Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model
By Cheng-Min Chao. Frontiers in Psychology, 2019
965 citations recorded by the source corpus.
This study developed and empirically tested a model to predict the factors affecting students’ behavioral intentions toward using mobile learning (m-learning). This study explored the behavioral intention to use m-learning from the perspective of consumers by applying the extended unified theory of acceptance and use of technology (UTAUT) model with the addition of perceived enjoyment, mobile self-efficacy, satisfaction, trust, and perceived risk moderators. A cross-sectional study was conducted by employing a research model based on multiple technology acceptance theories. Data were derived from an online survey with 1,562 respondents and analyzed using structural equation modeling. Partial least squares (PLS) regression was used for model and hypothesis testing. The results revealed that (1) behavioral intention was significantly and positively influenced by satisfaction, trust, performance expectancy, and effort expectancy; (2) perceived enjoyment, performance expectancy, and effort expectancy had positive associations with behavioral intention; (3) mobile self-efficacy had a significantly positive effect on perceived enjoyment; and (4) perceived risk had a significantly negative moderating effect on the relationship between performance expectancy and behavioral intention. Our findings correspond with the UTAUT model and provide a practical reference for educational institutions and decision-makers involved in designing m-learning for implementation in universities.
Subfields: Information Systems and Management, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/75ec6a12a62be99761d20b65f7cee5314f5619c6
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Citations in the corpus
- “Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model (2023, methodology): “UTAUT model offers the flexibility to be extended with other constructs to provide a more comprehensive understanding of user behaviour towards technology adoption and use [96].”
- Social Isolation and Acceptance of the Learning Management System (LMS) in the time of COVID-19 Pandemic: An Expansion of the UTAUT Model (2020, background): “Moreover, Chao (2019) aimed to empirically test the factors that influence student’s BI towards mobile learning through the addition of different factors such as perceived enjoyment, satisfaction, trust, risk, and mobile self-efficacy. Taiwo and Downe (2013) and Dwivedi et al. (2011) revealed, in th”