Determinants of Fintech Use in an Indonesian Healthcare Context: Evidence from an Extended Technology Acceptance Model
Abstract
Objective: Digital transformation in healthcare payments is accelerating globally, with financial technology (fintech) improving efficiency, transparency, and access. In Indonesia, adoption remains uneven, particularly in semi-urban areas with varying infrastructure, literacy, and trust. This study examined the determinants of patients’ intention to adopt fintech for healthcare payments in semi-urban Indonesia using an extended Technology Acceptance Model (TAM).
Material and Methods: A cross-sectional survey was conducted between June and August 2025 among 858 patients from community health centers, pharmacies, hospitals, and clinics in Banyumas Regency, Indonesia. The extended TAM incorporated perceived trust, perceived risk, digital financial literacy, and facilitating conditions. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to test the proposed model and to assess the relationships among these constructs, as well as measurement reliability, validity, and structural paths.
Results: All constructs demonstrated strong reliability (Cronbach’s α=0.785–0.873) and validity. Behavioral intention was significantly predicted by digital financial literacy (β=0.070, p-value=0.024), facilitating conditions (β=0.099, p-value<0.001), perceived ease of use (β=0.182, p-value<0.001), perceived usefulness (β=0.140, p-value<0.001), perceived risk (β=0.208, p-value<0.001), and social influence (β=0.253, p-value<0.001). Perceived trust predicted perceived risk (β=0.456, p-value<0.001) and indirectly affected behavioral intention. Overall, the model explained 49.6% of the variance in behavioral intention, with social influence (β=0.253, p-value<0.001) and perceived risk (β=0.208, p-value<0.001) emerging as the strongest predictors.
Conclusion: This study shows that fintech adoption for healthcare payments in semi-urban Indonesia is driven by both technological and socio-psychological factors, underscoring the importance of improving digital literacy, trust, and risk perception.
Keywords
Full Text:
PDFReferences
Danladi S, Prasad M, Modibbo UM, Ahmadi SA, Ghasemi P. Attaining sustainable development goals through financial inclusion: exploring collaborative approaches to Fintech adoption in developing economies. Sustainability 2023;15:13039.
Hakim L, Prawwatya N, Huda C, Fadila DFS, Rizaldi M. The role of fintech lending in expanding sharia financial inclusion and human development in Indonesia. Share J Ekon Dan Keuang Islam 2024;13:299-321.
World Bank. Digital-in-health: unlocking the value for everyone [Internet]. Washington (DC): World Bank; 2023 [cited 2025 Aug 9]. Available from: https://www.worldbank.org/en/topic/health/publication/digital-in-health-unlocking-the-value-for-everyone
Keelara R, Sutherland E, Almyranti M. Beyond the Pandemic: Leading Practices for the Future of Telemedicine. 173rd ed. 2025. doi: 10.1787/98863928-en.
Askari S, Ghofrani A, Taherdoost H. Fintech-enabled telemedicine: global healthcare advancement. In: Taherdoost H, Le N, Madanchian M, Farhaoui Y, eds. Advances in Finance, Accounting, and Economics. IGI Global; 2024;313-30. doi: 10.4018/979-8-3693-1561-3.ch012.
Rahayu R, Ali S, Aulia A, Hidayah R. The current digital financial literacy and financial behavior in Indonesian millennial generation. J Account Invest 2022;23:78-94.
Hengst TM, Lechner L, Dohmen D, Bolman CA. The facilitators and barriers of mHealth adoption and use among people with a low socio-economic position: a scoping review. Digital Health 2023;9:20552076231198702.
Hassan MdS, Islam MdA, Sobhani FA, Hassan MdM, Hassan MdA. Patients’ intention to adopt fintech services: a study on Bangladesh healthcare sector. IJERPH 2022;19:15302. doi: 10.3390/ijerph192215302.
Al-Anezi F. Interlinking FinTech and eHealth: a qualitative study. Front Public Health 2024;12:1398136.
Singh S, Sahni MM, Kovid RK. What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Manag Decis 2020;58:1675-97.
Xie J, Ye L, Huang W, Ye M. Understanding FinTech platform adoption: impacts of perceived value and perceived risk. J Theor Appl Electron Commer Res 2021;16:1893-911.
Judijanto L, Husnayetti H. The effect of financial literacy, digital literacy, and information security on qris adoption among students in banten. West Sci Account Financ 2024;2:310-20.
Mula K. Financial inclusion through digital payments: how technology is bridging the gap. J Comput Sci Technol Stud 2025;7:447-57.
Pentury F. The role of knowledge and penetration of fintech services in improving MSMEs of fishermen and marine farmers in remote small Islands Region. J Theor Appl Manage 2023;16:23-37. doi: 10.20473/jmtt.v16i1.43743.
Setiawan B, Nugraha DP, Irawan A, Nathan RJ, Zoltan Z. User innovativeness and fintech adoption in Indonesia. J Open Innov Technol Mark Complex 2021;7:188. doi: 10.3390/joitmc7030188.
Setyanti AM. Unlocking digital financial inclusion: a microdata-based study on Fintech Adoption in Subang Regency. Subang Int J Gov Account SINGA 2025;3:1-7.
Junitasari PDK, Indrajaya IGB, Wantara IGA, Dwipayana KWA. Pemahaman Penggunaan Financial Technology (Fintech) Dalam Konteks Sistem Pembayaran Dan Layanan Keuangan. J Inov Ekon Dan Keuang 2023;1:19-24.
Rosita AU, Sonia D, Putra DH, Fannya P. Minat Pasien Menggunakan Metode Transaksi Pembayaran QRIS di Pelayanan Rawat Jalan RSUD Koja. Indones Health Inf Manag J INOHIM 2024;12:23-30.
Sari AK, Fuad RN, Novelan MS. Sosialisasi Perlindungan Hukum Transaksi Digital dan Penerapan Fintech untuk Pembayaran Layanan Kesehatan di Puskesmas Hamparan Perak. J Pengabdi Kpd Masy Teknol Inf Dan Komun 2025;2:83-7.
Vhalery R. Kontribusi Informasi, Fasilitas, dan Loyalitas User Dalam Menggunakan Aplikasi Fintech di Masa Pandemi Covid-19. Sosio E-Kons 2021;13:99-108.
Lynn MR. Determination and quantification of content validity. Nurs Res 1986;35:382-6.
Perneger T V, Courvoisier DS, Hudelson PM, Gayet-Ageron A. Sample size for pre-tests of questionnaires. Qual Life Res 2015;24. doi: 10.1007/s11136-014-0752-2.
Andrade C, Menon V, Ameen S, Kumar Praharaj S. Designing and Conducting Knowledge, Attitude, and Practice Surveys in Psychiatry: Practical Guidance. Indian J Psychol Med 2020;42. doi: 10.1177/0253717620946111.
Taber KS. The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Res Sci Educ 2018;48:1273-96. doi: 10.1007/s11165-016-9602-2.
Rigdon EE. Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods. Long Range Plann 2012;45:341-58. doi: 10.1016/j.lrp.2012.09.010.
Shmueli G, Koppius OR. Predictive analytics in information systems research. MIS Q Manag Inf Syst 2011;35:553-572. doi: 10.2307/23042796.
Yang M, Mamun AA, Mohiuddin M, Nawi NC, Zainol NR. Cashless transactions: a study on intention and adoption of e-wallets. Sustainability 2021;13:831. doi: 10.3390/su13020831.
Geng L, Hui H, Liang X, Yan S, Xue Y. Factors affecting intention toward ICT adoption in rural entrepreneurship: understanding the differences between business types of organizations and previous experience of entrepreneurs. Sage Open 2023;13:21582440231197112. doi: 10.1177/21582440231197112.
Haque AB, Islam AKMN, Hyrynsalmi S, Naqvi B, Smolander K. GDPR Compliant Blockchains–A Systematic Literature Review. IEEE Access 2021;9:50593-606. doi: 10.1109/ACCESS.2021.3069877.
Act A. Health insurance portability and accountability act of 1996. Public Law 1996;104:191.
Barbaria S, Jemai A, Ceylan Hİ, Muntean RI, Dergaa I, Boussi Rahmouni H. Advancing compliance with HIPAA and GDPR in healthcare: a blockchain-based strategy for secure data exchange in clinical research involving private health information. Healthcare 2025;13:2594. doi: 10.3390/healthcare13202594.
Suroso A, Rafinda A. Motivation of SME adopt digital marketing. Int J Innov Creat Change 2021;15:696-710.
Al-Okaily M, Al-Qudah AA, Alkhwaldi AF, Alkhatib AW, Al-Okaily A, Abu-Salih B. Exploring FinTech trends in Jordan: insights from the post-COVID-19 era. foresight 2025;27:789-819.
Alkhwaldi AF, Abu-AlSondos IA, Shehadeh M, Ajouz M, Abdulmuhsin AA. Investigating user acceptance of AI-driven fintech services through the lens of the UTAUT model. In: International Conference on Technology and Innovation Management. Springer; 2024:305-15.
Dbesan AH, Abdulmuhsin AA, Alkhwaldi AF. Adopting knowledge-sharing-driven blockchain technology in healthcare: a developing country’s perspective. VINE J Inf Knowl Manag Syst 2025;55:683-709.
Abdulmuhsin AA, Dbesan AH, Rehman SU, Alnoor A, Alkhwaldi AF. Redefining knowledge-generation-driven blockchain for healthcare use: Insights from medical institutions. Health Serv Manage Res 2025:09514848251358332.
Khan WU, Shachak A, Seto E. Understanding decision-making in the adoption of digital health technology: The role of behavioral economics’ prospect theory. J Med Internet Res 2022;24:e32714.
Okunade SO, Olawumi AT, Adeyemi OJ, Amosun O. Socio-economic and security effects of financial exclusion in Africa: An experts’ View. Ann Soc Sci Manag Stud 2023.
Meyliana M, Fernando E, Surjandy S. The Influence of perceived risk and trust in adoption of FinTech services in Indonesia. CommIT Commun Inf Technol J 2019;13:31. doi: 10.21512/commit.v13i1.5708.
Putrevu J, Mertzanis C. The adoption of digital payments in emerging economies: challenges and policy responses. Digit Policy Regul Gov 2024;26:476-500.
Al-Anezi F. Interlinking FinTech and eHealth: a qualitative study. Front Public Health 2024;12:1398136.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.