IDEAS home Printed from https://ideas.repec.org/a/ids/ijient/v9y2022i2p142-162.html
   My bibliography  Save this article

Sustainable supply chain risk mitigation: a mixed method approach

Author

Listed:
  • Madhukar Chhimwal
  • Saurabh Agrawal
  • Girish Kumar

Abstract

The objective of this research is to find a way to minimise risk in the supply chain by identifying the critical success factors and analysing the relationship between sundry critical success factors. The proposed study constructs a model of the critical success factors using the interpretive structural modelling approach and tests the model using regression analysis technique. Analysis of the results indicates that there are some critical success factors which have high driving power and low dependence that require utmost attention and are of great paramount while other cluster consists of those critical success factors which are highly dependent and need futuristic actions. In this work, only regression analysis technique is used to validate the model that is developed using interpretive structural modelling approach. This type of relegation will help the supply chain managers to distinguish between independent and dependent critical success factors and how the relationships among the critical success factors will efficaciously minimise the risk in a supply chain. This study can be considered as a base study for the practitioners and academicians who are working in the area of risk management for achieving sustainability in the supply chain.

Suggested Citation

  • Madhukar Chhimwal & Saurabh Agrawal & Girish Kumar, 2022. "Sustainable supply chain risk mitigation: a mixed method approach," International Journal of Intelligent Enterprise, Inderscience Enterprises Ltd, vol. 9(2), pages 142-162.
  • Handle: RePEc:ids:ijient:v:9:y:2022:i:2:p:142-162
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=121744
    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:ijient:v:9:y:2022:i:2:p:142-162. 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=167 .

    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.