Cloud computing has grown from being a business concept to one of the fastest growing segments of modern ICT industry. Cloud computing are addressing many issues emerged by the globalization in terms of the ever faster pace of growth, shorter product life cycles, increased complexity of systems and higher investment needs. Cloud computing is enetrating all sectors of business applications and has influenced the whole IT industry. The business model has grown to be an alternative to traditional on-premise systems, where traditional environment, applications and additional IT infrastructure is maintained in-house within the organization. However, organizations are still reluctant to deploy their business in the cloud. There are many concerns regarding cloud computing services and despite all its advantages, cloud adoption is still very low at an organizational landscape. Hence, this master thesis aims to investigate what the drawbacks regarding a transition from an on-premise system to a cloud computing service are and how these relate to factors that influence the decision of adoption. Furthermore, this study will investigate how cloud service providers can develop a pro-active approach to manage the main drawbacks of cloud adoption. In order to fulfill the aim of the study, empirical research in form of data collection of  onducted interviews were carried out. The results of the study identified security and perceived loss of control as the main drawbacks in the transition from an on-premise system to a cloud computing service. Since these findings could be described as foremost technological and attitudinal, the thesis contributes to practitioners in terms of implications of communicating and educating customers and adherence to industry standards and certifications as important factors to address. Lastly, this thesis identified lack of understanding for cloud computing as a result of poor information, indicating for further research within this area.

Switching from traditional information technology to cloud based technology is becoming more common for organizations looking to obtain benefits such as scalability, pay-per-use, and increased availability. A cloud migration is a project of high-level complexity, and having a methodological step-by-step approach can assist an organization through the process. Although there is a substantial amount of research on cloud migration, there is a lack of step-by-step descriptions to guide organizations looking to switch to cloud technology.  This is a case study evaluation of a cloud migration, where the cloud migration process is explored and compared to established frameworks for cloud migration. The case study organization is a large Swedish retail company that performed a cloud migration between 2020-2022, when switching from a legacy point-of-sale system to a cloud based application for commerce. Data collection consisted of a document review, an archival data review, and a survey that was sent out to end users of the cloud application. These three methods were selected to obtain triangulation of data and to provide an accurate description of the cloud migration process of the case study organization.  The results of the study demonstrate that the evaluated cloud migration process had many similarities to the frameworks for cloud migration, although with differences in order of execution and emphasis on activities. Challenges experienced during the cloud migration process were related to interoperability, project complexity, and having a third-party service provider. By contrast, success factors of the cloud migration were proper planning for support flow and deployment, having substantial user support, and sufficient training for end users.  This study provides a description of an executed cloud migration with an overview of the process from start to finish, along with insights into challenges and lessons learned regarding project execution. This could be of value for organizations looking to migrate from legacy applications to cloud based applications.

Cette thèse cherche à traiter des sujets de l’adoption de cloud et la décision de cloud. Elle analyse des déterminants de l’adoption, discute des services de cloud et compare des fournisseurs de cloud. Cloud computing a des dimensions à la fois techniques et organisationnelles. Jusqu’à présent, la dimension organisationnelle a reçu peu d’attention, et cloud computing a été essentiellement considéré d’un point de vue technique. Cependant, la “cloudification” des systèmes d’information pose de nombreuses questions économiques et managériales qui doivent être évaluées. Il est donc important d’enrichir notre compréhension des phénomènes liés à la "virtualization" de l’information, à travers un examen de leurs caractéristiques multidimensionnelles. En général, cette thèse démontre que l’utilité perçue, la facilité d’utilisation perçue, la complexité et la compatibilité sont des facteurs clés de l’adoption du cloud, le savoir-faire informatique joue également un rôle important dans le processus de la décision ; la plupart des petits fournisseurs de cloud ont des performances plus stables et plus performantes que les grands fournisseurs de cloud, la performance du processeur ayant un impact significatif sur le prix. Cette thèse contribue beaucoup aux dimensions théoriques et managériales de la recherche sur cloud, mais il y a plus de travail de recherche à faire du point de vue de l’adoption de cloud et de la prise de décision dans le cloud. La recherche future se concentrera sur les limites de la recherche. / This dissertation addresses cloud computing adoption and decision-making issues. It analyzes adoption determinants, discusses cloud services, and compares cloud providers. Cloud computing has both technical and organizational dimensions. Until recently the organizational dimension has received little attention, and cloud computing has essentially been considered from a technical perspective. However, the "cloudification" of information systems poses many economic and managerial questions that need to be evaluated. It is therefore important to enrich our understanding of phenomena related to the "virtualization" of information, through an examination of their multidimensional characteristics. Overall, this dissertation finds that perceived usefulness, perceived ease of use, complexity and compatibility are key factors for cloud adoption, It know-how plays also an important role in the decision process; most small cloud providers have more stable and better computing performance than large cloud providers, the performance of CPU impact price significantly. This dissertation contributes a lot to the theoretical and managerial dimensions of cloud computing research, however, there exists more research work to do as the aforementioned research limitations from the perspective of cloud adoption and cloud decision-making. Future research will focus on the limitions of the research.

The purpose of this study is to investigate which factors that influence cloud adoption and contribute to existing research about cloud computing. Ten hypotheses were derived from the Technological, Organizational, and Environmental (TOE) framework combined with the Diffusion of Innovation (DOI) framework. Data was collected using a questionnaire and 91 individuals working in several industries and different countries participated in the study. The research model was tested using a quantitative approach using partial least squares structural equation modeling (PLS-SEM). The main factors that were identified as drivers for adoption of cloud computing are: digital strategy, competitive pressure, trading partner support, standardization, firm size and network and collaboration. These findings have important implications and great value to the research field, companies and cloud providers as they could formulate better strategies for a successful cloud adoption. The study also provides a new approach in research about cloud adoption where the type of enterprise system migrated to the cloud is taken into consideration. Findings in this study points towards system specific requirements influencing the adoption rate.

The decision to adopt cloud computing services should involve business units of an insurance company as well as information technology (IT) because cloud computing services are viewed as both a technology offering and business alternative. The purpose of this qualitative exploratory case study was to explore the strategies used by IT architects of an Illinois-based insurance company when adopting cloud computing services. The theory supporting this study was the technology acceptance model. The study's population consisted of IT architects from an Illinois-based insurance company that have used strategies to adopt cloud computing services. This study's data collection included semistructured interviews and review of organizational documents. Member checking with each participant increased the validity of this study's findings. Four major themes emerged from this study: strategies to adopt cloud computing services, strategies to adopt cloud services models, strategies to adopt cloud computing models, and concerns affecting the strategies to adopt cloud computing services. The study findings may assist IT architects in developing effective strategies to adopt cloud computing services for their respective business unit. This study might serve as a foundation for positive social change by decreasing customer concerns regarding critical information being compromised when adopting cloud computing services.

Information Technology (IT) leaders must leverage cloud computing to maintain competitive advantage. Evidence suggests that IT leaders who have leveraged cloud computing in small and medium sized organizations have saved an average of $1 million in IT services for their organizations. The purpose of this qualitative single case study was to explore strategies that IT leaders use to adopt cloud computing for their organizations. The target population consisted of 15 IT leaders who had experience with designing and deploying cloud computing solutions at their organization in Long Island, New York within the past 2 years. The conceptual framework of this research project was the disruptive innovation theory. Semistructured interviews were conducted and company documents were gathered. Data were inductively analyzed for emergent themes, then subjected to member checking to ensure the trustworthiness of findings. Four main themes emerged from the data: the essential elements for strategies to adopt cloud computing; most effective strategies; leadership essentials; and barriers, critical factors, and ineffective strategies affecting adoption of cloud computing. These findings may contribute to social change by providing insights to IT leaders in small and medium sized organizations to save money while gaining competitive advantage and ensure sustainable business growth that could enhance community standards of living.

No description available.

Industrial experts agree that cloud computing can significantly improve business and public access to low cost computing power and storage. Despite the benefits of cloud computing, recent research surveys indicated that its adoption in U.S. hospitals is slower than expected. The purpose of this study was to understand what factors influence cloud adoption in U.S. hospitals. The theoretical foundation of the research was the diffusion of innovations and technology-organization-environment framework. The research question was to examine the predictability of cloud computing adoption for U.S. hospitals as a function of 6 influential factors: relative advantage, compatibility, complexity, organizational size, structure, and culture. The research methodology included a cross-sectional survey with an existing validated questionnaire. A stratified random sample of 118 information technology managers from qualified U.S. hospitals completed the questionnaire. The categorical regression analysis rendered F statistics and R2 values to test the predictive models. The research results revealed that all 6 influential factors had significant correlations with the public cloud adoption intent (adjusted R2 = .583) while only the 3 technological factors had significant correlations with the private cloud adoption intent (adjusted R2 = .785). The recommendation is to include environmental factors and increase sample size in the similar future research. The developed predictive models provided a clearer understanding among hospital IT executives and cloud service providers of cloud adoption drivers. The potential implications for positive social change can be the increase of efficiency and effectiveness in U.S. hospital operation once their speed of cloud adoption has increased.

Decisions to deploy IT systems on public Infrastructure-as-a-Service clouds can be complicated as evaluating the benefits, risks and costs of using such clouds is not straightforward. The aim of this project was to investigate the challenges that enterprises face when making system deployment decisions in public clouds, and to develop vendor-neutral tools to inform decision makers during this process. Three tools were developed to support decision makers: 1. Cloud Suitability Checklist: a simple list of questions to provide a rapid assessment of the suitability of public IaaS clouds for a specific IT system. 2. Benefits and Risks Assessment tool: a spreadsheet that includes the general benefits and risks of using public clouds; this provides a starting point for risk assessment and helps organisations start discussions about cloud adoption. 3. Elastic Cost Modelling: a tool that enables decision makers to model their system deployment options in public clouds and forecast their costs. These three tools collectively enable decision makers to investigate the benefits, risks and costs of using public clouds, and effectively support them in making system deployment decisions. Data was collected from five case studies and hundreds of users to evaluate the effectiveness of the tools. This data showed that the cost effectiveness of using public clouds is situation dependent rather than universally less expensive than traditional forms of IT provisioning. Running systems on the cloud using a traditional 'always on' approach can be less cost effective than on-premise servers, and the elastic nature of the cloud has to be considered if costs are to be reduced. Decision makers have to model the variations in resource usage and their systems' deployment options to obtain accurate cost estimates. Performing upfront cost modelling is beneficial as there can be significant cost differences between different cloud providers, and different deployment options within a single cloud. During such modelling exercises, the variations in a system's load (over time) must be taken into account to produce more accurate cost estimates, and the notion of elasticity patterns that is presented in this thesis provides one simple way to do this.

Cloud technology requires a virtualized ubiquitous and scalable environment with shared resources. The general problem in cloud adoption is the absence of standardization across organizations. A standardized approach remained elusive since the inception of the Cloud First mandate. The purpose of this study was to explore leader-initiated change management (LICM) practices in cloud adoption within organizations. The theoretical framework included the classical theories of Kurt Lewin's organization change management, leader-member exchange, intentional change, and appreciative inquiry. A multiple case study design approach facilitated the exploration of LICM-value added practices to identify standardization in cloud adoption practices. Data collection included semistructured interviews from 8 high-level cloud adopters chosen from a resource pool of change management experts including a government chief information officer, academic college professor, military commander, and industry chief executive officer. Each interviewee represented an organization type providing perspectives on strategies for cloud adoption. Secondary data gathering included universal cloud standards and guidance from collaborative professional working groups. Emergent themes were identified after completing Yin's 5 stages of data analysis: LICM approaches for cloud decision-making, change management strategies, leader empowerment in action planning with progressive metrics, and successful learning outcomes in corporate universities. LICM strategies foster cooperative relationships and positive social change. Standardized cloud adoption practices also contribute to positive social change in reducing the environmental footprint through organizational efficiency.