Exploring UTAUT Research in Higher Education: A Bibliometric Analysis and Future Directions in the Era of AI and ChatGPT

Authors

  • Wenjun Mai National Higher Education Research Institute (IPPTN), Universiti Sains Malaysia (USM), Penang, Malaysia
  • Ahmad Zamri Khairani National Higher Education Research Institute (IPPTN), Universiti Sains Malaysia (USM), Penang, Malaysia

DOI:

https://doi.org/10.29333/iji.2026.1924a

Keywords:

bibliometric analysis, UTAUT, Higher education, E-learning, ChatGPT

Abstract

As emerging technologies evolve rapidly, understanding the determinants and barriers influencing technology use in daily life is essential. The Unified Theory of Acceptance and Use of Technology (UTAUT) model offers a valuable framework for analyzing technology adoption and use. This study examines publication trends, thematic themes, keywords, and the evolution of UTAUT research in higher education, while identifying future research directions. A comprehensive bibliometric analysis was conducted using 836 publications retrieved from Scopus (2005–2024). Employing VOSviewer and Bibliometrix, the analysis explores: (1) annual publication outputs, sources, and keywords; (2) publication trends, highly cited works, and leading researchers; (3) co-occurrence networks of UTAUT scholarship in higher education; and (4) thematic clusters and future research directions. The findings reveal steady growth in UTAUT research, reaching a peak in 2022 with 131 publications. Five major thematic clusters were identified, ranging from classical UTAUT constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) to emerging themes such as e-learning adoption, digital trust, and AI-driven tools like ChatGPT. This study highlights a critical transition: UTAUT research in higher education is increasingly intersecting with artificial intelligence, reshaping constructs such as student behavior, intention, and satisfaction. This study contributes to the identification of a transition in UTAUT research, from focusing primarily on adoption factors to engaging with the emerging challenges of artificial intelligence in higher education. This shift highlights how AI-driven educational technologies are reshaping constructs such as intention, behavior, and satisfaction. Practical implications include guiding institutions to design AI-enabled learning systems that enhance engagement. Overall, this research consolidates UTAUT scholarship while offering a forward-looking perspective that positions AI and ChatGPT at the center of higher education’s digital transformation.

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Published

2026-04-01

How to Cite

Mai, W., & Khairani, A. Z. (2026). Exploring UTAUT Research in Higher Education: A Bibliometric Analysis and Future Directions in the Era of AI and ChatGPT. International Journal of Instruction, 19(2), 59–86. https://doi.org/10.29333/iji.2026.1924a

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Section

Articles