IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v201y2024ics0040162524000520.html
   My bibliography  Save this article

The impact of healthcare 4.0 technologies on healthcare supply chain performance: Extending the organizational information processing theory

Author

Listed:
  • Saha, Esha
  • Rathore, Pradeep

Abstract

Increasing supply chain performance in an uncertain environment is a challenge for every industry, predominantly, healthcare sector. To address such issues, there is an urgent need for healthcare organizations like hospitals to build new capabilities. We suggest using organizational information processing theory (OIPT) as theoretical foundation for developing research model that investigates how healthcare 4.0 technologies (big data analytics, artificial intelligence and blockchain) enhance hospital supply chain processes and thereby the performance. According to our analysis of survey data from around 255 hospital managers in Indian hospitals, the three hospital supply chain processes, viz., operations, innovations, and risk management, and the supply chain performance are significantly impacted by these healthcare 4.0 technologies. Additionally, hospital supply chain operations and innovations partially mediate the association between healthcare 4.0 technologies and performance. We also found, the interaction between healthcare 4.0 technologies and hospital supply chain operations is moderated by type of healthcare organizations (private, and public hospitals). In addition to extending and validating the OIPT in context of digital hospital supply chains, these findings offer healthcare professionals empirical evidence to further maximize the benefits of healthcare 4.0 technologies for sustained hospital supply chain performance and integrate digital supply management into health system development.

Suggested Citation

  • Saha, Esha & Rathore, Pradeep, 2024. "The impact of healthcare 4.0 technologies on healthcare supply chain performance: Extending the organizational information processing theory," Technological Forecasting and Social Change, Elsevier, vol. 201(C).
    • Handle: RePEc:eee:tefoso:v:201:y:2024:i:c:s0040162524000520
    DOI: 10.1016/j.techfore.2024.123256
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162524000520
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2024.123256?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:eee:tefoso:v:201:y:2024:i:c:s0040162524000520. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.