IDEAS home Printed from https://ideas.repec.org/a/eee/techno/v149y2026ics0166497225001890.html

Digital divide in industry 5.0: Role of generative AI knowledge bases and intellectual capital in organizational resilience performance under territorial proximity

Author

Listed:
  • Abbas, Jawad
  • Dabić, Marina
  • Stojčić, Nebojša

Abstract

Generative AI knowledge bases (Gen AI-KB) are changing the strategies of companies that want to assert themselves in the age of Industry 5.0. But how can firms effectively utilise these advanced resources to strengthen their resilience and achieve superior performance levels? Based on the knowledge-based view (KBV), this study examines the mediating role of organisational resilience in the relationship between Gen AI-KB, intellectual capital, and organisational competitiveness and creative performance. The analysis of data from 279 Turkish manufacturing firms, using structural equation modelling (SEM), shows that both Gen AI-KB and intellectual capital significantly increase resilience, forging an important link between internal knowledge assets and firm performance. Multi-group analysis has shown that geographical contexts, such as the urban-rural divide, can significantly influence these dynamics. The findings of this study highlight the potential that generative AI and intellectual capital have to promote resilience and innovation, allowing firms to capitalise on the opportunities presented by Industry 5.0.

Suggested Citation

  • Abbas, Jawad & Dabić, Marina & Stojčić, Nebojša, 2026. "Digital divide in industry 5.0: Role of generative AI knowledge bases and intellectual capital in organizational resilience performance under territorial proximity," Technovation, Elsevier, vol. 149(C).
  • Handle: RePEc:eee:techno:v:149:y:2026:i:c:s0166497225001890
    DOI: 10.1016/j.technovation.2025.103357
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0166497225001890
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.technovation.2025.103357?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

    for a different version of it.

    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:eee:techno:v:149:y:2026:i:c:s0166497225001890. 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/01664972 .

    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.