IDEAS home Printed from https://ideas.repec.org/a/ids/ijbfmi/v5y2019i1p56-70.html
   My bibliography  Save this article

A comparative study of forecasting methods for sporadic demand in an auto service station

Author

Listed:
  • Rahul S. Mor
  • Jitendra Nagar
  • Arvind Bhardwaj

Abstract

Spare parts are essential in the automobile sector and forecasting of spare parts has always been the vital prospects in an automobile service parts station. In this paper, a comparison and efforts have been made at the service station of a reputed organisation to reduce the errors in demand forecasting of intermittent demand items. The errors are compared for various methods using mean absolute scaled error (MASE) and Syntetos and Boylan approximation (SBA) method which exhibited the least error for intermittent demand and lumpy demand pattern. While single exponential smoothing method is used for smooth and erratic demand pattern. All calculations are done in MS Excel and solver tool to find optimal values of smoothing parameters.

Suggested Citation

  • Rahul S. Mor & Jitendra Nagar & Arvind Bhardwaj, 2019. "A comparative study of forecasting methods for sporadic demand in an auto service station," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 5(1), pages 56-70.
    • Handle: RePEc:ids:ijbfmi:v:5:y:2019:i:1:p:56-70
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=99009
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijbfmi:v:5:y:2019:i:1:p:56-70. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=156 .

    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.