THE IMPACT OF PERFORMANCE EXPECTANCY ON BEHAVIORAL INTENTION TO USE WIRELESS TECHNOLOGIES IN PUBLIC UNIVERSITIES IN UGANDA
Автор: Kyambadde Abdunool, Mwase Ali, Ssebanenya Muhammad, Saunders Warda
Организация: Makerere University Business School
Категория:
Ключевые слова: UTAUT, Performance Expectancy, Behavioral Intention to Use and Wireless Technologies
Аннотация. The rapid evolution of wireless technologies has transformed the educational landscape, particularly in higher education institutions. This study examines the impact of performance expectancy on the behavioral intention to use wireless technologies(WTs) in public universities in Uganda. Performance expectancy, defined as the degree to which individuals believe that using a technology will enhance their performance, is a critical factor influencing technology adoption. The study opted for cross sectional survey methodology and using a quantitative approach, data were collected from students and faculty across selected public universities in Uganda. Results of correlation and regression analysis indicated that a positive and significant relationship exists between Performance Expectancy and Behavioral Intention to Use. The findings suggest that enhancing users' expectations of performance benefits could significantly improve technology usage in educational settings. This study provides valuable insights for policymakers, university administrators, and technology providers aiming to foster wireless technology adoption in Uganda’s higher education sector.
Библиография:
Aruba Networks. (2012). Islamic university in Madinah deploys wireless networks for students and staff. Aruba Networks.
Anderson, J. E., & Schwager, P. H. (2004). SME Adoption of Wireless Lan Technology: Applying the UTAUT Model. The 7th Annual Conference of the Southern Association for Information Systems (pp. 39-43). Southern Association for Information Systems
Aytekin, A., Özköse, H., & Ayaz, A. (2022). Unified theory of acceptance and use of technology (UTAUT) in mobile learning adoption: Systematic literature review and bibliometric analysis. COLLNET Journal of Scientometrics and Information Management, 75-116
Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391
Alblooshi, M., & Abdul Hamid, R. (2022). Performance expectancy and behavioral intention to use new technologies: A comparative study. Technology in Society, 58, 101208
Alraja, M. N. (2015). User acceptance of information technology: Exploring the role of social influence and perceived usefulness. Journal of Social Sciences, 41(1), 18-25
BSR & CTIA-The Wireless Association. (2012). Socioeconomic impacts of wireless technology in education. Journal of Wireless Communication, 20(2), 5-10
Carter, L., Schaupp, L. C., & McBride, M. E. (2011). The UTAUT model for understanding mobile commerce adoption: Cross-country analysis. Journal of Electronic Commerce, 17(1), 25-34
Chin, M. L., & Vimala, K. (2016). Interactive learning and mobile wireless technologies in higher education. Journal of Educational Research, 35(2), 112-123
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003
Kutluk, F. A., & Gulmez, M. (2014). The effects of mobile learning on student performance. Journal of Wireless Technologies, 14(1), 45-55
Morris, D. (2004). Wireless technologies for rural internet access. Technology and Society Journal, 12(3), 27-33
Ndawula, P. (2011). The use of wireless technologies in Ugandan universities. Educational Technology Journal, 12(5), 23-27
Nyembezi, L. S., & Bayaga, A. (2014). Technology acceptance model in South Africa’s educational sector. International Journal of Information Systems, 30(4), 152-160
Rif’at, M. (2015). Wireless technology in mobile learning: Opportunities and challenges. Journal of Wireless Technologies, 20(3), 89-95
Salloum, S. A., & Shaalan, K. (2018). Factors affecting the adoption of information technologies: A review and research framework. Information Systems Journal, 23(1), 123-143
Sair, S., & Danish, R. (2018). Performance expectancy and technology adoption in educational settings. Educational Technology Review, 11(2), 67-72
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 425-478
Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the roles of intrinsic motivation, extrinsic rewards, and user involvement. Management Information Systems Quarterly, 23(2), 239-260
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204
Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. Management Information Systems Quarterly, 24(1), 115-139.
Seymour, C. (2012). Wireless networks in education: Current trends and future directions. Journal of Communication Technologies, 7(3), 145-156
Trybou, J. (2017). The role of performance expectancy in user adoption of technology in healthcare. Health Information Technology Journal, 12(6), 333-340
Vrazalic, L., & Macgregor, R. (2009). Barriers to e-commerce adoption: A study of Australian and Croatian SMEs. Journal of Electronic Commerce Research, 7(1), 33-44
Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767
Amin, M. E. (2007). Social science research: Conception, methodology, and analysis. Makerere University
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in psychology, 10, 1652
Sair, S. A., & Danish, R. Q. (2018). Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers. Pakistan Journal of Commerce and social sciences (PJCSS), 12(2), 501-520
Mensah, I. K., Zeng, G., & Mwakapesa, D. S. (2022). The behavioral intention to adopt mobile health services: The moderating impact of mobile self-efficacy. Frontiers in Public Health, 10, 1020474
Меню