Investigating Demographic Variations in the Use of Online Public Services: A UTAUT-Based Multigroup Analysis
Downloads
This study aims to investigate demographic disparities in the adoption of online public services (OPS) in Vietnam, a nation experiencing rapid digital transformation while grappling with unequal access. Employing the Unified Theory of Acceptance and Use of Technology (UTAUT) as the analytical framework, data from 1,186 citizens were analyzed using PLS-SEM and multigroup analysis to determine whether the fundamental UTAUT relationships differ across these demographic segments. The findings indicate that women are more affected by family and community encouragement; ethnic minority users place greater reliance on performance expectancy “valuing time savings, reduced travel, and service accessibility” and rural users depend more on effort expectancy and facilitating conditions due to infrastructure constraints. These differences affirm that social and contextual factors significantly influence citizens’ behavioral intentions toward OPS use. The study’s novelty lies in incorporating demographic segmentation into the UTAUT framework within a developing-country context, thereby extending its theoretical applicability and providing actionable insights for an inclusive digital government. The results offer policymakers evidence-based guidance for designing targeted interventions to enhance accessibility and equity in Vietnam’s digital transformation process.
Downloads
[1] IPS & UNDP (2024). Review of 63 Provincial Online Public Service Portals from a User-Centric Perspective in 2024. In the series of Policy Discussion Papers on Governance and Participation. Commissioned by the Institute for Policy Studies and Media Development (IPS) and the United Nations Development Programme (UNDP), Ha Noi, Vietnam.
[2] Pramuditha, R., Muhafidin, D., Sumaryana, A., & Susanti, E. (2025). E-Government Implementation and Public Service Quality: Challenges and Opportunities in Indonesian Local Administration. Tec Empresarial, 20(1), 61-70. doi:10.1229/tecempresarialjournal.v20i1.531.
[3] Djatmiko, G. H., Sinaga, O., & Pawirosumarto, S. (2025). Digital Transformation and Social Inclusion in Public Services: A Qualitative Analysis of E-Government Adoption for Marginalized Communities in Sustainable Governance. Sustainability (Switzerland), 17(7), 2908. doi:10.3390/su17072908.
[4] F. S., O. (2024). A Systematic Literature Review of E-Government Implementation in Developing Countries: Examining Urban-Rural Disparities, Institutional Capacity, and Socio-Cultural Factors in the Context of Local Governance and Progress towards SDG 16.6. International Journal of Research and Innovation in Social Science, VIII(VIII), 1173–1199. doi:10.47772/ijriss.2024.808088.
[5] Nguyen, N. P. M. (2024). Identification of determinants of e-government trust and its impacts on e-government satisfaction and citizens’ continuance intention to use e-government in Ho Chi Minh City, Vietnam. International Journal of Information, Business and Management, 16(4), 160–174.
[6] Thi Uyen Nguyen, T., Van Nguyen, P., Thi Ngoc Huynh, H., Truong, G. Q., & Do, L. (2024). Unlocking e-government adoption: Exploring the role of perceived usefulness, ease of use, trust, and social media engagement in Vietnam. Journal of Open Innovation: Technology, Market, and Complexity, 10(2), 100291. doi:10.1016/j.joitmc.2024.100291.
[7] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. doi:10.2307/30036540.
[8] Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly: Management Information Systems, 36(1), 157–178. doi:10.2307/41410412.
[9] Senshaw, D., & Twinomurinzi, H. (2021). The Moderating Effect of Gender on Adopting Digital Government Innovations in Ethiopia. Proceedings of the 1st Virtual Conference on Implications of Information and Digital Technologies for Development, 734–751.
[10] Abu-Shanab, E., & Khasawneh, R. (2014). E-government adoption: The challenge of digital divide based on Jordanians’ perceptions. Theoretical and Empirical Researches in Urban Management, 9(4), 5–19.
[11] Rodríguez-Correa, P. A., Méndez-Rivera, C. A., Patiño-Toro, O. N., Valencia-Arias, A., Conejo, A. L. G. R., León, A. O., Vásquez, J. T. C., & Adan, T. E. A. (2025). Factors influencing the adoption of e-government by female university students. PLoS ONE, 20(1 January), 0317685. doi:10.1371/journal.pone.0317685.
[12] Cheah, J. H., Amaro, S., & Roldán, J. L. (2023). Multigroup analysis of more than two groups in PLS-SEM: A review, illustration, and recommendations. Journal of Business Research, 156, 113539. doi:10.1016/j.jbusres.2022.113539.
[13] Tri, N. M., & Thanh, D. Q. (2024). Addressing social issues to meet the requirements of sustainable development in Vietnam. Research Journal in Advanced Humanities, 5(3), 1001–1016. doi:10.58256/g3qfjw50.
[14] Senshaw, D., & Twinomurinzi, H. (2024). How women circumvent systemic constraints: Patriarchy’s extension to the adoption of digital government innovations. Information Polity, 29(4), 379–395. doi:10.1177/15701255241304596.
[15] Addai, B., & Arthur, B. (2020). Ghana’S Road To Cashless Economy: the E-Zwich Experience. Journal on Innovation and Sustainability RISUS, 11(1), 52–67. doi:10.23925/2179-3565.2020v11i1p52-67.
[16] Shithii, I. J. (2024). Factors Identifying Users’ Behavioral Intention to Adopt E-government Public Services in Bangladesh. International Journal of Management and Accounting, 1–6. doi:10.34104/ijma.024.00106.
[17] Silvestro, R., Schenatto, F. J. A., Santos, G. D., & Oliveira, G. A. (2024). Acceptance of a Mandatory E-Government System: The Public Employee Perspective. International Journal of Electronic Government Research, 20(1), 356406. doi:10.4018/IJEGR.356406.
[18] Sung, W. J., & Lee, J. (2024). A longitudinal study on the diffusion and the divide in the use of e-government services among vulnerable citizens in Korea. Government Information Quarterly, 41(2), 101938. doi:10.1016/j.giq.2024.101938.
[19] Sawhney, H., & Jayakar, K. P. (2007). Universal access. Annual Review of Information Science and Technology, 41(1), 159–221. doi:10.1002/aris.2007.1440410111.
[20] Guo, Y. (2024). Investigating the impact of culture dimensions on Chinese citizens’ continuous use of e-government websites: A cultural model-based study. Acta Psychologica, 244, 104196. doi:10.1016/j.actpsy.2024.104196.
[21] Rosenberg, D. (2021). Ethnic perspective in e-government use and trust in government: A test of social inequality approaches. New Media and Society, 23(6), 1660–1680. doi:10.1177/1461444820920655.
[22] Bélanger, F., & Carter, L. (2009). The impact of the digital divide on e-government use. Communications of the ACM, 52(4), 132–135. doi:10.1145/1498765.1498801.
[23] Ye, L., & Yang, H. (2020). From digital divide to social inclusion: A tale of mobile platform empowerment in rural areas. Sustainability (Switzerland), 12(6), 2424. doi:10.3390/su12062424.
[24] Salemink, K., Strijker, D., & Bosworth, G. (2017). Rural development in the digital age: A systematic literature review on unequal ICT availability, adoption, and use in rural areas. Journal of Rural Studies, 54, 360–371. doi:10.1016/j.jrurstud.2015.09.001.
[25] Philip, L., & Williams, F. (2019). Remote rural home based businesses and digital inequalities: Understanding needs and expectations in a digitally underserved community. Journal of Rural Studies, 68, 306–318. doi:10.1016/j.jrurstud.2018.09.011.
[26] Zhao, Y., Pinto Llorente, A. M., & Sánchez Gómez, M. C. (2021). Digital competence in higher education research: A systematic literature review. Computers and Education, 168, 104212. doi:10.1016/j.compedu.2021.104212.
[27] Reddick, C. G., & Zheng, Y. (2017). Determinants of citizens’ mobile apps future use in Chinese local governments: An analysis of survey data. Transforming Government: People, Process and Policy, 11(2), 213–235. doi:10.1108/TG-11-2016-0078.
[28] Helbig, N., Gil-García, J. R., & Ferro, E. (2009). Understanding the complexity of electronic government: Implications from the digital divide literature. Government Information Quarterly, 26(1), 89–97. doi:10.1016/j.giq.2008.05.004.
[29] Cardey, S., Eleazar, P. J. M., Ainomugisha, J., Kalowekamo, M., & Vlasenko, Y. (2024). Communication for Development: Conceptualising Changes in Communication and Inclusive Rural Transformation in the Context of Environmental Change. Social Sciences, 13(6), 324. doi:10.3390/socsci13060324.
[30] Johnson, I. G., & Vlachokryiakos, V. (2024). Socio-digital Rural Resilience: An Exploration of Information Infrastructures Within and Across Rural Villages During Covid-19. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1). doi:10.1145/3637400.
[31] Erdfelder, E., FAul, F., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. doi:10.3758/BRM.41.4.1149.
[32] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. doi:10.1108/EBR-11-2018-0203.
[33] Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. Handbook of Market Research. Springer International Publishing, Cham, Switzerland. doi:10.1007/978-3-319-57413-4_15.
[34] Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. doi:10.1080/10705519909540118.
[35] Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. doi:10.1037/0033-2909.88.3.588.
[36] Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European Journal of Epidemiology, 31(4), 337–350. doi:10.1007/s10654-016-0149-3.
[37] Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences. Routledge, New York, United States. doi:10.4324/9780203771587.
[38] Chin, W. W., & Newsted, P. R. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research. Statistical Strategies for Small Sample Research, 295-336. doi:10.4324/9781410604385-10.
[39] Matthews, L. M., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2016). Identifying and treating unobserved heterogeneity with FIMIX-PLS: Part II – A case study. European Business Review, 28(2), 208–224. doi:10.1108/EBR-09-2015-0095.
[40] Sarstedt, M., Becker, J.-M., Ringle, C. M., & Schwaiger, M. (2011). Uncovering and Treating Unobserved Heterogeneity with FIMIX-PLS: Which Model Selection Criterion Provides an Appropriate Number of Segments? Schmalenbach Business Review, 63(1), 34–62. doi:10.1007/bf03396886.
[41] Hair Jr, J. F., Ringle, C., Sarstedt, M., & Gudergan, S. P. (2017). Advanced Issues in Partial Least Square Structural Equation Modeling. SAGE Publications, New York, United States.
[42] Aguinis, H., Edwards, J. R., & Bradley, K. J. (2017). Improving Our Understanding of Moderation and Mediation in Strategic Management Research. Organizational Research Methods, 20(4), 665–685. doi:10.1177/1094428115627498.
[43] Henseler, J. (2012). PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. Studies in Classification, Data Analysis, and Knowledge Organization, 495–501. doi:10.1007/978-3-642-24466-7_50.
[44] Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405–431. doi:10.1108/IMR-09-2014-0304.
[45] Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319. doi:10.1108/S1474-7979(2009)0000020014.
[46] Chin, W. W., & Dibbern, J. (2010). An Introduction to a Permutation Based Procedure for Multi-Group PLS Analysis: Results of Tests of Differences on Simulated Data and a Cross Cultural Analysis of the Sourcing of Information System Services Between Germany and the USA. Handbook of Partial Least Squares, 171–193. doi:10.1007/978-3-540-32827-8_8.
[47] Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. doi:10.1177/002224378101800104.
[48] Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. doi:10.1007/s11747-014-0403-8.
[49] Bergh, D. (2015). Sample Size and Chi-Squared Test of Fit—A Comparison Between a Random Sample Approach and a Chi-Square Value Adjustment Method Using Swedish Adolescent Data. Pacific Rim Objective Measurement Symposium (PROMS) 2014 Conference Proceedings, 197–211. doi:10.1007/978-3-662-47490-7_15.
[50] Byrne, B. M. (2013). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. Psychology Press, New York, United States. doi:10.4324/9780203774762.
[51] Afonso, C. M., Roldán, J. L., Sánchez-Franco, M., & O, M. De. (2012). The moderator role of Gender in the Unified Theory of Acceptance and Use of Technology (UTAUT ): A study on users of Electronic Document Management Systems. 7th International Conference on Partial Least Squares and Related Methods, 1–8.
[52] Duan, Y., & Dong, X. (2025). Use intention and behavior in e-government among rural women: An extension of the UTAUT-2 model. Information Development, 02666669251316512. doi:10.1177/02666669251316512.
[53] Kim, S., & Lee, J. (2019). Gender and E-Participation in Local Governance: Citizen E-Participation Values and Social Ties. International Journal of Public Administration, 42(13), 1073–1083. doi:10.1080/01900692.2019.1575669.
[54] Duy An Vo, D. A. V., & Xuan Bao Dao, X. B. D. (2025). Assessment of the Current State of Digital Transformation in Vietnam. International Journal of Advances in Engineering and Management, 7(5), 433–443. doi:10.35629/5252-0705433443.
[55] Ndzabela, O., Lukman, Y., & Yakobi, K. (2025). Citizen Trust in E-Government Strategies. International Journal of Public Administration in the Digital Age, 12(1), 1–28. doi:10.4018/ijpada.385699.
[56] Nirmani I.A.P. (2025). Barriers to digital participation in developing countries: Identifying technological, social, and cultural obstacles to community involvement. GSC Advanced Research and Reviews, 23(2), 61–71. doi:10.30574/gscarr.2025.23.2.0130.
[57] Open Development Vietnam (2018). Population and distribution of ethnic minorities in Vietnam. Dataset OD Mekong DataHub, Viet Nam. Available online: https://data.vietnam.opendevelopmentmekong.net/en/dataset/population-and-distribution-of-ethnic-minorities-in-vietnam (accessed on May 2026).
[58] UNDP. (2020). The Viet Nam Provincial Governance and Public Administration Performance Index Measuring Citizens’ Experiences. UNDP Vietnam. Available online: www.papi.org.vn (accessed on May 2026).
[59] Okunola, O. M., Rowley, J., & Johnson, F. (2017). The multi-dimensional digital divide: Perspectives from an e-government portal in Nigeria. Government Information Quarterly, 34(2), 329–339. doi:10.1016/j.giq.2017.02.002.
[60] Fong, M. W. L. (2009). Digital Divide Between Urban and Rural Regions in China. Electronic Journal of Information Systems in Developing Countries, 36(1), 1–12. doi:10.1002/j.1681-4835.2009.tb00253.x.
- This work (including HTML and PDF Files) is licensed under a Creative Commons Attribution 4.0 International License.
