Cloud computing at a cross road: quality and risks in Higher Education

Ali, MB ORCID: https://orcid.org/0000-0001-5854-8245 2019, 'Cloud computing at a cross road: quality and risks in Higher Education' , Advances in Internet of Things, 9 , pp. 33-49.

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Abstract

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.

Item Type:	Article
Schools:	Schools > Salford Business School
Journal or Publication Title:	Advances in Internet of Things
Publisher:	Scientific Research Publishing
ISSN:	2161-6817
Depositing User:	Dr Mohammed Ali
Date Deposited:	09 Sep 2022 06:53
Last Modified:	09 Sep 2022 08:00
URI:	https://usir.salford.ac.uk/id/eprint/64820

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