Factors Identifying Users Behavioral Intention to Adopt E-government Public Services in Bangladesh
Israt Jahan Shithii*
Abstract
The paper discusses about the behavioral intention of users to adopt e-government public services using the UTAUT model. E-government helps to create efficient delivery of services to mass people. Bangladeshs government has a "Vision-2041" to become a smart government as a result many e-government services are implemented and initiated throughout the country. To be successful in this vision, the behavioral intention to adopt e-government services is necessary to identify. In this paper, primary data is collected to conduct the study. Fifteen questionnaires were formed to find the behavioral intention where the sample size is the portion of the population who uses e-government public services at least once in their life. SPSS software is used to analyze and validate hypotheses. The research finds that the factors of the UTAUT model that are adopted for conducting this research such as perceived performance expectancy, perceived effort expectancy, and perceived social influence have a positive relation toward the behavioral intention to adopt e-government services in Bangladesh.
Keywords
Article References:
Ahmed T. (2023). Role of E-Governance amid the pandemic in providing healthcare, education, and social services (HESS) in Bangladesh. Asian J. Soc. Sci. Leg. Stud., 5(5), 142-153. https://doi.org/10.34104/ajssls.023.01420153
Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, & perceived behavioral control. J. of Experimental Social Psychology, 22(5), 453-474.
Alenezi, H., Tarhini, A., & Sharma, S. (2015). Development of quantitative model to investigate the strategic relationship between information quality and e-government benefits. Transforming Government: People, Process and Policy, 9(3), 324-351. https://doi.org/10.1108/tg-01-2015-0004
Alhassan, U. (2023). E-government and the impact of remittances on new business creation in developing countries. Economic Change and Restructuring, 56(1), 181-214.
Benaida, M. (2023). e-Government Usability Evaluation: A Comparison between Algeria and the UK. Inter J. of Advanced Computer Science and Applications, 14(1).
Bougherra, M., Yenigun, C., & Hassan-Yari, H. (2023). E-government performance in democracies versus autocracies. Inter J. of Organizational Analysis, 31(7), 3275-3294.
Chau, P.Y. and Hu, P.J., (2002). Examining a model of information technology acceptance by individual professionals: An exploratory study. J. of Management Information Systems, 18(4), pp.191-229.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
Davis, F. D. (1989), "Perceived usefulness, perceived ease of use, and user acceptance of information technology", MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
E-Government Master Plan for Digital Bangladesh. (2019). E-Government Master Plan for Digital Bangladesh. Bangladesh Computer Council. Available in the online - https://bcc.portal.gov.bd/sites/default/files/
Hardi, R., and Gohwong, S. (2020). E-government-based urban governance on the smart city program in makassar, Indonesia. J. of Contemporary Governance and Public Policy, 1(1), 12-17.
Islam MT. (2020). The relationship between lengthy job recruitment process and NEET: a study on Bangladesh public service commission respect to selected years BCS exams, Can. J. Bus. Inf. Stud., 2(5), 96-104. https://doi.org/10.34104/cjbis.020.0960104
Jaeger, P.T. and Thompson, K.M., (2003). E-government around the world: Lessons, challenges, & future directions. Government Information Quarterly, 20(4), pp.389-394.
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36.
Kamal, M., and Themistocleous, M. (2009). Investigating Enterprise Application Integration Adoption in the Local Government Authorities. Handbook of Research on Strategies for Local E-Government Adoption and Implementation, 661-685. https://doi.org/10.4018/978-1-60566-282-4.ch035
Kock, N., and Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods: Sample size in PLS-based SEM. Information Systems J., 28(1), 227–261. https://doi.org/10.1111/isj.12131
Li, Y., and Shang, H. (2020). Service quality, perceived value, and citizens continuous-use intention regarding e-government: Empirical evidence from China. Information & Man-agement, 57(3), 103197.
Paul, S. (2023). Accessibility analysis using WCAG 2.1: evidence from Indian e-government websites. Universal access in the information society, 22(2), 663-669.
Saengchai, S., Sriyakul, T., & Jermsittiparsert, K. (2020). The impact of citizen trust, citizen disposition and favourable social characteristics on the adoption of e-government: Mediating roles of perceived behavioural control. Inter J. of Innovation, Creativity and Change, 12(11), 375-393.
Upadhyay, N., Kamble, A., and Navare, A. (2023). Virtual healthcare in the new normal: Indian healthcare consumers adoption of electronic government telemedicine service. Government Information Quarterly, 40(2), 101800.
Venkatesh, Morris, Davis, and Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
West, D. M. (2000). Assessing e-government: The Internet, democracy, and service delivery by state and federal governments. Providence, RI: Taubman Center for Public Policy, Brown University.
Article Info:
Academic Editor
Dr. Doaa Wafik Nada, Associate Professor, School of Business and Economics, Badr University in Cairo (BUC), Cairo, Egypt.
