pISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 5, No. 5 Mei 2024 http://jist.publikasiindonesia.id/
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2449
Consumer Vulnerability After Pandemic Covid-19
on Using Mobile Health Apps
Christina Sudyasjayanti
Universitas Ciputra Surabaya, Indonesia
*Correspondence
ABSTRACT
Keywords: consumer
vulnerability; consumer
resilience; consumer
adaptability; purchase
satisfaction.
This research has highlighted the topic of consumer
resilience after the COVID-19 pandemic. This research
topic will enhance the subject of Health app users in
Indonesia. This research aims to find out the answer to
these research questions: the consumer vulnerability caused
by the lowest technology literacy, the consumer resilience
related to customers’ trust and privacy concerns, and
consumer adaptability caused by lack of personalization
that will affect purchase satisfaction on Health Apps.
Respondents of this research will be limited to 200 people
who used Health Apps during 2020-2023. Those
respondents will be selected from the four biggest
provinces in Java. This research method uses linear
regression analysis to determine the influence of consumer
vulnerability and consumer resilience toward purchase
satisfaction and the moderating effect of consumer
adaptability upon consumer vulnerability toward purchase
satisfaction and consumer resilience toward purchase
satisfaction. The result showed that consumer adaptability
did not strengthen the relationship between consumer
vulnerability toward purchase satisfaction and consumer
resilience toward purchase satisfaction. Alas, each variable
significantly affected purchase satisfaction.
Introduction
The Indonesian Ministry of Health stated that more and more Indonesians are
using health applications (Skowron & Kristensen, 2012). This is why the Ministry of
Health regulates the mapping of the digitalization path of health care services in
Indonesia by releasing the 2024 Health Digital Transformation Strategy Blueprint at the
end of 2021 (Kirk & Rifkin, 2020). The digitalization of health services is carried out to
simplify and facilitate access to services for the general public without reducing the
quality and efficiency of health services. "Connection between key players in the health
industry in a vast and diverse country like Indonesia is a must to ensure the success of
digital transformation in health services," said the Chief Digital Transformation Office
of the Indonesian Ministry of Health, Setiaji, in the APL Digital Summit 2022
discussion in Jakarta. Mainly since the COVID-19 pandemic occurred, which had
Christina Sudyasjayanti
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2450
disrupted the mobility of many people. Boston Consulting Group (BCG) Managing
Director Sumit Sharma said that the pandemic had significantly boosted the local health
technology industry and increased health awareness. It was found that the applications
most used by Indonesians were Halodoc (71 percent), then Alodokter (56 percent), Klik
Dokter (30 percent), Good Doctor (13 percent), and YesDok (12 percent). The average
user of the application is 18-50 years old. The changing trends in the digital health
industry are also becoming more apparent. According to Sumit, pharmaceutical
companies and hospitals with digitized operations will be able to keep pace with
technological innovation and increase patient expectations for smoother and simpler
health services.
Figure 1. Global Health Application User Distribution Data
Source: databoks.id (2020)
While health apps have gained popularity in recent years, there are still several
gaps and challenges among customers when using these apps. Some individuals may
lack the technological skills to navigate and utilize health apps effectively. The
complexity of specific apps, especially those with advanced features, can be a barrier
for users unfamiliar with smartphones or digital platforms. The COVID-19 epidemic,
lockdown, and social distancing measures have disturbed consumer purchasing and
shopping patterns. As a result, customers have experimented with new channels and
developed new habits. 75% of US customers tested new brands or channels during the
crisis, according to a recent McKinsey & Co. study. Many of these consumers adopted
"digital and contactless services, including curbside pickup, delivery, and buying online
for in-store pickup" (Friedlingstein et al., 2020). When the crisis passed, most customers
intended to keep shopping at multichannel or fully digital stores. Chinese "pandemic-led
shifts to further online adoption and an increased focus on neighborhood and small-
format stores have become an ongoing normal," according to a new analysis from
market research firm Neilsen (Kursan Milaković, 2021). The recruitment of previously
cautious internet shoppers could be the last potential behavioral shift brought about by
the pandemic. (Standish & Bossi, 2020) makes the case that the epidemic has
Consumer Vulnerability After Pandemic Covid-19 on Using Mobile Health Apps
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2451
encouraged "late adopters" to make their first online purchases using the innovation
diffusion theory. During the pandemic, late adopters learn how to purchase online. The
ease and security of online shopping may help them get over their misgivings and
encourage them to keep shopping online once the pandemic is finished. Older
consumers usually adopt Internet purchasing later (Liu, He, Chen, & Gao, 2019).
Besides, trust and privacy concerns became the point consumers became aware of.
Many customers are concerned about the privacy and security of their health data when
using apps. They worry about potential data breaches, unauthorized access to their
personal information, or misuse by app developers or third parties (Skordoulis et al.,
2018)v. These concerns can deter individuals from fully engaging with health apps.
While "going digital" benefits individuals and society, there is also a greater risk of
privacy invasion. Therefore, academic and professional groups are paying more
attention to what might make a person more resilient to the adverse effects of these
online privacy invasions (Roskam et al., 2021).
Considering earlier theories, it is evident that outside factors like the COVID-19
epidemic cause changes in consumer behavior. However, it is crucial to evaluate how
customers' coping mechanisms for vulnerability, adaptation, and resilience to change
due to online shopping contribute to their behavioral processes regarding retail/purchase
satisfaction and repurchase. This is essential for businesses' following plans and
communication strategies. Hence, this research aims to answer the following research
questions: (1) Does consumer vulnerability caused by the lowest technology literacy
affect purchase satisfaction with healthy apps? (2) does consumer resilience related to
customers’ trust and customer privacy concerns affect purchase satisfaction on Healthy
Apps? (3) does consumer adaptability strengthen the relationship between consumer
vulnerability and consumer resilience toward purchase satisfaction?
Research Methods
The population of this research was the citizens of 4 provinces in Java, Indonesia.
They were DKI Jakarta, West Java, Central Java, and East Java, which have high
populations compared to other provinces in Indonesia. Those respondents were
classified based on their demographic data, such as age related to generation, domicile,
and education. In order to find the specific respondents, this research used a purposive
sampling technique with specific characteristics, such as using Mobile Health Apps
from 2020 to 2023 and purchasing some products or services on Mobile Health Apps
from 2020 to 2023. The questionnaire taken from the previous research: 14 items on
consumer vulnerability adapted from (Skowron & Kristensen, 2012), five items on
consumer resilience adapted from Connor & Davidson (2003), one item on consumer
adaptability adapted from Milakovic (2021), and for purchase satisfaction consisted of
three items that adapted from Wolter et al. (2017), Thomson (2006), and Chun and
Davies (2006), while one item was developed by Milakovic (2021).
In order to find out the result of those hypotheses, this research used SEM PLS to
analyze the statistical result. First, the validity test was done using the result of AVE’s
Christina Sudyasjayanti
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2452
value (Average Variance Extracted) of 0,5 and the value of the outer loading of 0,5.
Secondly, the inner model was conducted to analyze the relationship among variables,
which was measured through the value of R2. Lastly, path coefficients aimed to
measure the answer to the hypotheses with specific criteria, such as the t-statistics value
1.96 with p-values of 0,05.
Figure 2. Research Model
Source: Data Processing
Results and Discussion
This research investigates the relationship between consumer vulnerability and
consumer resilience during the COVID-19 outbreak toward purchase satisfaction
moderated by consumer adaptability. The findings strengthen the previous study about
consumer experience during the COVID-19 outbreak. The result showed that the
moderation effect of consumer adaptability upon consumer vulnerability toward
purchase satisfaction was rejected. The moderation effect of consumer adaptability on
consumer resilience toward purchase satisfaction also exists (Kholifah, 2022).
There were 200 respondents in this study, consisting of 92 men and 108 women.
The domicile is spread across four large provinces on the island of Java: 36% from DKI
Jakarta, 28% from West Java, 19% from Central Java, and 17% from East Java. The
highest average of respondents’ educational background of respondents was a
Bachelor's degree, 54%; next was High School, 31%; college, 12%; Master's Degree,
3%; and PhD/doctor, 1%. The most extensive generational distribution of respondents
was Gen Y, aged 25-40 years 56%, 38% Gen Z (18-24 years), and the remaining 8%
Gen X (aged 41-55 years and above).
Consumer Vulnerability After Pandemic Covid-19 on Using Mobile Health Apps
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2453
Table 1
Respondents
Characteristic
N
%
Gender
Male
92
46
Female
108
54
Domicile
DKI Jakarta
72
36
West Java
57
28
Central Java
37
19
East Java
34
17
Education
High school
62
31
College (D2/D3)
24
12
Bachelor degree
107
54
Master degree
5
3
PhD/Doctor
2
1
Generation
Gen X (41 - >55)
15
8
Gen Y (2540)
110
56
Gen Z (1824)
75
38
Based on Table 2, respondents showed that their answers diverged, as shown by
the Standard Deviation on each item. The highest standard deviation was shown by item
X2.2. It implied that respondents who answered, When under pressure, I can focus and
think clearly,” were diverse. On the contrary, the lower the standard deviation, the more
similar the values on the items or the more accurate they are with the mean value.
Table 2
Validity Reliability
Cronbac
h's Alpha
rho_A
Composite
Reliability
Avera
ge
Varian
ce
Extrac
ted
(AVE)
Measurement Items
(measured on a 5-Point
Likert Scale, where 1
means Strongly Disagree
and 5 Strongly Agree)
M1: The pandemic situation
provides an opportunity to
learn several new ways of
buying online.
0,763
0,782
0,842
0,520
X2.1. When things seem
hopeless, I never give up.
X2.2: When under pressure,
I can focus and think
clearly.
X2.3: I consider myself a
strong person.
X2.4: I can overcome
unpleasant feelings.
X2.5: I think I am in control
of my life.
Christina Sudyasjayanti
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2454
Cronbac
h's Alpha
rho_A
Composite
Reliability
Avera
ge
Varian
ce
Extrac
ted
(AVE)
Measurement Items
(measured on a 5-Point
Likert Scale, where 1
means Strongly Disagree
and 5 Strongly Agree)
0,858
0,866
0,889
0,502
Product Promotion
X1.6.: I often buy
advertised products/services
on Mobile Health Apps.
X1.7. I often make
purchases on Mobile Health
Apps based on information
from colleagues or family.
X1.8.: I usually buy
products/services available
on Mobile Health Apps
recommended by social
media (IG et al., etc.).
Purchase Ability
X1.9: When purchasing a
product/service on Mobile
Health Apps, I often have
many other alternatives
outside the application.
X1.11.: I can afford to buy
what I want on Mobile
Health Apps.
Distinguish Ability
X1.12.: I often buy
replacement goods/services
using mobile health apps
that are unavailable in
conventional stores.
X1.13.: When I buy a
product/service on Mobile
Health Apps, I usually
know if the information is
false.
X.1.14: When I buy
products or services on
Mobile Health Apps, I can
usually distinguish which
marketing methods are
fraudulent.
0,896
0,901
0,928
0,763
Y1: I think the market
approach taken by Mobile
Health Apps that I used
during the pandemic met
my expectations.
Y2: I am satisfied with the
Consumer Vulnerability After Pandemic Covid-19 on Using Mobile Health Apps
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2455
Cronbac
h's Alpha
rho_A
Composite
Reliability
Avera
ge
Varian
ce
Extrac
ted
(AVE)
Measurement Items
(measured on a 5-Point
Likert Scale, where 1
means Strongly Disagree
and 5 Strongly Agree)
Mobile Health app service I
used during the pandemic.
Y3: I will recommend the
Mobile Health Apps I used
during the pandemic to
others.
Y.4: My purchasing
experience with Mobile
Health Apps during the
pandemic was very
satisfying.
According to CFA analysis, not every item has significant factor loadings above
the advised level of > 0.50. This was true for the consumer vulnerability product
knowledge dimension (five items), and the consumer vulnerability distinguishes ability
dimension (one item). The minimal two manifest variables required for each component
and the low factor loadings meant that these items could not be included in the analysis.
This necessitated removing the customer vulnerability variable related to product
knowledge from subsequent CFA analyses.
Table 3 presents the CFA findings.
Item
Consumer
Resilience
(X2)
Consumer
Vulnerability
(X1)
Purchase
Satisfaction
(Y)
Consumer Vulnerability
X1.11
I can afford to buy what I
want on Mobile Health Apps.
0,722
X1.6
I often buy advertised
products/services on Mobile
Health Apps.
0,760
X1.7
I often make purchases on
Mobile Health Apps based on
information obtained from
colleagues or family.
0,784
X1.8
I usually buy
products/services available
on Mobile Health Apps
recommended by social
media (IG et al., etc.).
0,675
X1.9
When purchasing a
product/service on mobile
health apps, I often find
many alternatives outside the
application.
0,650
Christina Sudyasjayanti
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2456
Item
Consumer
Resilience
(X2)
Consumer
Vulnerability
(X1)
Purchase
Satisfaction
(Y)
X1.12
I often buy replacement
goods/services in Mobile
Health Apps, which are
unavailable in conventional
stores.
0,707
X1.13
When I buy a product or
service on Mobile Health
Apps, I usually know if the
information is false.
0,655
X1.14
When I buy a product or
service on Mobile Health
Apps, I can usually
distinguish which marketing
methods are fraudulent.
0,703
Consumer Resilience
X2.1
When things seem hopeless, I
never give up.
0,682
X2.2
When under pressure, I can
focus and think clearly.
0,528
X2.3
I consider myself a strong
person.
0,778
X2.4
I can overcome unpleasant
feelings.
0,778
X2.5
I think I am in control of my
life.
0,804
Purchase Satisfaction
Y1
I think the market approach
taken by Mobile Health Apps
that I used during the
pandemic met my
expectations.
0,875
Y2
I am satisfied with the mobile
health app service I used
during the pandemic.
0,876
Y3
I will recommend the Mobile
Health Apps I used during
the pandemic to others.
0,844
Y4
My purchasing experience
with Mobile Health Apps
during the pandemic was
very satisfying.
0,898
This research found that not all of the designed hypotheses were answered. This
research found that the p-value of the influence of consumer vulnerability on purchase
satisfaction was 0.000, meaning that H1 was accepted. This is in line with research
conducted by Shi et al. (2017) and Stewart & Yap (2020), which state that the higher a
person's level of technological literacy, the more influence it will have on the purchase