IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/7353083.html
   My bibliography  Save this article

On the Preorder Strategy for Loss-Averse Newsvendor Model under CVaR Measure

Author

Listed:
  • Jingfu Huang
  • Bo Feng
  • Chengfei Wang
  • Xinsheng Xu

Abstract

Due to rapid development of manufacturing and online retail, the life cycle of many products is becoming shorter and shorter. Hence, manufacturers may launch new products in selling season to maintain market share and attract new customers. Under these circumstances, manufacturers may release a presale information before the selling season, and the retailer correspondingly makes a preorder according to the estimation to the demand. For the case that the wholesale price rises gradually with time during the preselling period and the market demand is stochastic, based on minimizing the legacy loss via CVaR measure in risk management, we establish a loss-averse newsvendor’s preordering decision model. By model analysis, we establish the closed form solution to the model and provide the optimal preordering time and preordering quantity to the retailer. Some numerical experiments are made to show the validity of the model, and some managerial insights are explored through the numerical experiments.

Suggested Citation

  • Jingfu Huang & Bo Feng & Chengfei Wang & Xinsheng Xu, 2022. "On the Preorder Strategy for Loss-Averse Newsvendor Model under CVaR Measure," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, February.
  • Handle: RePEc:hin:jnlmpe:7353083
    DOI: 10.1155/2022/7353083
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/7353083.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/7353083.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/7353083?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:hin:jnlmpe:7353083. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.