Identifying the determinants of cloud computing adoption in higher education institutions

Mokhtar, Shamsul Anuar; Al-Sharafi, Abdulkarem; Ali, Siti Haryani Shaikh; Al-Othmani, Abdulaleem Z.

doi:10.1109/icictm.2016.7890787

Cited by 26 publications

(13 citation statements)

References 20 publications

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“…There are many other factors that also explain the adoption rate in an organization. The existence of theory, framework, and model are proven to help in understanding the factor and the process of adoption of technology innovations [19]. The Technological-Organizational-Environmental (TOE) framework by Tornatzky and Fleischer, the Diffusion of Innovation (DoI) theory by Rogers and the Theory Acceptance Model (TAM) are frequently used among researchers to explain technology innovation in the ICT acceptance and adoption in the organization [20].…”

Section: Introductionmentioning

confidence: 99%

Factors influencing cloud computing adoption in higher education institution

Isa

Suhaimi

Noordin

et al. 2020

IJEECS

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<table width="593" border="1" cellspacing="0" cellpadding="0"><tbody><tr><td valign="top" width="387"><p>There are few studies on factors influencing cloud computing adoption in higher education institutions. However, there are lacks of understanding of the cloud computing adoption issues in the university. The main objective of this study is to investigate factors influencing cloud computing adoption in a higher education institution. The research method involved using qualitative interviewing with relevant stakeholders and case study at one public university in Malaysia. The analysis was done by using Atlat.ti. There are eighteen factors that have been coded into three main categories of Technological, Organizational and Environmental. These are among factors to influence the decision of cloud computing adoption for a public university. The first category (Technological) consists of nine factors; (i) relative advantage, (ii) cost reduction, (iii) ease of use, (iv) compatibility, (v) operational requirement, (vi) security, (vii) sustainability, (viii) trialability and (ix) complexity, The second category (organizational) consists of four factors; (i) infrastructure readiness, (ii) top management, (iii) knowledge and IT skillset and (iv) financial. The third category (environmental) consists of five factors; (i) Cloud Service Provider, (ii) Geographical, (iii) Data Privacy, (iv) Guideline and Policy, (v) Service Level Agreement (SLA). The result may provide a reference for the adoption of cloud computing in the area of mobile learning or mobile computing. Future work involves conducting similar studies at other case studies including public and private universities in Malaysia.</p></td></tr></tbody></table>

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Section: Introductionmentioning

confidence: 99%

Factors influencing cloud computing adoption in higher education institution

Isa

Suhaimi

Noordin

et al. 2020

IJEECS

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“…CC is Open Journal of Business and Management a system that uses a network of services hosted remotely on the internet as a means of storing, managing and processing data, as opposed to a local machine or server [23]. There are also various intangible benefits of the cloud, such as cost efficiency, increased collaboration, flexibility and scalability, and greater reliability and accessibility [29] [46] [47] [48] [49].…”

Section: Benefits and Opportunities Of Cloud Computing For Higher Edumentioning

confidence: 99%

Contextual Analysis of Educational Monitoring and Progression as a Service (EMPaaS) System in Higher Education

Ali¹,

Wood–Harper²,

Al-Gahtani³

2019

OJBM

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The arrival of new technologies has opened a window of opportunity for UK higher education institutions. Although UK Higher education (HE) has recently become a huge phenomenon owing to an increase in students attending University, many UK universities are not investing enough in technology to facilitate teaching, management and research practices that aim to improve the student experience. This paper discusses the potential for an information system solution, which can facilitate the institutional practices in UK HEIs from multiple stakeholder perspectives. An existing system employed at a UK University known as "MyPGR" was evaluated in order to shed some light on the existing technical problems UK Universities are currently facing, with the support of a soft systems approach (CATWOE). The proposed solution is the Educational-Monitoring-and-Progression-as-a-Service (EMPaaS), which is based on the Cloud Computing model. EMPaaS has the potential to monitor student progression and key milestones relating to their PGR programme, in addition to enabling students to use free cloud applications to keep track of milestones and progressions. The highly accessible and flexible nature of cloud applications adds to the cost-effectiveness of adopting cloud services, which in turn frees up additional funds for UK Universities to pursue other important investments.

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“…TOE framework used to identify several of adoption process such as adoption decision, techniques of evaluation, proof of concept, the implementation, the challenges, the impact and etc. The TOE framework [6][7][8][9][10][11] and the DOI theory widely used [12,13]. Hence, the framework of adoption factors based on TOE and DOI were developed based on previous researcher's results as in Table 1, for gaining understanding of the adoption process of cloud computing adoption.…”

Section: Introductionmentioning

confidence: 99%

Cloud computing adoption reference model

Isa

Suhaimi

Noordin

et al. 2019

IJEECS

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<span>This paper presents a study to conceptualize a cloud computing adoption reference model. The case study on the cloud computing adoption was done in one local public university in Malaysia. The case study was conducted to understand in-depth and real context phenomenon by investigating the influencing factors of cloud computing adoption. The main objective of this study is to design a cloud computing adoption reference model. This study applied Technology-Organizational-Environmental (TOE) Framework by Tornatzky & Fleischer and Diffusion of Innovation by Rogers as the theoretical background of the Cloud Computing Adoption Reference. Ten interviews were conducted with key informants. The theme pattern analysis of data were done by using qualitative computer programs, Atlas.ti. The findings are shown in summarize patterns that supports the conceptualization of cloud computing adoption reference model. Future work include the adaption of cloud computing adoption reference model specifically for the niche area of mobile computing.</span>

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Identifying the determinants of cloud computing adoption in higher education institutions

Cited by 26 publications

References 20 publications

Factors influencing cloud computing adoption in higher education institution

Factors influencing cloud computing adoption in higher education institution

Contextual Analysis of Educational Monitoring and Progression as a Service (EMPaaS) System in Higher Education

Cloud computing adoption reference model

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