. Subsequently, we empirically test our predictions under real market conditions using six-year transactional data from promotional events at a national jewelry retailer. Finally, drawing upon the empirical estimates, we conduct a numerical study to assess the impact of stacked discounts on retail profitability. Our analytical model and the empirical results identify the inherent tradeoffs associated with stacked discounts and demonstrate the cost structures under which stacked discounts will decrease firm profitability despite an increase in initial sales. We conclude by discussing implications for retailers in assessing the impact of how they frame their price discounts.

Suggested Citation

  • Necati Ertekin & Jeffrey D. Shulman & Haipeng (Allan) Chen, 2019. "On the Profitability of Stacked Discounts: Identifying Revenue and Cost Effects of Discount Framing," Marketing Science, INFORMS, vol. 38(2), pages 317-342, March.
  • Handle: RePEc:inm:ormksc:v:38:y:2019:i:2:p:317-342
    DOI: 10.1287/mksc.2018.1137
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    References listed on IDEAS

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    3. Sun, Yimeng & Qiu, Ruozhen & Sun, Minghe, 2024. "A robust optimization approach for inventory management with limited-time discounts and service-level requirement under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 267(C).
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    5. Zhang, Hongchao & Yu, Yu & Qin, Yinggao, 2023. "The effects of constrained mobile coupons in the mobile channel," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    6. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).
    7. Attari, Amin & Chatterjee, Promothesh & Singh, Surendra N., 2022. "Taking a chance for a discount: An investigation into consumers’ choice of probabilistic vs. sure price promotions," Journal of Business Research, Elsevier, vol. 143(C), pages 366-374.

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