IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i15p7054-d1716957.html
   My bibliography  Save this article

Harnessing Artificial Intelligence and Human Resource Management for Circular Economy and Sustainability: A Conceptual Integration

Author

Listed:
  • Rubee Singh

    (Institute of Business Management, GLA University, Mathura 281406, India
    Department of Management Studies, Kumaun University, Nainital 263001, India)

  • Amit Joshi

    (Department of Management Studies, Kumaun University, Nainital 263001, India)

  • Hiranya Dissanayake

    (Department of Accountancy, Wayamba University of Sri Lanka, Kuliyapitiya 60200, Sri Lanka)

  • Deshika Nainanayake

    (Deshika Nainanayake, School of Business, Western Sydney University, Sydney, NSW 2751, Australia)

  • Vikas Kumar

    (University of Portsmouth, Portsmouth PO1 2UP, UK)

Abstract

In response to global sustainability challenges and digital transformation, this conceptual paper explores the intersection of Artificial Intelligence (AI), Human Resource Management (HRM), and Circular Economy (CE). Drawing on Resource-Based View, Stakeholder Theory, Institutional Theory, and the Socio-Technical Systems perspective, we propose an integrated framework in which AI and HRM function as complementary enablers of sustainable, circular transformation. The framework identifies enablers (e.g., green HRM, digital infrastructure), barriers (e.g., ethical concerns, skill gaps), and contextual mediators. This study contributes to sustainability and digital innovation literature and suggests practical pathways for ethically aligning workforce and AI capabilities in CE adoption.

Suggested Citation

  • Rubee Singh & Amit Joshi & Hiranya Dissanayake & Deshika Nainanayake & Vikas Kumar, 2025. "Harnessing Artificial Intelligence and Human Resource Management for Circular Economy and Sustainability: A Conceptual Integration," Sustainability, MDPI, vol. 17(15), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:7054-:d:1716957
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/15/7054/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/15/7054/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:15:p:7054-:d:1716957. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.