IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-662-47250-7_3.html
   My bibliography  Save this book chapter

Demand Forecasting Dynamic Equation Model

In: Optimization of Integrated Supply Chain Planning under Multiple Uncertainty

Author

Listed:
  • Juping Shao

    (Suzhou University of Science and Technology)

  • Yanan Sun

    (Suzhou Industrial Park Anwood Logistics System Co., Ltd)

  • Bernd Noche

    (University Duisburg-Essen)

Abstract

Demand forecasting is the prerequisite and foundation of carrying out the work of supply chain logistics plan. In many cases, demand forecasting is often used by managers to make procurement plans, production plans, transportation plans, and inventory plans, etc. However, the uncertain internal and external factors of the supply chain make prediction results always different from the reality. It means that there is a gap between forecasting and the reality. When the difference between forecast data and actual data is too significant, you will inevitably fail, even if the planning process itself is very close. Therefore, the effectiveness of supply chain is greatly affected by different kinds of forecasting approaches and technology used by supply chain node enterprises.

Suggested Citation

  • Juping Shao & Yanan Sun & Bernd Noche, 2015. "Demand Forecasting Dynamic Equation Model," Springer Books, in: Optimization of Integrated Supply Chain Planning under Multiple Uncertainty, edition 127, chapter 0, pages 37-55, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-47250-7_3
    DOI: 10.1007/978-3-662-47250-7_3
    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.

    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:spr:sprchp:978-3-662-47250-7_3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.