Editorial
An Examination of Factors Shaping Students’ Acceptance of Generative AI
@ARTICLE{10.4108/eettti.11597, author={Hang Le and Linh Tran Thi My and Dieu Duong Thi Xuan}, title={An Examination of Factors Shaping Students’ Acceptance of Generative AI}, journal={EAI Endorsed Transactions on Tourism, Technology and Intelligence}, volume={3}, number={1}, publisher={EAI}, journal_a={TTTI}, year={2026}, month={3}, keywords={Generative AI, trust, usage-related expectations, education, tourism}, doi={10.4108/eettti.11597} }- Hang Le
Linh Tran Thi My
Dieu Duong Thi Xuan
Year: 2026
An Examination of Factors Shaping Students’ Acceptance of Generative AI
TTTI
EAI
DOI: 10.4108/eettti.11597
Abstract
Recognizing the proliferation of generative artificial intelligence (AI) technologies in facilitating student learning, this study seeks to explore the key drivers shaping students’ intention to use this technology. Grounded in the Stimulus–Organism–Response (S–O–R) framework, we develop an integrative conceptual model and employ PLS-SEM to analyze data collected from 370 tourism students. The article reveals that peer and family influence exert a profound influence on the formation of usage-related expectations and trust. Meanwhile, anthropomorphism serves as an antecedent in shaping perceived usefulness and trust. Trust and perceived ease of use function as organism variables and significantly influence students’ intention. Importantly, trust emerges as a key driver in forming students’ intention to use generative AI. These findings provide implications for academic institutions in formulating AI adoption strategies to enhance teaching and learning practices.
Copyright © 2026 Hang Le Nguyen Tue et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
