Recent studies have stressed the importance of CC in a number of HEIs situated around the world [1] [3] [4] [13] [19] [20] [21] [22] [23]. Several studies have found that governments, in particular, are now backing CC initiatives in HEIs, namely Universities and Colleges who also purchase CC service third-party vendors [10] [11], as well as establish their own CC environments [9].

There is a myriad of research that supports the linkage between CC and HEIs, as well as the adoption and use of the technology at a user level, namely by students [24] - [29]. By employing TAM3 (Technology Acceptance Model), researchers have been able to demonstrate the acceptance or adoption of CC by students [25]. On an organisational level, Behrend [25] found that cost-effectiveness is considered as the key influencing factor toward the acceptance of CC [25]. Although Behrend [25] [26] did not study the levels of CC adoption and acceptance by teachers, they did exhibit “clear differences” in terms of their system needs when questioned.

HEIs are now moving to the cloud for a number of reasons [27], especially for economic purposes [30] [31]. In the context of education, Katzan [32] found that CC balances both economies of scale and control, providing a lower total cost of ownership. This is heavily linked to the quality of CC, which influences HEIs’ adoptive decision. This paper has defined quality as the key elements or characteristics, which make CC a powerful and viable technology to adopt, as well as reflecting the efficient and economic nature of the cloud.

Mell and Grance [33] identified five essential quality characteristics of the cloud:

· Broad Network Access: users can access network resources from a range of devices;

· Measured Service: the cloud can automatically control and enhance resource use via the introduction of a measured service, which can be altered to suit the needs of the HEI. This is a highly efficient and cost-effective aspect of the cloud as a metering service only allows users to pay for what they use, and thus no money is wasted on downtime;

· On-demand Self-Service: this enables students, teachers and admins, among other key HEI stakeholders (users) to have anytime, anywhere access to a number of cloud resources, such as email, storage and applications without human interaction with the service vendor;

· Rapid Elasticity: similar to measured service, rapid elasticity is the process of adjusting cloud system resources to meet user demands;

· Resource Pooling: this refers to the use of cloud resources via a network, and cloud vendors use shared computing resources to provide cloud services to their users [33] [34] [35].

The above quality characteristics are all linked to the advantages of adopting CC, particularly in terms of cost-effectiveness and the deployment of hardware and software [36]. CC enables HEIs to develop quality, low-cost education at a global level. Not only that, Shayan [37] found that depending on individual machines to meet computing needs is no longer financially justified. Similarly, Seigle [38] found that aggregating IT services also justifies the quality and efficient nature of the cloud, ranging from personnel and expertise to licencing.

Quality aspects of the cloud, as well as cost reductions and rapid developments in modern technologies, are clear justifications for CC adoption by HEIs [1] [27]. Sultan [1] found that the quality cloud improves efficiency, reduces costs, and is an ideal model for the education sector. The customisability of cloud services, as well as the pay-as-you-go metered service, have a significant effect on the financial decisions associated with IT spending. Therefore, CC encompasses a paradigm shift for various IT developments in HEIs.

Despite these compelling arguments for the adoption of CC via the quality aspects of the technology, there are, however, a number of risks associated with the cloud, which can sway HEIs’ adoptive decision, leading to non-adoption. The risks associated with the cloud leading to non-adoption, include confidence, surety and trust [37] [39] [40] [41] [42].

Confidence refers to users’ willingness and readiness to use and accept a cloud solution; this is a branch of cultural resistance in which users may reject the technology purely based on their unfamiliarity and the unwillingness to adapt to change [11]. Surety refers to the cloud solution delivering its intended purpose, which with new innovations can be uncertain since this is a novel technology, which many users will not be accustomed to. Trust refers to users’ acceptance of the cloud solution based on having full confidence in the technology, but given the many potential risks of novel technologies, users will more than likely not trust the innovation [1].

For example, Reeves, Blum [43] founds that “building an IT organization’s confidence in a solution requires a combination of consistent performance, verifiable results, service guarantees, transparency, and plans for contingencies” (p.33). It is clear that the majority of cloud services have a poor track record when it comes to building trust when migrating from existing services to a new solution that is supposed to add quality and benefit, given that it is a relatively new technology with potential uncertainty [41]. The cloud can therefore only flourish with time, experience and reputation. Another issue is that many HEIs are unskilled and lack the required knowledge to manage risk, as well as service performance at a third party service level, all of which requires a degree of confidence [37]. For example, a lack of confidence in CC in the commercial sector stems from:

· Poor risk management skills;

· Vendor lock-in;

· Management issues;

· Market immaturity;

· Inadequate or absent service level agreements (SLA).

In HEIs, similar issues occur via the concerns which are influenced by a lack of trust in such institutions to deliver quality cloud services to their stakeholders. Katz, Goldstein [41] found that Institutional culture is cited as a barrier to adopting the cloud. In other words, would the cloud solution be compatible with the HEIs needs and expectations? Another issue cited by Katz is IT security and privacy is given the regulatory compliance limiting potential adoption of CC. Potential adopters stressed that they would only be persuaded to move to the cloud if the security and privacy issues surrounding the cloud are addressed.

In short, CC is becoming heavily linked to e-learning systems in HEIs. Previously, conventional e-learning systems were only endogenous to HEIs [44]. CC can offer its stakeholders, such as students, teachers and admins, a quality low-cost computing solution, as well as the ability to develop virtual computing environments, especially in areas, such as distance or online learning and science education [3]. However, CC is still a relatively new technology that is vulnerable to risk, but with a long-term commitment, time and experience, potential adopters will begin to realise the true quality of this fascinating and innovative piece of computing technology. Therefore, this leaves potential stakeholders of CC at a cross-road. Please refer to Table 1 for a full summary of the quality and risks of CC.

The multiview framework, developed by Avison and Wood-Harper and the more recent multi-view 3 (MV3) framework by Bell and Wood-Harper [45] is an approach that support the analysis, design and the development of information systems (IS), as well as evaluating possible solutions to IS related issues from a number of perspectives. Using a soft systems approach, it draws on a number of elements, such as human activity systems, socio-technical systems, data analysis and structured analysis, besides tackling the different perspectives of people using IS. In other words, multiview helps to determine multiple perspectives through individual perceptions of the IS development process or in the context of this research the quality and risks of adopting a cloud solution in HEIs. Therefore, this research used the MV3 model to explore the quality and risks of CC in higher education. Further, the MV3 model is a novel framework, particularly to the CC and educational areas as to the researcher’s knowledge, no previous studies have applied such a model in this context.

Multiview can be used by researchers to explore the quality and risks associated with the adoption of technological innovation from multiple

perspectives [45] [46]. The model comprises of three perspectives: technical, organisational and personal [45]. In the current study, the technical perspective refers to the quality (or characteristics) and risks of the cloud, which influence adoption. The organisational perspective refers to HEIs, namely Universities’ and their decision to adopt the technology based on weighing the pros and cons of the cloud solution. The personal perspective refers to the individuals involved with the system, namely stakeholders, such as students, teachers, senior management and admins, as well as their needs and expectations from the cloud solution.

The proposed model has been inspired by the MV3 model by Bell and Wood-Harper [45]. It includes a number of elements, such as key stakeholders involved in the CC adoption process (personal), quality and risks of the cloud system (technical), and the targeted institution, UK Universities (organisational). Figure 1 demonstrates the research model.

The current literature has identified five key quality characteristics of adopting the cloud (Broad network Access; Measured Service; On-demand Self-Service; Rapid Elasticity; and Resource Pooling) [1] [27] [33] - [38]. In addition, five key risks of adopting the cloud (Confidence; Privacy; Security; Surety; and Trust) were also identified [37] [39] [40] [41] [43]. The framework was developed, considering these qualities and risks of the cloud, and consists of three key components.

The first component of the framework involves the multiple perspectives (TOP—Technical: cloud computing, Organisational: universities, and Personal: users i.e. students, teachers, senior management and admins). The next component involves the target institution or context (HEIs) and proposes a potential emerging technology to adopt (CC). The third component assesses the quality and risks of the cloud to influence HEI and stakeholder decisions to adopt CC based on user needs and expectations (outcome).

The following research questions were derived from the review of the current literature on the quality and risks of CC adoption:

RQ1: What quality characteristics of the cloud influence stakeholders’ (students, teachers, senior management and admins) acceptance of CC, leading to adoption?

RQ2: What risks of the cloud influence stakeholders’ (students, teachers, senior management and admins) rejection of CC, leading to non-adoption?

The interview findings of the research are presented in this section. There was a total of 18 University stakeholders who were interviewed, namely University students, lecturers, senior managers and admins, across two UK Universities situated in North-West England in order to determine the quality and risk factors which influence adoption and non-adoption of CC from multiple perspectives (technical, organisational and personal). Thematic analysis was used to analyse the data, where a number of themes were deduced from the findings according to each perspective of the MV3 methodology (see Research Model and Methods chapters). Moreover, Table 2 provides a summary of the research participants:

At a higher theoretical level, this research bridges between technological innovation, as well as IS adoption and development. In the field of technological innovation, this research applied a multi-perspective theory [45] to demonstrate an emerging technology known as cloud computing (CC). In doing so, this research explored the quality and risks of CC from multiple perspectives as a means to determine whether such an innovative solution would be viable for educational settings, namely UK HEIs or Universities. At a lower theoretical level, this research aimed to conceptualise CC adoption and development to determine which quality and risks influence adoption and non-adoption in UK Universities. At the base theoretical level, this research provided a literature review of existing qualities and risks of the cloud to address the current literature gap.

At a methodological level, since the majority of studies in CC adoption are quantitative-based, a qualitative study of CC adoption from multiple perspectives was conducted. To the authors’ knowledge, there are no existing studies that employ the multiview methodology to demonstrate the quality and risks of cloud adoption and development in educational settings. In addition, two case Universities situated in the UK were used to conduct the study where multiple stakeholders, such as students, lecturers, senior managers and admins were interviewed. This helped to develop a coherent and plausible narrative for the quality and risks associated with CC adoption from multipole perspectives.

At a practical level, a CC development framework was proposed based on the MV3 methodology. This framework was used to support the authors during the research process, as well as to determine the key qualities and risks that influence the adoption or non-adoption of CC from multiple perspectives. The key components include multi-perspective factors, namely technical (CC solution); organisational: (Universities), and personal (users i.e. students, teachers, senior management and admins), as well as an assessment of the quality and risks of the cloud to influence HEI and stakeholder decisions to adopt CC based on user needs and expectations (outcome).

One limitation was the limited cases that were used. This research was conducted using only two UK Universities. The research could have benefitted from more cases to obtain more generalised data and broader perceptions of the quality and risks of CC adoption from multiple perspectives. Further, the sample size could have been bigger as 16 participants could have attributed to the narrow perceptions of the quality and risks of CC adoption. Based on this limitation, the research did not fully capture multi-perspective view of CC quality and risks in UK HEIs. It is important for future studies to take on-board these limitations.

Future studies could take the findings of this study and apply them to other countries around the world. A comparative study of the quality and risks of CC in HEIs in developing and developed countries would help to distinguish between different stakeholder needs and expectations of the cloud as a means to facilitate the IS development process. Therefore, this will help future authors to conduct research on multiple case HEIs to obtain broader perceptions of CC in different countries around the world.

This study (to the authors’ knowledge) is the first to explore the determinants of CC adoption by HEIs in terms of quality and risk factors from multiple perspectives. The key quality factors reflected the essential characteristics of the cloud, such as Broad network Access, Measured Service, On-demand Self-Service, Rapid Elasticity, and Resource Pooling. Whereas, Confidence, Privacy, Security, Surety, and Trust were identified as the risk factors of the cloud. Understanding the impact of these factors can support multiple stakeholders, such as students, lecturers, senior managers and admins in their adoptive decision of CC in their respected institutions.

Security was highlighted as a key determinant to non-adoption as safeguarding sensitive information is vital in the cloud and the participants appeared unconvinced about the cloud achieving this. Therefore, trust was another key determinant to non-adoption. However, determinants to cloud adoption included the cloud having the potential to improve relationships between students and teachers via collaborative tools. Students even proposed cloud apps for mobile devices for accessing virtual learning materials and email securely off-campus. Meeting these expectations appear to be a convincing argument for cloud adoption.

In conclusion, it can be deduced that HEIs are in a position to adopt multiple cloud solutions. For example, e-mail and virtual learning services, as well as online collaboration tools and learning management systems to facilitate the teaching process and to build student-teacher relationships. However, the existing security and privacy factors of the cloud still represent a real concern for stakeholders and will more than likely reject the technology, which in turn leaves them at a cross-road. Future studies may help to steer stakeholders’ decision to adopt the cloud as the technology develops in the coming years.

The author would like to thank all of the participating subjects that made this research possible, as well as the author’s colleagues for their input, guidance and feedback about the research.

The authors declare no conflicts of interest regarding the publication of this paper.

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