Cloud computing has gained popularity due to its ability to simplify IT infrastructure, reduce costs, and provide remote access. Among EU countries and company sizes, Sweden stands out with the highest rate of cloud computing adoption. However, there is a lack of concrete research in the literature focusing on the determinants of cloud computing adoption specifically by large companies in Sweden. Previous studies have examined cloud adoption from various perspectives, with a particular emphasis on small and medium-sized enterprises (SMEs) rather than large companies. Additionally, technology-related determinants have received more attention compared to those related to business, conceptualization, and application domains. To address this knowledge gap, this research aims to investigate the determinants of CC adoption in large companies in Sweden. The research question was formulated as follows: What are the determinants of cloud computing adoption in large companies in Sweden? Case study was selected as the research strategy, and the data was collected through semi-structured interviews and analyzed through thematic analysis. Semi-structured interviews were conducted with employees working at a large company in Sweden, who have experience in the IT and cloud computing field. The TOE framework was used to categorize the determinants as sub-themes into three themes: technology context, organization context, and environment context. In Company X, 30 determinants were found, with 20 aligning with previous literature. These included factors such as security, compatibility, scalability, top management support, and competitive pressure. Additionally, 10 new determinants were identified, including robustness, perceived usefulness, innovativeness, knowledge and training, and geographical locations/data centers. The experience and lessons learned from Company X could assist other companies to have better preparation for cloud adoption by understanding the significance of various potential determinants and underlying problems.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-219647 |
| Date | January 2023 |
| Creators | Güldogan, Seher, Sun, Ruo Lin |
| Publisher | Stockholms universitet, Institutionen för data- och systemvetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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