Analyzing Continuance of Cloud Computing in Higher Education Institutions: Should We Stay, or Should We Go?

Yousef A. M. Qasem, Rusli Abdullah, Yusmadi Yah Jusoh, Rodziah Atan and Shahla Asadi
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Yousef A. M. Qasem: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, Malaysia
Rusli Abdullah: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, Malaysia
Yusmadi Yah Jusoh: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, Malaysia
Rodziah Atan: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, Malaysia
Shahla Asadi: Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia

Sustainability, 2021, vol. 13, issue 9, 1-37

Abstract: Higher Education Institutions (HEIs) consider resource optimization as an essential concern. Cloud computing (CC) in the fourth industrial revolution became the de-facto standard for delivering IT resources and services. CC is now a mainstream technology, andHEIs across the globe are rapidly transitioning to this model; hence, maintaining the retention of the customers of such technologies is challenging for cloud service providers. Current research concerning CC focused on adoption and acceptance. However, there is still a scarcity of research concerning such technology’s continued use in an organizational setting. Drawing on the prior literature in organizational-level continuance, this paper established a positivist quantitative-empirical study to bridge the research gap and assess the precursors for a continuance of cloud technology in HEIs. Subsequently, this study developed a conceptual framework by integrating the IS success model and the IS discontinuance model through the lens of the TOE framework. The data were collected from the decision-makers of Malaysian HEIs that have adopted CC services, and analyzed using Structural equation Modelling (SEM) based on Partial Least Squares (PLS). The results indicate that the continuance intention can be predicted by technology, organizational, environmental, and other contextualized factors, explaining 85.2% of the dependent variables’ variance. The paper closes with a discussion of the research limitations, contribution, and future directions.

Keywords: cloud computing; IS continuance; post adoption; organizational-level analysis; higher education institutions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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