IDEAS home Printed from https://ideas.repec.org/a/igg/jisscm/v18y2025i1p1-27.html
   My bibliography  Save this article

The Impact of Big Data Analytics on Sustainable Competitive Advantage Through Operational Engagement and Knowledge Process: A Hybrid ML-PLS Model Analysis in GCC Region

Author

Listed:
  • Ahmad Aburayya

    (City University, Ajman, UAE)

Abstract

The main goal of this study is to assess the maturity of BDA-AI technology implemented by medical equipment suppliers in the healthcare industry. Furthermore, it aims to measure the influence of this technology on the supplier's sustainable competitive advantage, which is mediated by operational business engagement and knowledge processes. This study utilised a cross-sectional design and an explanatory survey as a deductive method for hypothesis formation. The principal data gathering strategy entailed the self-administration of a questionnaire to medical equipment suppliers situated in the GCC. Out of 656 questionnaires distributed to medical equipment vendors, 483 were deemed usable, resulting in a response rate of 73.6%. The study employed Partial Least Squares Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN) methodologies to assess the collected data.

Suggested Citation

  • Ahmad Aburayya, 2025. "The Impact of Big Data Analytics on Sustainable Competitive Advantage Through Operational Engagement and Knowledge Process: A Hybrid ML-PLS Model Analysis in GCC Region," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global Scientific Publishing, vol. 18(1), pages 1-27, January.
    • Handle: RePEc:igg:jisscm:v:18:y:2025:i:1:p:1-27
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJISSCM.389021
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jisscm:v:18:y:2025: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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.