Understanding Continuance Intention toward Indonesia’s National Health Insurance Mobile Application (Mobile JKN): Integrating Innovation Resistance and UTAUT Perspectives
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Abstract
Digital transformation in public healthcare has accelerated the development of mobile service platforms designed to enhance accessibility, efficiency, and transparency. In Indonesia, Mobile JKN was introduced as a national digital innovation to support the National Health Insurance system. Despite extensive population coverage, active application usage remains substantially lower than total membership, indicating challenges in sustaining digital engagement. This study examines the determinants of continuance intention and its impact on word-of-mouth (WOM) and intention to recommend among Mobile JKN users. Drawing on Innovation Resistance Theory (IRT) and selected UTAUT constructs, this study proposes a hybrid framework incorporating usage barriers, value barriers, traditional barriers, performance expectancy, effort expectancy, social influence, and facilitating conditions as predictors of continuance intention. Continuance intention, the user’s intention to continue using a service or product, is modeled as a mediator that influences word-of-mouth (WOM) and recommendation behavior. Using a quantitative causal-explanatory design and Partial Least Squares Structural Equation Modeling, the findings indicate that value and traditional barriers significantly reduce continuance intention, while enabling factors enhance sustained usage. Continuance intention positively influences WOM and intention to recommend. This study extends IRT into digital public healthcare contexts and provides strategic insights for policymakers seeking to enhance digital service retention and citizen advocacy.
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References
Barata, A. (2021). Continuance intention and willingness to recommend digital services: The role of perceived value and satisfaction. Journal of Retailing and Consumer Services, 59, 102375. https://doi.org/10.1016/j.jretconser.2020.102375
Bergman, R., & Macada, A. C. G. (2023). Understanding continuance intention in digital platforms: The role of perceived usefulness and satisfaction. Information Systems and e- Business Management, 21(2), 345–362. https://doi.org/10.1007/s10257-022-00578-4
Chen, C. C., & Chang, Y. C. (2022). Innovation resistance in digital services: Examining functional and psychological barriers. Technological Forecasting and Social Change, 174, 121224. https://doi.org/10.1016/j.techfore.2021.121224
Donthu, N., Kumar, S., Pandey, N., Pandey, N., & Mishra, A. (2021). Mapping the electronic word-of-mouth (eWOM) research: A systematic review and bibliometric analysis. Journal of Business Research, 135, 758–773. https://doi.org/10.1016/j.jbusres.2021.07.015
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
Ferreira, J. J. (2023). Digital service loyalty and recommendation intention: The mediating role of continuance intention. Journal of Services Marketing, 37(4), 455–468. https://doi.org/10.1108/JSM-05-2022-0193
Gupta, A., Dogra, N., & George, B. (2020). What determines tourist adoption of smartphone apps? An analysis based on the UTAUT-2 framework. Journal of Hospitality and Tourism Technology, 11(1), 50–64. https://doi.org/10.1108/JHTT-02-2019-0024
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2019). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage Publications.
Hair, J. F., 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. https://doi.org/10.1007/978-3-030-80519-7
Hameed, I. (2024). The impact of continuance intention on electronic word-of-mouth behavior in digital services. Computers in Human Behavior Reports, 9, 100289. https://doi.org/10.1016/j.chbr.2023.100289
Himel, S. (2021). Traditional barriers and digital financial service adoption. International Journal of Bank Marketing, 39(6), 1024–1042. https://doi.org/10.1108/IJBM-01-2021- 0024
Jin, X., Zhang, J., & Li, Y. (2022). Understanding innovation resistance in digital transformation: Evidence from service platforms. Journal of Business Research, 144, 34–45. https://doi.org/10.1016/j.jbusres.2022.01.056
Jo, H. (2023). Digital loyalty and word-of-mouth intention: The moderating role of trust. Electronic Commerce Research, 23(2), 567–589. https://doi.org/10.1007/s10660-021-09514-8
Kaur, P., Dhir, A., Singh, N., Sahu, G., & Almotairi, M. (2020). An innovation resistance theory perspective on mobile payment solutions. Journal of Retailing and Consumer Services, 55, 102059. https://doi.org/10.1016/j.jretconser.2020.102059
Kautish, P., Paul, J., & Sharma, R. (2023). Value barrier and digital adoption resistance: A systematic analysis. Technological Forecasting and Social Change, 189, 122327. https://doi.org/10.1016/j.techfore.2023.122327
Kwangsawad, A., & Jattamart, A. (2022). Continuance intention in mobile applications: The role of satisfaction and perceived value. Sustainability, 14(9), 5307. https://doi.org/10.3390/su14095307
Migliore, G., Talwar, S., & Dhir, A. (2022). Innovation resistance and digital services usage. Journal of Retailing and Consumer Services, 64, 102789. https://doi.org/10.1016/j.jretconser.2021.102789
Nasir, S. (2021). Customer continuance intention and positive word-of-mouth behavior in digital platforms. Information Technology & People, 34(8), 2345–2367. https://doi.org/10.1108/ITP-03-2020-0172
Nguyen, T. T. H., Nguyen, T. H., & Nguyen, T. H. (2022). Continuance intention and electronic word-of-mouth: The mediating role of satisfaction. Journal of Retailing and Consumer Services, 67, 102987. https://doi.org/10.1016/j.jretconser.2022.102987
Octavius, G. S. (2021). Understanding intention to recommend digital services: The role of loyalty and continuance intention. International Journal of Information Management Data Insights, 1(2), 100040. https://doi.org/10.1016/j.jjimei.2021.100040
Ram & Sheth (1989). Consumer resistance to innovations: the marketing problem and its solutions. The Journal of Consumer Marketing, 6(2), 5 – 14.
Ray, S., Dhir, A., Bala, P. K., & Kaur, P. (2022). Why do people resist digital innovations? Aninnovation resistance theory perspective. Technological Forecasting and Social Change, 182, 121851. https://doi.org/10.1016/j.techfore.2022.121851
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill-building approach (7th ed.). Wiley.
Spinelli, R., Migliore, G., & Dhir, A. (2024). Innovation resistance theory in digital ecosystems: A systematic review. Journal of Business Research, 167, 114219. https://doi.org/10.1016/j.jbusres.2023.114219
Talwar, S., Dhir, A., Khalil, A., Mohan, G., & Islam, A. K. M. N. (2020). Point of adoption and beyond: Initial trust and mobile payment adoption using UTAUT2. Journal of Retailing and Consumer Services, 55, 102086. https://doi.org/10.1016/j.jretconser.2020.102086
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Viralta, M., García-Murillo, M., & Annabi, H. (2023). Electronic word-of-mouth in public digital services. Government Information Quarterly, 40(2), 101782. https://doi.org/10.1016/j.giq.2023.101782
Wang, Y., Wang, J., & Li, X. (2023). Intention to recommend in digital service platforms: The role of user experience. Computers in Human Behavior, 141, 107610. https://doi.org/10.1016/j.chb.2022.107610