IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v164y2023ics0148296323003454.html
   My bibliography  Save this article

Challenge or hindrance? How and when organizational artificial intelligence adoption influences employee job crafting

Author

Listed:
  • Cheng, Bao
  • Lin, Hongxia
  • Kong, Yurou

Abstract

While organizations are increasingly adopting artificial intelligence (AI), little is known about employees’ reactions to this new work environment. This study utilizes the transactional theory of stress and coping to establish a framework that examines the impact of organizational AI adoption on employees’ promotion- and prevention-focused job crafting based on the data from a three-wave time-lagged survey of 332 employees of eight companies in Chengdu, China. The findings indicated that the effects of organizational AI adoption on challenge/hindrance appraisals and subsequent job crafting depend on employees’ locus of control. Organizational AI adoption induces challenge appraisals for employees with an internal locus of control and leads to promotion-focused job crafting behaviors. When employees possess an external locus of control, organizational AI adoption induces their hindrance appraisal and leads to prevention-focused job crafting behaviors. These findings have theoretical and practical implications.

Suggested Citation

  • Cheng, Bao & Lin, Hongxia & Kong, Yurou, 2023. "Challenge or hindrance? How and when organizational artificial intelligence adoption influences employee job crafting," Journal of Business Research, Elsevier, vol. 164(C).
    • Handle: RePEc:eee:jbrese:v:164:y:2023:i:c:s0148296323003454
    DOI: 10.1016/j.jbusres.2023.113987
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296323003454
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2023.113987?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hazem Ahmed Khairy & Mohamed Ahmed & Arwa Asiri & Foziah Gazzawe & Mohamed A. Abdel Fatah & Naim Ahmad & Ayman Qahmash & Mohamed Fathy Agina, 2024. "Catalyzing Green Work Engagement in Hotel Businesses: Leveraging Artificial Intelligence," Sustainability, MDPI, vol. 16(16), pages 1-17, August.
    2. Ion Popa & Marian Mihai Cioc & Andreea Breazu & Catalina Florentina Popa, 2024. "Identifying Sufficient and Necessary Competencies in the Effective Use of Artificial Intelligence Technologies," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 1-33, February.

    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:jbrese:v:164:y:2023:i:c:s0148296323003454. 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.elsevier.com/locate/jbusres .

    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.