Cloud Computing Adoption
Abstract form my PhD Dissertation.
Author Dr. Williams Obinkyereh -Doctor Of Computer Science (Full publication can be read in ProQuest)
Cloud Computing Technology has emerged as computing paradigm which delivers computing as a service using the internet and as a “pay as you go” basis. Research has described some of the benefits of the Cloud Computing as cost savings, scalability, and efficiency (Armbrust, Fox, Griffith, Joseph, Katz, Konwinski & Zaharia, 2010; Avram, 2014; Choo, 2010). Cloud Computing adoption is very slow in Ghana despite the numerous benefits discussed in academic literature. This study addresses the problem of lack of adequate evidence concerning Cloud Computing adoption in Ghana as a result of insufficient research studies on Cloud Computing in Ghana.
The purpose of this quantitative correlational survey was to examine the factors that determine Cloud Computing adoption by information technology professionals in Ghana. The study is a quantitative non-experimental correlational survey to construct an empirical model to measure the relationship between perceived ease of use, perceived usefulness, perceived benefit, perceived security, perceived accessibility and Cloud Computing adoption in Ghana. The aim was to understand the factors that influence information technology professionals’ decision to adopt Cloud Computing in Ghana using Technology Acceptance Model as a theoretical framework. The study seeks to understand the factors that influence information technology professionals’ decision to adopt Cloud Computing in Ghana. A survey was conducted using a validated pre-existing survey instrument to collect data from a sample of 135 information technology professionals in Ghana.
Pearson’s correlation and multiple regression analyses were used to examine the relationship between perceived ease of use, perceived usefulness, perceived benefit, perceived security and perceived accessibility and Cloud Computing adoption in Ghana. Both Pearson correlation and simple linear regression analyses result indicated that there was a significant relationship between perceived usefulness, perceived benefit, perceived security and perceived accessibility and Cloud Computing adoption in Ghana. However, there was no significant relationship between perceived ease of use and Cloud Computing adoption in Ghana. The multiple regression revealed that the combined independent variables (perceived ease of use, perceived usefulness, perceived benefit, perceived security and perceived accessibility ) significantly predicted Cloud Computing adoption in Ghana, R = 0.464, R2 = 0.215 F (2,129) = 7.077, p < 0.001. This study fills the void in extant literature with regards to Cloud Computing adoption in Ghana. This study contributes to the lack of research studies on Cloud Computing adoption in Ghana. Recommendations for future studies include using mixed research method to replicate this study.