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FACTORS AFFECTING VIETNAMESE
PEOPLE'S INTENTION TO BUY HEALTH
CARE PRODUCTS ONLINE DURING
COVID-19
Dr. Nguyen Thi Phuong Giang*
Faculty of Commerce and Tourism
Industriual University of Ho Chi Minh City
Ho Chi Minh City, Viet Nam
nguyenthiphuonggiang@iuh.edu.vn
Do Thi Bich Tram
Faculty of Commerce and Tourism
Industriual University of Ho Chi Minh City
Ho Chi Minh City, Viet Nam
18072741.tram@student.iuh.edu.vn
Le Thi Anh Hang
Faculty of Commerce and Tourism
Industriual University of Ho Chi Minh City
Ho Chi Minh City, Viet Nam
18065561.hang@student.iuh.edu.vn
Le Thi My Nhien
Faculty of Commerce and Tourism
Industriual University of Ho Chi Minh City
Ho Chi Minh City, Viet Nam
18054601.nhien@student.iuh.edu.vn
Nguyen Binh Phuong Duy
Industrial University of Ho Chi Minh City
Ho Chi Minh City, Viet Nam
nguyenbinhphuongduy@iuh.edu.vn
Abstract—Since the beginning of 2020, the COVID-19
epidemic has been spreading in more than 200 countries,
infected more than 40 million people and more than 1
million people have died, leaving a severe impact on the
economy and society worldwide, causing countries to
constantly strengthen blockades and issue directives
restricting the road and mass gatherings of people outside
the public. The COVID-19 pandemic has re-erupted,
seriously affecting the business of businesses and
traditional stores. Many stores have to close their stores
despite being selling essential goods. With the current
covid epidemic situation, health care is at the forefront.
As a result, the goal of this research is to figure out what
elements impact customers' online purchase intentions
for healthcare items. This study combines two methods of
qualitative research and quantitative research. On a
database collected from the survey of 400 people and
analyzed using SPSS processing software. The study's
findings reveal that price, trust, social media marketing,
attitude, subjective norms, and health consciousness have
an effect on online purchasing intention on healthcare
products. The findings of the authors' research will be
used to provide suggestions to businesses and online
retailers in the context of the current COVID-19
epidemic.
Keywords— Health care products, Online purchase intention,
Product value, Trust, Subjective norms, Health consciousness.
I. INTRODUCTION
The COVID-19 epidemic has resurfaced, posing a major
threat to conventional enterprises and shops' business and
trade operations. Although many establishments sell
necessary commodities, many have to close. In light of the
aforementioned issue, people are increasingly turning to
internet shopping, which allows them to purchase safely and
conveniently. Health care products were one of the necessary
commodities that accounted for the bulk of purchases
throughout this translation period. Keeping oneself healthy
and handsome daily, as well as avoiding sickness and
strengthening your immune system, has been increasingly
popular in recent years, and the COVID-19 pandemic has
expedited this trend. When individuals are conscious of
maintaining their health and that of their families, health
protection and improvement become increasingly vital in life.
The purpose of this research is to find out what factors
influence customers' desire to buy health care items online in
Vietnam. As a result, the writers picked the topic "factors
affecting Vietnamese people's intention to buy health care
products online during covid-19" in addition to wanting to
learn more about this sector. After that, supply precise scales
and construct a consumer research model based on-premises
and data analysis outcomes. Assist companies and online
retailers in understanding and adjusting their rules to attract
more people to transact.
0302
978-1-6654-8303-2/22/$31.00 ©2022 IEEE
II. LITERATURE REVIEW
A. Unified Theory of Acceptance and Use of Technology
(UTAUT)
The Theory of Reasoned Action has the greatest impact on
the UTAUT model, which is a combination of eight preceding
models based on the theory of earlier technology adoption
models: TAM (Technology Acceptance Model), TPB (Theory
of Planned Behavior), and TRA (Theory of Reasoned Action).
The following are the primary components of the UTAUT
model:
Expected efficiency, expected effort, social effect, and
favorable conditions are among the four elements that directly
influence customer acceptance and usage behavior in
UTAUT. Independent factors that influence dependent
variables, purposeful behavior, and behavior usage are the
four basic ideas. Through four essential principles, gender,
age, experience, and volunteers who used the system
indirectly affected dependent variables. The usage of
technology is thought to be influenced by behavioral purpose
[1].
B. The Theory of Planning Behaviour (TPB)
TPB model is proposed in the article "From Intention to
Action: A Theory of Planned Behavior [2]. TPB is based on
TRA, a theory established by Martin Fishbein and Ajzen [3].
Behavioral trends are described as the degree of effort that
individuals strive to engage in, and are thought to incorporate
the motivational elements that drive behavior [4].
The TPB model assumes that the intention to do an action
may be used to predict or explain that behavior. The intention
is influenced by three factors: The first consideration is one's
attitude toward the activity. The subjective norms are the
second factor to consider. Perceived behavioral control is the
third factor to consider [5]. Behavioral control perception
relates to people's impressions of how simple or difficult it is
to manage their behavior in different situations and acts. TRA
theory gave us the subjective attitude and norm component.
The degree to which a person has a favorable or unfavorable
assessment of the action in issue is referred to as attitudes
toward behavior. Subjective norms are societal pressures on
people to do or not do specific activities [4].
C. Price (P)
The price of a product might be a good indicator of its
quality [6,7]. The buyer's decision is heavily influenced by
price. Prices are determined by various production techniques,
features, and product categories. Even when purchasing a
high-priced item, consumers want a high-quality product for
their money. Consumers, on the other hand, are less likely to
select items of inferior quality but lower pricing. Therefore,
price is a major consideration of consumers when buying [8].
In addition, quality products are also factors that consumers
consider [9]. Products with special functions will be more
expensive [10]. Therefore, consumers prefer multifunctional
products despite the more expensive price [11]. Consumers
frequently assume that high product costs imply great quality,
while consumers frequently dispute the quality of low-cost
items. When a person goes shopping, the price is frequently
the first item that they notice, followed by a variety of other
considerations. As a result, while purchasing health-care items
during COVID-19, customers will pay close attention to the
product's pricing and determine if it is worth the money.
Therefore, the author hypothesized as follows:
H1: Price has a positive effect on the intention of purchasing
health care products online.
D. Trust (T)
In the world of E-commerce, trust is an important [12]. The
idea of trust may be defined as the consumer's expectation that
the store, its employees, and its goods are trustworthy and will
fulfill their promises [13]. Trust becomes the most important
factor in the relationship of buyer and seller especially in e-
commerce [14]. It's also one of the reasons why people avoid
buying things over the internet [15]. Trust influenced purchase
decisions, especially to a purchase decision [16, 17].
Consumers’ trust leads to several benefits. First, customers are
pleased with the vendor, company, and transaction. Second,
customers show favorable behavior in terms of purchasing
items, loyalty, and firm support. Third, customer trust has a
positive impact on purchase intent. Fourth, buyers will select
to buy provided goods from a reputable firm. Because
consumers have few concrete and verifiable signals about the
skills and intentions of the service provider in the internet
world, reliability is an extremely crucial element [18]. Other
online research and purchase decisions are almost solely by
trust [19]. The hypothesis given is:
H2: Trust has a positive effect on the intention of purchasing
health care products online.
E. Social media marketing (SM)
As society progresses, business becomes increasingly
competitive, prompting businesses to seek out the best and
most efficient marketing approach possible. Marketing is an
important and successful part of a business's capacity to create
and sustain sales. As a result, a business must have a solid
strategy for recognizing market opportunities as well as the
potential for growth and sustainability. An increase in internet
users and the growing number of online businesses that use
social media as a means of making transactions using social
media such as Facebook, BBM, Whatsapp, Line, Instagram,
and others, as well as an increase in era progress with the
increasingly rapid features available on smartphones [20, 21].
Social media is used as a commercial platform as well as an
interactive platform in today's society. Social media is used as
both a business and an engaging platform in today's society
[22]. The use of social media platforms to promote brand
knowledge, recognition, recall, and action for companies,
corporations, goods, individuals, and other organizations is
known as social media marketing. It includes sharing,
microblogging, social networking, social bookmarking, and
social media marketing. Content marketing can take the form
of specific tactics like sharing coupons or announcing sales on
Facebook or Twitter, or it can take the form of broader brand-
building initiatives like communicating with customers or
creating interesting content for a blog, a YouTube video, or a
presentation with shared slides [23, 24]. Thus, the proposed
hypothesis is:
0303
H3: Social media marketing has a positive effect on the
intention of purchasing health care products online.
H4: Social media marketing has a positive effect on the
consumer trust in the intention of purchasing health care
products online.
F. Attitude (ATT)
The term "attitude" refers to one's overall assessment of
conduct [25], and it describes how positive or negative that
assessment was [26,27]. TPB claims that a person's mindset
determines whether or not they will engage in that conduct [4].
Aside from that, it has been shown that there is a link between
one's attitude toward conduct and one's purpose to carry out
such behavior [28]. Positive views toward dietary
supplements, such as the health advantages of reducing illness
effects and improving health, have resulted in a positive
approach to supplement purchasing. From there the group of
authors hypothesized, following:
H5: Attitude has a positive effect on the intention of
purchasing health care products online.
G. Subjective Norms (SN)
Subjective norms are a person's perceptions or ideas about
other people's beliefs that influence his or her decision to do
or not do something. Subjective norms are a person's
impressions or opinions about other people's viewpoints that
impact his or her decision to conduct or not carry out the action
in question. [29]. Subjective norms refer to “the belief in
which whether most people approve or disapprove of the
behavior” [30]. It's the motivation to exhibit a particular
behavior with the expectation considerations of others that are
considered important to the actor. They might be relatives,
friends, family members, or other significant individuals in the
life of the person who is engaging in the conduct. Subjective
norms, to put it another way, it is definable “as the customary
codes of behavior in a group of people or society” [30].
Subjective norms influence people's preferences in a favorable
and substantial way [31]. Aside from that, various studies have
shown the relevance of subjective standards as a predictor of
the likelihood of consumers engaging in health-related
behaviors [32, 33]. They're a category of subjective normative
or normative behaviors that refer to the expectation that a
person or group of people would approve and support a certain
activity. Subjective perception is a term used in the online
business world to describe how consumers experience societal
pressures while making purchases from online retailers. If a
person is unsure about the goods they require or where to get
it, they might seek advice guidance from friends and relatives.
They will then persuade the bulk of them, and they will decide
to do what they recommend [12]. During the COVID-19
pandemic, customers will choose to acquire healthy items that
others in their immediate circle, such as family and friends,
advocate based on the product's usage and functioning. From
previous studies, the author gives two hypotheses as follows:
H6: Subjective norms have a positive effect on the intention of
purchasing health care products online.
H7: Subjective norms have a positive effect on the consumer
attitude in the intention of purchasing health care products
online.
H. Health consciousness (HC)
According to previous research, health as a value has
numerous driving meanings and is linked to health-related
activity [34, 35, 36]. Customers who are concerned about their
health in their everyday activities are said to be health
consciousness [37, 38]. When buyers plan to make a purchase,
health issues are always emphasized. [37]. People pay more
attention to their health in this situation and are hence more
inclined to actively purchase health care products. At the same
time, increased health awareness has boosted the desire to buy
health-related items. As a consequence, the authors propose
the following theory:
H8: Health consciousness has a positive effect on the intention
of purchasing health care products online.
Figure 1. Suggested author model
(Source: Synthesis Author)
III. RESEARCH METHOD
The study was conducted with two methods: qualitative
research and quantitative research. Qualitative research is
done by discussing the group over the phone. From the results
of the group discussion, adjust the scale for the last time to
make the official scale and the official questionnaire.
Questionnaires for quantitative research are also set. The next
steps are quantitative research conducted with a total sample
collected of 400 samples through an online survey. The data
set obtained from the survey includes:
In terms of gender, the percentage of male participants was
30.5% less than that of females at 67.5%. The remaining 2%
are people who do not want to specify their gender. In terms
of age, the age of 18-22 years old with 307 customers
accounted for the highest proportion with 76.8%, the age of
28-32 years accounted for 8%, under 18 years accounted for
7.8%, from 23 to 27 years old and over 37 years old accounted
for 2.8% and from 33 to 37 years old accounted for the lowest
rate of 2%. Therefore, the customers who care a lot about
health care products are a young age. In terms of occupations,
the percentage of students participating in the survey
accounted for the highest percentage of 59.8%. Because the
research team is a student, most of the survey samples will be
0304
sent to students. In addition, the percentage of office workers
also accounts for 16.5% compared to other industries; for
cadres and civil servants accounting for 6.5%; Other
occupations accounted for 17.3%. The survey conducted in a
variety of industries gives research a better overview of their
intention to buy health care products online.
Then the data is analyzed using SPSS software for EFA
analysis and linear regression analysis. Finally, the research
team discusses the research results and offers some ways to
manage the impacts to improve consumers' intention to buy
health care products in Vietnam during COVID-19.
IV. RESULT
A. Cronbach's alpha test
To ensure that the scales in the study are reliable enough,
each scale will be tested using Cronbach's alpha method.
TABLE I. CRONBACH'S ALPHA ANALYSIS OF SURVEY DATA
Scale
Number of
variables
observed
Coefficient
Cronbach’s
Alpha
Coefficient
Total
Correlation
Price (P)
4
0.860
0.687 - 0.729
Trust (T)
5
0.903
0.717 – 0.778
Social media
marketing (SM)
5
0.883
0.667 – 0.761
Attitude (ATT)
3
0.777
0.576 – 0.642
Subjective Norms
(SN)
3
0.865
0.684 – 0.782
Health
Consciousness
(HC)
4
0.880
0.718 – 0.757
Purchase Intention
(PI)
4
0.866
0.682 – 0.753
Results from Table I show that the reliability of the 7
scales all have Coefficient Cronbach's Alpha > 0.6 [39] and
ranges from 0.777 to 0.903. In addition, the coefficient total
correlation > 0.3 [40]. This shows that the P, T, SM, ATT, SN,
HC, PI scales are up to standard and statistically significant.
B. Explore factor analysis (EFA)
To ensure the value of the components in the element hints
and explore other factors. The study will perform an EFA
analysis of independent variables at the same time, while the
remaining variables depending on "purchasing intention" will
be analyzed separately.
TABLE II. EFA DISCOVERY FACTOR ANALYSIS RESULTS
Factor
KMO
(sig.)
Cumulative%
Eigenvalues
Factor
Loading
1.
Independent
variable
0.934
0.000
73.487%
1.028
T
0.708 –
0.765
HC
0.761 –
0.765
SM
0.713 –
0.780
P
0.688 –
0.774
SN
0.685 –
0.817
ATT
0.654 –
0.812
2. Dependent
variable
0.822
0.000
71.493%
2.860
PI
0.822 –
0.869
After 2 analyses, the authors removed the SM5 variable
due to factor loading < 0.3. Results from Table 2 show that,
at the independent factor, KMO value = 0.934 and Sig value
= 0.000 < 0.05 [39], from there the data is appropriate for
factor analysis. Cumulative reached 73.487% (>50%), the six
extracted factors explained 73.487% of the fluctuations in the
observed data. The Eigenvalues coefficient is 1.028, the
extraction coefficient is well-meaning information.
At the PI dependency variable factor, the KMO value
equals 0.822 (conditions greater than 0.5 and less than 1) and
the Sig value = 0.00 < 0.05 shows that the data is suitable for
conducting factor analysis. Cumulative achieved 71.493%
(>50%) with this result showing that the 5 extracted factors
explained 71.493% of the fluctuations in the observed data.
The Eigenvalues coefficient is 2.860 >1, the extraction
coefficient makes good sense of information.
C. Regression analysis
The authors use the hypothetical model in section 2.6 to do a
linear regression analysis to see how independent factors
affect dependent variables.
Linear regression analysis of 6 independent variables for
dependent variables
TABLE III. A SUMMARY OF THE FACTORS THAT INFLUENCE
THE INTENTION TO BUY HEALTH CARE PRODUCTS ONLINE
Model
R
R²
Radj²
Std. Error of the
Estimate
Durbin-Watson
1
.815
.665
.660
.39681
2.089
a. Dependent variable: PI
b. Predictors: (Constant), SM, ATT, T, HC, SN, P
The R² determining coefficient shows how much of the
dependent variable is explained by the independent variable
(%). Regression results show a defining coefficient of R² =
.665 (≠0) that is, 66.5% of this indicator means that the
variation of PI variables is explained by the variation of 6
factors (T, HC, P, SM, SN, ATT), the remaining 33.5%
belonged to other random factors and errors. In this model, use
the Radj² index (Adjusted R Square) = .669 (66%) This
indicator can help determine the suitability of the model that
0305
will be more accurate and safe. The value of Durbin-Watson
is 2,089 in the range of 1.5-2.5 from which it is inferred that
the data does not have the highest correlation phenomenon,
the data meets the requirements.
TABLE IV. ANOVA FACTORS THAT AFFECT THE QUALITY OF
THE RELATIONSHIP OF INTENT TO BUY THE ONLINE
HEALTHCARE PRODUCTS
Sum of Squares
df
Mean Square
F
Sig.
Regression
122.718
6
20.453
129.894
.000
Residual
61.882
393
.157
Total
184.599
399
a. Dependent variable: PI
b. Predictors: (Constant), SM, ATT, T, HC, SN, P
The results showed that F = 129.894 and the significant
level Sig. = 0.000 (sig ≤ 0.05), this means that the regression
model fits the data and that the variables are statistically
significant at a level of 5%.
TABLE V. THE WEIGHTING OF REGRESSION FACTORS THAT
INFLUENCE THE INTENTION TO BUY HEALTH CARE
PRODUCTS ONLINE
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
Collinearity
Statistics
Hyps
Result
B
Std.
Error
Beta
Tolerance
VIF
-.251
.165
-1.520
.129
T
.127
.035
.145
3.655
.000
.539
1.855
H2
Accept
HC
.285
.042
.273
6.715
.000
.516
1.937
H8
Accept
P
.154
.039
.159
3.905
.000
.513
1.951
H1
Accept
SN
.184
.038
.196
4.878
.000
.526
1.900
H6
Accept
ATT
.222
.051
.164
4.319
.000
.595
1.682
H5
Accept
SM
.101
.041
.101
2.489
.013
.515
1.941
H3
Accept
Results from Table V showed that the VIF index ranged
from 1.682 – 1.951 < 2. Therefore, we can conclude that the
phenomenon of multicollinearity in this model is small. The
Sig. of all variables T, HC, P, SN, ATT, SM are less than 0.05,
it should be concluded that the above variables affect the
intention to buy health care products online. Variables T, HC,
P, SN, ATT, SM have the same effect on variables depending
on the intention to buy health care products online due to
having a positive Beta coefficient.
From the results of the analysis we have a regression equation
that is:
PI = 0.273HC + 0.196SN + 0.164ATT + 0.159P + 0.145T +
0.101SM
Linear regression analysis of SM variables for T variables
TABLE VI. ANOVA SM FACTOR IMPACTS T
Sum of
Squares
df
Mean Square
F
Sig.
Regression
67.252
1
67.252
152.604
.000b
Residual
175.396
398
.441
Total
242.648
399
a. Dependent variable: T
b. Predictors: (Constant), SM
The results showed that F = 120.162 and a significant level
of Sig. = 0.00 (sig. ≤ 0.05), this indicates that the regression
model fits the data and the variables are statistically significant
at the 5% level.
TABLE VII. WEIGHTING OF SM FACTOR REGRESSION
AFFECTS T
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
Collinearity
Statistics
Hyp
Result
B
Std.
Error
Beta
Tolerance
VIF
1.163
.189
6.170
.000
SM
.602
.049
.526
12.353
.000
1.000
1.000
H4
Accept
VIF index = 1.000 < 2, therefore we can conclude that the
phenomenon of multicollinearity in this model is small.
Because the TT variable's Sig. is less than 0.05, it's safe to
assume that the SM variable mentioned above has an influence
on T. β standardized of variables TT = 0.602, which shows
that the SM variable has the same effect on the T dependent
variable.
Linear regression analysis of the SN variable for ATT
variables
TABLE VIII. ANOVA SN FACTOR IMPACTS ATT
Sum of
Squares
df
Mean Square
F
Sig.
Regression
23.241
1
23.241
120.162
.000b
Residual
76.980
398
.193
Total
100.221
399
a. Predictors: (Constant), SN
b. DepeZdent Variable: ATT
F = 120.162 and a significant level of Sig. = 0.00 (sig. ≤ 0.05)
were found, indicating that the regression model matches the
data and that the variables included are statistically significant
at 5%.
TABLE IX. WEIGHTING OF REGRESSION OF SN FACTORS
AFFECTING ATT
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
Sig.
Collinearity
Statistics
Hyp
Result
B
Std.
Error
Beta
Tolerance
VIF
2.672
.116
23.129
.000
SN
.333
.030
.482
10.962
.000
1.000
1.000
H7
Accept
D. Hypothesis testing
From the results of linear regression analysis, the H1, H2,
H3, H5, H6, H8 hypotheses in Table V, H4 hypotheses in
0306
Table VII and H7 in Table IX all have Sig = 0.000 values. As
a result, all of the hypotheses H1, H2, H3, H4, H5, H6, H7,
and H8 are all accepted.
According to the findings, the defining factor R² = 66.5
percent translates to 66.5% of the change in the customer's
propensity to purchase health care items online over the Covid
period being explained by six factors (P, T, SM, ATT, SN,
HC) positively impacting online purchasing intentions health
care products during Covid and the remaining 33.5% are
explained by other external factors not mentioned in this
study.
V. DISCUSSION
The study team set out to explore the elements that affected
online purchase intentions in terms of health care for
consumers during COVID-19 based on the findings of the
aforesaid investigation.
According to the linear regression equation after the
analysis, We can conclude that Vietnamese consumers'
intention to buy health care products online is influenced by
six main factors: price, trust, social media marketing, attitude,
subjective norms, and health consciousness. A new model has
been proposed by relying on SPSS data research results and
previously related studies, The model is a combination of the
6 variables mentioned above, the most prominent of which are
three variables: health consciousness, attitude, and trust, in
which subjective norms variables affect attitude variables and
social media marketing variables affect trust variables.
Compared to previous models, the authors proposed some new
elements in this study that have an impact on online
purchasing intentions. As a consequence, the linear regression
equation appropriately depicts the study model's correlation
between independent and dependent variables.
The study's findings are in line with those of earlier
research. Sutanto Hidayat et al [41] conducted research.
Health consciousness and attitude have an impact on the
intention to buy hand sanitizer products during the epidemic
in Indonesia. Sri Mukti Wirawati et al. [42]. The research of
reliability also has a positive impact on consumer purchasing
intentions according to research by Ismat Ara Eti et al. [43].
This research focuses on the role of social media in the intent
of consumers in Bangladesh during COVID-19. Subjective
norms are also mentioned in research by Lee Jing Ru et al.
[44] Research-based Technology Acceptance Model (TAM)
and Theory of Planning Behavior research (TPB) to research
Shopee consumers' purchasing intentions. In addition, the
price factors of the product/service are also a significant factor
affecting the purchasing decision of the consumer [45].
VI. CONCLUSION
Based on the results of the study's examined and discussed
data, the authors came up with the following characteristics
that have a beneficial influence on customers' desire to buy
health care items online during Covid-19: Price, Trust, Social
Media Marketing, Attitude, Subjective Norms, and Health
Consciousness, in which the "Health Consciousness" has the
greatest influence on the desire to purchase online health care
items. This indicates that during COVID-19, customers
consistently prioritize their health and utilize it as a
justification for purchasing for themselves. Moreover, the
"Subjective Norms" of the individual customer with the
psychology of worry and befuddlement during the epidemic,
the intention of consumers to purchase goods can be
influenced by others around them such as family and friends
before deciding to purchase health care items. The authors
provided a solution model for consumer purchase intents and
solutions adapted to online commerce for enterprises based on
theory and research findings. Then, to satisfy the demands of
consumers and the times, devise business processes,
marketing plans, and other activities. This improves and
promotes company efficiency, assists firms in developing
suitable plans, and creates a consistent income flow in the
COVID-19 period, which is still quite complicated in the
country and throughout the world.
The researchers discovered elements that affected the
willingness to purchase health care products at covid-19 in
Vietnam based on the study's findings. This survey also
reveals that to establish a consumer-oriented e-commerce
firm, executives must concentrate on the following: Focus on
the quality of information about health care products in online
stores. The website's information material must be accurate,
full, clear, and dependable. Customers should be able to refer
to and pick items based on the information provided by online
businesses. Trust and social media marketing are two equally
vital variables that will aid organizations in their growth
during this time. To be able to satisfy the aforementioned two
objectives, start with the business itself. Build trust and have
a competent marketing and communication staff.
Although the team put in a lot of effort to complete the
study during implementation, it, like many other studies, has
significant limitations. Due to a lack of time to complete the
inquiry, the team did not undertake a full examination of the
criteria supplied. The authors' study, which only looked at
customers' intentions to buy health-care items in Vietnam,
may not be conclusive. As a result, the group proposes to
broaden the area of study in several nations in the region,
allowing it to provide more appropriate models and solutions.
Because this is a global issue, the degree of interest in this
research topic is quite high. Finally, the authors advise that
future research should look at other aspects or characteristics
that may impact customers' willingness to buy health-care
items.
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