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Style goods pricing with demand learning

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  • Sen, Alper
  • Zhang, Alex X.

Abstract

For many industries (e.g., apparel retailing) managing demand through price adjustments is often the only tool left to companies once the replenishment decisions are made. A significant amount of uncertainty about the magnitude and price sensitivity of demand can be resolved using the early sales information. In this study, a Bayesian model is developed to summarize sales information and pricing history in an efficient way. This model is incorporated into a periodic pricing model to optimize revenues for a given stock of items over a finite horizon. A computational study is carried out in order to find out the circumstances under which learning is most beneficial. The model is extended to allow for replenishments within the season, in order to understand global sourcing decisions made by apparel retailers. Some of the findings are empirically validated using data from U.S. apparel industry.

Suggested Citation

  • Sen, Alper & Zhang, Alex X., 2009. "Style goods pricing with demand learning," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1058-1075, August.
    • Handle: RePEc:eee:ejores:v:196:y:2009:i:3:p:1058-1075
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    References listed on IDEAS

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    Cited by:

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    2. Zhang, Bin & Duan, Dongxia & Ma, Yurui, 2018. "Multi-product expedited ordering with demand forecast updates," International Journal of Production Economics, Elsevier, vol. 206(C), pages 196-208.
    3. Qi Chen & Qi Xu, 2022. "Joint optimal pricing and advertising policies in a fashion supply chain under the ODM strategy considering fashion level and goodwill," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1075-1105, July.
    4. Avittathur, Balram & Biswas, Indranil, 2017. "A note on limited clearance sale inventory model," International Journal of Production Economics, Elsevier, vol. 193(C), pages 647-653.
    5. Catherine Cleophas & Daniel Kadatz & Sebastian Vock, 2017. "Resilient revenue management: a literature survey of recent theoretical advances," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(5), pages 483-498, October.
    6. Qi Chen & Qi Xu, 0. "Joint optimal pricing and advertising policies in a fashion supply chain under the ODM strategy considering fashion level and goodwill," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-31.
    7. Wen, Xin & Choi, Tsan-Ming & Chung, Sai-Ho, 2019. "Fashion retail supply chain management: A review of operational models," International Journal of Production Economics, Elsevier, vol. 207(C), pages 34-55.
    8. Adhikari, Arnab & Bisi, Arnab & Avittathur, Balram, 2020. "Coordination mechanism, risk sharing, and risk aversion in a five-level textile supply chain under demand and supply uncertainty," European Journal of Operational Research, Elsevier, vol. 282(1), pages 93-107.

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