Date of Conferral

2017

Degree

Ph.D.

School

Management

Advisor

Nikunja Swain

Abstract

According to research, the risks of adopting new technology and the technological and organizational factors that influence adopting it are not clear. Thus, many financial institutions have hesitated to adopt cloud-computing. The purpose of this quantitative, cross-sectional study was to evaluate the cyber-risk implications of cloud-computing adoption in the U.S. financial services sector. The study examined 6 technological and organizational factors: organization size, relative advantage, compliance, security, compatibility, and complexity within the context of cyber-risk. Using a combination of diffusion of innovation theory and technology-organization-environment framework as the foundation, a predictive cybersecurity model was developed to determine the factors that influence the intent to adopt cloud-computing in this sector. A random sample of 118 IT and business leaders from the U.S. financial services sector was used. Multiple regression analysis indicated that there were significant relationships between the intent to adopt cloud-computing by the leaders of financial organizations and only 2 of the 6 independent variables: compliance risk and compatibility risk. The predictive cybersecurity model proposed in this study could help close the gaps in understanding the factors that influence decisions to adopt cloud-computing. Once the rate of cloud-computing adoption increases, this study could yield social change in operational efficiency and cost improvement for both U.S. financial organizations and their consumers.

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