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Joint optimization on pricing, promotion and inventory control with stochastic demand

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  • Zhang, Ju-Liang
  • Chen, Jian
  • Lee, Chung-Yee

Abstract

Firms often utilize and coordinate dynamic adjustment of price, non-price promotions such as advertisement and recruitment of excellent salespeople and proper inventory replenishment policies to satisfy customer demands and achieve maximal profit. This paper provides an analytical model for obtaining optimal decisions jointly on pricing, promotion and inventory control. Specifically, we study a single item, finite horizon, periodic review model in which the demand is influenced by price and promotion, and the objective is to maximize the total profit. We characterize the optimal policy and provide solution for coordinating promotion, pricing and inventory replenishment. We show that the optimal promotion policy is a threshold policy under some reasonable assumptions and once the promotion is determined the optimal inventory/pricing policy is a base-stock-list-price policy. Numerical study is also provided to demonstrate the contribution of our model.

Suggested Citation

  • Zhang, Ju-Liang & Chen, Jian & Lee, Chung-Yee, 2008. "Joint optimization on pricing, promotion and inventory control with stochastic demand," International Journal of Production Economics, Elsevier, vol. 116(2), pages 190-198, December.
    • Handle: RePEc:eee:proeco:v:116:y:2008:i:2:p:190-198
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    References listed on IDEAS

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    Cited by:

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      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
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    7. Terzi, Mourad & Ouazene, Yassine & Yalaoui, Alice & Yalaoui, Farouk, 2023. "Lot-sizing and pricing decisions under attraction demand models and multi-channel environment: New efficient formulations," Operations Research Perspectives, Elsevier, vol. 10(C).
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    9. Udayan Chanda & Alok Kumar, 2019. "Optimization of EOQ Model for New Products Under Multi-Stage Adoption Process," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 1-25, April.
    10. Ma, Shaohui & Fildes, Robert & Huang, Tao, 2016. "Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information," European Journal of Operational Research, Elsevier, vol. 249(1), pages 245-257.
    11. Saha, Subrata & Chatterjee, Debajyoti & Sarkar, Biswajit, 2021. "The ramification of dynamic investment on the promotion and preservation technology for inventory management through a modified flower pollination algorithm," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    12. Tunuguntla, Vaishnavi & Basu, Preetam & Rakshit, Krishanu & Ghosh, Debabrata, 2019. "Sponsored search advertising and dynamic pricing for perishable products under inventory-linked customer willingness to pay," European Journal of Operational Research, Elsevier, vol. 276(1), pages 119-132.
    13. Tsao, Yu-Chung, 2015. "Cooperative promotion under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 167(C), pages 45-49.
    14. Kim, Sang-Won & Bell, Peter C., 2011. "Optimal pricing and production decisions in the presence of symmetrical and asymmetrical substitution," Omega, Elsevier, vol. 39(5), pages 528-538, October.
    15. Xiaxia Ma & Wenliang Bian & Xiqing Yang & Shengnan Niu & Yongming Cai & Jie Guan & Wenbin Wang, 2022. "Online Retailer’s Contingent Free-Shipping Decisions under Large-Scale Promotions Considering Delayed Delivery," Sustainability, MDPI, vol. 14(17), pages 1-22, August.
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    17. Zhu, Stuart X., 2013. "Dynamic replenishment, production, and pricing decisions, in the face of supply disruption and random price-sensitive demand," International Journal of Production Economics, Elsevier, vol. 146(2), pages 612-619.

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