IDEAS home Printed from https://ideas.repec.org/a/ids/ijpqma/v11y2013i1p57-72.html
   My bibliography  Save this article

Labour productivity measurement through classification and standardisation of products

Author

Listed:
  • Mohammadreza Salehi
  • Hadi Shirouyehzad
  • Reza Dabestani

Abstract

In today's competitive world, productivity is a fundamental concept in assessing economic performance of organisations. Due to the fierce competition and customer requirement variation, organisations should produce various types of products. This type of production requires a sophisticated productivity measurement system and organisations still confront with the challenges of lacking an appropriate system. Labour productivity is one of the most important indices among partial productivity indicators and plays a key role in the productions and services as outcome. In this paper, labour productivity issue is examined by nearest neighbour algorithm (NNA) in order to classify products. In the following, considering the required workforce for standard parts in each category and also their production processes, multiple regression method is applied to calculate the value of products and to standardise outputs. A case study is also presented to examine the validity of proposed method. Some advantages of this method include; increasing labour productivity, improving production system, a more precise planning and responding to market fluctuation.

Suggested Citation

  • Mohammadreza Salehi & Hadi Shirouyehzad & Reza Dabestani, 2013. "Labour productivity measurement through classification and standardisation of products," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 11(1), pages 57-72.
    • Handle: RePEc:ids:ijpqma:v:11:y:2013:i:1:p:57-72
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=50568
    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:ijpqma:v:11:y:2013:i:1:p:57-72. 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=177 .

    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.