A study on cloud-based computing factors that benefit to information technology shared service center (ITSSC) / Nasirah Abu Samah
Cloud-based computing has recently emerged as a new paradigm for hosting and delivering services over the internet. Cloud-based is attractive to the business organization as it eliminates the requirement for users to plan ahead for provisioning, and allows the organization to start from the small an...
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| Format: | Thesis |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/64604/1/64604.pdf |
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| Summary: | Cloud-based computing has recently emerged as a new paradigm for hosting and delivering services over the internet. Cloud-based is attractive to the business organization as it eliminates the requirement for users to plan ahead for provisioning, and allows the organization to start from the small and increase resources only when there is a rise in service demands. However, despite the fact that cloud-based computing offers huge opportunity to the Information Technology (IT) industry, yet the Shared Service Center (SSC) business environment. In this study, we aim to study the cloud-based computing factors that benefit to Information Technology Shared Service Center (ITSSC) organization. The researcher present seven popular factors of the technology adoption and design a propose model of cloud-based computing factors that may benefit to ITSSC. A questionnaire has been designed based on the propose model and distributed among the target sample population. We run two tests to study the data by using descriptive statistic and factor analysis. This is to determine which factors are highly correlated benefits to ITSSC organization. The collected data from the distributed questionnaire was pre-process in Microsoft Excel (MS) 2010. Hence, the raw data was imported to Statistical Package for the Social Sciences (SPSS) software package 20 to run. the factor analysis to identify the correlation between variables in the data. Finally, less correlated variables will be eliminated by using data reduction and extraction method, Principal Component Analysis (PCA) in factor analysis phase. As a result, final model of cloud-based factors is generated by extracting the non-correlated factor. We conclude that the final model is the most highly correlated of cloud-based computing factor that benefit to ITSSC organization. |
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