IDEAS home Printed from https://ideas.repec.org/a/ids/ijpqma/v37y2022i3p405-421.html
   My bibliography  Save this article

Modelling the enablers of quality management practices using ISM

Author

Listed:
  • H. Mahesh Prabhu
  • Samhit Nayak
  • Sriram Pai
  • Pranith Prabhakar
  • B. Gowrava Shenoy

Abstract

Quality plays a vital role in ensuring customer satisfaction in the recent era of globalisation and quality management practices play a crucial role in achieving quality standards. The purpose of this paper is to represent an approach to the effective implementation of quality management practices by identifying the subtleties between various enablers of quality management. A hierarchical model is developed using interpretive structural modelling (ISM) depicting the mutual relationships among the enablers of quality management practices. The analysis indicates that there is a category of enablers with high driving power and low dependency that needs full focus and has strategic value, whereas another group consists of those variables that are highly dependent and are the resulting behaviour. The classification of enablers into independent and dependent variables would enable quality managers to concentrate on the important variables that are the key in building a strong quality management system in the organisation.

Suggested Citation

  • H. Mahesh Prabhu & Samhit Nayak & Sriram Pai & Pranith Prabhakar & B. Gowrava Shenoy, 2022. "Modelling the enablers of quality management practices using ISM," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 37(3), pages 405-421.
  • Handle: RePEc:ids:ijpqma:v:37:y:2022:i:3:p:405-421
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=126931
    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:37:y:2022:i:3:p:405-421. 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.