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Timing of Product Allocation: Using Probabilistic Selling to Enhance Inventory Management

Author

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  • Scott Fay

    (Department of Marketing, Martin J. Whitman School of Management, Syracuse University, Syracuse, New York 13244)

  • Jinhong Xie

    (Department of Marketing, Warrington College of Business, University of Florida, Gainesville, Florida 32611)

Abstract

This paper examines probabilistic selling (PS) as an inventory-management mechanism, paying special attention to the impact of the timing of product assignment to buyers of probabilistic goods. In practice, sellers tend to offer probabilistic products only after major demand uncertainty has been resolved. By deferring product assignments, a firm is able to obtain more information about demand for each specific product before deciding which product to assign to consumers. However, our analysis demonstrates that PS can be an effective inventory-management mechanism even if the firm allocates products before knowing which product will be more popular and, thus, scarcer. Interestingly, we show that it can be more profitable for the firm to allocate products to consumers before, rather than after, learning the true demand for a product because, although early allocation imposes higher inventory costs (as a result of larger required inventory levels), it also enables the firm to charge higher prices. Our results also reveal that, when introducing probabilistic goods, the firm should order less inventory (relative to the case where probabilistic goods are not offered) if costs are very low but more inventory otherwise. Finally, we show that PS, as an inventory-management mechanism, can create a win--win situation, both improving profit and increasing social welfare. This paper was accepted by J. Miguel Villas-Boas, marketing .

Suggested Citation

  • Scott Fay & Jinhong Xie, 2015. "Timing of Product Allocation: Using Probabilistic Selling to Enhance Inventory Management," Management Science, INFORMS, vol. 61(2), pages 474-484, February.
  • Handle: RePEc:inm:ormnsc:v:61:y:2015:i:2:p:474-484
    DOI: 10.1287/mnsc.2014.1948
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Quan Zheng & Xiajun Amy Pan & Janice E. Carrillo, 2019. "Probabilistic Selling for Vertically Differentiated Products with Salient Thinkers," Marketing Science, INFORMS, vol. 38(3), pages 442-460, May.
    2. Guang Yang & Ying Wang & Mulin Liu, 2023. "Optimal Policy for Probabilistic Selling with Three-Way Revenue Sharing Contract under the Perspective of Sustainable Supply Chain," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    3. Yeu-Shiang Huang & Tzu-Yi Wu & Chih-Chiang Fang & Tzu-Liang (Bill) Tseng, 2021. "Decisions on Probabilistic Selling for Consumers with Different Risk Attitudes," Decision Analysis, INFORMS, vol. 18(2), pages 121-138, June.
    4. Yifan Wu & Shibo Jin, 2022. "Joint pricing and inventory decision under a probabilistic selling strategy," Operational Research, Springer, vol. 22(2), pages 1209-1233, April.
    5. Yuetao Gao & Yue Wu, 2023. "Regulating Probabilistic Selling of Counterfeits," Management Science, INFORMS, vol. 69(8), pages 4498-4517, August.
    6. Yong Chao & Lin Liu & Dongyuan Zhan, 2016. "Vertical Probabilistic Selling under Competition: the Role of Consumer Anticipated Regret," Working Papers 16-14, NET Institute.
    7. Aleksandra Kovacheva & Hristina Nikolova, 2024. "Uncertainty marketing tactics: An overview and a unifying framework," Journal of the Academy of Marketing Science, Springer, vol. 52(1), pages 1-22, January.
    8. Zhang, Juliang & Deng, Lan & Liu, Huimin & Cheng, T.C.E., 2022. "Which strategy is better for managing multi-product demand uncertainty: Inventory substitution or probabilistic selling?," European Journal of Operational Research, Elsevier, vol. 302(1), pages 79-95.
    9. Zhang, Mingyang & Zhang, Juliang & Cheng, T.C.E. & Hua, Guowei, 2018. "Why and how do branders sell new products on flash sale platforms?," European Journal of Operational Research, Elsevier, vol. 270(1), pages 337-351.
    10. Guo, Xiaolong & Bian, Junsong & Wu, Peiyan & Shi, Victor & Chen, Huangen, 2023. "Probabilistic product design with regret-anticipated consumers," International Journal of Production Economics, Elsevier, vol. 263(C).

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