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Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory
8 references·16 citing·46 second hop
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(2025)Perceived risk: The concept and its measurement (1986)Risk Perceptions and Pleasure Travel: An Exploratory Analysis (1992)Risk, uncertainty and the theory of planned behavior: A tourism example (2009)Consumer perceived risk: conceptualisations and models (1999)The role of perceived risk in the quality-value relationship: A study in a retail environment (1999)Enhance green purchase intentions (2012)Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model (2003)Predicting e-services adoption: a perceived risk facets perspective (2003)Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal–Agent Perspective1 (2007)
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References

  • 2003User Acceptance of Information Technology: Toward A Unified View144,945 cited
  • 1960Consumer Behavior as Risk Taking1,879 cited
  • 1993Perceived Risk: Further Considerations for the Marketing Discipline1,349 cited
  • 1972The Components of Perceived Risk1,253 cited
  • 2021Using the UTAUT model to understand students’ usage of e-learning systems in developing countries556 cited
  • 2020Consumers’ Decision-Making Process on Social Commerce Platforms: Online Trust, Perceived Risk, and Purchase Intentions431 cited
  • 2012The history of UTAUT model and its impact on ICT acceptance and usage by academicians259 cited
  • 2021Young Generation’s Mobile Payment Adoption Behavior: Analysis Based on an Extended UTAUT Model182 cited

Cited by

  • 2024Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective143 cited
  • 2024Acceptance of artificial intelligence in university contexts: A conceptual analysis based on UTAUT2 theory125 cited
  • 2023Modeling Students’ Perceptions of Chatbots in Learning: Integrating Technology Acceptance with the Value-Based Adoption Model101 cited
  • 2024Acceptance and use of artificial intelligence and AI-based applications in education: A meta-analysis and future direction76 cited
  • 2025Students' behavioural intention to use content generative AI for learning and research: A UTAUT theoretical perspective

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64 cited
  • 2024Exploring Chinese University Educators’ Acceptance and Intention to Use AI Tools: An Application of the UTAUT2 Model52 cited
  • 2024Users’ continuance intention towards an AI painting application: An extended expectation confirmation model51 cited
  • 2024Driving Factors of Generative AI Adoption in New Product Development Teams from a UTAUT Perspective49 cited
  • 2024Pre-service teachers' technology acceptance of artificial intelligence (AI) applications in education49 cited
  • 2025International perspectives on artificial intelligence in higher education: An explorative study of students’ intention to use ChatGPT across the Nordic countries and the USA49 cited
  • 2024From literacy to learning: The sequential mediation of attitudes and enjoyment in AI-assisted EFL education47 cited
  • 2025Determinants of behavioral intentions and their impact on student performance in the use of AI technology in higher education in Indonesia: A SEM-PLS analysis based on TPB, UTAUT, and TAM frameworks40 cited
  • 2024Factors That Affect the Acceptance of Educational AI Tools by Greek Teachers—A Structural Equation Modelling Study36 cited
  • 2024Adoption of artificial intelligence in higher education: an empirical study of the UTAUT model in Indian universities36 cited
  • 2025Exploring the Factors Influencing AI Adoption Intentions in Higher Education: An Integrated Model of DOI, TOE, and TAM36 cited
  • 2025Drivers of Acceptance of Generative AI Through the Lens of the Extended Unified Theory of Acceptance and Use of Technology35 cited