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THE RELATIONSHIP BETWEEN BANKING SERVICE QUALITY AND
CUSTOMER SATISFACTION IN COMMERCIAL BANKS IN THUA THIEN
HUE PROVINCE VIET NAM: THE TEST ON STRUCTURAL EQUATION
MODELING (SEM)
Duong Ba Vu Thi, Phu Xuan University, Viet Nam
Email: [email protected]
Tran Bao An, Phu Xuan University, Viet Nam
Email: [email protected]
Tran Duc Tri, College of Economics Hue University, Viet Nam
Email: [email protected]
Huynh Anh Thuan, College of Economics Hue University, Viet
Nam
Email: [email protected]
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THE RELATIONSHIP BETWEEN BANKING SERVICE QUALITY AND
CUSTOMER SATISFACTION IN COMMERCIAL BANKS IN THUA THIEN
HUE PROVINCE VIET NAM: THE TEST ON STRUCTURAL EQUATION
MODELING (SEM)
ABSTRACT
This study aims to identify the relationship between service
quality and customer satisfaction in commercial banks in Thua Thien
Hue on the basis of a survey conducted from 439 customers. Adjusted
SERVPERF model; reliability Cronbachs Alpha analysis, exploratory
factor analysis (EFA), confirmatory factor analysis (CFA) and
structural equation modeling analysis (SEM) are the principal data
analysis methods in this study.
The research result has shown that the quality of banking
services is measured by six components which are shown in order of
importance to positive effect on customer satisfaction, including
Reliability about service delivery process (RELI), Assurance (ASS),
Tangibles (TAN), Reliability about promise to customer (RELII),
Empathy (EMP) and Responsiveness (RES).
Keywords: Thua Thien Hue; Relationship; Service quality;
Satisfaction. 1. Introduction In the current business environment
which is constantly changing and contains intense competition,
commercial banks are facing with many challenges. One of the
biggest challenges is competitiveness. When competitive pressures
increase, service quality is considered as a competitive factor of
the banks and it is also considered as an essential key to create
the difference among banks (Kazi Omar, 2011). So, delivering
service quality system accordant with customer demand is considered
as one of the crucial ways that could create competitiveness and
sustainable competitive advantages for banks. To assess the
suitability of banking service quality to the customers needs,
customer satisfaction on service quality is an important measure.
And satisfying customers has become an important asset for the
banks in an effort to improve service quality, which will enhance
the banks competitiveness [8], [12]. So far, there are many studies
about the relationship between banking service quality and customer
satisfaction in the world such as Levesque study, McDougall (1996);
Almad Jamal, Kamal Naser (2002) and Addo Kwarteng (2012). In
Vietnam, Dinh Phi Ho (2009, 2012); Gioi & Huy (2012) have
studies in a number of local banks (Ho Chi Minh City, Da Nang).
These studies have mentioned and clarified this relationship in
different banks. Although these studies have a number of different
points (components affecting quality of banking services and the
relationship between these components and customer satisfaction)
due to different characteristics of customer behavior in each
locality, research locations, but in general, these studies showed
significant relationship between service quality and customer
satisfaction in the bank.
Reality shows that this significant research issue is quite
limited in Thua Thien Hue. Therefore, the study of the relationship
between service quality and customer satisfaction in the banking
sector is very essential.
This article will focus on identifying the components of the
banking service quality and the extent of its impact on customer
satisfaction through the case studies in commercial banks in Thua
Thien Hue. 2. Literature review and research model
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2.1 Service quality The conceptualization and measurement of
service quality is one of the most
debated topics in service marketing literature (Brady and
Cronin, 2001). There are many of different definitions about
service quality. Here, some important definitions of service
quality are coming as following:
Service quality is determined by the differences between
customers expectations of services providers performance and their
evaluation of the services they received (Parasuraman et al., 1985,
1988). Service quality is the consumer's judgment about an entity's
overall excellence or superiority; it is a form of attitude, and
results from a comparison of expectations to perceptions of
performance received (Zeithaml, 1987). Or service quality can be
defined as the difference between customers expectations for
service performance prior to the service encounter and their
perceptions of the service received (Asubonteng et al., 1996).
Generally, the authors described service quality as a form of
attitude that results from the comparison of consumer expectations
with service performance delivered.
As we have known, service is intangible, heterogenic, and
inseparable, which makes service quality difficult to measure and
understand (Parasuraman et al., 1985).
Many researchers tried to define and measure service quality for
a long time. The result is there are many instruments to measure.
Among instruments, the most popular model used for evaluation of
service quality is SERVQUAL, a well-known scale developed by
Parasuraman et al. (1985, 1988).
Parasuraman et al. (1988) developed and tested the five
components scale of the service quality, called SERVQUAL scale,
consisting of 22 variables to measure five components of service
quality, which are: reliability, responsiveness, assurance, empathy
and tangibles.
The measurement model that Parasuraman et al. (1988) suggested
still has controversy by many scholars around the world. In the
framework of this debate, Cronin and Taylor (1992) stated that
service quality can be generalized to a similar viewpoint,
attitude. They announced a model that only mentions the performance
instead of performance minus expectation" (SERVQUAL) to measure
service quality. This model is called SERVPERF (Service
performance).
When using the SERVQUAL model, respondents expressed confusion
when answering questions twice on the expected and perceived
versions (Bouman & Van der Wiele, 1992). In addition to the
long questionnaire, the expectation concept is also vague for the
respondents (Phong & Thuy, 2007). Therefore, using SERVPERF
model will get better result than SERVQUAL. SERVPERF model
questionnaire is also brief more than half compared to SERVQUALs,
which will enhance willingness for answering questionnaires from
respondents.
Therefore, our research approaches how to assess the service
quality by performance (SERVPERF scale) by Cronin and Taylor
(1992). 2.2 Customer satisfaction
Customer satisfaction is considered as the foundation of the
marketing concept on satisfying needs and wants of consumers
(Spreng, MacKenzie, & Olshavsky, 1996). There are many
definitions of customer satisfaction. For example:
Customer satisfaction is defined as an "evaluation of the
perceived discrepancy between prior expectations and the actual
performance of the product" (Tse and Wilton, 1988).
Satisfaction is the reaction of the customer when meeting the
want (Oliver, 1997)
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Customer satisfaction is the degree of a person's state of
feeling derived from comparison of results obtained from consuming
products/services with his expectation. Satisfaction level depends
on the difference between getting results and expectations, if
actual results are lower than expected, the customer is not
satisfied, if the actual results match the expectations, the
customer will be satisfied , if actual results are higher than
expected, the customer is very satisfied (Kotler, 2002).
Thus, satisfaction is a function of the difference between
getting results and expectations (Kotler, 2003). 2.3. The
relationship between service quality and customer satisfaction
The relationship between service quality and customer
satisfaction is the topic has been discussed consecutively in the
last decades. Many studies have attempted to establish the essence
of the relationship between service quality and customer
satisfaction (Jamal & Naser, 2002). Among them, a number of
studies have shown a causal linkage between satisfaction and
service quality (Jamal & Naser, 2002).
Many studies on customer satisfaction in the service sector have
been made (Fornell, 1992) and have generally concluded that service
quality and satisfaction are two distinct concepts (Bitner, 1990;
Boulding et al, 1993).
Service quality and satisfaction are two different concepts but
are closely related to each other in studying about service
(Parasuraman et al, 1988). According to some previous studies in
other countries around the world and in Vietnam, the relationship
between these two concepts has been clarified from the supermarket
industry (Dabholkar, 1996; Tho & Trang, 2006; Phong & Thuy,
2007), Hotel (Mahdavinia, 2007; Giao & Hao, 2011; Huy &
Quang, 2012) to the banking sector (Levesque & McDougall, 1996;
Almad Jamal & Kamal Naser, 2002; Najjar & Bishu, 2006;
Dhandabani, 2010; Siddiqi, 2011; Addo &Kwarteng, 2012; Dinh Phi
Ho, 2009, 2012; Giao, 2010, 2011; Gioi & Huy, 2012). In
summary, these studies have shown the existence of a positive
relationship between components of service quality and customer
satisfaction with different levels depending on each service
sectors characteristics. Therefore, it can be confirmed that the
quality of service is the cause of customer satisfaction. The
reason is that quality is related to service delivery, and
satisfaction can be only assessed after using the service. If
quality is improved, but not based on the needs of the customer,
the customer will never be satisfied with the service. Hence, when
using services, if customers feel high-quality services, they will
be satisfied with the service. Conversely, if customers feel
low-quality services, dissatisfaction will appear.
On the basis of theoretical research on criteria of evaluating
the service quality and the relationship between service quality
and customer satisfaction above, along with the characteristics of
the banking sector, the proposed research model is shown in Figure
1.
Customer satisfaction
(GSAT)
Reliability (REL)
Responsiveness (RES)
Assurance (ASS)
Empathy (EMP)
Tangibles (TAN)
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Figure 1: The proposed research model
In which: Reliability (REL): The ability to perform the promised
service dependably and
accurately. Responsiveness (RES): The willingness to help
customers and provide prompt
service. Assurance (ASS): The knowledge and courtesy of
employees and their ability
to convey trust and confidence. Empathy (EMP): The provision of
caring, individualized attention to
customers. Tangibles (TAN): The appearance of physical
facilities, equipment, personnel,
and communication materials. 3. Research methodology To achieve
the research objectives, the study was carried out with process
consists of two steps: (1) pilot study, and (2) main study. 3.1.
Pilot study
* Secondary data: the researchers gathered information from
books, newspapers, textbooks, internet, specialized scientific
journals related to service quality and customer satisfaction.
* Qualitative pilot study: Qualitative pilot study was conducted
through discussions with experts and customers. First, discussions
with experts was conducted through in-depth interviews with senior
managers of commercial banks in Hue. This was followed by group
discussions with 20 customers regularly using banking services. The
main purpose of this study step is to explore, adjust or edit the
banking service quality and customer satisfaction scales.
Based on the theoretical basis from secondary materials combined
with discussions with experts and customers, the designed
questionaire consists of 02 parts, part I: information about
answered subjects, part II: measurement of banking service quality
and customer satisfaction. This section is designed to include 29
observed variables. In particular, the first 26 observed variables
used to measure service quality according to Servperf model, 03
next observed variables used to measure customer satisfaction1.
Each observed variable is measured based on the 5-point Likert
scales, from completely disagree (strongly disagree) to completely
agree (strongly agree).
* Quantitative pilot study: Quantitative pilot study was
conducted through pre-interview with customers to complete
questionnaires for the survey process. 3.2. Main study
Main study was carried out by quantitative research methods. To
perform the study, we conducted a sample survey through direct
interviews customers of commercial banks with questionaires to
collect data.
Because the data analysis methods used in this study based on
analysis of linear structural model SEM, to achieve reliable
estimates for this method, sample
1 Based on the study of Lassar et al. (2000), the scale of
customer satisfaction includes 03 observed variables: Satisfied
with the quality of banking services (SAT1), About the bank's
services to others (SAT2), Continue to use the bank's services in
the future (SAT3).
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size is often large (n> 200: Hoelter, 1983). On the other
hand, based on the experience rule (Bollen, 1989), it requires at
least 5 samples for a estimated parameter. Hence, following the
above, based on the number of parameters to be estimated, the
sample size targetted in this study was more than 400.
Sample was selected by convenience sampling method of size n =
500. Thus, 500 questionnaires were given out, 456 collected,
reaches 91.2%. In 456 collected questionnaires, there was 17
questionnaires did not meet requirements due to missing information
were rejected. Finally, 439 questionnaires were used in the
analysis.
Data collected from 439 questionnaires corresponding to 439
surveyed customers were entered and processed on SPSS, AMOS
software with using analytical techniques such as: descriptive
statistics, testing the reliability of a scale by Cronbach's
coefficient alpha, explore factor analysis (EFA), confirmatory
factor analysis, structural equation modeling analysis. 4. Results
and discussions 4.1. Sample description
Table 1: Descriptive statistics of the respondent profile Items
Frequency %
Sex Male 249 56.8 Female 190 43.2
Age From 18 to 35 223 50.8 36 - 55 141 32.1 Above 55 75 17.1
Income Under 5 million/month 241 55.0 From 5 10 million/month
144 32.8 Above 10 million/month 54 12.2
Occupation
White-collar employee 151 34.5 Businessman 131 29.7 Retired 52
11.8 Student 80 18.3 Others 25 5.7
Bank
Agribank 51 11.6 BIDV 50 11.4 Vietcombank 52 11.8 Vietinbank 53
12.1 Sacombank 48 10.9 MB 49 11.2 ACB 45 10.3 EAB 47 10.7 Eximbank
44 10.0
Source: Interview data analysis by SPSS Regarding gender, 190
female customers accounted for 43.2% of the sample
size and 249 male clients, accounting for 56.8% of the sample
size. Regarding age group, surveyed customers are mainly in the age
from 18 to 35
years, accounting for 50.8%. Next are the age of 36 - 55 years
and the age of 55 years at the rate of 32.1% and 17.1%
respectively.
Regarding income, it is primarily focused on customers whose
income below 5 million/month and 5-10 million/month, accounting for
87.8% of the sample size. Customers whose income above 10
million/month have relatively low numbers, only 12.2% of the sample
size.
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Regarding career, surveyed customers are mainly white-collar
employee and businessman accounting for 64.2% of the sample size;
followed by students accounting for 18.3%, 11.8% of retirement; the
remaining is the other labor.
Regarding bank of transaction, proportion of bank customers
surveyed in the sample is distributed fairly equally ranging from
10 to 12.1%. 4.2. Reliability analysis
Table 2 shows the Cronbach's Alpha coefficients of all scales
are larger than 0.6 and the totals correlation coefficient of
corrected items are greater than 0.3.
According to Nunnally and Burnstein (1994), selection criteria
of Cronbach's Alpha is higher than 0.6 and the total correlation
coefficient is higher than 0.3. Therefore, this result can conclude
that all scales achieved reliability and used for subsequent
analysis of EFA. Table 2: Cronbachs Alpha testing result of service
quality and satisfaction scales
No. Scale Number of observed variables
Cronbachs Alpha
Minimum total correlation
coefficient 1 Reliability (REL) 8 0.761 0.391 2 Empathy (EMP) 4
0.840 0.535 3 Responsiveness (RES) 5 0.888 0.674 4 Assurance (ASS)
5 0.936 0.799 5 Tangibles (TAN) 4 0.954 0.776 6 Satisfaction (GSAT)
3 0.741 0.492
Source: Interview data analysis by SPSS 4.3. Exploratory Factor
Analysis (EFA)
To use factor analysis techniques, we must consider the
appropriateness of factor analysis. Keiser-Meyer-Olkin (KMO)
measure of sampling adequacy and Bartlett's Test of Sphericity are
the indexes used to consider that appropriateness. If KMO index is
in the range from 0.5 to 1 and the Bartlett test has the value Sig.
< 2, the factor analysis is considered appropriate [20]. KMO
test results and Bartlett's Test for the scale of quality banking
services show that the database is fully suitable for factor
analysis because the KMO index reaches 0.843 and Bartletts test has
statistical significance (Sig. = 0.000 1, variance extracted is
50.311%; all itemfactor loadings are simultaneously above 0.5.
Table 3: EFA results on banking service quality components
Item Factor
2 In this study, the authors choose = 0,05
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1 2 3 4 5 6
ASS1 0.898
ASS3 0.885
ASS5 0.876
ASS4 0.837
ASS2 0.765
TAN4 0.980
TAN1 0.977
TAN3 0.927
TAN2 0.788
REL5 0.975
REL4 0.952
REL3 0.812
REL1 0.735
REL2 0.560
RES5 0.906
RES4 0.878
RES2 0.775
RES3 0.685
RES1 0.639
EMP3 0.983
EMP4 0.961
EMP2 0.541
EMP1 0.505
REL7 0.940
REL6 0.940
REL8 0.926
Cronbachs Alpha 0.936 0.954 0.902 0.888 0.840 0.960
Eigenvalue 7.536 4.026 3.250 2.189 1.943 1.360
Variance explained (%) 28.020 14.752 11.698 7.582 6.391
4.495
Cumulative (%) 28.020 42.772 54.470 62.052 68.444 72.939
Source: Interview data analysis by SPSS
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Table 4: EFA result on satisfaction components
Item Loading factors
SAT2: Introduce banks services to other people 0.819
SAT1: Satisfied with banking service quality 0.717
SAT3: Continue using services of this bank in the next time
0.570
Cronbach's Alpha 0.741
Eigenvalue 1.979
Variance extracted (%) 50.311
Source: Interview data analysis by SPSS
After testing the scale by Cronbach's alpha coefficient and EFA,
we have the modified model shown in Figure 2.
Figure 2: Modified research model
4.4. Confirmatory Factor Analysis (CFA) In the CFA analysis, we
can carry out for each concept, several concepts, or all
concepts included in the model (called the critical model).
Here, the concepts are level one concept so CFA analysis should be
done for all concepts in the model.
Confirmatory Factor Analysis CFA was conducted with 29 observed
variables. From the analysis, 6 EFA factors are extracted to
service quality scale and 1 factor is extracted to the satisfaction
scale. These factors create corresponding scale groups forming
concept measurement models and taken into CFA analysis to consider
the appropriateness of the model to market data.
To assess the scale by Confirmatory Factor Analysis
(Confirmatory Factor Analysis - CFA), the research group used Chi -
square criteria adjusted by degrees of freedom (Cmin / df), the
Comparative fit index (CFI), the Tucker and Lewis index (TLI) and
the Root Mean Square Error approximation (RMSEA).
If a model has TLI, CFI 0.9 (Bentler & Bonett, 1980), CMIIN
/ df 3 (Carmines & McIver, 1981), RMSEA 0.08 (Steiger, 1990),
the model is considered to be consistent with market data.
Customer satisfaction
(GSAT)
Assurance (ASS)
Reliability about service delivery process (RELI)
Responsiveness (RES)
Tangibles (TAN)
Empathy (EMP)
Reliability about promise to customer (RELII)
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Five scale evaluation criteria include: (1) Composite
Reliability, (2) Variance Extracted, (3) Unidimensionality, (4)
Convergent Validity and (5) Discriminant Validity (Hair et al,
2009).
CFA result of the banking service quality scale model shows that
the model has 355 degrees of freedom; Cmin / df = 2.858, TLI =
0.940, CFI = 0.948 and RMSEA = 0.065 should be confirmed the model
fits the market data.
The scale evaluation criteria are shown as follows: (1)
Composite Reliability, (2) Variance Extracted: The integrated
reliability of the component (concept) Assurance (ASS) is 0.938
with total variance extracted is 75%; of the component (concept)
Reliability about service delivery process (RELI) is 0.904 with
total variance extracted is 66.3%; of the component (concept)
Responsiveness (RES) is 0.875 with variance extracted is 59.5%; of
the component (concept) Tangibles is 0955 with variance extracted
is 84.2%; of the component (concept) Empathy is 0.844 with variance
extracted is 60.4%; of the component (concept)
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Reliability about promise to customer (RELII) is 0.960 with
variance extracted is 88.9% and the component (concept) Customer
Satisfaction is 0.749 with variance extracted is 50.3%. All
coefficients are greater than 0.5 and 50%, satisfy the conditions
of integrated reliability and total variance extracted (Fornell
& Larcker, 1981 Hair, 1998). (2) Unidimensionality: Figure 1
shows that only component (concept) Empathy (EMP) do not reach
unidimensionality because relationship between errors exists (e22
and e23), and other components (concepts) reach unidimensionality.
(3) Convergent Validity: Gerbring & Anderson (1988) argues that
scale achieves convergent values when weight of standardized scales
are high (>0.5) and statistically
significant (p0.5) and statistically significant with all
p-values are equal to 0.000. Therefore, we conclude the observed
variables used to measure 6 components of the service quality scale
and 1 component of satisfaction scale achieves convergent value.
(4) (Discriminant Validity): We found that the correlation
coefficients between component concepts are less than 1
(statistically significant), so all concepts of component achieve
discriminant validity.
Table 5: Test results of correlation coefficients between
concepts (components)
Relationship R SE CR Sig.
ASS REL-II 0.548 0.040014185 11.29599412 0.000
ASS EMP 0.275 0.045992115 15.76357181 0.000
ASS TAN -0.034 0.04780883 21.62780397 0.000
ASS RES 0.463 0.042400267 12.6650147 0.000
ASS REL-I -0.14 0.04736537 24.068217 0.000
REL-I REL-II -0.06 0.047750304 22.19881155 0.000
REL-I EMP -0.01 0.047834095 21.11464617 0.000
REL-I TAN -0.082 0.04767539 22.69514743 0.000
RES TAN 0.148 0.047309681 18.00899891 0.000
RES EMP 0.3 0.045633101 15.33974225 0.000
RES REL-II 0.502 0.041372229 12.03705995 0.000
REL-I RES -0.102 0.047586991 23.1575893 0.000
TAN EMP -0.093 0.047629169 22.94812231 0.000
EMP REL-II 0.23 0.046554021 16.5399246 0.000
TAN REL-II -0.098 0.047606222 23.06421192 0.000
ASS GSAT 0.77 0.030521778 7.535602878 0.000
REL-I GSAT 0.204 0.046830528 16.99745926 0.000
RES GSAT 0.569 0.039337738 10.95640006 0.000
TAN GSAT 0.158 0.047235619 17.82553136 0.000
EMP GSAT 0.343 0.044934506 14.6212801 0.000
REL-II GSAT 0.649 0.036393445 9.64459397 0.000
Source: Interview data analysis by AMOS
4.5. Testing the relationship between service quality and
customer satisfaction by structural equation modeling (SEM)
After CFA analyzing, structural equation modeling SEM was used
to determine the relationship between the banking services quality
and customer
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satisfaction. SEM analysis was conducted from the adjusted
research model (Fig. 2). SEM result shows TLI index = 0939 (>
0.9), CFI = 0.946 (> 0.9), Cmin / df = 2.913 (
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4.5. Discussions This study explored and determined the
relationship between 06 components
of quality banking services for customer satisfaction. In
addition, this article also identified the extent of the impact of
each component to customer satisfaction, while previous studies
only identified 02, 04, 05 components of quality service affect
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customer satisfaction (eg, Dinh Phi Ho, 2009, 2012; About &
Huy, 2012; Zaim et al, 2010; Mengi, 2009; Kumar et al, 2010; Lai,
2004, Baumann, 2007; Ahmed et al, 2010). In these components which
can affect to customer satisfaction, the factor Reliability about
service delivery process (RELI) has the strongest effect. This is
consistent with some previous studies (eg, Arasli, 2005; Najjar
& Bishu, 2006; Jamal & Naser, 2002).
Currently, customers become busier and their time budget should
be distributed to more work so they esteem their time. Therefore,
when doing anything, they wish to be precise to help them limit
waste of valuable time due to doing improperly. During bank
transaction, customers often require theirs to be done correctly,
accordantly to help them avoid wasting time due to repeating
transactions when wrong.
Therefore, the study results show the fact that Reliability
about service delivery process (RELI) impacts (influences) the most
to customer satisfaction is a perfect fit. And, in order to improve
customer satisfaction, thereby contributing to maintain
relationships with customers, banks need to have oriented solutions
from identified components through research results, especially
Reliability about service delivery process (RELI). 5. Conclusion
and future research suggestions
Research results have shown that customer satisfaction in the
case of commercial banks in Thua Thien Hue affected by service
quality components in order of importance, they are: Reliability
about service delivery process (RELI), Assurance (ASS), Tangibles
(TAN), Reliability about promise to customer (RELII), Empathy (EMP)
and Responsiveness (RES). In particular, Reliability about service
delivery process (RELI) is the strongest component affects customer
satisfaction. On the other hand, the results obtained from the
analysis of structural equation modeling, it was found that 06
components of quality banking services explain only 61.3% of
customer satisfaction; the remaining 38.7% is due to impact from
other components.
Hence, in order to improve customer satisfaction, the commercial
banks in Thua Thien Hue needs to focus on improving the banking
service quality component, including components Reliability about
service delivery process (RELI), Assurance (ASS), Tangibles (TAN),
Reliability about promise to customer (RELII), Empathy (EMP) and
Responsiveness (RES).
In addition to the contributions, this study still has some
limitations so that suggestions for future research are as
follows:
First, this study only surveyed customers of 09 commercial
banks, so it still limits the generalizability of the research
issues. Thus, further studies need to expand the scope in other
banks in Thua Thien Hue province to explore; and analyze the
relationship between service quality and customer satisfaction in
banking sector.
Second, this study only discovered the relationship between the
components of service quality with customer satisfaction but it has
not evaluated specific components of service quality and customer
satisfaction. Therefore, further research is necessary to evaluate
in more detail on this issue.
Third, this study has not mentioned the component prices
(interest rate, service charges) to the customer satisfaction.
Meanwhile, the service price can be very influential on
satisfaction perception and value (Zeithaml and Bitner, 2000).
According to Levesque and McDougall (1996) competitive interest
rate is one of the important determinants of customer satisfaction
in banking sector. Besides, this study has not tested the
relationship between satisfaction to customer loyalty while between
satisfaction and customer loyalty have positive relationships with
each other (Donio et
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al., 2006; Story and Hess, 2006; Cheng et al., 2008). Therefore,
further research needs to add component prices to factors affecting
customer satisfaction as well as it must to test the relationship
between satisfaction and customer loyalty to conduct research.
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