Analysis the Critical Factors of M-government Service Acceptance: An Integrating Theoretical Model between TAM and ECM
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Abstract
The development of smartphones has an essential role in digital services, which have the advantage of access to health services that can be performed anywhere and anytime. Unfortunately, the diffusion process of smartphone technology in the provision of health services faces the problem of decreasing the actual use of mobile health applications. Previous studies on m-government health services have also focused on using TAM and UTAUT to predict individual user behavior. A gap in the literature has been identified in previous studies. This study investigates the critical factors for the individual acceptance of m-government health services, especially the Peduli Lindungi mobile health service. The two theoretical models, TAM and ECM, were integrated to enhance the body of knowledge in predicting individual behavior in the m-government healthcare context. A quantitative method was used to analyse a total of 200 data. PLS-SEM was used to analyze the outer and inner models. The findings of this study support all hypotheses. The study's findings show that Perceived Usefulness, Perceived Easy to Use, and Satisfaction significantly affect on Intention Use; Perceived Usefulness, Perceived Easy to Use, and Expectation Confirmatory significantly affect on Satisfaction, Perceived Easy to Use has a significant effect on Perceived Usefulness. Expectation confirmation significantly affected Perceived Usefulness and perceived ease of use. The proposed model is successfully validated. Future research could consider integrating these theoretical models to assess the critical factors influencing the acceptance and use of digital services in other contexts.
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NURUL HUDA, Mohammad.
Analysis the Critical Factors of M-government Service Acceptance: An Integrating Theoretical Model between TAM and ECM.
Policy & Governance Review, [S.l.], v. 7, n. 2, p. 109-124, may 2023.
ISSN 2580-4820.
Available at: <https://journal.iapa.or.id/pgr/article/view/721>. Date accessed: 19 sep. 2024.
doi: https://doi.org/10.30589/pgr.v7i2.721.
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
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Breil, B., Kremer, L., Hennemann, S., & Apolinário- Hagen, J. (2019). Acceptance of mHealth Apps for Self-Management A mong People with Hypertension. In German Medical Data Sciences: Shaping Change–Creative Solutions for Innovative Medicine: Vol. September (Issue 267, pp. 282–288). https://doi. org/10.3233/SHTI190839
Byambasuren, O., Sanders, S., Beller, E., & Glasziou, P. (2018). Prescribable mHeal th apps identified from an overview of systematic reviews. Npj Digital Medicine, 1(12). https:// doi.org/https://doi.org/10.1038/s41746-018-0021-9
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2),189–217. https://doi.org/. http://dx.doi. org/10.1287/isre.14.2.189.16018
Cho, V., & Hung, H. (2009). A Study of the Relationship between PEOU and PU in Technology Acceptance in E-Learning. In Ubiquitous Commerce for Creating the Personalized Marketplace: Concepts for Next Generation Adoption (pp. 149–170). Information Science Reference. https://doi. org/10.4018/978-1-60566-378-4.ch010
Davis, F. D. (1989). Per ceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/https://doi.org/10.2307/249008
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model. Information Systems Frontiers, 21(June), 719–734. https://doi. org/10.1007/s10796-017-9774-y
Eid, R., & Selim, H. (2020). Understanding citizen intention to use m-government services : an empirical study in the UAE. Transforming Government: People, Process and Policy, 15(4), 463–482. https://doi.org/https://doi.org/10.1108/TG-10-2019-0100
Garavand, A., Samadbeik, M., Nadri, H., Rahimi, B., & Asadi, H. (2020). Effective Factors in Adoption of Mobile Health Applications between Medical Sciences Students Using the UTAUT Model. Methods of Information in Medicines\, 58(04/05), 131–139. https:// doi.org/10.1055/s-0040-1701607
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer On Partial Least Squares Structural Equation Modelling (PLS-SEM). SAGE Publication.
Huda, M. N., Kurniasari, E. N., & Ruroh, S. M. (2022). A Systematic Literature Review of E-Government Evaluation. Journal of Local Government Issues, 5(1). https://doi.org/ https://doi.org/10.22219/logos.v5i1.19784
Huda, M., & Yunas, N. S. (2016). The Development of e-Government System in Indonesia. Jurnal Bina Praja: Journal of Home Affairs Governance, 08(1), 97–108. https://doi.org/https://doi. org/10.21787/jbp.08.2016.97-108
Hussain, A., Saare, M. A., Jasim, O. M., & Mahdi, A. A. (2018). A Heuristic Evaluation of Iraq E-Portal. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10, 1–10.
Jaya, I. G . M., H e r mi na, N., & Sune ngs i h , N. (2019). CB-SEM and VB-SEM: Evaluating Measurement model of Business Strategy of Internet Industry in Indonesia. International Journal of Scientific & Engineering Research, 10(10), 878–883.
Jayani, D. H. (2021). Proporsi Populasi Generasi Z dan Milenial Terbesar di Indonesia. Databoks. https://databoks.katadata.co.id/datapublish/2021/05/24/proporsi-populasi-generasi-z-dan-milenial-terbesar-di-indonesia
Jr., J. F. H., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook. Springer Cham. https://doi.org/https://doi.org/10.1007/978-3-030-80519-7
Khwaja, M. G., & Zaman, U. (2020). Configuring the evolving role of ewom on the consumers information adoption. Journal of Open Innovation: Technology, Market, and Complexity, 6(4), 1–13. https://doi. org/10.3390/joitmc6040125
Kock, N. (2018). Minimum Sample Size Estimation in PLS-SEM: An Application in Tourism and H os pitality Res earch . In C . Ali, F., Rasoolimanesh, S.M. and Cobanoglu (Ed.), Applying Partial Least Squares in Tourism and Hospitality Research (pp. 1–16). Emerald Publishing Limited. https://doi.org/https://doi.org/10.1108/978-1-78756-699-620181001
Lee, S., Choi, M. J., Rho, M. J., Kim, D., Choi, I. Y., Carlo, G. L., & Kim, D. (2018). Factors Affecting User Acceptance in Overuse of Smartphones in Mobile Health Services : An Empirical Study Testing a Modified Integrated Model in South Korea. Frontiers in Psychiatry, 9(December), 1–9. https://doi. org/10.3389/fpsyt.2018.00658
Li, Q. (2020). Healthcare at Your Fingertips: The Acceptance and Adoption of Mobile Medical Treatment Services among Chinese Users. International Journal of Environmental Research and Public Health,17(18), 1–21. https://doi.org/10.3390/ijerph17186895
Lin, F., Fofanah, S. S., & Liang, D. (2011). Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success. Government Information Quarterly, 28(2), 271–279. https://doi.org/10.1016/j. giq.2010.09.004
Lu, H., Lin, W., Raphael, C., & Wen, M. (2022). A study investigating user adoptive behavior and the continuance intention touse mobile health applications during the COVID-19 pandemic era: Evidence from the telemedicine applications utilized in Indonesia. Asia Pacific Management Review, Februar y. https://doi.org/https://doi. org/10.1016/j.apmrv.2022.02.002
Malisuwan, S., Kaewphanuekrungsi, W., & Milindavanij, D. (2016). Digital Divide in Thailand: Analysis and Recommendations. International Journal of Advanced Research in Engineering and Technology, 7(1), 41–46.
Maznorbalia, A. S., & Awalluddin, M. A. (2020). Users Acceptance of E-Government System in Sintok, Malaysia: Applying the UTAUT Model. Policy & Governance Review, 5(1), 66–81. https://doi.org/https://doi.org/10.30589/pgr.v5i1.348
Napitupulu, D. (2016). e-Government Maturity Model Based on Systematic Review and Meta-Ethnography Approach. Jurnal Bina Praja: Journal of Home Affairs Governance, 08(2), 263–275. https://doi.org/https://doi.org/10.21787/jbp.08.2016.263-275
Napitupulu, D. (2 0 1 7 ). Empir ical Study of Critical Success Factors for E-Government Implementation in Indonesia Based on Factor Analysis Approach. Jurnal Bina Praja: Journal of Home Affairs Governance, 09(1), 83–99. https://doi.org/https://doi. org/10.21787/jbp.09.2017.83-99
Nunes, A., Limpo, T., & Castro, S. L. (2019). Acceptance of Mobile Health Applications : Examining Key Determinants and Moderators. Frontiers in Psychology, 10(December), 1–9. https://doi.org/10.3389/fpsyg.2019.02791
Nusairat , N. M., Abdellatif, H., Al-Gasawneh, J . A., Haideh, A. H. O. A.-, Aloqoo l, A., R abah, S., & Ahmad, A. M. K. (2021). Determinants of behavioral intentions to use mobile healthcare applications in Jordan. International Journal of Data and Network Science, 5, 547–556. https://doi. org/10.5267/j.ijdns.2021.8.013
Nyoro, M., Kamau, J. W., Wanyembi, G. W., Titus, W. S., & Dinda, W. A. (2015). Review of Technology Acceptance Model usage in predictinge-commerce adoption. International Journal of Application or Innovation in Engineering & Management, 4(1), 46–49. https://pdfs.semanticscholar.org/4148/ ccfef2b4e1623ff6077e1dec5cf12679b0f9. pdf
Pai, R. R., & Alathur, S. (2019). Determinants of individuals’ intention to use mobile health: insights from India. Transforming Government: People, Process and Policy, 13(3/4), 306–326. https://doi.org/10.1108/ TG-04-2019-0027
Poong, Y.-S., & Eze, U. C. (2008). TAM vs. PCI: An Ana lysis on t he Theoret ica l M odel Parsimony and Robustness across Cultures. Communications of the IBIMA, 1, 198–201. https://ibimapublishing.com/articles/ CIBIMA/2008/970415/970415.pdf
Rahmadany, A. F. (2021). Literature Study of Electronic Government Implementation in the Perspective of Indonesia’s Electronic Government Ranking Dimensions. Jurnal Bina Praja: Journal of Home Affairs Governance, 13(2), 281–292. https://doi.org/https://doi.org/10.21787/jbp.13.2021.281-292
Rossel, P., Finger, M., & Misuraca, G. (2006). Mobile†e-Government Options: Between Technology- driven and User-centric. The Electronic Journal of E-Government, 4(2), 79–86.
Saare, M. A., Hussain, A., & Yue, W. S. (2019). Conceptualizing Mobile Health Application Use Intention and Adoption Among Iraqian Older Adults : From the Perspective of Expanded Technology Acceptance Model. International Journal of Intera, 13(10), 28–41. https://doi.org/https://doi.org/10.3991/ ijim.v13i10.11285
Sádaba, C. (2016). Youngsters, Digital Technology and Unplugging. Коммуникации. Медиа. Дизайн, 1(2), 129–140. https://cmd-journal.hse.ru/article/view/6487
Sarassina, R. R. F. (2022a). Understanding Mobile Payment Continuance in Indonesia: A Brand Equity Perspective Continuance Model. CommIT Journal, 16(1), 105–115. https:// doi.org/https://doi.org/10.21512/commit. v16i1.7882
Shemesh, T., & Barnoy, S. (2020). Assessment of the Intention to Use Mobile Health Applications Using a Technology Acceptance Model in an Israeli Adult Population. Telemedicine Journal and E-Health, 26(9), 1141–1149. https://doi.org/10.1089/tmj.2019.0144
Wang, G., Alatas, S., & Wiraniagara, A. (2019). Factors Affecting Acceptance of Mobile Health Insurance in Indonesia : TAM Applicability. International Journal of Advanced Trends in Computer Science and Engineering, 8(6), 3004–3011. https://doi.org/https://doi. org/10.30534/ijatcse/2019/54862019
Wilson, N., Keni, K., Henriette, P., & Tan, P. (2021). The Role of Perceived Usefulness and Perceived Ease-of-Use Toward Satisfaction and Trust which Influence Computer Consumers ’ Loyalty in China. Gadjah Mada International Journal of Business, 23(3), 262–294. https:// doi.org/10.22146/gamaijb.32106
Wirtz, B. W., Birkmeyer, S., & Langer, P. F. (2019). Citizens and mobile government: an empirical analysis of the antecedents and consequences of mobile government usage. International Review of Administrative Sciences, 0(0), 1–19. httpss://doi.org/10.1177/0020852319862349
Xie, C., Jia, S., & He, C. (2020b). An Empirical Study on the Factors Affecting Elderly Users ’ Continuance Intention of Shared Nurses. Risk Management and Healthcare Policy, 13, 1849–1860. https://doi.org/10.2147/ RMHP.S261827
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