Doctor of Philosophy
School of Computing and Information Technology
Cloud Computing (CC) is an emerging technology that can potentially revolutionise the application and delivery of IT. There has been little research, however, into the use of CC in Small and Medium-Sized Enterprises (SMEs). With all the promised benefits of cloud computing for cost-cutting, and its perceived advantages to businesses in focusing on their core business activities by outsourcing their IT capabilities to the cloud, the indicators show that CC has been adopted very slowly. Migration to CC has various challenges which go beyond the technology itself. There is also a significant research gap in the investigation of the adoption of this innovation in SMEs. This investigation is imperative because SMEs are the backbone of the economies of many nations in the world and cloud computing can potentially leverage their competitiveness. The business sector, with its characteristics of limited resources, is particularly interesting as cloud solutions can be implemented on a demand basis with no need for initial investment.
In the past few years, rapid advancements and developments in CC have encouraged many organisations in different industries to accept and use it as a beneficial technology. Studies have indicated that CC, enabled through virtualization technologies, has become a useful computing paradigm for businesses. However, CC poses critical issues such as privacy and security, standards, legislations, performance, and servicing costs. The socio-technical context has a strong influence on CC adoption. The heterogeneity of the cloud services is one of the major characteristics of CC.
In Australia, cloud computing is increasingly becoming important, especially with the new accessibility provided by the development of the National Broadband Network (NBN). This infrastructure will give SMEs opportunities of affordable access to computing resources. However, academic studies investigating the socio-technical issues that might be influencing the adoption of CC are scant where the consideration of Australian SMEs are concerned. To fill the void, a research model was developed based on the diffusion of innovation theory (DOI), the technology-organization- environment (TOE) framework, and a review of the relevant literature. Data were collected using mixed methods. The first study was a qualitative study and data was collected from eleven Australian SMEs and four cloud service providers. The second study was a nationwide empirical study with 203 Australian SMEs across the country.
The third study of this research, presents a model to support the decision-making process, using a multi-criteria decision method known as PAPRIKA, for assessing the socio-technical aspects influencing cloud adoption decisions made by SMEs. Due to the multifaceted nature of the CC adoption process, the evaluation of various cloud services and deployment models has become a major challenge. This study presents a systematic approach for evaluating CC services and deployment models. Subsequently, the researcher conducted conjoint analysis activities with five SME decision-makers as part of the distribution process of this decision modelling, based on pre-determined criteria. With the help of the proposed model, cloud services and deployment models can be ranked and selected.
The main contributions of this research are threefold. First, they extend the existing knowledge of CC adoption by Australian SMEs. Second, they provide SMEs, cloud service providers, and policy makers with insights into the determinants of CC adoption, which are useful for planning and making decisions in the adoption of CC. Third, the research provides a practical decision model that can be used commercially to assist SMEs with a more knowledgeable framework for making their decisions in the adoption of CC.
Al Isma'ili, Salim Zahir, A Multi-Perspective Framework for Modelling and Analysing the Determinants of Cloud Computing Adoption among SMEs in Australia, Doctor of Philosophy thesis, School of Computing and Information Technology, University of Wollongong, 2017. https://ro.uow.edu.au/theses1/67