Ethics Awareness As A Moderating Factor In Generative AI Adoption Among Business School Students
DOI:
https://doi.org/10.29284/ijasis.12.1s.2026.181-192Keywords:
Adoption Determinants, Artificial Intelligence, Business Schools, Ethics Awareness, Moderating FactorAbstract
The rapid proliferation of generative artificial intelligence (GAI) tools has transformed higher education, raising urgent questions about their ethical use and acceptance. This study examines the moderating effect of ethics awareness on the adoption of GAI among business school students in the Baltic Sea region. Designing on the Unified Theory of Acceptance and Use of Technology (UTAUT2) and its extensions, the research integrates constructs of performance expectancy, effort expectancy, social influence, study value, habit, and ethics awareness. A survey of 441 students across Baltic Sea region business schools was analyzed using partial least squares structural equation modeling (PLS-SEM).
Results indicate that performance expectancy, social influence, study value, habit, and ethics awareness significantly predict GAI use, whereas effort expectancy has a limited influence. Habit emerged as the strongest driver, underscoring the importance of routinized engagement. Moderation analyses reveal that ethics awareness amplifies the effects of social influence and habit but attenuates the impacts of performance expectancy, effort expectancy, and study value. These findings suggest that ethical sensitivity does not discourage adoption but channels it toward socially validated and responsible practices.
The study contributes to theory by extending UTAUT2 with ethics awareness as a critical construct and offers practical implications for business schools. Embedding ethical literacy alongside technical proficiency is crucial to ensure the responsible integration of AI. Limitations include regional sampling; future research is encouraged to explore cross-cultural contexts and longitudinal adoption patterns.
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This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
