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
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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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Discussion
The purpose of this study is to verify independent factors that influence the satisfaction
of telemedicine customers that will affect the intention to use telemedicine applications in
Indonesia using the UTAUT2 model. Several independent factors such as performance
expectancy, effort expectancy, social influence, price value, and geographical location were
analyzed together to determine the significance of each independent factor to user satisfaction
with telemedicine to behavior intention to use telemedicine. Based on the demographic
collected during the survey, we found out that the Halodoc application which was selected by
64% of the participants as the only telemedicine application they have used. At the same time,
Halodoc is also chosen by 25% of participants who select more than two telemedicine
applications they have used in the past.
Performance expectancy measures the degree to which a user believes that using
technology will help them achieve better productivity or outcomes. In our study, we focused
Determinants of Behavioral Intention Toward Telemedicine Services in Indonesia Post-
Pandemic COVID-19
Syntax Idea, Vol. 6, No. 09, September 2024 3903
on the impact of performance expectancy from a telemedicine application on user satisfaction
which eventually will increase the behavior intention to use the telemedicine application.
From this study, we found that most participants expect that by using telemedicine
applications they can get useful healthcare services that can be delivered faster and time
efficiently which can help them to be able to improve and manage their day-to-day health
better. Participants will use the telemedicine application more often should they believe the
benefits of using telemedicine are better compared to visiting healthcare facilities. This study
confirms that performance expectancy has a direct positive contribution to user satisfaction
that will lead to an increase in participants’ behavioral intention to use telemedicine
applications. The positive influence of performance expectancy on user satisfaction has also
been mentioned in several previous studies (Lisana, 2024; Pramudita et al., 2023; Rahi, 2022).
Effort expectancy can be described as the level of ease of use of a technology which has
an impact on user eagerness to use the technology. From our study, we found that most of the
survey participants believe it is easy for them to use telemedicine applications even when the
participants come from various backgrounds with different levels of information technology
literacy. Most of the participants believed most of the telemedicine applications are easy to
use and easy to learn for first-time or less frequent users. There is no significant difficulty or
obstacle to operating the application, and they believe they can master the use of telemedicine
applications. The more user-friendly the application will increase the possibility that an
application will be used more often. This study found effort expectancy is the second most
important factor that gives a positive contribution to user satisfaction. The positive influence
of effort expectancy on user satisfaction has also been mentioned in several previous studies
(Chen & Ong, 2022; Esawe, 2022; Lisana, 2024; Pramudita et al., 2023).
Social influence measures the degree to which an individual perceives that other people,
who are important and have a significant influence on telemedicine applications, believe they
should use the new technology. Through this study, we found that social influence has the
lowest positive contribution to user satisfaction in using telemedicine applications. Even
though social influence is the least significant influence on user satisfaction with telemedicine
applications, most of the respondents believe people close to them, such as family and
colleagues at work, should use telemedicine applications. The respondents also believe that
using telemedicine applications makes them look more prestigious or better compared to
those who do not use telemedicine. In some previous studies (Chetioui et al., 2023; K. Gupta
& Arora, 2020; Lisana, 2024) social influence was also noted to have a positive influence on
user satisfaction with mobile or internet-based applications (such as telemedicine and mobile
banking).
Price value is defined as consumers' cognitive trade-off between the perceived benefits
of the applications and the cost of using them. In this study, we found that price value is the
most significant factor that has a positive influence on user satisfaction compared to the other
factors. This finding is consistent with previous studies (K. P. Gupta et al., 2019; Kalinić et
al., 2019; Pramudita et al., 2023). This finding confirmed that most of the users of
telemedicine believe they can get greater benefits compared to the cost they pay. They also
Desi S.W. Utami, Fajri Satria Wika, Hertinur Betthy S., Oscar
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believe that telemedicine costs are within their budget. This finding might be attributed to the
fact that 58% of the users of telemedicine are coming from high-income users.
Geographical location was the last variable tested in this study that has a positive
influence on the user satisfaction of telemedicine users. Geographical location is related to
how the location of a user has an impact on the user’s intention to use a telemedicine
application. Indonesia's population which is spreading across the entire archipelago with
different levels of healthcare facility conditions between provinces may cause some problems
for people of Indonesia to access healthcare services. This study confirms that geographical
location has a positive influence on user satisfaction among telemedicine users. Most of the
users believe they can access telemedicine applications easily from their current location. This
study also confirms that the location of the users plays a significant role in determining user
intention to use telemedicine applications. The telemedicine application helps users from one
location to have access to better healthcare facilities or health workers in different locations
easily.
This study verifies that user satisfaction has a positive influence on user behavior and
intention to use telemedicine. This finding is in line with previous studies (Kalinić et al.,
2019; Lee et al., 2021; Pramudita et al., 2023). Based on this study, user satisfaction highly
influences user intention to use or reuse telemedicine applications = 0.676, p-value =
0.000). Through this study, we found that users believe telemedicine applications can satisfy
their needs and expectations which leads to user intention to use telemedicine applications in
the future whenever they want to get healthcare services. To some extent, they also intend to
use telemedicine applications as their first choice option in terms of healthcare services.
CONCLUSION
User satisfaction is still a mediating factor for behavioral intention to use telemedicine.
The price value is the most significant factor in driving user satisfaction, which can be an
opportunity for telemedicine providers to maintain existing customers and use a competitive
advantage by providing more affordable prices with the same level of services or higher, and
apply pricing strategy. Future research may exercise acceptable prices for services provided
by telemedicine applications in Indonesia.
This study could provide a better understanding of the telemedicine user ratio in each
province by applying the location of respondents as part of a filter questionnaire. In addition
to the above recommendation, future research may include data privacy to measure user
satisfaction as it becomes a serious concern.
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