Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach
ژورنال:Information & Management
سال:November 2015
قیمت اصلی:35.95$
Highlights
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All six theoretical models have good explanatory power of behavioral intention (BI).
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Based on variance explanation, the motivational model (MM) and the technology acceptance model (TAM) have stronger explanatory powers.
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The theory of planned behavior (TPB) and the TAM have larger effect size compared to other theories.
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Perceived usefulness (PU), attitude (ATT), cloud service quality (CSQ), perceived behavior control (PBC), result demonstration (RD), visibility (VIS), and cloud self-efficacy (CSE) are important factors of a unified model.
Abstract
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.
Keywords
- Cloud computing classroom, Innovation, Behavioral intention, Self efficacy (SE),Service quality (SQ), Innovation diffusion theory (IDT)
Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach
