The Influence
Of The E-WOM, E-Trust, and E-Service
on Purchase Decision
(Study on
TikTokShop Marketplace Users
in West Jakarta)
Agus
Sriyanto
Universitas
Budi luhur, South Jakarta, DKI Jakarta, Indonesia
Email: [email protected]
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ABSTRACT |
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E-WOM, E-Trust, E-Service, Purchase Decisions. |
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The research aimed to investigate the influence of E-WOM, E-Trust, and E-Service
on purchase decisions among active users of the TikTokShop
marketplace in West
Jakarta. These variables
were chosen due to their critical
roles in shaping consumer behavior and influencing purchasing decisions in online market contexts. E-WOM (Electronic Word of
Mouth) reflects the power of
recommendations and reviews from peers and online
communities, which are crucial factors in modern consumer decision-making processes. E-Trust (Electronic Trust) is
fundamental in establishing and
maintaining relationships
between consumers and online platforms,
influencing user confidence in the platform's reliability, security, and credibility. E-Service (Electronic Service) directly impacts user experience and satisfaction within online marketplaces, as the quality of service
provided significantly influences consumer perceptions and purchasing decisions. By examining the dynamics of E-WOM, E-Trust, and E-Service within the TikTokShop market context, the research aims to provide
insights that can inform strategies
to enhance user engagement, trust, and ultimately
drive purchase decisions on the platform. |
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INTRODUCTION
One of the marketplaces that is increasingly
popular today is TikTokShop. TikTokShop is a marketplace connected to the
TikTok social media application. Tiktok itself was initially
a social media platform that
provided space for its users
to create, disseminate, and watch short videos
or commonly referred to as content
The COVID-19 pandemic
period has become one of the
most impactful on the use
and popularity of Tiktok. The large number of
people who were laid off during
the pandemic made their movements
limited. In this condition, various ways they do
to be able
to spend their time at
home, one of which is
by looking for entertainment via the Tiktok application.
With this application they can pour their
creativity by making fun videos, dancing,
or other interesting content. Apart from being
an entertainment medium, Tiktok can also
be a medium for disseminating information related to COVID-19 at that time.
Many of its
users use the TikTok application
to provide health tips, facts
about viruses, and other essential
messages to fellow users. This
is what makes
the Tiktok application experience an increase in popularity. Digital marketing strategies must always be considered
in this digital era because
they greatly influence consumer purchasing decisions
According to Petcharat
In this digital
era, E-WOM is one of the essential
things for consumers to share
information about their experiences, especially in terms of online shopping.
The existence of E-WOM can be a driving
factor that influences purchasing decision-making. E-WOM has a significant
influence on consumer purchasing decisions
Another factor influencing consumers' purchasing decisions in online shopping is E-Trust. E-trust is something
that leads to a level of trust
between customers and brands or
companies through electronic media. Electronic trust
or E-Trust is essential in digital technology, including digital marketing. The high level of trust
allows customers to feel safe,
comfortable, and confident in transacting online
In addition to E-WOM and E-Trust, E-Service is another factor
that influences purchasing decisions in the marketplace. E-Service is a service a brand or company
provides through digital
media. E-Service includes online
customer service, online purchase process, product delivery, and communication
between sellers and buyers via the marketplace. A company or brand
needs to continue improving its services digitally
to attract consumers and create
sales. The most essential thing in electronic services, called E-Service in the marketplace, is a quick response to customer chats.
METHODS
Population
The population in this study is TikTokShop
marketplace users in West Jakarta. This population includes individuals with experience interacting with E-WOM, E-Trust, and
E-Service in digital business. The standard population in this study is consumers
who are active in using social media or digital platforms, have a history of purchasing products
or services online, and have
adequate internet access.
Sample
The criteria used in sampling are people in West Jakarta who are TikTokShop marketplace users and have
made transactions
Information:
n = number
of samples
z
= z score at 95% confidence = 1.96
p
= maximum estimate = 0.5
d = sampling error = 10%
Through the
formula above, it can be calculated
the number of samples to
be used as follows: 
Using the Lemeshow Formula above, the sample
value (n) obtained is 96.04. To get accurate results, the sample taken
in this study was divided into 100 respondents.
Research Model
This
study used multiple linear regression analysis techniques because it has more than
one independent variable. Multiple linear regression equation models were used to test hypotheses
regarding the influence of E-WOM (X1), E-Trust
(X2), E-Service (X3), and Purchase
Decision (Y). Analysis of the regression
line equation is to determine
the influence of variable X as an independent variable (free) with variable Y as the dependent variable
(bound). Regression analysis aims to
(i) determine the magnitude of the
quantitative influence of X changes on
Y changes, whether positive or negative
and (ii) estimate or forecast the
value of Y if the X variable
that correlates with Y increases or decreases, Priyatno (2017), while correlation aims to determine
the relationship of variable X to
Y. The regression equation used in this study is: Y = a + β1 X1 +
β2 X2 + β3 X3 + ε
Information:
Y = Purchase Decision A = Constant
β1, .....
, β3 = Regression coefficient
of each variable
X1 = E-WOM
X2 = E-Trust
X3 = E-Service
RESULTS
Normality Test
According to Santoso (2018), the normality test is carried out
to determine whether the resulting
error has a normal distribution
in a regression model. The basis for
decision making to detect normality is that if
the data spreads around the diagonal line and follows
the diagonal direction, then the regression
model meets the normality assumption and can also
be seen from
the customarily distributed digram graph (Priyatno, 2017).
Multicollinearity Test
The method of decision making is that if
the smaller the Tolerance value and the greater
the VIF value, the closer the
multicollinearity problem will
occur. Most studies stated that if the
tolerance is more than 0.1 and
VIF is less than 10, multicollinearity does not occur.
Table 1. Regression
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
1,893 |
1,578 |
|
1,200 |
,233 |
|
E-Wom |
,413 |
,068 |
,439 |
6,115 |
,000 |
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|
E-Trust |
,297 |
,081 |
,299 |
3,673 |
,000 |
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E-Seevice |
,233 |
,085 |
,234 |
2,738 |
,007 |
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a. Dependent Variable:
Puchace Decision |
||||||
Source: SPSS 25 data processing results
From
the results above, it can
be known that the value
of the Variance
Inflation Factor (VIF) of each variable,
namely the E-WOM variable, is 1.931, the E-Trust variable is 2.491, and the E-Service variable is 2.734. All three have a Tolerance
of more than
0.1 and VIF of less than 10; it
can be concluded
that for the variables E-WOM, E-Trust, and E-Service, No multicollinearity problems occur.
Heteroscedasticity Test
According to Santoso (2018),
test heteroscedasticity
is Used To find out whether,
in a regression model, there
is an inequality
of variance in residuals (error). If the variance of
the residual from one observation
to another is fixed, it
is called homoscedasticity. If the variance is different,
it is referred
to as heteroscedasticity. A
regression model is said to be
good if heteroscedasticity
does not occur. The basis for decision making the presence or
absence of heteroscedasticity:
1. Heteroscedasticity occurs if the points
at the output
form a specific regular pattern.
2. 
If the
points in the output do not form
a specific orderly pattern, heteroscedasticity does not occur.
Source: SPSS 25 data processing results
Figure 1. Scatterplot
Chart
Figure 2. above
shows the spread of data points as follows:
1. The data points
spread above and below or
around the number 0.
2. Data points
don't clump together just above
and below them.
3. Unpatterned spread of data points
So it can be
concluded that the independent variable is free
from the classical assumption of heteroscedasticity and is worthy
of use in research.
Correlation Test
Correlation analysis determines the linear closeness of the relationship
between two variables (Priyatno, 2017).
Table 2. Correlation
Test Correlations
|
E-WOM |
E-Trust |
E-Service |
Purchasing Decision |
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E-WOM |
Pearson Correlation |
1 |
,628** |
,669** |
,783** |
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Sig. (2-tailed) |
|
,000 |
,000 |
,000 |
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N |
100 |
100 |
100 |
100 |
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E-Trust |
Pearson Correlation |
,628** |
1 |
,756** |
,751** |
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Sig. (2-tailed) |
,000 |
|
,000 |
,000 |
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N |
100 |
100 |
100 |
100 |
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|
E-Service |
Pearson Correlation |
,669** |
,756** |
1 |
,753** |
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Sig. (2-tailed) |
,000 |
,000 |
|
,000 |
|
|
N |
100 |
100 |
100 |
100 |
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|
Purchasing Decision |
Pearson Correlation |
,783** |
,751** |
,753** |
1 |
|
Sig. (2-tailed) |
,000 |
,000 |
,000 |
|
|
|
N |
100 |
100 |
100 |
100 |
|
**. Correlation
is significant at the 0.01 level (2-tailed).
Source : SPSS 25 data processing results
Table 3. Correlation
Level Table
|
Coefficient Interval |
Relationship Level |
|
0,80 – 1,000 |
Very Powerful |
|
0,60 – 0,799 |
Strong |
|
0,40 – 0,599 |
Strong enough |
|
0,20 – 0,399 |
Low |
|
0,00 – 0,199 |
Very Low |
Source: Riduwan
and Engkos Achmad Kuncoro
(2013)
Furthermore, we can
see the relationship
between the variables E-WOM (X1), E-Trust (X2), and
E-Service (X3) to purchasing
decisions (Y). Based on Table 3. above,
the description of the output
regarding correlation, it can be
interpreted as follows:
E-WOM Variable
(X1) with Purchase Decision (Y) : (r = 0.783 : Sig
= 0.000)
Based on Table 3. showing
the relationship between the E-WOM variable and purchasing decision of 0.783, it can be
concluded that the magnitude of
the relationship between E-WOM and purchasing decision shows a strong correlation.
E-Trust Variable
(X2) with Purchase Decision (Y) : (r = 0.751 : Sig
= 0.000)
Based on Table 3, which
shows the relationship between the E-Trust variable and the purchase
decision of 0.751, it can be
concluded that the magnitude of
the relationship between E-Trust and the purchase decision
shows a strong correlation.
E-Service Variable
(X3) with Purchase Decision (Y) : (r = 0.753 : Sig
= 0.000)
Based on Table 3, which
shows the relationship between the E-Service variable and the purchase
decision of 0.753, it can be
concluded that the magnitude of
the relationship between E-Service and purchasing decision shows a strong correlation.
Partial Test (Test t)
Partial hypothesis testing (t-test) is used to
examine the effect of E-WOM (X1), E-Trust (X2) and E-Service (X3) on purchasing decisions (Y) individually or partially. The partial test is done
by comparing tcount with ttable so it is often
called t test. The degree of freedom
on the t test is n-k where n (number of data), k (number of variables).
Table 4. Partial
Test (Test t)
Coefficientsa
|
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
|||
|
Type |
|
B |
Std. Error |
Beta |
||
|
1 |
(Constant) |
1,893 |
1,578 |
|
1,200 |
,233 |
|
E-WOM |
,413 |
,068 |
,439 |
6,115 |
,000 |
|
|
E-Trust |
,297 |
,081 |
,299 |
3,673 |
,000 |
|
|
E-Service |
,233 |
,085 |
,234 |
2,738 |
,007 |
|
a. Dependent
Variable: Purchase Decision
Source : SPSS 25 data processing results
From table 4. above it can be
concluded that:
Variable E-WOM (t count = 6.115 ; Sig 0.000)
tcount (6.115) > ttable (1.984) then Ha received Sig value
(0.000) < 0.05 then Ha received. That
is, the variable
coefficient E-WOM (X1) partially
significantly influences the purchase decision variable.
E-Trust variable
(t count
= 3.673 ; Sig 0.000)
tcount (3.673) > ttable (1.984) then Ha received Sig value
(0.000) < 0.05 then Ha received. That
is, the coefficient
of the E-Trust variable (X2) partially significantly influences the purchase decision
variable.
Variable E-WOM (t count = 2.738 ; Sig 0.007)
tcount (2.738) > ttable (1.984) then Ha received Sig value
(0.007) < 0.05 then Ha received. That
is, the coefficient
of the E-Service variable (X3) partially significantly influences the purchase decision
variable.
Coefficient of Determination (R2) Analysis Test
Table 5. Coefficient of Determination Analysis
Model Summary
|
Type |
R |
R Square |
Adjusted R Square |
Std. Error of
the Estimate |
|
1 |
.863a |
,744 |
,736 |
1,909 |
a. Predictors:
(Constant), E-Service, E-WOM, E-Trust
Source : SPSS 25 data processing results
To see the effect
of E-WOM, E-Trust, and
E-Service variables against
purchasing decisions. The calculation results will be seen
in the summary model, especially the R Square number (squared correlation number). The number R Square is also
called the coefficient of determination (KD). As for the calculation results, table 4.22. Because the independent
variable is more than two,
the adjusted R Square (Adj R2) is used. The magnitude of the
coefficient of determination (adjusted R Square) is 0.736. So the adjusted R Square (Adj R2) or the coefficient of determination (KD) in the calculation above is 0.736 or equal to
73.6% (the formula for calculating the Coefficient of Determination is r2 x 100%).
KD = r2 x
100%
KD =
0.736 x 100%
KD = 73.6
%
This figure means that
the combined influence of E-WOM, E-Trust, and E-Service on purchasing decisions is 73.6% while the remaining 26.4% (100% -
73.6%) is influenced by other causal
factors outside this regression model. For example, price, promotion, quality and others.
Interpretation of Research Results
The Effect
of E-WOM on Purchasing Decisions
The results of testing the first hypothesis in this study, show that E-WOM has a significant influence on purchasing
decisions; this can be seen
from the probability value of count (6.115) > table (1.984) and Sig
value (0.000) < (0.05). The results
of the author's
research show that the E-WOM variable has a significant effect on purchasing decisions.
This shows that consumers feel that the
existence of E-WOM that matches their
expectations of a product will influence
their purchasing decisions. According to research by
Elsa Riski Yulindasari, 2022, the results
showed that E-WOM had a significant and positive effect on purchasing decisions;
this proves that the results
of research conducted by the
author with previous research consistently have a significant influence between E-WOM on purchasing decisions.
The Effect of
E-Trust on Purchasing Decisions
The results
of testing the first hypothesis in this study, show that E-Trust has a significant influence on purchasing
decisions; this can be seen
from the probability value of calculate (3.673) > table (1.984) and Sig
value (0.000) < (0.05). The results
of the author's
research show that E-Trust variables have a significant effect on purchasing
decisions. This shows that consumers
will prefer to buy a product
they trust. According to Nuri Purwanto's research, 2021, the results showed
that E-Trust had a significant
and positive effect on purchasing
decisions. This proves that the
results of research conducted by the author
with previous research are consistent that there is
a significant influence between E-Trust and purchasing decisions.
The
Effect of E-Service on Purchasing Decisions
The results of testing the first hypothesis in this study, show that E-Service has a significant influence on purchasing
decisions; this can be seen
from the probability value of calculate (2.378) > table (1.984) and Sig
value (0.007) < (0.05). The results
of the author's
research show that the E-Service variable has a significant effect on purchasing
decisions. This shows that consumers
are happier if served quickly and precisely when
buying a product so that purchasing
decisions are made. According to Ismi Suaidi's research, 2022, the results showed
that E-Service had a significant
and positive effect on purchasing
decisions. This proves that the
results of research conducted by the author
with previous research are consistent that there is
a significant influence between E-Service and purchasing decisions.
CONCLUSION
Research on the impact of
E-WOM, E-Trust, and E-Service on
purchasing decisions within the TikTokShop
Marketplace unveils significant
insights. Electronic Word of
Mouth (E-WOM) substantially
influences consumers' choices on TikTokShop,
underscoring the importance of positive
online word-of-mouth in shaping purchasing decisions. The study also sheds light on
the influential roles of E-Trust and E-Service, which significantly contribute to repeat purchase
decisions on the platform. This highlights the interconnectedness of trust-building and effective digital services in shaping consumer preferences and ultimately driving purchasing behaviors within the digital marketplace. From a managerial perspective, the implications drawn from the
research offer valuable guidance for businesses navigating the dynamic landscape of online commerce.
Firstly, there is a clear call
for companies to expand and
optimize their use of social
media, particularly on platforms like TikTokShop. This recommendation reinforces empirical support for integrating social media into comprehensive marketing strategies, emphasizing the need for
proactive engagement, positive E-WOM cultivation, and strategic digital marketing efforts. Secondly, the research
underscores the critical importance of investing in digital customer service (E-Service). Managers are urged to establish a robust technological foundation that ensures efficient and responsive customer support, secure online transactions,
and effective inventory management. This dual-focus on leveraging social
media and enhancing digital
service capabilities emerges as key pillars for businesses
seeking to thrive in the evolving
landscape of online retail.
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|
Copyright holder: Agus
Sriyanto (2024) |
|
First publication rights: International Journal
of Social Service and Research (IJSSR) |
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