Affiliation:
1. Taibah University, Saudi Arabia
Abstract
Cloud computing has become a popular topic in the research community because of its ability to transform computer software, platforms, and infrastructure as a service. However, cloud computing literature currently lacks user studies despite the fact that users play a crucial role in the success and failure of emerging technologies. This paper presents a study aimed at investigating users’ acceptance of cloud computing in Saudi Arabia. As a baseline, it utilizes the Technology Acceptance Model (TAM) along with five additional factors believed to affect users’ acceptance of new technology in the region in order to achieve the study goals. These factors are gender, age, education level, job domain, and nationality. The results demonstrated a high level of acceptance of cloud computing and a valid TAM in its standard form. The results also indicated that age, education, job domain, and nationality have a significant effect on users’ attitudes toward the adoption of cloud computing. However, no difference was found in the attitude toward the adoption of cloud computing between male and female employees.
Reference36 articles.
1. Al-Harby, F., Qahwaji, R., & Kamala, M. (2009, September 7-11). The effects of gender differences in the acceptance of biometrics authentication systems within online transaction. Paper presented at the International Conference on CyberWorlds.
2. Al-Harby, F., Qahwaji, R., & Kamala, M. (2010). Users' acceptance of secure biometrics authentication system: Reliability and validate of an extended UTAUT Model. In Proceedings of the International Conference on Networked Digital Technologies (Vol. 87, pp. 254-258).
3. Amazon Web Services. (n.d.). Amazon Elastic Compute Cloud (Amazon EC2). Retrieved from http://aws.amazon.com/ec2/
4. An extension of the technology acceptance model in an ERP implementation environment
5. Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R. H., & Konwinski, A. (2009). Above the clouds: A Berkeley view of cloud computing (Tech. Rep. No. UCB/EECS-2009-28). Berkeley, CA: University of California, Berkeley.
Cited by
35 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献