IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v45y2026i4p660-679.html

Examining business students’ intentions to misuse ChatGPT through the lens of deterrence and neutralisation theories

Author

Listed:
  • Sandeep Goyal
  • Sumedha Chauhan
  • Luvai Motiwalla

Abstract

The present study investigated the business school students’ intention to misuse Generative Artificial Intelligence (GenAI) technologies like ChatGPT to complete their academic assignments. This study contextualises the key elements from deterrence and neutralisation theories, including the role of gender, which influence the students’ misuse intention in higher education towards using GenAI to assist in completing their academic work. We collected data from 413 business school students in India who had already used ChatGPT for their academic assignments. The analysis indicates a positive relationship between all neutralisation techniques and misuse intention. Regarding deterrence elements, the severity of formal sanctions, the certainty of shame, and moral beliefs negatively affect the students’ misuse intention. In terms of the moderating influence of gender, we found that male students, as compared to females, are relatively likely to exhibit a greater degree of neutralisation behaviour and a lesser degree of deterrence behaviour. Overall, the results show that neutralisation techniques have a greater impact than deterrence factors in controlling the misuse of GenAI for academic assignments. The study further reflects how the impact of neutralisation constructs and deterrence factors varies between males and females in using GenAI at higher education institutions.

Suggested Citation

  • Sandeep Goyal & Sumedha Chauhan & Luvai Motiwalla, 2026. "Examining business students’ intentions to misuse ChatGPT through the lens of deterrence and neutralisation theories," Behaviour and Information Technology, Taylor & Francis Journals, vol. 45(4), pages 660-679, February.
  • Handle: RePEc:taf:tbitxx:v:45:y:2026:i:4:p:660-679
    DOI: 10.1080/0144929X.2025.2525307
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2025.2525307
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0144929X.2025.2525307?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

    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:taf:tbitxx:v:45:y:2026:i:4:p:660-679. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .

    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.