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Autor/inn/enYadegaridehkordi, Elaheh; Nilashi, Mehrbakhsh; Shuib, Liyana; Samad, Sarminah
TitelA Behavioral Intention Model for SaaS-Based Collaboration Services in Higher Education
QuelleIn: Education and Information Technologies, 25 (2020) 2, S.791-816 (26 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1360-2357
DOI10.1007/s10639-019-09993-1
SchlagwörterCollege Students; Student Attitudes; Adoption (Ideas); Computer Uses in Education; Information Storage; Users (Information); Intention; Foreign Countries; Performance; Social Influences; Self Efficacy; Cooperative Learning; Peer Influence; Familiarity; Predictor Variables; Malaysia
AbstractDespite 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. (As Provided).
AnmerkungenSpringer. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2022/1/01
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