IDEAS home Printed from https://ideas.repec.org/a/bla/popmgt/v32y2023i8p2529-2545.html
   My bibliography  Save this article

Joint pricing and inventory management under minimax regret

Author

Listed:
  • Chengzhang Li
  • Mengshi Lu

Abstract

We study the problem of jointly optimizing the price and order quantity for a perishable product in a single selling period, also known as the pricing newsvendor problem, under demand ambiguity. Specifically, the demand is a function of the selling price and a random factor of which the distribution is unknown. We employ the minimax regret decision criterion to minimize the worst‐case regret, where the regret is defined as the difference between the optimal profit that could be obtained with perfect/complete information and the realized profit using the decision made with ambiguous demand information. First, given the interval in which the random factor lies with high probability, we characterize the optimal pricing and ordering decisions under the minimax regret criterion and compare their properties with those in the classical models that seek to maximize the expected profit. Specifically, we explore the impact of inventory risk by comparing the optimal price and the risk‐free price and study comparative statics with respect to the degree of demand ambiguity and the unit ordering cost. We further show that the minimax regret approach avoids the high degree of conservativeness that is often incurred in the application of the commonly used max–min robust optimization approach. Second, when partial distributional information of the random factor is available, we adopt the Wasserstein distance to depict the distributional ambiguity and characterize the set of worst‐case distributions and the maximum regret given the selling price and order quantity. Third, we compare the minimax regret approaches with the traditional profit‐maximization approach in a data‐driven setting. We show via a numerical study that the minimax regret approaches outperform the traditional profit‐maximization approach, especially when the data are scarce, the demand has high volatility, and the number of exercised prices is small. Furthermore, leveraging the partial distributional information of the random factor can further improve the performance of the minimax regret approach.

Suggested Citation

  • Chengzhang Li & Mengshi Lu, 2023. "Joint pricing and inventory management under minimax regret," Production and Operations Management, Production and Operations Management Society, vol. 32(8), pages 2529-2545, August.
  • Handle: RePEc:bla:popmgt:v:32:y:2023:i:8:p:2529-2545
    DOI: 10.1111/poms.13991
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/poms.13991
    Download Restriction: no

    File URL: https://libkey.io/10.1111/poms.13991?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:popmgt:v:32:y:2023:i:8:p:2529-2545. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.