Telemedicine Application Adoption During the COVID-19 Pandemic: The Lens of the UTAUT Framework Model
DOI:
https://doi.org/10.61098/jarcis.v2i1.148Keywords:
Telemedicine, UTAUT, Intention to adopt, Task Technology Fit, Metode SEM SMARTPLSAbstract
The objective of this study is to analyze the impact of various factors such as performance expectancy, effort expectancy, social influence, facilitating conditions, technology characteristics, task characteristics, and self-efficacy within the framework of the UTAUT model on the intention to adopt telemedicine applications, particularly in light of the ongoing Covid-19 pandemic. A quantitative approach is employed for data analysis, with data being gathered through the distribution of online questionnaires. The research sample consists of 350 respondents, and the data is examined using the Structural Equation Modeling (SEM) technique facilitated by the SmartPLS software. The findings reveal a positive and significant relationship between task technology fit and technology fit, as well as between technology characteristics and technology fit. Furthermore, task technology fit is shown to positively and significantly influence the intention to adopt telemedicine applications, where the services are anticipated to offer health assistance to users of the application. This study offers valuable insights for application developers to enhance features and services to attract public interest in utilizing telemedicine applications..
Downloads
References
. Covid19.go.id, “Peta Sebaran Kasus Per Provinsi,” May 10, 2022. [Online]. Available: https://covid19.go.id/peta-sebaran. [Accessed: May 11, 2022].
. P. Pol dan A. M. Deshpande, “Telemedicine mobile system,” 2016.
. M. A. Y. Yamin dan B. A. Alyoubi, “Adoption of telemedicine applications among Saudi citizens during COVID-19 pandemic: An alternative health delivery system,” 2020.
. A. Jnr. Bokolo, “Exploring the adoption of telemedicine and virtual software for care of outpatients during and after the COVID-19 pandemic,” 2020
. E. F. Anggriani, N. Mutiah, dan F. Febriyanto, “Analisis Penerimaan dan Kepuasan User Aplikasi Peduli Lindungi Mempergunakan Metode UTAUT 2 dan EUCS,” JSiI (Jurnal Sistem Informasi), vol. 10, no. 1, pp. 12-19, 2023.
. R. H. Dai, R. Raupu, dan I. R. Padiku, “Penerapan Metode UTAUT Dalam Menganalisis Tingkat Kepuasan Pengguna Sistem Informasi Kearsipan Dinamis Terintegrasi (Srikandi),” Digital Transformation Technology, vol. 4, no. 1, pp. 87-96, 2024.
. H. Miner, B.A., A. Fatehi, M.D., D. Ring, M.D., Ph.D., dan J. S. Reichenberg, M.D., MBA, “Clinician Telemedicine Perceptions During the COVID-19 Pandemic,” Systems, vol. 115, no. 9, pp. 1704-1723, 2020.
. V. Venkatesh, M. G. Morris, G. B. Davis, dan F. D. Davis, “User acceptance of information technology: toward a unified view,” 2003.
. E. Park dan J. Ohm, “Factors influencing users’ employment of mobile map services,” Telematics and Informatics, 2014.
. H. San Martín and Á. Herrero, “Influence of the user’s psychological factors on the online purchase intention in rural tourism: Integrating innovativeness to the UTAUT framework,” Tour. Manag., vol. 33, no. 2, pp. 341–350, Apr. 2012, doi: 10.1016/j.tourman.2011.04.003.
. Venkatesh, Thong, and Xu, “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology,” MIS Q., vol. 36, no. 1, p. 157, 2012, doi: 10.2307/41410412.
. H. Mahardika, D. Thomas, M. T. Ewing, dan A. Japutra, “Experience and facilitating conditions as impediments to consumers’ new technology adoption,” The International Review of Retail, Distribution and Consumer Research, pp. 1-20, 2018.
. L. M. Maruping, H. Bala, V. Venkatesh, dan S. A. Brown, "Going beyond intention: Integrating behavioral expectation into the unified theory of acceptance and use of technology," Journal of the Association for Information Science and Technology, vol. 68, no. 3, pp. 623-637, 2017.
. K. S. Tan, S. C. Chong, dan B. Lin, "Intention to Use Internet Marketing: A Comparative Study between Malaysians and South Koreans," Kybernetes, vol. 42, pp. 888-905, 2013. doi: 10.1108/K-12-2012-0122
. Z. Vörös, D. Kehl, dan J.-F. Rouet, “Task Characteristics as Source of Difficulty and Moderators of the Effect of Time-on-Task in Digital Problem-Solving,” Journal of Educational Computing Research, 2020.
. R. R. Pai dan S. Alathur, “Assessing awareness and use of mobile phone technology for health and wellness: insights from India,” Health Policy Technol, 2019.
. K. Sohraby, D. Minoli, dan T. Znati, Wireless Sensor Networks: Technology, Protocols, and Applications, Wiley Publisher, 2007.
. M. A. Y. Yamin dan B. A. Alyoubi, "Adoption of telemedicine applications among Saudi citizens during COVID-19 pandemic: An alternative health delivery system," Journal of Infection and Public Health, vol. 13, no. 12, pp. 1845-1855, 2020.
. M. Memon, B. A. Soomro, dan N. Shah, “Enablers of entrepreneurial self-efficacy in a developing country,” 2019.
. M. Aljukhadar, S. Senecal, dan J. Nantel, "Is more always better? Investigating the task-technology fit theory in an online user context," Information & Management, vol. 51, no. 4, pp. 391-397, 2014.
. D. L. Goodhue dan R. L. Thompson, “Task technology fit and individual performance,” MIS Quarterly, vol. 19, no. 2, pp. 213-236, 1995.
. T. Hærem, B. T. Pentland, dan K. D. Miller, "Task complexity: Extending a core concept," Academy of Management Review, vol. 40, no. 3, pp. 446-460, 2015.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Beno Rahman, Agata Pratiwi Prawitasari, Yulius Anggi Setiawan, Lianna wijaya

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.