Ndagi, Abdullahi
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AI Adoption, Technostress, and Knowledge-Sharing Behaviour among University Students Vinahapsari, Cinthia Annisa; Arumsari, Arumsari; Wibowo , Maynard Zac; Zaenah , Eny Rahma; Nguyen, Thi Thu Hang; Ndagi, Abdullahi
TIJAB (The International Journal of Applied Business) Vol. 10 No. 2 (2026): JUNE 2026
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/tijab.v10.I2.2026.86105

Abstract

Background: Despite growing attention to AI in education, existing studies have predominantly focused on learning outcomes and academic performance, while behavioural responses to AI adoption, particularly knowledge-sharing behaviour and the role of technostress, remain underexplored. Moreover, technostress is commonly viewed as a negative consequence of technology use, with a limited understanding of its potential role in stimulating adaptive collaborative behaviour among university students. Therefore, understanding the psychological and behavioural implications of AI adoption has become crucial to investigate in higher education contexts. Objective: This study examines the relationship between AI adoption and technostress, as well as knowledge-sharing behaviour, among university students. Method: A quantitative survey was conducted with 105 first-semester students who had experience using AI in their academic tasks. After screening, 84 valid responses were analysed using Partial Least Squares Structural Equation Modeling. Results: AI adoption significantly increases technostress. Unexpectedly, technostress is positively associated with knowledge-sharing behaviour rather than negatively, as commonly assumed. This finding aligns with the Job Demands–Resources (JD-R) perspective, in which technological demands may also stimulate adaptive collaboration. However, technostress does not significantly mediate the relationship between AI adoption and knowledge-sharing behaviour. Conclusion: By showing that technostress can serve as a context-dependent challenge that fosters, rather than suppresses, collaborative behaviour in AI-supported learning settings, this study contributes to the organizational behaviour literature. It further reveals that knowledge sharing is driven more by social adaptation than by technological pressure, offering new insight into how students respond to AI adoption in universities. Keywords: AI adoption; knowledge-sharing behaviour; organizational behaviour; technostress; university students