Graduation Year
2008
Document Type
Dissertation
Degree
Ph.D.
Degree Granting Department
Psychology
Major Professor
Michael D. Coovert, Ph.D.
Committee Member
Carnot Nelson, Ph.D.
Committee Member
Paul Spector, Ph.D.
Committee Member
Doug Rohrer, Ph.D.
Committee Member
Toru Shimizu, Ph.D.
Keywords
Perceived ease of use, Perceived usefulness, Personality, Experience, Intent to use
Abstract
Organizations invest sizable amounts of financial and human capital toward developing and implementing innovative technology solutions that will help them achieve organizational objectives. Professionals are now able to use online social networking technology to maintain and grow their network of business contacts virtually, resulting in increased efficiency and the ability to foster relationships with colleagues who otherwise would not be accessible. Organizations can use the benefits of online social networking to their strategic advantage if they understand the nature of the technology and how it is used. The Technology Acceptance Model is often used to explain the acceptance of new technology at work, and can predict which workers are likely to adopt a newly-implemented technology as it was intended to be used. It is not clear, however, if the model can predict the acceptance of social networking technology, and it does not account for experience the user might have had with similar systems. Five hundred students completed a questionnaire about their prior usage of online social networking systems as well as an assessment of their perceptions of the technology in terms of ease of use and usefulness, and the social forces influencing usage decisions. Findings suggest the Technology Acceptance Model is a reasonable model of the acceptance of online social networking systems, but the subjective norm component was not predictive of acceptance.
Scholar Commons Citation
Willis, Timothy J., "An Evaluation of the Technology Acceptance Model as a Means of Understanding Online Social Networking Behavior" (2008). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/568