JRSSEM 2021, Vol. 01, No. 4, 340 – 361
E-ISSN: 2807 - 6311, P-ISSN: 2807 - 6494
DOI : 10.36418/jrssem.v1i4.29 https://jrssem.publikasiindonesia.id/index.php/jrssem/index
THE EFFECT OF SERVICE QUALITY AND BRAND IMAGE ON
REPURCHASE INTENTION WITH BRAND TRUST AS
MEDIATING VARIABLE BY THE GENERATION Z OF E-
WALLET CONSUMERS IN JAKARTA
Dwi Asri Ningrum
1*
Mohamad Rizan
2
Agung Kresnamurti Rivai P
3
1,2,3
Faculty of Economics, Universitas Negeri Jakarta, Indonesia
e-mail: [email protected]
1
, mohamadrizan7[email protected]d
2
, [email protected]
3
*Correspondence: [email protected]
1
Submitted: 23 October 2021, Revised: 10 November 2021, Accepted: 14 November 2021
Abstract. The purpose of this study was to examine the effect of service quality (X1) and brand
image (X2) on repurchase intention (Z) through brand trust (Y1) as an intervening variable on
generation Z e-wallet consumers in Jakarta. Data collection methods use questionnaire-style
tools to conduct surveys. The sample of this study is 300 respondents of Gen Z consumers
aged 17-26 in Jakarta who have made at least five transactions or payments through the e-
wallet application in the last month. Data analysis technology uses SPSS 25 version and SEM
from LISREL 8.8 version statistical package to process and analyze research data. The results
show that: 1) service quality has a significant effect on brand trust for generation Z e-wallet
consumers in Jakarta, 2) brand image has a significant effect on brand trust on generation Z
e-wallet consumers in Jakarta, 3) brand trust has a significant effect on repurchase intention
of generation Z e-wallet consumers in Jakarta, 4) service quality has a significant effect on
repurchase intention of generation Z e-wallet consumers in Jakarta, 5) brand image has a
significant effect on repurchase intention of generation Z e-wallet consumers in Jakarta, 6)
service quality has a significant effect on repurchase intention through brand trust as an
intervening on generation Z e-wallet consumers in Jakarta, 7) brand image has a significant
effect on repurchase intention through brand trust as an intervening on generation Z e-wallet
consumers in Jakarta. This research can contribute new information and knowledge about e-
wallet in developing countries, especially Indonesia.
Keywords: service quality; brand image; brand trust; repurchase intention; generation z; e-
wallet consumers.
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 341
INTRODUCTION
In the Industrial Revolution 4.0 period,
there was rapid development in digital
technology. The internet can reach a
broader target market. The Southeast Asian
region, including Indonesia, ranks third for
the highest internet usage growth in the
world, which is 9.6% in one year Kemp,
2021.
Fintech is a digital transformation
introducing new concepts in the financial
services industry Kaushal & Ghosh, (2016).
Intense pressure from Gen Z is the main
driving force for Fintech providers & banks
to digitize monetary services so that they
are available through digital channels,
especially smartphones Meola, (2017).
Fintech transactions in Indonesia in 2017
reached US$ 18.65%. Around 14 percent or
US$ 280 billion of this value will be
controlled by payment Fintech.
E-commerce has changed the way
people transact using electronic money
payments, and one of them is an e-wallet.
According to the Times (2021), an e-wallet
is an electronic wallet that is practically
used for online payments and financial
transactions using a smartphone. Based on
data from Capgemini, (2021). Global e-
commerce continues to grow at 19% CAGR
(2017 - 2023), reaching $6.5 trillion. E-
wallet is the preferred e-commerce
payment method with a 52% market share
in 2023.
Cashless payments through the digital
system refer to alternative prices, primarily
to suppress the spread of COVID-19. Based
on research results from Capgemini & BNP
Paribas, the number of e-wallet users will
increase from 2.3 billion in 2019 to nearly 4
billion in 2024 Capgemini, (2021).
There are many features and
advantages in e-wallet that make it easier
for consumers' financial transactions.
Transaction speed and the convenience of
paying anytime and anywhere are the top
two factors that motivate users to make
payments via e-wallet. However, from the
growth opportunities of e-wallet globally,
several problems hinder the use of e-wallet.
Where cash still dominates. The
information shows that 64% of the
populace matured 15 years over still don't
have bank accounts, and just around 4% of
the public has credit cards KPMG, (2017).
No. 2 after the virtual card globally.
Based on data from The Asian Banker,
Indonesia has 270 million people, and more
than 50% still do not have a bank account
due to geographical barriers. The low
development of e-wallets in Indonesia is
the element behind one of the authors'
research on e-wallets. On the other hand,
the Capgemini & BNP Paribas survey found
that over the next two to three years, e-
wallet will become a digital payment
initiative Capgemini, (2021). An overview by
the Indonesian Internet Service Providers
Association (APJII) uncovered that 56% or
95.8 million of Indonesia's Internet users
never shopped online. At the same time,
there are approximately 6,000,000 online
merchants in Indonesia.
From the problems above, Indonesia
has more than 60% of the population
equipped with smartphones Banker, (2021).
The increasing number of cellular
technology and the penetration of internet
users can affect the expansion of e-wallet
Capgemini, (2021).
Current research is focused on
342 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
Generation Z, which has the most
interaction with technology today. Gen Z is
the generation born between 1995 and
2009. Jakarta is currently one of the major
emerging markets, which forms the basis
for the future growth of Indonesia's
financial technology and the growing trend
of electronic transactions already visible in
Jakarta, making it an exciting area to be
researched Smartcity Jakarta, (2019).
In Indonesia, as indicated by a new
report by Iprice, GoPay, OVO, DANA,
LinkAja are the best four e-wallets with the
most significant number of month-to-
month active users and the most
downloads from the second quarter of
2019 to the second quarter of 2020.
Saleem et al. (2017) identify in
Pakistan’s aviation industry, service quality,
and trust affect repurchase intentions are
straightforwardly and positively correlated
through customer satisfaction. Service
quality straightforwardly and positively
correlated with repurchasing intentions
through brand image. Sullivan & Kim
(2018) state that repurchase intention can
be increased by the brand trust that
consumers get from the service quality of
the e-wallet and the brand image of the e-
wallet itself. Brand Image simultaneously
has a positive and significant impact on
purchasing decisions, as stated by
Juwariyah, (2021).
This research is to see more about how
the Indonesian people, especially the
people of Jakarta, recognize e-wallet.
Likewise, this study also aims to decide the
elements that impact buyers' taking on e-
wallet, regardless of whether service quality
and brand image significantly affect brand
trust and repurchase intention of e-wallet.
Whether the brand trust significantly
affects repurchase intention of e-wallet by
Generation Z in Jakarta. The choice to focus
just on this age is relied upon to
comprehend the mental conduct that
underlies Generation Z in utilizing an e-
wallet.
Service Quality
As indicated by Al-Tit (2015), service
quality is an assessment by comparing
consumer expectations with the perceived
service experience of consumers. Chang et
al., (2020) conceptualize service quality with
two elements, namely "what" and "how".
The “what" element describes the service
output, i.e., what the company/service
provider delivered. The “how" element
details the service delivery process, i.e., how
it is shown. According to Pakurár et al.,
(2019), there are several things related to
dimensions of service quality or also called
SERVQUAL, that are tangible, reliable,
responsive, assurance, and empathy. In the
research of Al-dweeri et al. (2017), service
quality has a positive and significant impact
on brand trust. Improving service quality in
dealing with potential customers can
increase brand trust because it is one of the
essential elements of brand trust in internet
shopping. According to Lasmy et al. (2019),
the researchers observed that service
quality significantly affects repurchase
intention on Grab and GoJek as online
transportation.
Hypothesis 1: Service quality significantly
affects brand trust in generation Z e-wallet
consumers in Jakarta.
Hypothesis 4: Service quality significantly
affects the repurchase intention of
generation Z e-wallet consumers in Jakarta.
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 343
Brand Image
In Kotler et al.'s (2016) study, brand
image is a buyer's view of a brand, as
reflected in the brand associations in
customers' recollections. Srivastava &
Sharma (2013) identify the brand image as
an essential concept to prove the
reputation and credibility of the company
in customer satisfaction with the products
or services used. A few dimensions of the
brand image shown by Išoraitė (2018) are
1. brand identity, brand character, brand
association, brand attitude, customer
benefits. In the study of Han et al. (2019), it
is observed that the hypothesis of the
brand image significantly affects brand
trust in South Korean airlines. According to
Iskandar & Berlianto, (2018), exploration
expressed that brand image significantly
affects repurchase intention. For specific
brands, customers foster intellectual and
emotional reactions, then, at that point,
over and over purchase particular brands.
Hypothesis 2: Brand image significantly
affects brand trust on generation Z e-wallet
consumers in Jakarta.
Hypothesis 5: Brand image significantly
affects the repurchase intention of
generation Z e-wallet consumers in Jakarta.
Brand Trust
Brand trust is belief in product/service
performance/brand safety, as consumer
expectations and beliefs that the brand will
continue to provide its best functions and
performance for the benefit of consumers
(Han et al., 2019). In marketing relation,
brand trust is the readiness of buyers to be
associated with the next transaction in the
future, which reflects trust in the seller's
value-based conduct, in this way
prompting repurchase intention Javed &
Wu, (2020). According to Kim et al., (2003),
brand trust has several dimensions: ability,
benevolence, and integrity. In Horng (2020)
research, brand trust in products will
significantly affect repurchase intention for
products traded on any website.
Hypothesis 3: Brand trust significantly
affects the repurchase intention of
generation Z e-wallet consumers in Jakarta.
Repurchase Intention
Repurchase intention is the subjective
probability that experienced customers will
keep purchasing items/services/products
from a similar company Trivedi & Yadav,
(2020). Repurchase intention is an activity
where service users or customers positively
respond to their first purchase so that they
experience repeat purchases in the future
Lasmy et al., (2019). According to Kotler et
al. (2016), the dimensions of repurchase
intention, namely transactional intentions,
referential intentions, preferential
intentions, and exploratory intentions. In Qi
& Yao (2020) research, brand trust
intervenes in connecting multi-channel
integration service quality with repurchase
intention. In the exploration of Benhardy et
al. (2020), brand trust positively moderates
the connection of brand image with
repurchase expectation for BINUS Online
Learning.
Hypothesis 6: Service quality significantly
affects repurchase intention through brand
trust as an intervening on generation Z e-
wallet consumers in Jakarta.
Hypothesis 7: Brand image significantly
affects repurchase intention through brand
trust as an intervening on generation Z e-
344 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
wallet consumers in Jakarta.
Figura. 1 Research Model
Source: Data processed by the author
(2021)
METHODS
This research utilizes a quantitative
approach. The data collection method in
this study is a survey method. According to
Hardani et al. (2020), the survey research
method uses a questionnaire as a research
instrument.
Respondent
The population taken in this study are
Generation Z consumers in the Jakarta area
who have made transactions or payments
through the e-wallet application. In this
study, the sampling technique utilized is
non-probability sampling that uses the
method of purposive sampling, which this
study has criteria. The respondents sought
were consumers of Generation Z aged 17-
26 years who live in the Jakarta area and
have made transactions or payments
through e-wallet applications at least five
times in the last month. In this study, 300
respondents participated online using
Google Form.
Measurement
Data retrieval was conducted using
questionnaires and using a Likert
measuring scale. There are five-point rating
scales in this study, so respondents are
more facilitated because the categories
have a precise order, ranging from
“strongly disagree” to “strongly agree”
Malhotra & Dash, 2010. The questionnaire
is divided into several sections. The first
part contains questions about the
respondent's identity, such as age,
occupation, income, domicile. The
following section contains statements of
several indicators that are adjusted to the
variables to be studied. It adapted the
information regarding service quality from
Ahmad & Zhang (2020), Sultan & Wong
(2019), and Saleem et al. (2017). For the
brand image statement based on the
literature from Benhardy et al. (2020),
Išoraitė (2018), and Zhang (2015). For the
brand trust, which it adopted from Qalati et
al. (2021), Benhardy et al. (2020), and Han
et al. (2019), and the repurchase intention
statement adapted from Trivedi & Yadav
(2020), Lasmy et al. (2019), Saleem et al.
(2017), and Tandon et al. (2017).
Analysis
This research uses SPSS software
version 25 and LISREL version 8.8 to analyze
the data. This research uses the SEM
(Structural Equation Modelling). The model
of data analyzed in this research includes
descriptive analysis, validity test using the
Pearson test that, when the calculated r-
value is greater than the r table, the
Pearson value is considered valid. But on
the other hand, when the computed r is
smaller than the table r-value, the
calculated r-value is invalid. When testing
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 345
reliability, the Cronbach Alpha method is
used to measure reliability. Its range is 0 to
1, and the value is 0.6 to 0.7, which is
considered the acceptable minimum. If the
Cronbach Alpha value is 0.7 and can be
reduced to 0.6 in the exploratory research,
it can declare the variable reliable Hair et
al., (2010). According to Malhotra & Dash
(2010), several models are divided into
three parts: the absolute fit measure, the
suitable incremental standard, and the
Parsimon appropriate action. The full SEM
model in this study aims to analyze the four
variables to know the influence and
relationship between variables. It must first
test the complete model for the goodness
of fit. The service quality, brand image, and
brand trust are variables measured by five
indicators. Six indicators measure the
variable of repurchase intention.
Calculating direct and indirect effects using
SEM is to compare the coefficients of direct
and indirect influence, then check whether
the hypothesis is significant or not. It can
see that the mediating role of the variable
is more important or the direct relationship
is more excellent. In this research, the
standardized total effect value states the
hypothesis result of testing from the
connection between the variables. The
development of the data analysis will
determine the size of the impact and the
relationship between the variables. The test
criteria look at the t-values between
variables and then compare them with their
critical values (t-table). With this, the
relationship with t-values > 1.96 can be
declared significant.
346 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
RESULTS AND DISCUSSION
Source: Data processed by the author (2021)
Table 2. Descriptive Analysis Table Brand Image
Item
Statement
SD
D
N
A
SA
SQ1
The completeness of the features in
the e-wallet application makes it
easier for me to make financial
transactions online.
2
3
56
132
107
0.67%
1.00%
18.67%
44.00%
35.67%
SQ2
The admin fee for each transaction
paid on the e-wallet application is
cheaper than other digital payment
applications.
2
7
66
143
82
0.67%
2.33%
22.00%
47.67%
27.33%
SQ3
The e-wallet application speeds up
or improves my time efficiency when
transacting financially online.
1
5
52
128
114
0.33%
1.67%
17.33%
42.67%
38.00%
SQ4
I am satisfied with the experience of
using the e-wallet application.
1
4
55
139
101
0.33%
1.33%
18.33%
46.33%
33.67%
SQ5
The services provided by the e-wallet
application match or are better than
what I expected
2
5
63
142
88
0.67%
1.67%
21.00%
47.33%
29.33%
Total Frequency
8
24
292
684
492
Percentage
0.53
%
1.60
%
19.47
%
45.60
%
32.80
%
Item
Statement
SD
D
N
BI1
The e-wallet companies have a good
and credible reputation.
1
3
75
0.33%
1.00%
25.00%
BI2
The e-wallet application has a
distinctive logo so that it is easy for
me to remember.
3
3
61
1.00%
1.00%
20.33%
BI3
In my opinion, e-wallet applications
offer more advantages than other
digital payment applications.
1
5
68
0.33%
1.67%
22.67%
BI4
Technological innovations and
features in e-wallet applications are
very modern.
2
2
61
0.67%
0.67%
20.33%
BI5
The e-wallet application is always
remembered as a digital payment
transaction application that is more
1
4
59
0.33%
1.33%
19.67%
Table 1. Descriptive Analysis Table Service Quality
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 347
Source: Data processed by the author (2021)
Table 3. Descriptive Analysis Table Brand Trust
Item
Statement
SD
D
N
A
SA
BT1
The e-wallet application has
guaranteed the confidentiality of my
data.
3
7
94
116
80
1.00%
2.33%
31.33%
38.67%
26.67%
BT2
The e-wallet application guarantees
security in transactions and payment
processes made by me.
3
3
77
126
91
1.00%
1.00%
25.67%
42.00%
30.33%
BT3
I believe transacting and making
payments with an e-wallet poses no
risk.
1
12
100
111
76
0.33%
4.00%
33.33%
37.00%
25.33%
BT4
I didn't find it difficult when using the
e-wallet application.
1
2
70
133
94
0.33%
0.67%
23.33%
44.33%
31.33%
BT5
I didn't have any problems or
problems when using the e-wallet
application.
2
10
63
138
87
0.67%
3.33%
21.00%
46.00%
29.00%
Total Frequency
10
34
404
624
428
Percentage
0.67%
2.27%
26.93%
41.60%
28.53%
Source: Data processed by the author (2021)
practical than other digital payment
applications.
Total Frequency
8
17
324
Percentage
0.53%
1.13%
21.60%
348 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
Table 4. Descriptive Analysis Table Repurchase Intention
Source: Data processed by the author (2021)
Discussion
In Table 1, the service quality variable
(X1) has 5 indicators with answer options
using a Likert scale 1-5 s beginning from 1
= Strongly Disagree, 2 = Disagree, 3 =
Neutral, 4 = Agree, 5 = Strongly Agree.
Contained in table 1, the descriptive
analysis of the Service Quality (X1) variable,
that the option S = Agree is the option
most chosen by respondents compared to
other options, namely 684 or 45.60% with
the statement:
"Admin fees for each transaction paid
on e-wallet applications is cheaper
than other digital payment
applications."
Furthermore, the second most chosen
option from respondents is option four =
Strongly Agree with 492 or 32.80% with the
statement.
"The e-wallet application speeds up
or improves my time efficiency when
transacting financially online."
Thus, the option expressing
disagreement has a lower total score than
the agree option. So, it can conclude that
respondents tend to answer positively to
the Service Quality statement (X1).
In Table 2, the brand image variable
(X2) has 5 indicators with answer options
using a Likert scale 1-5 beginning from 1 =
Strongly Disagree, 2 = Disagree, 3 =
Average, 4 = Agree, 5 = Strongly agree.
Item
Statement
SD
D
N
A
SA
RI1
I have repeatedly transacted and
made payments with the e-wallet
application.
2
5
58
120
115
0.67%
1.67%
19.33%
40.00%
38.33%
RI2
The e-wallet application is the first
choice when transacting or making
payments online.
2
7
65
130
96
0.67%
2.33%
21.67%
43.33%
32.00%
RI3
I like transaction activities or
payments through e-wallet
applications.
2
4
58
142
94
0.67%
1.33%
19.33%
47.33%
31.33%
RI4
The e-wallet application is the best
digital payment application
compared to other digital payment
applications.
2
9
73
145
71
0.67%
3.00%
24.33%
48.33%
23.67%
RI5
I recommend using the e-wallet app
to others.
2
6
75
133
84
0.67%
2.00%
25.00%
44.33%
28.00%
RI6
I rarely consider switching to a digital
payment application other than an e-
wallet application.
1
11
92
123
73
0.33%
3.67%
30.67%
41.00%
24.33%
Total Frequency
11
42
421
793
533
Percentage
0.61%
2.33%
23.39%
44.06%
29.61%
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 349
Contained in table 1, the descriptive
analysis of the brand image variable (X2),
that option 4 = Agree is the option most
chosen by respondents compared to other
options, namely 709 or 47.27% with the
statement:
"E-wallet companies have a good and
credible reputation."
Furthermore, the second largest
option from respondents was option five =
Strongly Agree with a total of 442 or
29.47% with the statement:
"The e-wallet application has a
distinctive logo so that it is easy for me
to remember."
Thus, the option expressing
disagreement has a much lower total value
than the agree option. So, it can conclude
that respondents tend to answer positively
to brand image statements (X2).
In Table 3, the brand trust variable (Y)
has 5 indicators with answer options using
a Likert type 1-5 beginning from 1 =
Strongly Disagree, 2 = Disagree, 3 =
Average, 4 = Agree, 5 = Strongly agree.
Contained in table 3, the descriptive
analysis of the brand trust variable (Y) that
option 4 = Agree is the option most chosen
by respondents compared to other options,
namely 624 or 41.60% with the statement:
"I do not get any problems or
obstacles when using e-wallet
application."
Furthermore, the second largest
option from respondents was option five =
Strongly Agree with a total of 428 or
28.53% with the statement:
"I do not find any difficulties when
using the e-wallet application."
Thus, the option expressing
disagreement has a lower total score than
the agree option. So, it can conclude that
respondents tend to answer positively to
brand trust statements (Y).
In Table 4, the repurchase intention
variable (Y) has 6 indicators with answer
options using a Likert scale 1-5 beginning
from 1 = Strongly Disagree, 2 = Disagree, 3
= Average, 4 = Agree, 5 = Strongly agree.
Contained in table 4, descriptive analysis of
the repurchase intention variable (Z) that
option 4 = Agree is the option most chosen
by respondents compared to other options,
namely 793 or 44.06% with the statement:
"E-wallet application is the best digital
payment application so far. compared
to other digital payment applications”.
Furthermore, the second largest
option from respondents is option five =
Strongly Agree with a total of 533 or
29.61% with the statement:
"I have repeatedly transacted and made
payments with the e-wallet application."
Table 5. Validity Test Results
Variable
Cronbach’s
Alpha
N of
Items
Information
Service Quality (X1)
0,872
5
Reliable
Brand Image (X2)
0,885
5
Reliable
Brand Trust (Y)
0,900
5
Reliable
Repurchase Intention (Z)
0,876
6
Reliable
350 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
Source: Data processed by the author (2021)
Table 6. Reliability Test Results
Source: Data processed by the author (2021)
Validity and Reliability Test
In table 5, the results of the
respondent's answers will be processed by
the researcher by considering the validity
requirements, namely r arithmetic r table
with a significance of 5%, where the value
of the r table from 300 samples is 0.113.
Therefore, the results of the validity of each
item/item must be greater than 0.113. The
method used in the validity test is Pearson
Product Moment Correlation using SPSS
version 25 software. Based on Table 5, the
results for all indicators on the four
research variables show that they have a
calculated r-value greater than the r table.
From these results, it can state that all
hands are valid.
In Table 6, the reliability test is
performed with the Cronbach Alpha
formula. If the reliability value is less than
0.6, it can be said to be not very good, while
0.7 is acceptable, and 0.8 can be said to be
good. According to Table 6 above, the
Cronbach alpha coefficient value of the
service quality variable (X1) with five
indicators is 0.872. The Cronbach alpha
Variable
Indicators
r-values
r-table
Information
Service Quality
(X1)
SQ1
0,830
0,113
Valid
SQ2
0,789
0,113
Valid
SQ3
0,792
0,113
Valid
SQ4
0,841
0,113
Valid
SQ5
0,817
0,113
Valid
Brand
Image
(X2)
BI1
0,806
0,113
Valid
BI2
0,819
0,113
Valid
BI3
0,853
0,113
Valid
BI4
0,841
0,113
Valid
BI5
0,821
0,113
Valid
Brand Trust
(Y)
BT1
0,864
0,113
Valid
BT2
0,857
0,113
Valid
BT3
0,845
0,113
Valid
BT4
0,816
0,113
Valid
BT5
0,841
0,113
Valid
Repurchase
Intention
(Z)
RI1
0,765
0,113
Valid
RI2
0,803
0,113
Valid
RI3
0,797
0,113
Valid
RI4
0,789
0,113
Valid
RI5
0,782
0,113
Valid
RI6
0,782
0,113
Valid
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 351
Source: Data processed by the author (2021)
coefficient value of the brand image (X2)
with five hands is 0.885. The Cronbach
alpha coefficient of brand trust (Y) with five
indicators is 0.900. The Cronbach alpha
coefficient value of repurchase intention (Z)
with six hands is 0.876. The Cronbach α
coefficient values of the four variables are
all greater than 0.70, so it can be concluded
that the indicator measurement tools of the
four research variables used are reliable
and can be used for further analysis.
Confirmatory Factor Analysis
Table 7. Confirmatory Factor Analysis
Service Quality
The
goodness
of Fit
Indices
Cut-
off
Value
Result
Model
Evaluation
CMIN/DF
< 3
2,304
Good Fit
GFI
≥
0,90
0,98
Good Fit
SRMR
<
0,05
0,022
Good Fit
RMSEA
≤
0,08
0,066
Good Fit
AGFI
≥
0,90
0,95
Good Fit
NNFI
≥
0,90
0,99
Good Fit
CFI
≥
0,90
0,99
Good Fit
Figure 2. Model First Order Construct
Variable Service Quality
In table 7 and figure 2, the results of
the test service quality variable
instrument (X1), which has five indicators.
after processing the model on the first-
order construct shows results that there
are no wasted indicators and produces a
good level of acceptance with the effects
of CMIN/DF 2.304; GFI 0.98; SRMR 0.022;
RMSEA 0.066; AGFI 0.95; NNFI 0.99; CFI
0.99. Thus, the model is good because the
goodness of fit indices are in the excellent
fit category, so there is no need to modify
the model.
Table 8. Confirmatory Factor Analysis
Brand Image
The
goodnes
s of Fit
Indices
Cut-
off
Value
Resul
t
Model
Evaluatio
n
CMIN/DF
< 3
2,168
Good Fit
GFI
≥ 0,90
0,99
Good Fit
SRMR
< 0,05
0,019
Good Fit
RMSEA
≤ 0,08
0,062
Good Fit
AGFI
≥ 0,90
0,96
Good Fit
NNFI
≥ 0,90
0,99
Good Fit
CFI
≥ 0,90
0,99
Good Fit
Source: Data processed by the author
(2021)
352 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
Source : Data proccesed by author (2021)
Figure 3. Model First Order Construct
Variable Brand Image
In table 8 and figure 3, the test
results of the brand image variable
instrument (X2), which has five indicators,
then after processing the model on the
first-order construct shows the results
that there are no wasted indicators and
produces a good level of acceptance with
the effects of CMIN/DF 2,168; GFI 0.99;
SRMR 0.019; RMSEA 0.062; AGFI 0.96;
NNFI 0.99; CFI 0.99. Thus, the model is
good because the goodness of fit indices
are in the excellent fit category, so there
is no need to modify the model.
Table 9. Confirmatory Factor Analysis
Brand Trust
Goodness
of Fit
Indices
Cut-
off
Value
Result
Model
Evaluation
CMIN/DF
< 3
1,840
Good Fit
GFI
≥ 0,90
0,99
Good Fit
SRMR
< 0,05
0,017
Good Fit
RMSEA
≤ 0,08
0,053
Good Fit
AGFI
≥ 0,90
0,96
Good Fit
NNFI
≥ 0,90
0,99
Good Fit
CFI
≥ 0,90
1,00
Good Fit
Source: Data processed by the author
(2021)
Figure 4. Model First Order Construct
Variable Brand Trust
In table 9 and figure 4, the test results
of the brand trust variable instrument (Y),
which has five indicators, then after
processing the model on the first-order
construct shows the results that there are
no wasted indicators and produces a good
level of acceptance with the effects of
CMIN/DF 1,840; GFI 0.99; SRMR 0.017;
RMSEA 0.053; AGFI 0.96; NNFI 0.99; CFI
1.00. Thus, the model is good because the
goodness of fit indices are in the excellent
fit category, so there is no need to modify
the model.
Table 10. Confirmatory Factor Analysis
Repurchase Intention
Goodness
of Fit
Indices
Cut-
off
Value
Result
Model
Evaluation
CMIN/DF
< 3
2,313
Good Fit
GFI
≥ 0,90
0,98
Good Fit
SRMR
< 0,05
0,027
Good Fit
RMSEA
≤ 0,08
0,066
Good Fit
AGFI
≥ 0,90
0,95
Good Fit
NNFI
≥ 0,90
0,98
Good Fit
CFI
≥ 0,90
0,99
Good Fit
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 353
Figure 5. Model First Order Construct
Variable Repurchase Intention
In table 10 and figure 5, the test
results of the repurchase intention variable
instrument (Z), which has six indicators,
then after processing the model on the
first-order construct shows the results that
there are no wasted indicators and
produces a good level of acceptance with
the effects of CMIN/DF 2,313; GFI 0.98;
SRMR 0.027; RMSEA 0.066; AGFI 0.95; NNFI
0.98; CFI 0.99. Thus, the model is good
because the goodness of fit indices are in
the excellent fit category, so there is no
need to modify the model.
Full Structural Equation Modelling
(SEM)
Table 11. Confirmatory Factor Analysis
Full Model SEM
The
goodness
of Fit
Indices
Cut-
off
Value
Result
Model
Evaluation
CMIN/DF
< 3
1,641
Good Fit
GFI
≥ 0,90
0,91
Good Fit
SRMR
< 0,05
0,035
Good Fit
RMSEA
≤ 0,08
0,046
Good Fit
AGFI
≥ 0,90
0,89
Marginal Fit
NNFI
≥ 0,90
0,99
Good Fit
CFI
≥ 0,90
0,99
Good Fit
Source: Data processed by the author
(2021)
The model is good because the RMSEA
value is 0.046 or less than 0.08. Also, most
of the goodness of fit indices criteria are
already in the excellent fit category, so
there is no need to modify the model.
In Figure 6 below, the full SEM model
in this research aims to analyze the
connection between the four variables to
see whether the independent variable can
influence the dependent variable. The
complete model should first be tested for
goodness of fit, as was done for each
variable in the previous figure. If the model
does not reach the expected value, it is
necessary to modify the indices according
to the suggestion in the Lisrel software.
From the data processing results, the whole
model formed has met the requirements to
be a good fit.
354 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
Source: Data processed by the author (2021)
Figure 6. Structural Equation Model Results
Table 12. Result of Direct and Indirect Effect
Dependent
Variable
Independent
Variable
Direct
Effect
Indirect
Effect
Brand Trust
←
Service Quality
0,43
Brand Trust
←
Brand Image
0,41
Repurchase
Intention
←
Service Quality
0,19
0,23
Repurchase
Intention
←
Brand Image
0,20
0,22
Repurchase
Intention
←
Brand Trust
0,55
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 355
Figure 7. T-values SEM
Table 13. Hypothesis testing
Hypothesis
Path
Path
Coefficient
t
values
Interpretation
H1
SQàBT
0,43
4,38
Significant
H2
BIàBT
0,41
4,21
Significant
H3
BTàRI
0,55
6,56
Significant
H4
SQàRI
0,19
2,00
Significant
H5
BIàRI
0,20
2,23
Significant
Source: Data processed by the author (2021)
Table 14. Mediation Hypothesis Testing
Source: Data processed by the author (2021
Test for Direct and Indirect Effects
Hypothesis
Path
Indirect
Effect
t
values
Interpretation
H6
SQàBTàRI
0,23
3,72
Significant
H7
BIàBTàRI
0,22
3,61
Significant
356 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
Table 12 above shows the direct and
indirect influence on the independent
variable to the dependent variable. It can
see that the direct result of variable service
quality (X1) on brand trust (Y) is 0.43, and
the direct influence of variable brand image
(X2) on brand trust (Y) is 0.41. The direct
effect of brand trust (Y) on repurchase
intention (Z) is 0.55. The immediate impact
of the service quality variable (X1) on
repurchase intention (Z) is 0.19, and the
indirect impact is 0.23. This also occurs in
the brand image variable (X2) on
repurchase intention (Z) with a direct effect
of 0.20 and an indirect effect of 0.22. This is
because, in this research model, the
variable brand trust (Y) acts as an
intervention between service quality (X1)
and brand image (X2) on repurchase
intention (Z).
Hypothesis testing
According to the structural equation
model results performed in Table 13 and
Table 14 above, seven hypotheses have
been tested. In figure 7, table 13, and table
14, If the t value of the structural equation
result is> 1.96, there are significant effects
between the variables, and the hypothesis
is acceptable, and vice versa. If the t value
<1.96, the products between the variables
are not significant or unacceptable. Where
all relationships are declared to have a
substantial effect because they have an at-
value > 1.96, hypothesis testing was done
by looking at the path coefficient value in
the structural equation model in Figure 7
above.
Based on table 13 and table 14, it can
see that the results of hypothesis testing
are as follows:
1. Service quality variable (X1) on brand
trust (Y) has a path coefficient value of
0.43 and an at-value of 4.38 > 1.96. The
first hypothesis, which states that service
quality (X1) significantly affects brand
trust (Y) in the e-wallet application, has
substantial results. H1 can be accepted.
These results are consistent with
previous research conducted by Sultan
& Wong (2019), that service quality has
a positive and significant impact on
brand trust. Several previous studies
also support this, such as research
conducted by Najib & Sosianika, (2019)
and Al-dweeri et al., (2017).
2. Brand image variable (X2) on brand trust
(Y) has a path coefficient value of 0.41
and an at-value of 4.21 > 1.96. These
results are consistent with previous
studies conducted by Han et al. (2019),
which pointed out that the brand image
significantly impacts Korean Airlines’
brand trust. The second hypothesis,
which states that brand image (X2)
substantially affects brand trust (Y) in the
e-wallet application, has substantial
results. H2 can be accepted. Several
previous studies also support this, such
as the study conducted by Kim et al.,
(2003) and Benhardy et al. (2020).
3. The brand trust variable (Y) on
repurchase intention (Z) has a path
coefficient value of 0.55 and an at-value
of 6.56 > 1.96. So the third hypothesis,
which states that brand trust (Y) has a
significant effect on repurchase
intention (Z) on e-wallet applications,
has substantial results so that H3 can be
accepted. This research is supported by
Dwi Asri Ningrum, Mohamad Rizan, Agung Kresnamurti Rivai P | 357
the results found in the Horng, (2020)
study, which states that brand trust in
products will significantly affect
repurchase intention for products
traded on any website. In addition, the
findings of Han et al. (2019) also found
relationships and similar results,
indicating that trust in the company's
brand has a positive impact on the
company's product or service
repurchase intentions.
4. The service quality variable (X1) on
repurchase intention (Z) has a path
coefficient value of 0.19 and an at-value
of 2.00 > 1.96. The fourth hypothesis,
which states that service quality (X1) has
a significant effect on repurchase
intention (Z) on e-wallet applications,
has substantial results, H4 can be
accepted. These results prove similar
results to previous studies by Lasmy et
al. (2019), stating that service quality
substantially impacts the repurchase
intention of Grab and GoJek as online
transportation. Several previous studies
also support this, such as the study
conducted by Chang et al. (2020) and
Saleem et al. (2017)
5. The brand image variable (X2) on
repurchase intention (Z) has a path
coefficient value of 0.20 and an at-value
of 2.23 > 1.96. So that the fifth
hypothesis, namely brand image (X2),
has a significant effect on repurchase
intention (Z) in e-wallet applications so
that H5 can be accepted. The results
found in this research are consistent
with the study conducted by Saleem et
al. (2017), who pointed out that brand
image results are directly and
significantly related to the repurchase
intention of the Pakistan Airlines
industry. Several previous studies also
support this, such as the study
conducted by Kotler et al. (2012).
6. The service quality variable (X1) is
thought to affect repurchase intention
(Z) through brand trust (Y). This model
has an indirect effects value of 0.23 and
an at-value of 3.72 > 1.96. So the sixth
hypothesis, which states that service
quality (X1) has a significant effect on
repurchase intention (Z) through brand
trust (Y) as an intervening in e-wallet
applications, has substantial results so
that H6 can be accepted. This is
supported by research by Ahmad &
Zhang (2020), which states that brand
trust significantly moderates the
relationship between service quality
with repurchase intention. The research
results of Qi & Yao, (2020) also found
the intermediary relationship between
brand trust in multi-channel integration
service quality and repurchase intention
and similar effects.
7. The brand image variable (X2) is thought
to affect repurchase intention (Z)
through brand trust (Y). This model has
an indirect effects value of 0.22 and an
at-value of 3.61 > 1.96. So the seventh
hypothesis, which states that brand
image (X2) has a significant effect on
repurchase intention (Z) through brand
trust (Y) as an intervening in e-wallet
applications, has substantial results so
that H7 can be accepted. The research
results in this study are consistent with
previous studies by Benhardy et al.
(2020), which showed that brand trust
actively regulates the relationship
between brand image and repurchase
358 | The Effect of Service Quality and Brand Image on Repurchase Intention With Brand Trust
as Mediating Variable by The Generation Z of E-Wallet Consumers in Jakarta
intention.
CONCLUSION
In this research, the conclusion is an
influence between service quality (X1) and
brand image (X2) on repurchase intention
(Z) through brand trust (Y1) as an
intervening variable on generation Z e-
wallet consumers in Jakarta. This study
used 300 samples and produced seven
hypotheses. There are several academic
suggestions, namely that further research
can use other variables in the use of e-
wallet applications, further analysis can be
deepened and expanded by changing the
object of study, adding samples, changing
the characteristics of respondents with the
aim of further research to obtain more
diverse data and add the latest research
references. There are several management
suggestions, namely that companies can
maintain admin fees on e-wallet
applications which are cheaper than other
digital payment applications, e-wallet
companies can maintain and even increase
the good and credible reputation that
already exists in consumer perception, the
absence of problems or obstacles when it
must support consumers using e-wallet
applications, prevented so that in the future
there will not be any problems, or make
solutions if there are problems that occur
consumers so that consumer confidence in
e-wallet applications can be maintained by
e-wallet companies, customer satisfaction
and pleasure It must be noted, customer
expectations must be comparable and even
exceed the services provided to increase
repurchase intention.
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