IDEAS home Printed from https://ideas.repec.org/a/ids/ijpqma/v31y2020i1p1-27.html
   My bibliography  Save this article

An interpretative structural modelling approach to analysing root causes of defective jobs: a case study in an automobile service industry

Author

Listed:
  • Dharyll Prince Abellana

Abstract

This paper addresses, explores, and analyses one of the critical productivity and quality problems in the automobile service industry, which is defective jobs or rework due to bad repairs through a case study conducted in Cebu City, Philippines. The paper determined 22 potential causes of the quality problem through the focus group discussion. An interpretative structural modelling is adopted to model the interrelationships of the identified causes in a hierarchical structure. The study has two primary outputs: 1) a list of potential causes of defective jobs; 2) a digraph presenting the interrelationships of the determined causes. The results of this study will significantly contribute to the literature as it provides scholars insights as well as a methodology to analyse quality problems in a causal analysis environment. Moreover, it will also be beneficial to practitioners as it provides them with essential managerial insights that can be useful in practice.

Suggested Citation

  • Dharyll Prince Abellana, 2020. "An interpretative structural modelling approach to analysing root causes of defective jobs: a case study in an automobile service industry," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 31(1), pages 1-27.
    • Handle: RePEc:ids:ijpqma:v:31:y:2020:i:1:p:1-27
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=109327
    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:31:y:2020:i:1:p:1-27. 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.