A behavioral intention model for SaaS-based collaboration services in higher education - Yadegaridehkordi, Elaheh; Nilashi, Mehrbakhsh; Shuib, Liyana; Samad, Sarminah (Springer, 2020)
Despite numerous potential benefits of cloud computing usage, there are still some users reluctant to adopt this technology. This study aims to investigate the factors that influence student adoption of cloud computing in higher education settings and to generate a set of decision rules to guide through a series of critical decisions needed in this adoption process. Accordingly, a two-stage Structural Equation Modelling (SEM)-Classification and Regression Trees (CART) methodology is applied in order to test the overall research model and related hypotheses as well as to generate decision rules to predict behavioural intention towards adoption. Using survey questionnaire method, a total of 418 valid questionnaires are collected from students of top-ranked Malaysian universities. The results show that task-technology fit, performance expectancy, effort expectancy, social influence, self-efficacy, collaboration technology experience, peer and superior influence and familiarity with group members are significant predictors of intention to adopt cloud computing. The findings of this study can serve as a guideline for the ministry of education, university administrators, and cloud service providers to manage the successful adoption of cloud computing in the education sector. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.