Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach

Cloud computing is an innovative information technology that has been applied to education and has facilitated the development of cloud computing classrooms; however, student behavioral intention (BI) toward cloud computing remains unclear. Most researchers have evaluated, integrated, or compared only few theories to examine user BI. In this study, we tested, compared, and unified six well-known theories, namely service quality (SQ), self-efficacy (SE), the motivational model (MM), the technology acceptance model (TAM), the theory of reasoned action or theory of planned behavior (TRA/TPB), and innovation diffusion theory (IDT), in the context of cloud computing classrooms. This empirical study was conducted using an online survey. The data collected from the samples (n = 478) were analyzed using structural equation modeling. We independently analyzed each theory, by formulating a united model. The analysis yielded three valuable findings. First, all six theoretical models and the united model exhibited adequate explanatory power. Second, variance explanation, Chi-squared statistics, effect size, and predictive relevance results revealed the ranking importance of the theoretical models. Third, the united model provided a comprehensive understanding of the factors that significantly affect the college students' BI toward a cloud computing classroom. The discussions and implications of this study are critical for researchers and practitioners.