Main Article Content
Abstract
The growing adoption of e-Government services, such as Satu Data Indonesia (SDI), requires a deeper understanding of factors that influence the long-term usage of these services. This study aims to explore the continuance usage intention of e-Government services by applying Technology Continuance Theory (TCT). The research examines the roles of Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Satisfaction (SAT), and Attitude (ATT) in driving the sustained use of SDI. Data were collected through an online survey involving 175 respondents who have used the SDI platform. The findings reveal that while PU significantly influences both satisfaction and attitude, PEOU only affects PU and does not directly influence attitude. Furthermore, ATT is the strongest predictor of continuance intention (CI), with SAT indirectly influencing continuance intention through ATT. These results suggest that user retention depends more on developing positive attitudes through satisfying experiences rather than solely focusing on system usability or usefulness. The study provides valuable insights for policymakers and service developers to enhance e-Government services for sustained user engagement.
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References
- Abdul Rahim, N. F., Abbasi, G. A., Iranmanesh, M., Christopher, N., & Amran, A. (2023). Determinants of continuous intention to use e-government services: an extension of technology continuance theory. Journal of Systems and Information Technology, 25(3), 245–267. https://doi.org/10.1108/JSIT-09-2020-0166
- Afrizal, D., & Wallang, M. (2021). Attitude on intention to use e-government in Indonesia. Indonesian Journal of Electrical Engineering and Computer Science, 22(1), 435–441.
- Ali, M. H., Zailani, S., Iranmanesh, M., & Foroughi, B. (2019). Impacts of environmental factors on waste, energy, and resource management and sustainable performance. Sustainability, 11(8), 2443.
- Almahamid, S. M., & McAdams, A. C. (2010). Determinants of user continuance intention to use e-government. International Journal of Electronic Governance, 3(4), 343–372.
- Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411.
- Anil Kumar, K., & Natarajan, S. (2020). An extension of the Expectation Confirmation Model (ECM) to study continuance behavior in using e-Health services. Innovative Marketing, 16(2), 15–28. https://doi.org/10.21511/im.16(2).2020.02
- Attard, J., Orlandi, F., Scerri, S., & Auer, S. (2015). A systematic review of open government data initiatives. Government Information Quarterly, 32(4), 399–418.
- Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J. (2014). Trust transfer in the continued usage of public e-services. Information and Management, 51(6), 627–640. https://doi.org/10.1016/j.im.2014.05.016
- Bernot, A., Tjondronegoro, D., Rifai, B., Hasan, R., Liew, A. W.-C., Verhelst, T., & Tiwari, M. (2024). Institutional Dimensions in Open Government Data: A Deep Dive Into Indonesia’s Satu Data Initiative and Its Implications for Developing Countries. Public Performance & Management Review, 1–31.
- Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
- Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015–1033. https://doi.org/10.1108/JEIM-10-2018-0237
- Hair Joseph, F., Black William, C., Babin Barry, J., & Anderson Rolph, E. (2010). Multivariate data analysis: A global perspective. Upper Saddle River, NJ: Pearson/Prentice Hall.
- Kim, N. K., Rahim, N. F. A., Iranmanesh, M., & Foroughi, B. (2019). The role of the safety climate in the successful implementation of safety management systems. Safety Science, 118, 48–56.
- Kumar, M. S., & Krishnan, D. S. G. (2020). Perceived usefulness (Pu), perceived ease of use (peou), and behavioural intension to use (biu): Mediating effect of attitude toward use (AU) with reference to mobile wallet acceptance and adoption in rural India.
- Liao, C., Chen, J.-L., & Yen, D. C. (2007). Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: An integrated model. Computers in Human Behavior, 23(6), 2804–2822.
- Liao, C., Palvia, P., & Chen, J.-L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309–320. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2009.03.004
- 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/https://doi.org/10.1016/j.giq.2010.09.004
- Minh, K. S., Zailani, S., Iranmanesh, M., & Heidari, S. (2019). Do lean manufacturing practices have negative impact on job satisfaction? International Journal of Lean Six Sigma, 10(1), 257–274.
- Nabavi, A., Taghavi-Fard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016). Information technology continuance intention: A systematic literature review. International Journal of E-Business Research (IJEBR), 12(1), 58–95.
- Pinem, A. A., Immanuella, I. M., Hidayanto, A. N., & Phusavat, K. (2018). Trust and its impact towards continuance of use in government-to-business online service. Transforming Government: People, Process and Policy, 12(3/4), 265–285.
- Rahi, S., Othman Mansour, M. M., Alghizzawi, M., & Alnaser, F. M. (2019). Integration of UTAUT model in internet banking adoption context. Journal of Research in Interactive Marketing, 13(3), 411–435. https://doi.org/10.1108/JRIM-02-2018-0032
- Ramdhani, A., Alamanda, D. T., Nurdiaman, A. M., & Arief, M. (2019). Problem Arising from New Technology on E-Government, the Use of Hay. U Application in Bandung, Indonesia. Jurnal Manajemen Indonesia, 19(2), 149–159.
- Santhanamery, T., & Ramayah, T. (2014). Explaining the e-Government usage using expectation confirmation model: The case of electronic tax filing in Malaysia. Government E-Strategic Planning and Management: Practices, Patterns and Roadmaps, 287–304.
- Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587–632). Springer.
- Shih, H.-P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351–368.
- Titah, R., & Barki, H. (2008). E-Government adoption and acceptance: A literature review and research framework. E-Government Research: Policy and Management, 42–97.
- Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application (JITTA), 11(2), 2.
References
Abdul Rahim, N. F., Abbasi, G. A., Iranmanesh, M., Christopher, N., & Amran, A. (2023). Determinants of continuous intention to use e-government services: an extension of technology continuance theory. Journal of Systems and Information Technology, 25(3), 245–267. https://doi.org/10.1108/JSIT-09-2020-0166
Afrizal, D., & Wallang, M. (2021). Attitude on intention to use e-government in Indonesia. Indonesian Journal of Electrical Engineering and Computer Science, 22(1), 435–441.
Ali, M. H., Zailani, S., Iranmanesh, M., & Foroughi, B. (2019). Impacts of environmental factors on waste, energy, and resource management and sustainable performance. Sustainability, 11(8), 2443.
Almahamid, S. M., & McAdams, A. C. (2010). Determinants of user continuance intention to use e-government. International Journal of Electronic Governance, 3(4), 343–372.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411.
Anil Kumar, K., & Natarajan, S. (2020). An extension of the Expectation Confirmation Model (ECM) to study continuance behavior in using e-Health services. Innovative Marketing, 16(2), 15–28. https://doi.org/10.21511/im.16(2).2020.02
Attard, J., Orlandi, F., Scerri, S., & Auer, S. (2015). A systematic review of open government data initiatives. Government Information Quarterly, 32(4), 399–418.
Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J. (2014). Trust transfer in the continued usage of public e-services. Information and Management, 51(6), 627–640. https://doi.org/10.1016/j.im.2014.05.016
Bernot, A., Tjondronegoro, D., Rifai, B., Hasan, R., Liew, A. W.-C., Verhelst, T., & Tiwari, M. (2024). Institutional Dimensions in Open Government Data: A Deep Dive Into Indonesia’s Satu Data Initiative and Its Implications for Developing Countries. Public Performance & Management Review, 1–31.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015–1033. https://doi.org/10.1108/JEIM-10-2018-0237
Hair Joseph, F., Black William, C., Babin Barry, J., & Anderson Rolph, E. (2010). Multivariate data analysis: A global perspective. Upper Saddle River, NJ: Pearson/Prentice Hall.
Kim, N. K., Rahim, N. F. A., Iranmanesh, M., & Foroughi, B. (2019). The role of the safety climate in the successful implementation of safety management systems. Safety Science, 118, 48–56.
Kumar, M. S., & Krishnan, D. S. G. (2020). Perceived usefulness (Pu), perceived ease of use (peou), and behavioural intension to use (biu): Mediating effect of attitude toward use (AU) with reference to mobile wallet acceptance and adoption in rural India.
Liao, C., Chen, J.-L., & Yen, D. C. (2007). Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service: An integrated model. Computers in Human Behavior, 23(6), 2804–2822.
Liao, C., Palvia, P., & Chen, J.-L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309–320. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2009.03.004
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/https://doi.org/10.1016/j.giq.2010.09.004
Minh, K. S., Zailani, S., Iranmanesh, M., & Heidari, S. (2019). Do lean manufacturing practices have negative impact on job satisfaction? International Journal of Lean Six Sigma, 10(1), 257–274.
Nabavi, A., Taghavi-Fard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016). Information technology continuance intention: A systematic literature review. International Journal of E-Business Research (IJEBR), 12(1), 58–95.
Pinem, A. A., Immanuella, I. M., Hidayanto, A. N., & Phusavat, K. (2018). Trust and its impact towards continuance of use in government-to-business online service. Transforming Government: People, Process and Policy, 12(3/4), 265–285.
Rahi, S., Othman Mansour, M. M., Alghizzawi, M., & Alnaser, F. M. (2019). Integration of UTAUT model in internet banking adoption context. Journal of Research in Interactive Marketing, 13(3), 411–435. https://doi.org/10.1108/JRIM-02-2018-0032
Ramdhani, A., Alamanda, D. T., Nurdiaman, A. M., & Arief, M. (2019). Problem Arising from New Technology on E-Government, the Use of Hay. U Application in Bandung, Indonesia. Jurnal Manajemen Indonesia, 19(2), 149–159.
Santhanamery, T., & Ramayah, T. (2014). Explaining the e-Government usage using expectation confirmation model: The case of electronic tax filing in Malaysia. Government E-Strategic Planning and Management: Practices, Patterns and Roadmaps, 287–304.
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587–632). Springer.
Shih, H.-P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351–368.
Titah, R., & Barki, H. (2008). E-Government adoption and acceptance: A literature review and research framework. E-Government Research: Policy and Management, 42–97.
Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application (JITTA), 11(2), 2.