Dr Mohammed Albakri m.albakri@salford.ac.uk
Lecturer
The key determinants of cloud computing provide a convincing argument for HEIs and its stakeholders to adopt the innovation. These benefits re- flect the essential quality characteristics of the cloud, such as Broad network Access; Measured Service; On-demand Self-Service; Rapid Elasticity; and Re- source Pooling. However, there are also risks associated with the cloud, lead- ing to non-adoption, such as Confidence, Privacy, Security, Surety and Trust. Understanding the impact of these factors can support multiple stakeholders, such as students, lecturers, senior managers and admins in their adoptive de- cision of CC in their respected institutions. Using the Multiview 3 (MV3) methodology, a research model was proposed to explore the key qualities and risks that determine the adoption or non-adoption of CC by UK HEIs from multiple perspectives. An exploratory qualitative study was con- ducted on 32 University stakeholders across 2 UK Universities. The find- ings suggest that security, privacy and trust are the key determinants to non-adoption as participants felt that the cloud cannot fully guarantee the safeguarding of sensitive information. Determinants to cloud adoption in- clude improving relationships between students and teachers via collabo- rative tools, in addition to proposing cloud apps for mobile devices for ac- cessing virtual learning materials and email securely off-campus. In con- clusion, University stakeholders are still at a cross-road when it comes to cloud adoption, but future advances of the cloud may help to steer their decision to adopt this innovative technology given its overwhelming po- tential.
Ali, M. (2019). Cloud computing at a cross road: quality and risks in Higher Education. Advances in internet of things, 9, 33-49. https://doi.org/10.4236/ait.2019.93003
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 2, 2019 |
Publication Date | Jul 5, 2019 |
Deposit Date | Sep 9, 2022 |
Publicly Available Date | Sep 9, 2022 |
Journal | Advances in Internet of Things |
Print ISSN | 2161-6817 |
Electronic ISSN | 2161-6825 |
Publisher | Scientific Research Publishing |
Volume | 9 |
Pages | 33-49 |
DOI | https://doi.org/10.4236/ait.2019.93003 |
Publisher URL | https://doi.org/10.4236/ait.2019.93003 |
Published Version
(402 Kb)
PDF
Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Understanding big data driven decision making in British
financial organisations
(2022)
Presentation / Conference
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search