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Dynamic Pricing in a Multi-Period Newsvendor Under Stochastic Price-Dependent Demand

Author

Listed:
  • Mehran Ullah

    (Department of Industrial & Management Engineering, Hanyang University, Ansan, Gyeonggi-do 155 88, Korea)

  • Irfanullah Khan

    (Department of Industrial & Management Engineering, Hanyang University, Ansan, Gyeonggi-do 155 88, Korea)

  • Biswajit Sarkar

    (Department of Industrial & Management Engineering, Hanyang University, Ansan, Gyeonggi-do 155 88, Korea)

Abstract

The faster growth of technology stipulates the rapid development of new products; with the spread of new technologies old ones are outdated and their market demand declines sharply. The combined impact of demand uncertainty and short life-cycles complicate ordering and pricing decision of retailers that leads to a decrease in the profit. This study deals with the joint inventory and dynamic pricing policy for such products considering stochastic price-dependent demand. The aim is to develop a discount policy that enables the retailer to order more at the start of the selling season thus increase the profit and market share of the retailer. A multi-period newsvendor model is developed under the distribution-free approach and the optimal stocking quantities, unit selling price, and the discount percentage are obtained. The results show that the proposed discount policy increases the expected profit of the system. Additionally, the stocking quantity and the unit selling price also increases in the proposed discount policy. The robustness of the proposed model is illustrated with numerical examples and sensitivity analysis. Managerial insights are given to extract significant insights for the newsvendor model with discount policy.

Suggested Citation

  • Mehran Ullah & Irfanullah Khan & Biswajit Sarkar, 2019. "Dynamic Pricing in a Multi-Period Newsvendor Under Stochastic Price-Dependent Demand," Mathematics, MDPI, vol. 7(6), pages 1-15, June.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:6:p:520-:d:237841
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    References listed on IDEAS

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    4. Mojtaba Farrokh & Ehsan Ahmadi & Minghe Sun, 2023. "A robust stochastic possibilistic programming model for dynamic supply chain network design with pricing and technology selection decisions," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1082-1120, September.

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