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Vol.14, No.4, November 2025. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Adoption of Generative Artificial Intelligence: The Roles of Perceived Usefulness, Self-Efficacy, and Workload
Yann-Jy Yang, Sheng-Hsiang Yang, Ko-Hui Wu, Ruei-Xu Zhang, Chih-Chien Wang
© 2025 Chih-Chien Wang, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 14, Issue 4, Pages 2926-2934, ISSN 2217-8309, DOI: 10.18421/TEM144-03, November 2025.
Received: 21 January 2025. Revised: 22 July 2025.
Abstract:
As generative artificial intelligence (Generative AI) continues to advance rapidly, its applications have become increasingly prevalent. However, uncertainties persist regarding users' attitudes and willingness to adopt Generative AI. This study integrates Task-Technology Fit and Self-Efficacy Theories to examine key factors influencing Generative AI adoption. The study conducted an empirical survey (n=336) and revealed that workload, AI self-efficacy, and perceived usefulness significantly impact adoption. These findings contribute to theoretical advancements and offer practical recommendations for facilitating Generative AI implementation in business contexts.
Keywords – Artificial Intelligence, Generative AI, self-efficacy, workload, perceived useful, task-technology fit theory. |
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