Acceptance of Halodoc’s Online Teleconsultation During Covid-19

##plugins.themes.academic_pro.article.main##

Amelia Andriani
Margaretha Pink Berlianto

Abstract

This research aims to analyse the positive effect of  performance expectancy, effort expectancy, social influence, attitude toward using technology, perceived ease of use, and  perceived usefulness on behaviour intention, the positive effect of   behaviour intention on usage behaviour. This study used quantitative research and data collection was collected using questionnaire. The target population of this research were people that have done online teleconsultation at Halodoc and willing to be respondents of this research. The number of samples were determined to be which 224 samples.  The sampling technique use was purposive sampling. Partial Least Square-Structural Equation modelling (PLS-SEM) is applied to this study. The results of data analysis showed all of the hypothesis supported that  performance expectancy, effort expectancy, social influence, attitude toward using technology, perceived ease of use, and  perceived usefulness have positive effect on behaviour intention. Lastly, behaviour intention has a positive effect on  usage behaviour in acceptance of Halodoc’s online teleconsultation during COVID-19.

##plugins.themes.academic_pro.article.details##

How to Cite
Andriani, A., & Berlianto, M. P. (2022). Acceptance of Halodoc’s Online Teleconsultation During Covid-19. Enrichment : Journal of Management, 12(2), 1566-1574. Retrieved from https://enrichment.iocspublisher.org/index.php/enrichment/article/view/432

References

Ahadzadeh, A. S., Wu, S. L., Ong, F. S., & Deng, R. (2021). The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study. Journal of medical Internet research, 23(12), e28086.
Alexandra, S., Handayani, P. W., & Azzahro, F. (2021). Indonesian hospital telemedicine acceptance model: the influence of user behavior and technological dimensions. Heliyon, 7(12), e08599.
Alhasan, A., Audah, L., Ibrahim, I., Al-Sharaa, A., Al-Ogaili, A. S., & M. Mohammed, J. (2020). A case-study to examine doctors’ intentions to use IOT healthcare devices in Iraq during COVID-19 pandemic. International Journal of Pervasive Computing and Communications. https://doi.org/10.1108/ijpcc-10-2020-0175
Burhan, O. F. A. (2021, March 1). Pengguna Halodoc Naik Dua Kali Lipat, Layanan Dokter paling diminati. Startup Katadata.co.id. Retrieved March 28, 2022, from https://katadata.co.id/yuliawati/digital/603cc92f0dd5d/pengguna-halodoc-naik-dua-kali-lipat-layanan-dokter-paling-diminati
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in psychology, 10, 1652.
Coronavirus cases: Worldometer. (n.d.). Retrieved March 28, 2022, from https://www.worldometers.info/coronavirus/#countries
Fatmawati, E. (2015). Technology Acceptance model (TAM) untuk menganalisis penerimaan terhadap sistem informasi di perpustakaanM INFORMASI PERPUSTAKAAN. Iqra: Jurnal Perpustakaan dan Informasi, 9(1), 196942.
Ghozali, I., & Latan, H. (2015). Partial least squares konsep, teknik dan aplikasi menggunakan program smartpls 3.0. Badan Penerbit Universitas Diponegoro Semarang.
Halodoc. (2016). Media informasi. halodoc. Retrieved March 28, 2022, from https://www.halodoc.com/media
Hoque, R. and Sorwar, G. (2017), “Understanding factors influencing the adoption of mHealth by the elderly: an extension of the UTAUT model”, International Journal of Medical Informatics, Vol. 101, pp. 75-84
Ifinedo, P. (2016). Applying uses and gratifications theory and social influence processes to understand students' pervasive adoption of social networking sites: Perspectives from the Americas. International Journal of Information Management, 36(2), 192-206.
J. M. Tsai, M. J. Cheng, H. H. Tsai, S. W. Hung, & Y. L. Chen, (2019). Acceptance and resistance of telehealth: The perspective of dual-factor concepts in technology adoption, Int. J. Inf. Manage., Vol. 49, No. March, pp. 34–44
Kaium, M.A., Bao, Y., Alam, M.Z. and Hoque, M.R. (2020), “Understanding continuance usage intention of mHealth in a developing country”, International Journal of Pharmaceutical and Healthcare Marketing, Vol. 14 No. 2, pp. 251-272, doi: 10.1108/ijphm-06-2019-0041.
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212.
Khan, I., Xitong, G., Ahmad, Z., & Shahzad, F. (2019). Investigating factors impelling the adoption of e-health: a perspective of African expats in China. Sage Open, 9(3), 2158244019865803.
Kissi, J., Dai, B., Dogbe, C. S., Banahene, J., & Ernest, O. (2020). Predictive factors of physicians’ satisfaction with telemedicine services acceptance. Health informatics journal, 26(3), 1866-1880.
Kotler, Philip. (2014). ManajemenPemasaran,.Edisi 13. Jilid 1. Prenhalindo.Jakarta
Lee, W. I., Fu, H. P., Mendoza, N., & Liu, T. Y. (2021, May). Determinants impacting user behavior towards emergency use intentions of m-health services in Taiwan. In Healthcare (Vol. 9, No. 5, p. 535). Multidisciplinary Digital Publishing Institute.
Lu, X., Zhang, R., & Zhu, X. (2019). An empirical study on patients’ acceptance of physician-patient interaction in online health communities. International Journal of Environmental Research and Public Health, 16(24), 5084. https://doi.org/10.3390/ijerph16245084
Manda, E.F., Salim, R., 2021. Analysis of the influence of perceived usefulness, perceived ease of use and attitude toward using technology on actual to use Halodoc application using the technology acceptance model (TAM) method approach. Int. Res. J. Adv. Eng. Sci. 6 (1), 135–140. http://irjaes.com/wp-content/uploads/2021/01/IRJ AES-V6N1P101Y21.pdf.
Pikkemaat, M., Thulesius, H., & Nymberg, V. M. (2021). Swedish primary care physicians’ intentions to use telemedicine: A survey using a new questionnaire–physician attitudes and intentions to use telemedicine (pait). International Journal of General Medicine, 14, 3445.
Pusparisa, Y. (2020). Indonesia peringkat KE-3 global Memanfaatkan Aplikasi Kesehatan: Databoks. Databoks Pusat Data Ekonomi dan Bisnis Indonesia. Retrieved March 28, 2022, from https://databoks.katadata.co.id/datapublish/2020/10/13/indonesia-peringkat-ke-3-global-memanfaatkan-aplikasi-kesehatan
Qin, H., Prybutok, V. R., & Zhao, Q. (2010). Perceived service quality in fast‐food restaurants: Empirical evidence from China. International Journal of Quality & Reliability Management.
Rahi, S. (2021), "Assessing individual behavior towards adoption of telemedicine application during COVID-19 pandemic: evidence from emerging market", Library Hi Tech, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/LHT-01-2021-0030
Ramírez-Rivas, Catalina & Alfaro-Pérez, Jorge & Ramírez-Correa, Patricio & Mariano, Ari. (2020). Telemedicine Acceptance in Brazil : Explaining behavioral intention to move towards internet-based medical consultations. 1-4. 10.23919/CISTI49556.2020.9140996.
Telemedicine - World Health Organization. (2010). Retrieved March 28, 2022, from https://www.who.int/goe/publications/goe_telemedicine_2010.pdf
Tsai, C. H. (2014). Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioral model of telehealth systems. International journal of environmental research and public health, 11(5), 4905-4925.
Tsai, C. H. (2014). The adoption of a telehealth system: the integration of extended technology acceptance model and health belief model. Journal of Medical Imaging and Health Informatics, 4(3), 448-455.
Tsai, J. M., Cheng, M. J., Tsai, H. H., Hung, S. W., & Chen, Y. L. (2019). Acceptance and resistance of telehealth: The perspective of dual-factor concepts in technology adoption. International Journal of Information Management, 49, 34-44.
Utomo, Y., & Walujo, D. A. (2018). Penerapan konstruk technology acceptance model (tam) pada layanan mobile application di pdam surya sembada kota surabaya. WAKTU: Jurnal Teknik UNIPA, 16(1), 39-48.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
Venkatesh, V., Thong, J., & Xu, X. (2012). Consumers Acceptance and Use Information Technology: Extending The Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 157-178.
Wang, Z., & Li, H. (2016). Factors Influencing Usage of Third Party Mobile Payment Services in China: An Empirical Study.
Yuswohady, Rachmaniar , A., Fatahillah, F., Brillian, gilang, & Hanifah, I. (2021). Overview Healthcare Industry Outlook 2021 – Consumeri Indonesia. Retrieved March 28, 2022, from https://inventureknowledge.id/overview-healthcare-industry-outlook-2021/