Perceived Risk and Marketing Mix Influencing Generation Y Fashion
Clothes Purchasing Decisions via Online Social Media
TANOMPONG PANICH1, ARUNEE LERTKORNKITJA2*,
NUTTHARIN PARIWONGKHUNTORN3, SASITHORN PHONKAEW4
1Faculty of Business Administration
Rajamangala University of Technology Thanyaburi
Khlong Luang District, Pathum Thani 12110
THAILAND
2Faculty of Business Administration & Technology
Stamford International University
Prawet District, Bangkok 10250
THAILAND
3College of Management Bangkok
University of Phayao
Pathum Wan District, Bangkok 10330
THAILAND
4MSME Business School
Assumption University of Thailand
Bangsaothong District, Samuthprakarn, 10540
THAILAND
*Corresponding Author
Abstract: - Electronic technological advancements have led to an increase in online purchasing. Customers
typically perceive risks while doing transactions electronically, especially when money is involved. Therefore,
this research aims to investigate the perceived risk factors and marketing mix factors influencing Generation Y
fashion clothing purchasing decisions made through online social media. The target sample was the Generation Y
group of people aged 20 to 40 (born between 1980 to 2000) who had purchased trendy clothes over social media in
the previous 6 months. A total of 400 questionnaires were obtained by delivering both online and offline. The
gathered data were analyzed by descriptive statistics and multiple regression analysis. The findings revealed that
psychological risk, social risk, and financial risk influenced Gen Y fashion clothing purchasing decisions
through online social media. In the marketing mix, according to the findings, place, privacy, and product are the
three most important elements influencing Gen Y fashion clothing purchasing decisions through online social
media, with a statistical significance of .05. Several managerial implications are addressed, as well as potential
research opportunities.
Key-Words: - Perceived risk, Marketing mix, Purchasing decision, Fashion clothes, Generation Y, Online social
media.
Received: May 5, 2023. Revised: September 14, 2023. Accepted: October 16, 2023. Available online: November 24, 2023.
1 Introduction
Online shopping has become a part of people's daily
lives due to the convenience, price reductions, and
promotions available to consumers. In 2019, global
e-commerce sales reached USD 26.7 trillion, [1]. E-
commerce in Thailand increased by 81% in 2020,
with a total value of 29.4 billion baht (USD 842.4
million). As a result, merchants and manufacturers
launched online shops on a variety of platforms to
gain access to consumers' increasing spending
power; more crucially, starting a business online no
longer required a physical storefront, [2]. Social
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DOI: 10.37394/23207.2024.21.19
Tanompong Panich, Arunee Lertkornkitja,
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E-ISSN: 2224-2899
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media marketing (SMM), thus, is frequently used to
personalize audience experiences, increase sales,
and sustain and develop relationships with
customers, [3]. Because of their most social media
active users worldwide, social media platforms such
as Facebook, Instagram, Twitter, or Line@, have
emerged as Thailand's most popular platform and
channel for selling things, [4]. Food delivery, toys,
furniture, and clothing are the fastest-growing
online sales businesses, [5]. The increased number
of online vendors has resulted in more competitive
online shopping. As a result, merchants and digital
marketers must constantly investigate and improve
the consumer experience, as well as adapt their
marketing strategies, [6], [7], to meet customer
expectations and successfully respond to the
demands of consumers of various age groups
through online commerce platforms.
Online shopping provides significant benefits to
consumers in terms of convenience, flexibility of
product selection, and swift payment via Internet
banking. However, there is a risk of being duped
when shopping online, such as money fraud and
identity theft. Consumers must consider this danger
when deciding to shop online to avoid falling victim
to scammers that masquerade themselves as online
retailers, [8], [9], [10]. According to Sift, a global
network of merchant digital fraud protection
services, cybercrime will climb by 69% in 2020,
resulting in more than USD 1 trillion in losses, [11].
In Thailand, the Technology Crime Suppression
Division (TCSD) reported losses from online fraud
totaling more than 1 billion baht (USD 28.6 million)
in 2018, and this figure was expected to rise as
online purchasing grows, [12]. As a result of these
concerns, research on consumer online purchasing
conviction, [13], and perceived risk influencing
consumer online shopping has gained significant
attention in recent years, such as the studies of, [14],
[15]. However, [16], have noted that earlier research
findings lacked conceptual logic.
For this study, the authors were interested in
studying Generation Y, also known as the
Millennial Generation, who were born between
1981 and 2000, [17]. In 2016, Gen Y made up 28.54
percent of Thailand's population, [18]. In terms of
economics, Gen Y has vast purchasing power and
will steer the global economy for the next 20 years,
[19]. When compared to other cohorts, Gen Y has
the greatest total average internet usage, [20]. This
cohort possesses expertise in online communication
and information technology, [21]. This group was
socialization, fashion-conscious, brand-loyal, and
driven by the presence of confidence with a retailer,
[22]. It has also been observed that they prefer to
purchase fashion, health, beauty, and information
technology products through online platforms, [23].
Academics, researchers, corporate executives, and
public politicians are all interested in studying Gen
Y to better understand their fast-changing behavior,
[19], which is heavily influenced by information and
opinions obtained through social media or
Electronic-Word-of-Mouth (E-WOM), [13].
Taking into account these critical challenges in
Gen Y economics and the increase in their online
purchasing, the purpose of this research is to
investigate and examine the impact of risk
perception components and marketing mix aspects
on this population's decision to purchase fashion
products via online social media. The research
findings will serve as guidance for merchants on
what to do to ensure the survival and growth of their
businesses. It can also provide a strategy for
lowering risk perception and developing marketing
mix strategies to satisfy the needs of Gen Y
consumers. Furthermore, it will assist academics
and researchers in comprehending the conceptual
logic of risk perception and marketing mix factors
that influence Gen Y decision-making.
2 Problem Formation
2.1 Purchasing Decisions
Purchasing decisions refer to the decision of
consumers to make purchases, which is the
consumer's choice to buy or not to buy a product.
Consumer purchasing behavior is influenced by
cultural factors, social factors, personal factors, and
psychological factors, [24]. Specifically, the
purchase decision is to select something specific
from the available options. It is the process by
which customers make decisions. It is made up of
internal factors such as consumer motivation,
perception, learning, personality, and attitudes that
indicate the need and awareness of having a diverse
range of products and consumer-involved activities
in relation to the information obtained. Finally, the
evaluation of those alternatives is based on the
information provided by the manufacturer. In online
shopping, consumers’ purchasing decisions are
influenced by technology adoption. People opt to
accept and use new technology when they
understand and recognize that it will provide
benefits, compatibility, ease of use, privacy
protection, and confidence to them, [25].
2.2 Perceived Risk Factors
Perceived risk is commonly defined as a consumer's
sense of uncertainty and adverse consequences that
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may arise as a result of an unexpected purchasing
outcome, [26]. In the twenty-first century, scholars
began to pay attention to the potential risk of
internet buying. Users can access internet buying via
various applications and services to satisfy their
demands, [27]. In the context of e-commerce, risk
perception refers to the consumer's belief that their
use of the internet is unsafe, or that online
commerce may have negative consequences, [28].
When shopping online, the perceived risk is
substantially larger than when shopping in-store,
[29]. According to the above definition of perceived
risk, consumer perception of risk is an inner feeling
that cannot be directly witnessed; the dimensions of
risk can only be predicted by certain factors.
Academics have paid growing attention to risk
perception studies, which have highlighted various
dimensions of risk, [30]. Hence this study addresses
risk as a multi-dimensional construct, drawing on
the concepts and studies of, [31], [32], [33], [34],
[35], which include six dimensions of perceived
risk.
a) Financial risk, also known as economic risk, is
the possibility of monetary losses during online
purchasing. In other words, financial risk refers to
the potential of losing money as a result of
purchasing any goods or services as well as extra
charges (e.g., a possibility that the product may need
to be repaired, and delivery risk).
b) Performance risk is the potential loss incurred
when a product/service does not perform as
expected or can be used for a limited time.
c) Security risk is the possible fear of external
instruction resulting in the assessment of personal
financial information and even the withdrawal of
money from accounts.
d) Social risk is the chance that a consumer’s
shopping behavior will be rejected by other society
members or the possible loss of status in one's social
group as a result of purchasing a product or service,
which is referred to as social risk.
e) Psychological risk refers to customers'
purchasing attitudes that frequently cause them to
become anxious or stressed. This anxiety leads to a
loss of self-esteem (ego loss) when their purchasing
experience does not meet their expectations.
f) Time risk is the sum of lost time and effort spent
researching and purchasing a product or service that
ends up being disappointing.
Research findings indicate that customers' risk
perceptions are critical and influence online
purchasing decisions. For instance, research
conducted by, [31], revealed that when buying
clothes online, respondents were most concerned
about security risk, followed by performance risk,
payment risk, delivery risk, time risk, financial risk,
and social risk. According to, [36], consumers'
perceived risks during the online purchase process
could be ranked as financial risk, performance risk,
and service risk. The study, [30], discovered
significant differences in user and non-user
perceptions of risk, such as financial risks,
psychological risks, and safety concerns. While,
[15], indicated that financial risk, social risk,
performance risk, psychological risk, physical risk,
convenience risk, and overall risk were relevant in
online buying regardless of how high or low the
involvement with the products or services involved.
Finally, [37], discovered that perceived risks had an
inverse and negative relationship with online
purchasing behavior.
2.3 Online Marketing Mix Factors Concept
(6Ps)
The marketing mix is a collection of tactical
marketing tools that a firm may control and utilize
to identify market demands and serve the target
market. It is divided into four elements consisting of
product, price, place, and promotion, [38], [39]. The
authors in, [40] pointed out that the new digital
channels and media revolution in society and
marketing bring both enormous opportunities as
well as challenges for businesses. It has become
apparent that the consumer decision process in
online purchasing is becoming increasingly
information-intensive; that is, people use more
information and multiple information sources to
make decisions, [41]. When performing online
shopping, a consumer must trade-off between
privacy and convenience; they must determine how
much personal information they would allow third
parties to access and gather, [42]. In response, [43],
[44], have incorporated personalisation and privacy
aspects into the online marketing mix (6Ps).
Personalization is defined as individualized services
and the collection of customer data to create
strategies to attract customers and encourage repeat
purchases. Whereas privacy pertains to customer
confidentiality, which includes not publishing
customer information without their permission.
The studies show the significance and impact of
the marketing mix on customers' online shopping
decisions. For example, [45], investigated how
marketing mix characteristics influence the decision
to purchase fashion products via social media. It
was observed that the distribution channels had the
highest mean score, followed by payment security,
product, promotion, price, and product placement.
The study, [46], on the other hand, reported that
security was the most essential factor in fashion
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clothing online purchasing decisions. Per, [47], the
distribution channel is the most influential
marketing mix factor in the pre-purchase decision-
making process. Privacy, on the other hand, was
proven to be the most influential marketing mix
aspect both during the buying and post-purchasing
process. Finally, the study of, [48], showed a
positive relationship between all six dimensions of
the marketing mix and purchasing decisions. In
particular, price, personalized service, and privacy
had a statistically significant influence on online
herbal product purchasing decisions.
Research Hypotheses
Based on all concepts and theories, the following
assumptions and conceptual framework (Figure 1)
were developed for this study.
H1: Perceived risk factors (financial, performance,
security, social, psychological, time) influence
Gen Y's fashion clothes purchasing decisions
through social media.
H2: Marketing mix factors (product, price, place,
promotion, personalized service, privacy)
influence Gen Y's fashion clothes purchasing
decisions through social media.
Fig. 1: Conceptual framework
3 Problem Solution
The population group used in this research is people
born between 1980 and 2000 (or aged 20 to 40
years), according to a survey conducted by the Thai
Office of the National Economic and Social
Department Council, [19]. The sample consists of
Gen Y people who have purchased fashion clothes
via social media in the last six months. The
unknown precise population formula was applied to
calculate sample size at a confidence level of 95%
and an error ratio of 0.05, [49]. The sample size
should have been 385 people according to this
method, however, the authors rounded up to 400
samples. For convenient sampling, the
questionnaires were then delivered both online and
offline.
A questionnaire was developed to collect data.
The questionnaire's reliability and validity were
evaluated; the IOC (Item Objective Congruence)
score was greater than 0.67. A pilot test with 30
samples was then carried out. Cronbach’s alpha
coefficients for marketing mix (0.88), perceived risk
(0.90), and purchase decision (0.96) were all greater
than 0.70, indicating that questionnaire items were
reliable, [50]. The sample would be examined with
screening questions to generate a valid sample with
the appropriate attributes. The primary question was
his or her birth year, with a supplementary question
asking whether he or she had acquired clothes on
online social media in the previous 6 months.
To get a valid sample with the desired
characteristics, the researchers screened the sample
with a primary question regarding the year of birth
and a question asking whether or not he or she had
bought fashion clothes through online social media
in the past 6 months. To avoid data analysis errors,
the researchers examined and screened the received
questionnaires to check whether there were any
questionnaires with a large amount of missing data,
or questionnaires with outliers or extreme values.
After that, the completed questionnaires were
examined using descriptive statistics such as
frequency, percentage, mean, and standard
deviation. Multiple regression analysis using the
Enter method was used to infer causal relationships
between the independent and dependent variables as
well as for prediction and forecasting. In particular,
to examine the hypotheses using inferential
statistics.
4 Conclusion
In this current study, there were 400 respondents of
which 58.25% of respondents were male, 31.75%
were between the ages of 21 to 25, 69.75% had
completed bachelor's degrees, 47.5% worked in
private organizations, and 39.75% earned less than
10,000 Baht per month. 58.5% of respondents
brought fashion clothing through social media once
a month, with 50.5% spending less than 500 Baht on
average. The following are the research findings
relating to how risk perception and marketing mix
factors influence Gen Y fashion clothing purchase
decisions made via online social media:
Perceived risk
factors
- Financial
- Performance
- Security
- Social
- Psychological
- Time
Marketing mix
factors
- Product
- Price
- Place
- Promotion
- Personalized service
- Privacy
Gen Y's fashion clothes
purchasing decisions
through social media
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1. Measuring perceived risk, marketing mix, and
purchasing decision.
Table 1 presents the average mean scores obtained
for Gen Y buying fashion clothes through online
social media. The findings revealed that the
respondents placed a high value on the overall risk
perception factors. Among the six perceived risks,
personal risk factors: social risk, and psychological
risk associated with fashion clothes are ranked as
the first two predominant risk dimensions.
Dimensions such as performance risk, financial risk,
security risk, and time risk are also significant risks
in the purchase of fashion clothing via Gen Y's
online social media.
Marketing mix factors are also essential criteria
that respondents place a high value on place, which
involves convenience, the ability to buy anywhere
and at any time, and ease of use, which is ranked
first among the six marketing mix dimensions.
Product, promotion, personalized service, privacy,
and price are listed on the respective order.
Table 1. Mean and standard deviation (S.D.) of the
importance level of perceived risk, marketing mix,
and purchasing decisions.
Mean
S.D.
Interpre
tation
Ranki
ng
3.82
0.69
High
4
3.82
0.67
High
3
3.79
0.69
High
5
3.86
0.68
High
1
3.83
0.66
High
2
3.70
0.75
High
6
3.80
0.69
High
3.82
0.69
High
2
3.57
0.72
High
6
4.04
0.77
High
1
3.80
0.77
High
3
3.70
0.71
High
4
3.66
0.74
High
5
3.77
0.73
High
The decision to buy fashion clothes
4.12
0.80
High
1
4.07
0.78
High
2
3.90
0.90
High
3
4.03
0.83
High
The respondents place a high level of importance
on the overall purchasing decision criteria. When
each aspect was examined individually, it was
determined that the choice to purchase fashion
clothes relies on the quality and usability of the
product had the highest average mean score
followed by the value of the product and perceived
risk level, respectively.
2. Multiple Regression Analysis
Table 2. Multiple regression analysis of perceived
risk factors and customer purchasing decisions.
Perceived
Risks Factors
b
SE
β
t
p-
value
Constant
166
0.23
7.37
0.00*
Financial risk
󰇛󰇜
0.15
0.07
0.14
2.43
0.02*
Performance
risk 󰇛󰇜
0.02
0.07
0.02
0.24
0.81
Security risk
󰇛󰇜
0.02
0.07
0.22
0.31
0.76
Social risk
󰇛󰇜
0.16
0.07
0.15
2.17
0.03*
Psychology
risk 󰇛󰇜
0.34
0.07
0.31
5.07
0.00*
Time risk 󰇛󰇜
-0.05
0.06
0.05
-0.90
0.37
R = 0.499, R2 = 0.249, Adjust R2 = 0.238, F = 21.743,
Sig. = 0.000*
*Statistically significant at the 0.05 level
From Table 2, the multiple regression analysis
confirms the relationship between perceived risk
factors and Gen Y’s decision to purchase fashion
clothes. The findings indicate that psychological
risk (X5, β = 0.34) is the most influential dimension
influencing Gen Y fashion clothing purchasing
decisions through online social media followed by
social risk (X4, β = 0.16), and financial risk (X1, β =
0.15). The following formula could be used to
forecast Gen Y purchasing decisions:
   
When the Adjust R2 value of 0.238 was taken
into consideration, the variables could be predicted
by 23.8%, showing that H1 was supported.
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Table 3. Multiple regression analysis of marketing
mix factors and customer purchasing decisions.
Marketing
Mix Factors
b
SE
β
t
p-value
Constant
2.33
0.21
11.07
0.00*
Product ()
0.15
0.07
0.14
2.04
0.04*
Price ()
0.07
0.07
0.07
0.92
0.36
Place ()
0.20
0.06
0.22
3.40
0.00*
Promotion
()
0.04
0.09
0.04
0.48
0.63
Personalized
service ()
0.09
0.09
0.09
0.98
0.33
Privacy ()
0.21
0.06
0.22
3.26
0.00*
R = 0.411, R2 = 0.169, Adjust R2 = 0.157, F = 13.351,
Sig. = 0.000*
* Statistically significant at the 0.05 level
From Table 3, the multiple regression analysis
confirms the relationship between marketing mix
factors and Gen Y’s decision to purchase fashion
clothes. The findings indicate that place (Z3, β =
0.22), privacy (Z6, β = 0.22), and product (Z1, β =
0.14) are the three most important factors
influencing Gen Y fashion clothing purchasing
decisions through online social media. The
following formula could be used to predict Gen Y
purchasing decisions:
   
When the Adjust R2 value of 0.157 was taken
into consideration, the variables could be predicted
by 15.7%, showing that H2 was supported.
5 Discussion
The findings revealed that when it comes to
purchasing fashion clothing through online social
media, Gen Y places high importance on marketing
mix and risk perception aspects. Marketing mix
variables namely product, place, and privacy factors
as well as risk perception namely financial, social,
and psychological concerns, all have statistically
significant impact on Gen Y's decision to purchase
fashion clothes via online social media.
These current research results are consistent with
the previous studies, but it is interesting to note that
certain findings are different. This study supports
the findings of, [51], that perceived psychological
risk influences consumers' decisions to buy clothes
online, especially when consumers are concerned
about after-sales service if the product is not
delivered, or the ordered clothes cannot be worn.
Thus, merchants should be aware of the
psychological risks that customers face by
employing customer interaction tactics such as
product reviews and comments to support them
throughout the pre-purchase process until they make
a decision. According to, [30], [52], a positive
online shopping experience is related to consumer-
perceived risk. Non-online users, in particular, have
a substantially greater psychological risk perception
than users. In other words, a positive experience or
satisfied customers will have more trust in online
fashion retail merchants, increasing the likelihood of
repurchasing, [53].
Another significant criterion for Gen Y online
social media fashion clothing purchases is perceived
social risk. The findings: personal risks
(psychological risk and social risk) differ from, [31],
[35]. These differences might be explained by
cohort and culture. According to, [54], the social
status image of Gen Y is crucial because they tend
to show their lifestyle preferences through an
interest in fashionable clothing and unique dressing.
Further, among the major dimensions of cultural
values, individualism/ collectivism culture and
uncertainty avoidance, [55], are the most important
cross-cultural perceived risks identified by
researchers looking for possible cultural
explanations for differences in risk perception
between countries, [35]. Thailand was identified as
a country that prefers to avoid uncertainty; they are
less risk-taking because they are driven by a fear of
failure or loss. In addition, Thailand's collectivist
culture, emphasizes group values and the necessity
of belonging to specific social groups People in
collectivist cultures are susceptible to social
influences and the consequences of negative
outcomes because they want to be accepted by the
group and society around them, [56]. This empirical
study confirms, [15]’s, results that financial risks
influence online purchases regardless of whether the
product is highly relevant or not to the consumer.
When doing online purchasing, products are not
delivered before making a purchase; as a result,
customers are concerned about losing money if the
goods are not delivered. The most common payment
methods offered by social media merchants are
money transfers and cash-on-delivery (COD).
According to, [14], the COD mechanisms can
effectively mitigate the impact of perceived product
risks, resulting in substantial financial risk
reduction.
In the online marketing mix, the place is
involved with a presentation on the interface screen
of the device. This empirical study supports the
findings of, [47], that place influences customers'
online shopping decisions. As a result of its rapid
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growth, online social media has become one of the
most convenient trade channels accessible. There
are no restrictions in terms of time or location.
Consumers can search for products and place orders
at any time, from any location, using a variety of
communication devices. When making an online
order, consumers must provide and document
personal information such as their name, address,
telephone number, e-mail address, and credit card
number as well as conversations between the buyer
and vendor. As a result, privacy is an important
marketing mix component that influences Gen Y's
social media fashion clothing purchases. This
current study supports the findings of, [46], which
found that privacy influenced the decision to buy
fashion clothes from e-commerce websites. In other
words, online buyers who have a high degree of
privacy concern will perceive an important risk of
information disclosure which will eventually impact
their purchasing decisions, [57]. In addition, this
research is consistent with, [58], that product factors
affect the decision to buy fashion clothes through
Facebook and Instagram. When shopping online
buyers do not have direct contact with the product,
as a result, product presentation and branding are
becoming more crucial in consumers' online
purchasing decisions. The brand acts as a stimulus
and evokes the emotions of consumers who are then
more likely to decide to purchase products online,
[59].
To alleviate risk perception for Gen Y social
media fashion clothing purchases, online merchants
should realize that this cohort was born in the digital
age. They are technologically competent and have a
high risk tolerance. They enjoy sharing, engaging
with, discovering, and utilizing content on social
networking sites, [13]. E-WOM, or text and articles
published on social media platforms, plays a crucial
role in Gen Y communication. Word-of-mouth such
as comments, and product reviews provided by
customers on the internet is a significant kind of E-
WOM communication, [60], which is critical in the
information search process on product types and
pricing to conduct comparisons before making a
selection, [61]. Consumers may get information
about the quality of products or services that
significantly influence their purchase behavior of
consumers, [62]. Therefore, a retail brand reputation
must be developed to enhance purchase intention
and customer loyalty, [53].
6 Limitations and Suggestions
This research established certain criteria for the
sample population's age range and the timing of
prior online purchases. As a consequence,
researchers had to spend more time screening and
collecting data than usual. Furthermore, because this
study only included information from Gen Y, future
research should include information from other
generations to evaluate any differences in buying
behavior, such as the impact of risk perception
factors and marketing mix factors on online
purchases. Future researchers should also study the
effect of information and opinions transmitted via
social media (E-WOM), as well as the power of
creative content, on the online purchasing behavior
of Gen Y shoppers and/or other generation groups.
Finally, to obtain more comprehensive study
findings, researchers should examine and collect
information about the marketing mix and risk
management tactics of online sellers and
entrepreneurs.
References:
[1]
United Nations Conference on Trade and
Development, UNCTAD, "Global e-
commerce jumps to $26.7 trillion, COVID-19
boosts online sales," 3 May 2021, [Online].
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
- Tanompong Panich initiated the conceptualization
of the research, designed the research
methodology, and acquired funding for the
research project that resulted in this present work.
He also carried out and planned research data
collection.
- Arunee Lertkornkitja planned and coordinated
research activities, wrote the initial draft as well as
reviewed and edited the published work.
- Nuttharin Pariwongkhuntorn worked with the data
collection team to coordinate their efforts.
- Satithorn Phonkaew conducted the formal
analysis.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
The financial resources for this study were granted
by the Rajamangala University of Technology
Thanyaburi.
Conflict of Interest
The authors have no conflicts of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2024.21.19
Tanompong Panich, Arunee Lertkornkitja,
Nuttharin Pariwongkhuntorn, Sasithorn Phonkaew
E-ISSN: 2224-2899
222
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