The Economic Impact of Real-Time Connectivity and User Readiness on Digital Health Adoption: An Extended TAM Perspective
Abstract
This study examines the key determinants of digital health application adoption, extending the Technology Acceptance Model (TAM) to incorporate the economic and practical implications of real-time connectivity and user technology readiness. Given the escalating investment in mobile health technologies, understanding the factors driving user adoption is crucial for maximizing return on digital health investments and achieving widespread public health benefits. Utilizing a quantitative research design, we applied structural equation modeling to analyze survey data from 421 potential users. Our findings confirm the significant positive influence of perceived usefulness, perceived ease of use, and user technology readiness on adoption intention, thereby expanding the TAM framework. Crucially, real-time connectivity significantly impacts TAM factors, highlighting the economic necessity of robust technological infrastructure and user preparedness for successful digital transformation in healthcare. This research offers practical implications for developers, healthcare providers, and policymakers, emphasizing the need to prioritize user-centric designs, reliable connectivity, and initiatives that enhance technology readiness to foster the widespread adoption of interactive digital health solutions and optimize their economic and social impact.
References
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[19] Khoa, Bui Thanh. (2025). The Triple Helix of Digital Engagement: Unifying Technology Acceptance, Trust Signaling, and Social Contagion in Generation Z’s Social Commerce Repurchase Decisions. Journal of Theoretical and Applied Electronic Commerce Research, 20 (2):145. DOI: 10.3390/jtaer20020145
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[25] Tran, Anh Viet, and Bui Thanh Khoa. (2025a). Generation Z Customers’ Online Outbound Tourism Booking Intention in Vietnam: Extending the Technology Acceptance Model with Intercultural Competence. Geojournal of Tourism and Geosites, 60 (2spl): 1119-1127. DOI: https://doi.org/10.30892/gtg.602spl09-1485
[26] Tran, Anh Viet, and Bui Thanh Khoa. (2025b). Global Research Trends in Circular Economy: A Bibliometric Analysis in E‐Commerce. Human Behavior and Emerging Technologies, 2025 (1): 1-20. DOI:https://doi.org/10.1155/hbe2/8645845
[27] Tran, C. D., and T. T. Nguyen. (2021). Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps. Technol Soc, 67:101755. DOI: https://doi.org/10.1016/j.techsoc.2021.101755
[28] Uyen, Vo Thi Thao, Nguyen Minh Ly, Nguyen Thi Trang Oanh, and Bui Thanh Khoa. (2025). Decoding Fear of Missing Out in Social Commerce: A Novel Integration of TAM and TRA for Online Purchasing Behavior. Journal of Logistics, Informatics and Service Science, 12 (3): 50-62. DOI:https://doi.org/10.33168/JLISS.2025.0304
[29] Venkatesh, Morris, Davis, and Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27 (3): 425-478. DOI: https://doi.org/10.2307/30036540
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[31] Zhang, Jing, and En Mao. (2023). What Makes Consumers Adopt a Wearable Fitness Device? International Journal of E-Business Research, 19 (1):1-17. DOI: https://doi.org/10.4018/ijebr.323204
[2] Aljedaani, Bakheet, Aakash Ahmad, Mansooreh Zahedi, and M. Ali Babar. (2023). End-users’ knowledge and perception about security of clinical mobile health apps: A case study with two Saudi Arabian mHealth providers. Journal of Systems and Software, 195:111519. DOI: https://doi.org/10.1016/j.jss.2022.111519
[3] Anh, Nguyen Thi Mai, et al. (2024). The Effect of Technology Readiness on Adopting Artificial Intelligence in Accounting and Auditing in Vietnam. Journal of Risk and Financial Management, 17 (1): 27. DOI:10.3390/jrfm17010027
[4] Ben-Zeev, D., A. Beaulieu, J. Guler, A. Larsen, and A. Bawaneh. (2024). Readiness for mHealth interventions in Jordan: Refugee camp and urban community survey. Internet Interv, 36. DOI:10.1016/j.invent.2024.100746
[5] Çavmak, Doğancan, Sait Söyler, and Şeyda Çavmak. (2024). Understanding the Role of Technology Readiness and Digital Health Literacy in Intention to Use Remote Healthcare Services. Sağlık ve Hemşirelik Yönetimi Dergisi, 11 (2):233-242. DOI: https://doi.org/10.54304/shyd.2024.62681
[6] Cuong, Do Bui Xuan Khanh, Tran, Bui Thanh Khoa, and Le Dao Ngoc Thanh. (2025). Digital Transformation and Sustainable Tourism: An Integrated Model for Heritage Destination Revisitation in the Service Innovation Era. Journal of Service, Innovation and Sustainable Development, 6 (1):14-28. DOI:https://doi.org/10.33168/SISD.2025.0102
[7] Davis, Fred D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13 (3):319-340. DOI: https://doi.org/10.2307/249008
[8] Duy, N. B. P., V. T. T. Nguyen, and B. T. Khoa. (2025). From flow experience determinants to user behavior: A study on online food ordering platforms via mobile applications. Journal of Open Innovation: Technology, Market, and Complexity, 11 (2). DOI: https://doi.org/10.1016/j.joitmc.2025.100551
[9] Guk, K., et al. (2019). Evolution of Wearable Devices with Real-Time Disease Monitoring for Personalized Healthcare. Nanomaterials (Basel), 9 (6): 813. DOI: https://doi.org/10.3390/nano9060813
[10] Hair Jr, et al. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Washington DC: Sage publications.
[11] Isakovic, M., U. Sedlar, M. Volk, and J. Bester. (2016). Usability Pitfalls of Diabetes mHealth Apps for the Elderly. J Diabetes Res, 2016: 1604609. DOI: https://doi.org/10.1155/2016/1604609
[12] Jabbar, Abdul, Pervaiz Akhtar, and Samir Dani. (2020). Real-time big data processing for instantaneous marketing decisions: A problematization approach. Industrial Marketing Management, 90: 558-569. DOI:https://doi.org/10.1016/j.indmarman.2019.09.001
[13] James, D. C. S., and C. Harville, 2nd. (2018). Smartphone Usage, Social Media Engagement, and Willingness to Participate in mHealth Weight Management Research Among African American Women. Health Educ Behav, 45 (3): 315-322. DOI: https://doi.org/10.1177/1090198117714020
[14] Jayakumar, Sujayaraj Samuel, Ashwini Kumar, and Vikas Kumar Kharbas. (2024). Real-Time Connectivity with the Industrial Internet of Things. 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT).
[15] Kakria, P., N. K. Tripathi, and P. Kitipawang. (2015). A Real-Time Health Monitoring System for Remote Cardiac Patients Using Smartphone and Wearable Sensors. Int J Telemed Appl, 2015 (1): 373474. DOI:https://doi.org/10.1155/2015/373474
[16] Kang, Tae Wook, and Yunjeong Mo. (2024). A comprehensive digital twin framework for building environment monitoring with emphasis on real-time data connectivity and predictability. Developments in the Built Environment, 17:100309. DOI: https://doi.org/10.1016/j.dibe.2023.100309
[17] Khanh, Tran, Bui Thanh Khoa, and Do Bui Xuan Cuong. (2025). Digital Pathways to Sustainability: Empirical Evidence of Tourism Industry Transformation in the Industry 5.0 Era. Journal of Management Changes in Digital Era, 2:110-119. DOI: https://doi.org/10.33168/JMCDE.2025.0108
[18] Khoa, B. T., and T. T. Huynh. (2024). Why do generation X customers use wearable fitness technology equipment after recovering from coronavirus? The role of perceived health risks. Heliyon, 10 (12): e32978. DOI: https://doi.org/10.1016/j.heliyon.2024.e32978
[19] Khoa, Bui Thanh. (2025). The Triple Helix of Digital Engagement: Unifying Technology Acceptance, Trust Signaling, and Social Contagion in Generation Z’s Social Commerce Repurchase Decisions. Journal of Theoretical and Applied Electronic Commerce Research, 20 (2):145. DOI: 10.3390/jtaer20020145
[20] Mishra, Divya, Pushpa Singh, and Shivani Agarwal. (2022). AI- and IoT-Based Architecture in Healthcare. In Transformation in Healthcare with Emerging Technologies, 1-18. Chapman and Hall/CRC.
[21] Mujuni, D., et al. (2024). Beyond diagnostic connectivity: Leveraging digital health technology for the real-time collection and provision of high-quality actionable data on infectious diseases in Uganda. PLOS Digit Health, 3 (8). DOI: https://doi.org/10.1371/journal.pdig.0000566
[22] Priya, M. Mary Adline. (2024). "Optimized connectivity." In Antennas for Industrial and Medical Applications with Optimization Techniques for Wireless Communication, 162-171. CRC Press.
[23] Sachdev, Kanica, and Brejesh Lall. (2025). Next‐Gen Networked Healthcare: Requirements and Challenges. Current and Future Cellular Systems: Technologies, Applications, and Challenges, 165-183. DOI:https://doi.org/10.1002/9781394256075.ch9
[24] Singh, Suruchi, et al. (2022). Blockchain with cloud for handling healthcare data: A privacy-friendly platform. Materials Today: Proceedings, 62: 5021-5026. DOI: https://doi.org/10.1016/j.matpr.2022.04.910
[25] Tran, Anh Viet, and Bui Thanh Khoa. (2025a). Generation Z Customers’ Online Outbound Tourism Booking Intention in Vietnam: Extending the Technology Acceptance Model with Intercultural Competence. Geojournal of Tourism and Geosites, 60 (2spl): 1119-1127. DOI: https://doi.org/10.30892/gtg.602spl09-1485
[26] Tran, Anh Viet, and Bui Thanh Khoa. (2025b). Global Research Trends in Circular Economy: A Bibliometric Analysis in E‐Commerce. Human Behavior and Emerging Technologies, 2025 (1): 1-20. DOI:https://doi.org/10.1155/hbe2/8645845
[27] Tran, C. D., and T. T. Nguyen. (2021). Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps. Technol Soc, 67:101755. DOI: https://doi.org/10.1016/j.techsoc.2021.101755
[28] Uyen, Vo Thi Thao, Nguyen Minh Ly, Nguyen Thi Trang Oanh, and Bui Thanh Khoa. (2025). Decoding Fear of Missing Out in Social Commerce: A Novel Integration of TAM and TRA for Online Purchasing Behavior. Journal of Logistics, Informatics and Service Science, 12 (3): 50-62. DOI:https://doi.org/10.33168/JLISS.2025.0304
[29] Venkatesh, Morris, Davis, and Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27 (3): 425-478. DOI: https://doi.org/10.2307/30036540
[30] Yang, Q., et al. (2022). Modeling the Intention and Adoption of Wearable Fitness Devices: A Study Using SEM-PLS Analysis. Front Public Health, 10: 918989. DOI: https://doi.org/10.3389/fpubh.2022.918989
[31] Zhang, Jing, and En Mao. (2023). What Makes Consumers Adopt a Wearable Fitness Device? International Journal of E-Business Research, 19 (1):1-17. DOI: https://doi.org/10.4018/ijebr.323204
Published
2025-09-30
How to Cite
TRAN, Anh Viet; KHOA, Bui Thanh.
The Economic Impact of Real-Time Connectivity and User Readiness on Digital Health Adoption: An Extended TAM Perspective.
Theoretical and Practical Research in Economic Fields, [S.l.], v. 16, n. 3, p. 549-558, sep. 2025.
ISSN 2068-7710.
Available at: <https://journals.aserspublishing.eu/tpref/article/view/9099>. Date accessed: 28 oct. 2025.
doi: https://doi.org/10.14505/tpref.v16.3(35).02.
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