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Joint inventory and pricing decisions when customers are delay sensitive

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  • Güler, M. Güray
  • Bilgiç, Taner
  • Güllü, Refik

Abstract

We consider the joint pricing and inventory problem of a capacity constrained service facility with several classes of customers. The customers are differentiated with their sensitivity for waiting and their willingness to pay for the service. We model the problem using an M/M/1 queueing system with non-preemptive priorities. We give closed form solutions for the inventory decisions. We also show that the prices given by the first order conditions are also incentive compatible in the sense that they optimize the profit of the firm even if the firm does not know the type of an arriving customer and let the customer choose a price from the menu of prices. We approximate the problem and provide simple and explicit solutions when there is a single customer type. In numerical illustrations, we show that the customers, who are more sensitive to wait, do not enter the system until the base stock level is above a threshold. We provide extensions of our results for M/G/1 and M/M/m systems.

Suggested Citation

  • Güler, M. Güray & Bilgiç, Taner & Güllü, Refik, 2014. "Joint inventory and pricing decisions when customers are delay sensitive," International Journal of Production Economics, Elsevier, vol. 157(C), pages 302-312.
    • Handle: RePEc:eee:proeco:v:157:y:2014:i:c:p:302-312
    DOI: 10.1016/j.ijpe.2014.04.028
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    References listed on IDEAS

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    Cited by:

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    2. Shahsavar, Aria & Sadeghi, J. Kiarash & Shockley, Jeff & Ojha, Divesh, 2021. "On the relationship between lean scheduling and economic performance in shipbuilding: A proposed model and comparative evaluation," International Journal of Production Economics, Elsevier, vol. 239(C).
    3. Ehsan Ardjmand & Gary R. Weckman & William A. Young & Omid Sanei Bajgiran & Bizhan Aminipour, 2016. "A robust optimisation model for production planning and pricing under demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 54(13), pages 3885-3905, July.
    4. Peng Hu & Ye Lu & Miao Song, 2019. "Joint Pricing and Inventory Control with Fixed and Convex/Concave Variable Production Costs," Production and Operations Management, Production and Operations Management Society, vol. 28(4), pages 847-877, April.
    5. Li, Yang & Liu, Feng, 2021. "Joint inventory and pricing control with lagged price responses," International Journal of Production Economics, Elsevier, vol. 241(C).
    6. Wang, Qiang & Zhao, Nenggui & Wu, Jie & Zhu, Qingyuan, 2021. "Optimal pricing and inventory policies with reference price effect and loss-Averse customers," Omega, Elsevier, vol. 99(C).
    7. Lin, Zhibing, 2016. "Price promotion with reference price effects in supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 52-68.
    8. M. Güler & Taner Bilgiç & Refik Güllü, 2015. "Joint pricing and inventory control for additive demand models with reference effects," Annals of Operations Research, Springer, vol. 226(1), pages 255-276, March.
    9. Ahmadi-Javid, Amir & Hoseinpour, Pooya, 2015. "A location-inventory-pricing model in a supply chain distribution network with price-sensitive demands and inventory-capacity constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 238-255.
    10. Xiang Li & Yongjian Li, 2016. "On lot-sizing problem in a random yield production system under loss aversion," Annals of Operations Research, Springer, vol. 240(2), pages 415-434, May.
    11. Fathi, Mahdi & Khakifirooz, Marzieh & Diabat, Ali & Chen, Huangen, 2021. "An integrated queuing-stochastic optimization hybrid Genetic Algorithm for a location-inventory supply chain network," International Journal of Production Economics, Elsevier, vol. 237(C).
    12. Mokhtari, Hadi, 2018. "Economic order quantity for joint complementary and substitutable items," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 154(C), pages 34-47.
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