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Factors Affecting Adoption of Telemedicine for Virtual Healthcare Services in Indonesia

Journal of Information Systems Engineering and Business Intelligence · Vol. 9 No. 1 (2023) · pp. 47–69

DOI
10.20473/jisebi.9.1.47-69
ISSN
2443-2555, 2598-6333
Published
2023-04-28
Publisher
Universitas Airlangga
Language
eng
License
creativecommons.org/licenses/by/4.0

Abstract

Background: The utilization of virtual healthcare services, particularly telemedicine, has been accelerated by the COVID-19 pandemic. Although the pandemic is no longer the primary concern, telemedicine still holds potential for long-term adoption. However, implementing telemedicine in Indonesia as an online platform for remote healthcare delivery still faces issues, despite its potential. Further investigation is required to identify the factors that affect its adoption and develop strategies to surmount implementation challenges. Objective: This study aims to examine and enrich knowledge about the adoption of telemedicine in Indonesia. Methods: A cross-sectional survey was conducted through an online questionnaire to collect data. Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was employed by integrating with several factors, such as eHealth Literacy, Privacy Concerns, and Trust. Gender and age were considered as moderating variables. Data samples were analyzed using Partial Least Square – Structural Equation Modeling (PLS–SEM). Results: The findings suggest that performance expectancy, effort expectancy, social influence, eHealth literacy, and trust have a significant impact on adults' behavioral intention to use telemedicine. However, facilitating condition, price value, and privacy concern do not show any significant effects on adults' Behavioral Intention to Use Telemedicine. Conclusion: This study highlights the importance of understanding adoption factors to develop effective strategies. Results show performance expectancy, effort expectancy, social influence, eHealth literacy, and trust are significant factors, while facilitating condition, price value, and privacy concern are not. The UTAUT2 model is a good predictive tool for healthcare adoption. To increase usage intention, several aspects must be considered in the implementation of telemedicine. Keywords: Adoption, Behavioral Intention to Use, Telemedicine, UTAUT2, Virtual Healthcare.

Collaboration network of the authors

16 authors · 36 co-authorship links · 10 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Indonesia
  • Perbanas Institute
  • National Research and Innovation Agency
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Nandhita Zefania MaharaniUniversity of Indonesia3
Erisva Hakiki PurwaningsihUniversity of Indonesia3
Hisyam AthayaUniversity of Indonesia3
Sari SisilianingsihUniversity of Indonesia3
Ra'idah Naufaliana DewiPerbanas Institute1
Dwi Atmodjo WpPerbanas Institute1
Andre NurrohmanUniversity of Indonesia1
Hanifa FissalmaUniversity of Indonesia1
Alex FerdinansyahUniversity of Indonesia1
Dana Indra SensuseUniversity of Indonesia1
Deden Sumirat HidayatNational Research and Innovation Agency1
Shabrina Salsabila KurniawanUniversity of Indonesia1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://e-journal.unair.ac.id/JISEBI/oai, first harvested 29 Okt 2026, last seen 29 Okt 2026.
Original metadata (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Factors Affecting Adoption of Telemedicine for Virtual Healthcare Services in Indonesia</dc:title>
	<dc:creator>Alviani, Rima</dc:creator>
	<dc:creator>Purwandari, Betty</dc:creator>
	<dc:creator>Eitiveni, Imairi</dc:creator>
	<dc:creator>Purwaningsih, Mardiana</dc:creator>
	<dc:description xml:lang="en-US">Background: The utilization of virtual healthcare services, particularly telemedicine, has been accelerated by the COVID-19 pandemic. Although the pandemic is no longer the primary concern, telemedicine still holds potential for long-term adoption. However, implementing telemedicine in Indonesia as an online platform for remote healthcare delivery still faces issues, despite its potential. Further investigation is required to identify the factors that affect its adoption and develop strategies to surmount implementation challenges.
Objective: This study aims to examine and enrich knowledge about the adoption of telemedicine in Indonesia.
Methods: A cross-sectional survey was conducted through an online questionnaire to collect data. Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was employed by integrating with several factors, such as eHealth Literacy, Privacy Concerns, and Trust. Gender and age were considered as moderating variables. Data samples were analyzed using Partial Least Square – Structural Equation Modeling (PLS–SEM).
Results: The findings suggest that performance expectancy, effort expectancy, social influence, eHealth literacy, and trust have a significant impact on adults' behavioral intention to use telemedicine. However, facilitating condition, price value, and privacy concern do not show any significant effects on adults' Behavioral Intention to Use Telemedicine.  
Conclusion: This study highlights the importance of understanding adoption factors to develop effective strategies. Results show performance expectancy, effort expectancy, social influence, eHealth literacy, and trust are significant factors, while facilitating condition, price value, and privacy concern are not. The UTAUT2 model is a good predictive tool for healthcare adoption. To increase usage intention, several aspects must be considered in the implementation of telemedicine.
 
Keywords: Adoption, Behavioral Intention to Use, Telemedicine, UTAUT2, Virtual Healthcare.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Airlangga</dc:publisher>
	<dc:date>2023-04-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://e-journal.unair.ac.id/JISEBI/article/view/41371</dc:identifier>
	<dc:identifier>10.20473/jisebi.9.1.47-69</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Information Systems Engineering and Business Intelligence; Vol. 9 No. 1 (2023): April; 47-69</dc:source>
	<dc:source>2443-2555</dc:source>
	<dc:source>2598-6333</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://e-journal.unair.ac.id/JISEBI/article/view/41371/24455</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 The Authors. Published by Universitas Airlangga.</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>