IDEAS home Printed from https://ideas.repec.org/a/ids/ijmdma/v22y2023i2p123-159.html
   My bibliography  Save this article

Modelling the causal relationships of the readiness factors for industrial internet of things adoption using DEMATEL-based rough set theory

Author

Listed:
  • Detcharat Sumrit

Abstract

Adopting an emerging technology such as IIoT is a complex process with high risks and failure rate. Therefore, a profound understanding of readiness factors and interrelationships prior to adoption is essential for manufactures. This paper proposes a model framework of the causal relationships of the readiness factors for IIoT adoption using decision-making trial and evaluation laboratory (DEMATEL)-based rough set theory (RST). DEMATEL is to identify the interrelationships among readiness factors, while RST is to capture the ambiguity and subjective information in the decision-making process. The proposed framework is illustrated by taking a case of Thai agro-food processing industry. The finding suggests that the Thai agro-food processing industry needs to focus on three main readiness factors being 'top management support and commitment', 'digital business model' and 'strategic technology roadmap for digitalisation', respectively. This study also provides a deep insight to adopt IIoT for better understanding of the essential readiness factors.

Suggested Citation

  • Detcharat Sumrit, 2023. "Modelling the causal relationships of the readiness factors for industrial internet of things adoption using DEMATEL-based rough set theory," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 22(2), pages 123-159.
    • Handle: RePEc:ids:ijmdma:v:22:y:2023:i:2:p:123-159
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=129832
    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:ijmdma:v:22:y:2023:i:2:p:123-159. 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=19 .

    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.