How to cite:
Desi S.W. Utami, Fajri Satria Wika, Hertinur Betthy S., Oscar (2024) Determinants of Behavioral
Intention Toward Telemedicine Services in Indonesia Post-Pandemic COVID-19, (06) 09,
E-ISSN:
2684-883X
DETERMINANTS OF BEHAVIORAL INTENTION TOWARD TELEMEDICINE
SERVICES IN INDONESIA POST-PANDEMIC COVID-19
Desi S.W. Utami, Fajri Satria Wika, Hertinur Betthy S., Oscar
Universitas Prasetiya Mulya, Indonesia
Abstract
The COVID-19 pandemic has significantly disrupted daily life & accelerated the adoption of
digital technologies across various sectors, including healthcare. In Indonesia, this shift has
prompted the rapid development and implementation of Telemedicine services by both start-
ups and established healthcare institutions. This study aims to identify the factors that
influence customer intention to use Telemedicine services in the post-pandemic period, using
the Unified Theory of Acceptance and Use of Technology (UTAUT2) model. The research
focuses on five key variables: Price Value, Effort Expectancy, Geographical Location,
Performance Expectancy, and Social Influence. Data collected from 507 respondents across
Indonesia through an online questionnaire reveals that user satisfaction is critical for further
use of Telemedicine services. The findings indicate that improvements in the affordability,
user-friendliness, accessibility, effectiveness, and social endorsement of Telemedicine
services significantly enhance user satisfaction. The study provides practical
recommendations for Telemedicine providers to improve these factors, thereby increasing
customer retention and adoption rates. This research contributes to the understanding and
offers insights for optimizing telemedicine services in Indonesia in relation to evolving post-
pandemic behaviors.
Keywords: Telemedicine Services, Digital Application, User Satisfaction, Customer
Intention, Post-pandemic COVID-19.
INTRODUCTION
The COVID-19 pandemic has fundamentally altered the way people live, work, and
interact, driving an unprecedented shift towards digital solutions in various sectors.
Healthcare is one of the sectors that transformed during the COVID-19 pandemic. To
minimize the spread of the virus, governments worldwide implemented social distancing &
lockdown measures (Srisathan & Naruetharadhol, 2022). These policies significantly reduced
in-person interactions and accelerated the adoption of digital technologies for everyday
activities such as working, shopping, learning, and seeking medical advice.
In Indonesia, the healthcare sector has witnessed a rapid transformation, with digital
health services becoming increasingly important. The need for maintaining social distance
while providing essential healthcare services led to the massive adoption of Telemedicine.
Defined by the National Library of Medicine as the use of electronic information and
communication technologies to provide and support healthcare when distance separates the
participants, Telemedicine became a crucial tool during the pandemic. It facilitated remote
JOURNAL SYNTAX IDEA
p–ISSN: 2723-4339 e-ISSN: 2548-1398
Vol. 6, No. 09, September 2024
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consultations, reducing the need for physical visits to healthcare facilities and thereby
minimizing the risk of virus transmission (Tandon et al., 2018).
The pandemic urged necessity for Telemedicine has proved the important for innovation
and growth within the digital health ecosystem. According to (Richards, 2023), technologies
advancements and the growing number of internet users in Asia are reshaping the healthcare
landscape, making it more digitally oriented. Indonesia, with its large population and limited
access to healthcare services in rural areas, has emerged as one of the top countries utilizing
online health applications. (Vivi Silvia, 2020) reported that 57% of survey respondents in
Indonesia used online health applications, reflecting a significant demand for remote
healthcare services (Zobair et al., 2019).
As the pandemic subsides and social distancing measures are relaxed, it becomes crucial
to understand the factors that will continue to drive the adoption of Telemedicine. This study
aims to identify the determinants of customer intention to use Telemedicine services in the
post-pandemic era. Using the Unified Theory of Acceptance and Use of Technology
(UTAUT2) model, this research examines five key variables: Price Value, Effort Expectancy,
Geographical Location, Performance Expectancy, and Social Influence. By analyzing data
from 507 respondents across Indonesia, this study tested the factors that influence user
satisfaction and future use intentions of Telemedicine services.
Understanding these factors is essential for healthcare providers and policy makers to
enhance the effectiveness and adoption of Telemedicine. By addressing the critical
determinants of user satisfaction, Telemedicine providers can better meet the needs of their
customers, ensuring the sustainability and growth of digital healthcare services in Indonesia’s
evolving post-pandemic landscape. Moreover, Indonesia’s large population and geographical
challenges give opportunities for innovating Telemedicine services.
RESEARCH METHOD
The online questionnaire was created using Google Forms. Then it was distributed using
social media platforms in Indonesia such as WhatsApp, Facebook, and Instagram. Some of
the eligibility criteria for filler participants are: (1) have used telemedicine applications
(Halodoc, Alodokter, Fit Aja, GoodDoctor, Yakes, etc.). The exclusion criteria were those
who did not complete the questionnaire in its entirety.
A total of 877 people participated in this study. From this data, 507 respondents who
were users of telemedicine applications in the last year will be analyzed. This sample size
meets the minimum criteria for analysis using Statistical Product and Service Science. Table 1
shows the demographic characteristics of respondents.
The questionnaire includes the following sections: (1) demographic information
including gender, age, marital status, employment status, education level, province, and
monthly income, (2) performance expectancy, (3) effort expectancy, (4) social influence, (5)
Price value, (6) geographical location, (7) user satisfaction, (8) Behavioral intention. Each
indicator construct is measured using a five-point Likert scale starting from strongly disagree
(1) to strongly agree (5). Seen in Table 2 are the indicators used to measure various factors
that influence the intention to use telemedicine services in Indonesia. Specifically, SEM is
carried out using SPSS to find out the cause of different latent variable relationships (SPSS,
2015).
Determinants of Behavioral Intention Toward Telemedicine Services in Indonesia Post-
Pandemic COVID-19
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SPSS is one of the most widely used application programs for the analysis of statistics
in social sciences. It is used by market researchers, survey companies, health researchers,
government, educational researchers, marketing organizations, and others. SPSS can read
various types of data or enter data directly into its SPSS Data Editor. Whatever the structure
of the raw data file, the data in Data The SPSS editor must be formed in the form of rows
(cases) and columns (variables). Case contains information for one unit of analysis, while
variables are collected information of each case.
In research that uses quantitative methods, the quality of data collection is largely
determined by the quality of the instruments or data collection tools used. Research
instruments are said to be of good quality and can be accounted for if they are proven valid
and reliable. Testing the validity and reliability of the instrument, of course, must be adapted
to the form of the instrument that will be used in the research. Testing the validity and
reliability of the questionnaire is needed to ensure that the questionnaire used in research can
measure research variables well. validity shows the extent to which the measuring instrument
can measure what it wants to measure. testing Cronbach's alpha statistics, an instrument is
said to be reliable for measuring variables if it has an alpha value greater than 0.60. Looking
at Cronbach's alpha value and each variable, the level of reliability is generally acceptable at a
value of 0.60. Test that reliability below 0.60 is considered unreliable..
RESULT AND DISCUSSION
The R-Square values for Behavioral Intention and User Satisfaction are 0.456 and
0.657, respectively, indicating that 45.6% of the variance in behavioral intention can be
explained by user satisfaction, while 65.7% of the variance in user satisfaction can be
explained by performance expectancy, effort expectancy, social influence, price value, and
geographical location. This indicates that both models have moderate strength of predictive
accuracy.
Reliability testing is conducted through Cronbach’s Alpha and composite reliability
values. These values need to be evaluated if they are above 0.70 or not. The upper limit
commonly used as a criterion is composite reliability, while the lower limit is Cronbach’s
Alpha. If both have values > 0.70, it can be said that the variables in this study are reliable
with the assumption that the model is correct. However, it should be noted that the values
should not exceed 0.95 as it may cause redundancy. Table 3 enlists reliability and convergent
validity analysis are presented.
Communality is the proportion of variance for each observed variable that can be
explained by the factors. Communalities between 0.25 and 4.0 are acceptable, with values
above 0.6 considered ideal.
The Kaiser-Meyer-Olkin (KMO) Test is a measure of how suited the data is for Factor
Analysis. The test measures sampling adequacy for each variable in the model and for the
complete model. The statistic is a measure of the proportion of variance among variables that
might be common variance. The lower the proportion, the more suited your data is to Factor
Analysis.
For reference, Kaiser put the following values on the results:
Desi S.W. Utami, Fajri Satria Wika, Hertinur Betthy S., Oscar
3900 Syntax Idea, Vol. 6, No. 09, September 2024
1. 0.00 to 0.49 unacceptable.
2. 0.50 to 0.59 miserable.
3. 0.60 to 0.69 mediocre.
4. 0.70 to 0.79 middling.
5. 0.80 to 0.89 meritorious.
6. 0.90 to 1.00 marvelous.
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Pandemic COVID-19
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