Predicting the adoption of cloud-based technology using fuzzy analytic hierarchy process and structural equation modelling approaches

Abstract

With the emergence of cloud-based technology, personalized learning mechanism has increasingly become a fundamental requirement for most learning systems. This study aimed to identify the key factors that influence user adoption of cloud-based collaborative learning technology in the educational context. Grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT), personalization construct was linked to the behavioral intention, performance expectancy and effort expectancy. This research applied a new methodological approach combining both Fuzzy Analytic Hierarchy Process (FAHP) and Structural Equation Modelling (SEM) to determine the relative weight and importance of the factors as well as to test the proposed hypotheses in the research model. Using a survey questionnaire, data was collected from 150 students of four Malaysian public universities. The findings of FAHP demonstrated that performance expectancy, social influence, and personalization were the most important factors predicting behavioral intention to adopt cloud-based collaborative learning technology from experts’ point of view. The results of the SEM showed that users’ behavioral intention was significantly influenced by performance expectancy, effort expectancy, social influence and personalization. Although, personalization performed a direct influence on behavioral intention, its indirect influence through performance expectancy and effort expectancy was also considerable. This study and its findings can serve as a baseline by which cloud service providers, ministry of education, and educational institutions can make strategic and strong decisions about adoption of cloud-based technology in educational environments.