Regression Analysis of Cloud Computing Adoption for U.S. Hospitals

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 IT 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 developed predictive models provided a clearer understanding among hospital IT executives and cloud service providers of cloud adoption drivers.