An Empirical Study on College Students’ Behavioral Intention to Use Generative Artificial Intelligence
An Integrated Model Based on the Innovation Diffusion Theory and Trust Theory
Bibliographic Data
| ID | 22006149 |
|---|---|
| Authors | Tao Luo (0000-0001-9959-2453, Guangdong Polytechnic Normal University, corresponding author), Shuyan Cao (Guangdong Polytechnic Normal University) |
| Year | 2026 |
| Volume | 16 |
| Issue | 1 |
| Publication date | 2026-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | SAGE Open (JOURNAL) |
| Journal identifiers | ISSN: 2158-2440 • E-ISSN: 2158-2440 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/21582440251409860 |
| OpenAlex | W7118905820 |
| Language | EN |
| References cited | 99 |
This study, grounded in Innovation Diffusion Theory and Trust Theory, examines the factors influencing college students’ intention to adopt generative AI. A survey of 586 randomly selected students gathered self-reported data on eight factors: relative advantage, compatibility, complexity, observability, trialability, perceived usefulness, trust, and behavioral intention. Using structural equation modeling (SEM), the study analyzed the relationships among these factors. The results showed that relative advantage did not significantly impact perceived usefulness or behavioral intention. Complexity negatively affected behavioral intention but no significant impact on perceived usefulness. Compatibility, observability, and trialability positively influenced both perceived usefulness and behavioral intention. Perceived usefulness positively affected trust and behavioral intention, and trust also positively influenced behavioral intention. Mediation analysis showed that trust partially mediated the relationship between perceived usefulness and behavioral intention. Additionally, perceived usefulness acted as a partial mediator in the relationships between compatibility, observability, trialability, and behavioral intention. Gender moderated the relationship between perceived usefulness and trust, indicating gender differences in trust-building. The study offers valuable insights into students’ behavioral intention to use generative AI and offers practical recommendations for promoting the technology in education
Behavioral modeling · Empirical research · Generative grammar · Generative model · Mediation · Structural equation modeling · Survey data collection · Theory of planned behavior · AI in Service Interactions · Diverse Interdisciplinary Research Innovations · Technology Adoption and User Behaviour
Structural Equation Modeling with Mplus
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R
Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence
Students’ voices on generative AI
Testing measurement invariance of composites using partial least squares
Factors influencing autonomous vehicle adoption
Generative AI and the future of education
Mediation analysis in partial least squares path modeling
Chatting and cheating
Common method biases in behavioral research
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
User Acceptance of Computer Technology
An Integrative Model of Organizational Trust
Self-Reports in Organizational Research
An Integrated Framework Approach to Understanding Vietnamese People’s Intention to Adopt Smart Home Solutions
Exploring University Students’ Adoption of ChatGPT Using the Diffusion of Innovation Theory and Sentiment Analysis With Gender Dimension
A Multi-Industry Analysis of the Future Use of AI Chatbots
Embracing or rejecting AI? A mixed-method study on undergraduate students’ perceptions of artificial intelligence at a private university in China
Unlocking innovation
Consumer experience and perception in gamification marketing
Determinants of Intention to Use Artificial Intelligence-Based Diagnosis Support System Among Prospective Physicians
The Impact of Massive Open Online Courses (Moocs) on Knowledge Management Using Integrated Innovation Diffusion Theory and the Technology Acceptance Model
A Primer on Generative Artificial Intelligence
Understanding teachers’ willingness to use artificial intelligence-based teaching analysis system
Exploring college students' risk perception and acceptance intention of facial recognition technology in China
Is ChatGPT scary good? How user motivations affect creepiness and trust in generative artificial intelligence
Participant or spectator? Comprehending the willingness of faculty to use intelligent tutoring systems in the artificial intelligence era
Classroom anxiety, learning motivation, and English achievement of Chinese college students
Twenty-four years of empirical research on trust in AI
Interactivity, humanness, and trust
How to Increase Sport Facility Users’ Intention to Use AI Fitness Services
Impact of Motivation Factors for Using Generative AI Services on Continuous Use Intention
The role of changes in pronunciation ability and anxiety through Gen-AI on EFL learners’ self-directed speaking motivation and social interaction confidence - A CHAT perspective
Key factors influencing intention to use ChatGPT
Back-Translation for Cross-Cultural Research
| Citation velocity | historical |
|---|---|
| Highly cited | No |