IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02311919.html
   My bibliography  Save this paper

Dynamic Lot-Sizing Models for Retailers with Online Channels

Author

Listed:
  • Haoxuan Xu

    (EM - EMLyon Business School)

  • Yeming Gong
  • Chengbin Chu
  • Jinlong Zhang

Abstract

This paper studies inventory replenishment planning problems for retailers with online channels. Such retailer is able to obtain advance demand information (ADI) in an environment of time-varying demands. We incorporate ADI into dynamic lot-sizing models to formulate the replenishment planning problems for retailers in three scenarios: (1) companies act as pure-play online retailers with customers homogeneous in demand lead time, (2) online customers are heterogeneous in demand lead time with priorities, and (3) retailers operate in a bricks and clicks structure, in which demands come from online and offline channels, with either independent or interactive channels. We formulate the problem in the general scenario of interactive demand channels as a mixed-integer linear programming model, and then develop a unified model through reformulation. Based on the optimality properties, we design a dynamic programming algorithm with polynomial running time to solve the unified model. The numerical experiments for several online retailers find that the method can significantly reduce the total inventory cost.

Suggested Citation

  • Haoxuan Xu & Yeming Gong & Chengbin Chu & Jinlong Zhang, 2017. "Dynamic Lot-Sizing Models for Retailers with Online Channels," Post-Print hal-02311919, HAL.
    • Handle: RePEc:hal:journl:hal-02311919
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. MacCarthy, Bart L. & Zhang, Lina & Muyldermans, Luc, 2019. "Best Performance Frontiers for Buy-Online-Pickup-in-Store order fulfilment," International Journal of Production Economics, Elsevier, vol. 211(C), pages 251-264.
    2. Li, Xiang & Li, Yongjian & Cao, Wenjing, 2019. "Cooperative advertising models in O2O supply chains," International Journal of Production Economics, Elsevier, vol. 215(C), pages 144-152.
    3. Alım, Muzaffer & Beullens, Patrick, 2020. "Joint inventory and distribution strategy for online sales with a flexible delivery option," International Journal of Production Economics, Elsevier, vol. 222(C).
    4. Hübner, Alexander & Hense, Jonas & Dethlefs, Christian, 2022. "The revival of retail stores via omnichannel operations: A literature review and research framework," European Journal of Operational Research, Elsevier, vol. 302(3), pages 799-818.
    5. Alım, Muzaffer & Beullens, Patrick, 2022. "Improving inventory system performance by selective purchasing of buyers’ willingness to wait," European Journal of Operational Research, Elsevier, vol. 300(1), pages 124-136.
    6. Saha, Kushal & Bhattacharya, Subir, 2021. "‘Buy online and pick up in-store’: Implications for the store inventory," European Journal of Operational Research, Elsevier, vol. 294(3), pages 906-921.
    7. Wu, Xiang & (Yale) Gong, Yeming & Xu, Haoxuan & Chu, Chengbin & Zhang, Jinlong, 2017. "Dynamic lot-sizing models with pricing for new products," European Journal of Operational Research, Elsevier, vol. 260(1), pages 81-92.

    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:hal:journl:hal-02311919. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.