The Relationship between Service Quality and Customer Satisfaction – a Case of a Commercial Bank in Vietnam

Bạn đang xem bản rút gọn của tài liệu. Xem và tải ngay bản đầy đủ của tài liệu tại đây (277.2 KB, 13 trang )

(1)<div class='page_container' data-page=1>

*University of Economics and Business, Faculty of Business Administration, Thi Lien Pham: Tel:
0983820460. Email:

** University of Economics and Business, Faculty of Business Administration, Hue Minh Nguyen: Tel:
01689931018. Email:

■2012 JSPS Asian CORE Program, Nagoya University and VNU University of Economics and Business

The Relationship between Service Quality and Customer Satisfaction

– a Case of a Commercial Bank in Vietnam

University of Economics and Business, Faculty of Business Administration, Thi Lien Pham *
University of Economics and Business, Center for Business Administration Studies Hue Minh Nguyen**

Abstract :

Service quality and its relationship with customer satisfaction have received considerable academic and businesses
attention in recent years. But the nature of the exact association between these two constructs is not well-explained in the
literature. This study used SERVPERF model as proposed by Cronin & Taylor (1992) to assess perceived service quality
at a Vietnamese commercial bank, and then study the relationship between service quality and customer satisfaction on
banking service’s quality. The results of a survey are used in this paper. Based on 123 valid responses from customers, the
study indentified three components – RELI-ASS (reliability combined with assurance), RESPONSIVENESS, and
EMPATHY – which explain customers’ perceived service quality at the bank. The relationship between these service
quality components and customer satisfaction is also investigated through regression analysis. It is found that these three
components of service quality have positive relationship with customer satisfaction in which RESPONSIVENESS has
the most significant impact on customer satisfaction level. In addition, based on these findings, the study also gives some
suggestions for banks to further improve service quality and customer satisfaction level.

Keywords : Service quality, customer satisfaction, SEVPERF model

1. Introduction

In recent years, Vietnam’s economy has been taking
ongoing efforts to integrate into the international
economy. The opening economy is requiring more and
more trading transactions which all relate to monetary
field. With the role of stabilizing financial market that
will facilitate the rapid growth of domestic trades and
international trades, banks in Vietnam have to cope
with many challenges, especially the increasingly
intensive competition. They have to compete to each
other not only in market share but also in the ability to

comply with international standards of banking
services.

</div>
(2)<div class='page_container' data-page=2>

profitability. From these facts, assessing the quality of
banking services, researching relationship between
service quality and customer satisfaction on banking
service’s quality are necessary to develop banking
services in the future.

This study examines banking services at Military Bank,
uses SERVPERF model (Cronin and Taylor, 1992) to
research the relationship between service quality and
customer satisfaction on banking service’s quality. The
research uses quantitative method and the strategy of
inquiry is survey. It was carried out at Transaction
center of Military Bank, No.3 Lieu Giai, Hanoi. Data
collected from this survey was analyzed by SPSS16.0
in order to find out the relationship between customers’

assessment about Military Bank’s service quality and
their satisfaction level.

This paper is divided into 7 main parts. Besides this
introduction part, Section 2 provides literature review
for the study. Research methodology is given in
Section 3. Section 4 presents research analysis and
results which is followed by findings and discussion
part in Section 5. After giving limitations of the study
and suggestions for further research in Section 6, the
paper provides a conclusion part in Section 7.

2. Literature review and conceptual 
framework

2.1. Service quality and customer satisfaction

2.1.1. Service quality

Services are one of the two key components of 
economics - the other being goods - and they are
consumed at the point of sale. Philip Kotler defined a
service is a product that consists of any activity, benefit
or satisfaction that one party can offer to another for
sale. Services are essentially intangible and do not
result in the ownership of anything (Kotler et al., 
2005).

The American Society for Quality gave the definition
of quality as “the totality of features and characteristics

of a product or service that bears on its ability to satisfy
stated or implied needs” (Jay et al., 2009, pp.156).

Service quality was defined by Kotler et al., 2005 as 
the ability of a service to perform its functions
including the overall durability, reliability, precision,
ease of operation and repair, and other valued
attributes.

Banking service is somehow special because it operates 
in a field of monetary trading in which money is
material, and sources of capital come from outside. In
this study, banking service quality is defined as the 
ability to satisfy the customer’s requirements and needs.
This ability includes everything that customers think
they will be received from those services like accurate
process, affordable price, on-time delivery, attitude of
staffs, etc.

Measuring quality in service sector is more difficult 
than measuring quality of manufactured sector because
quality evaluations are not made solely on the outcome
of a service; they also involve evaluations of the
process of service delivery. One of many service
quality research models on the world nowadays is
SERVPERF scale proposed by Cronin and Taylor
(1992). This scale based on SERVQUAL scale
(Parasuraman et al., 1985, 1988) which assess service 
quality through the gaps between customer
“expectations” - (E) and “perceptions” - (P). However,

SERVQUAL has been criticized on its confusion, and
SERVPERF was proposed by Cronin and Taylor
(1992) in which “expectation” - (E) component of
SERVQUAL be discarded and instead “performance” -
(P) component alone be used. Cronin and Taylor
provided empirical evidence across four industries
namely banks, pest control, dry cleaning, and fast food
to corroborate the superiority of their “performance –
only” instrument (Sanjay K Jain and Garima Gupta,
2004). The scale measure performance of five service
quality components termed Tangible, Reliability,
Responsiveness, Assurance, and Empathy
(Parasuraman et al., 1988):

</div>
(3)<div class='page_container' data-page=3>

equipments, personnel, etc.

- Reliability involves the ability to perform the
promised service dependably and accurately.

- Responsiveness concerns the willingness or
readiness of employees to help customers and provide
services.

- Assurance refers to knowledge and courtesy of
employees and their ability to convey trust and
confidence.

- Empathy is individualized cares and attentions
that the firm provides to its customers.

2.1.2. Customer satisfaction

The definition of customer satisfaction has been widely
debated as organizations increasingly attempt to
measure it. Customer satisfaction can be experienced
in a variety of situations and connected to both goods
and services. It is highly personal assessment that is
greatly affected by customer expectations (Center for
the study of social policy, 2007).

Philip Kotler defined customer satisfaction is the extent 
to which a product’s perceived performance matches a
buyer’s expectations. If the product performance falls
short of expectations, the buyer is dissatisfied. If
performance matches or exceeds expectations, the
buyer is satisfied or delighted (Kotler et al., 2005). 
Customer satisfaction is an important theoretical as
well as practical issue for the marketers and consumer
researchers. Customer satisfaction can be considered as
the essence of success in today’s highly competitive
world of business (Vanniarajan, T., Anbazhagan, B.,
2007).

2.1.3. Relationship between service quality and 
customer satisfaction

Parasuraman stated that there is a distinction between
service quality and customer satisfaction: perceived
service quality is a global judgment or attitude relating
to the superiority of the service, whereas customer

satisfaction is related to a specific transaction
(Parasuraman et al., 1988).

However, many researchers have investigated the

</div>
(4)<div class='page_container' data-page=4>

that service quality and customer satisfaction have a
positive relationship in which service quality is an
antecedent as well as an important factor impacting on
customer satisfaction.

2.2. Research model and hypothesis

2.2.1. Research model

SERVPERF is one of popular models measuring
service quality in the world. It was used in research
such as “SERVPERF analysis in retail banking” by
Vanniarajan, T. and Anbazhagan, B., 2007;
“SERVPERF Analysis in Banking Services” by
M.Muzaffar Zahoor; “Measuring information science
system service quality with SERVQUAL: Users’
perceptions of relative importance of the five
SERVPERF dimensions” by Hollis Landrum et al.
(2009).

This study will use the SERVPERF scale to measure
perceived performance of banking service. Five
components of service quality are Tangible, Reliability,
Responsiveness, Assurance, and Empathy:

- Tangible: the appearance of bank’s staffs, physical
facilities at transaction centers, materials providing for
customers.

- Reliability: bank’s ability to perform services
accurately and on time right at the first time.

- Responsiveness: bank’s willingness to provide
services and help customers.

- Assurance: the trust in bank’s service, trust in
employees’ professional skills as well as serving
attitude.

- Empathy: bank’s attentions and cares to each
individual customer.

The SERVPERF score which represents the perceived
performance on components of service quality can be
expressed in the following equation (Sanjay K Jain and
Garima Gupta, 2004):

Where: SQ = perceived service quality of individual
“i”

k = Number of attributes/items

P = perception of individual “i” to performance of

service on item “j”

In addition, the research also analyzes the relationship
between service quality and customer satisfaction. This
relationship is modeled as following:

Figure 1: Research model

2.2.2. Hypotheses

There are several hypotheses for this research model as
following:

- H1: Tangible component and customer
satisfaction have a positive relationship. That means
the higher/lower customer evaluate tangible factor, the
higher/lower level of customer satisfaction.

- H2: Reliability component and customer
satisfaction have a positive relationship. That means
the higher/lower customer evaluate reliability factor,
the higher/lower level of customer satisfaction.

- H3: Responsiveness component and customer
satisfaction have a positive relationship. That means
the higher/lower customer evaluate responsiveness
factor, the higher/lower level of customer satisfaction.
- H4: Assurance component and customer
satisfaction have a positive relationship. That means
the higher/lower customer evaluate assurance factor,

the higher/lower level of customer satisfaction.

- H5: Empathy component and customer
satisfaction have a positive relationship. That means

B

a

n

k

in

g

s

er

v

ic

e

q

u

a

li

ty

Tangible

Reliability

Responsiveness

Customer

satisfaction

Assurance

Empathy

H3
H1

H1

</div>
(5)<div class='page_container' data-page=5>

the higher/lower customer evaluate empathy factor, the
higher/lower level of customer satisfaction.

3. Research methodology

After reviewing literature and building research model,
the research process follows these stages:

 Designing questionnaire

Questionnaire was designed in Vietnamese, and
divided into three main parts (Appendix):

- Part I asks participants about which services they
used in Military Bank.

- Part II is designed to collect assessments from
customers about perceived service quality of Military
Bank, and their satisfaction level.

- Part III includes questions about customers’ basic
information to classify participants.

Part II comprised 22 variables in total. Assessing
perceived service quality under SERVPERF model
includes 20 variables to measure 5 service quality
components – Tangible, Reliability, Responsiveness,
Assurance, and Empathy; the 2 remaining variables are
used to measure customer satisfaction. This
measurement bases on a 5-point rating scale which
corresponding to 1 = strongly disagree, 2 = somewhat
disagree, 3 = neither agree nor disagree, 4 = somewhat

agree, 5 = strongly agree.

 Sampling and collecting data

According to a staff in Transaction center, there are
about 100 customers coming to Transaction center
every week day. Most customers are young people
who come to open bank account or card. Many others
come to give savings or represent for their company to
make payment transactions.

This study has 22 variables in totals. According to Hair
et al., (1998), cited in Nguyen Thi Phuong Tram 
(2008), the sample size should be at least 5 responses
per 1 observed variable. In order to collect at least 5
responses per 1 observed variable, the study need to
collect at the minimum sample size of 110 responses.
To get this sample size, 150 questionnaires were given
to customers.

Method to collect data was conducting surveys with
customers who come to make transactions in
Transaction center of Military Bank – No.3, Lieu Giai,
Hanoi. Questionnaires were provided to customers
who have free time and be ready to answer survey
questions. It took each customer about 10 to 15
minutes to answer the questionnaire. Survey process
was carried out from April 5th 2012 to April 14th 2012.

 Analysing data

At first, data will be input and screened to identify
missing samples. After rejecting all invalid samples,
data will be encoded and analyzed in SPSS 16.0 as the
following:

a. Reliability analysis by Cronbach’s alpha 
Cronbach’s alpha is a common measure of internal
consistency (reliability) of a test or scale. Internal
consistency describes the extent to which all the items
in a test measure the same concept or construct and
hence it is connected to the inner-relatedness of the
items within the test (Tavakol et al., 2011).

The value of alpha (α) may be between negative
infinity and 1. However, only positive values of alpha
have meaning. In general, alpha coefficient ranges in
value from 0 to 1, and the increase of this value means
that the correlations between the items increase (Amit
Choudhury, 2010). In this study, scales which have
Cronbach’s alpha coefficient greater than or equal to
0.6 will be accepted.

Besides assessing the reliability of scales, Cronbach’s
alpha analysis also helps to check whether any item is
not consistence with the rest of the scale through
item-total correlations. Variables which have greater
than 0.3 item-total correlations will be accepted; the
others which have smaller than 0.3 item-total
correlations will be eliminated from analysis data.

b. Exploratory factor analysis

</div>
(6)<div class='page_container' data-page=6>

analysis is base on Kaiser-Meyer-Olkin (KMO)
Measure. In case of KMO has value between 0.5 and
1.0 and Sig. is smaller than 0.5, factor analysis is more
appropriate factor analysis. In case of KMO has value
smaller than 0.5 or Sig. is greater than 0.5, it indicates
that factor analysis may not be appropriate.

By performing exploratory factor analysis, investigator
can decide the number of factors to extract in the
model. The Kaiser creation states that investigator
should use a number of factors equal to the number of
the eigenvalues of the correlation matrix that are
greater than one (DeCoster, 1998).

An important part in exploratory factor analysis is
interpreting factor matrixes. This research will use
Varimax rotation process to produce multiple group
factors. Factor loadings which indicate correlations
between the variables and the factors are required to
have greater than 0.5 values. Then, a factor can be
interpreted in terms of the variables that have high load
on it.

c. Regression analysis

Regression analysis is a modelling technique for
analysing the relationship between dependent variable

(customer satisfaction) and independent variables
(tangible, reliability, responsiveness, assurance, and
empathy). Then, base on regression function, we can
assess the impact of each independent variable on
dependent variable as well as predict the change in
dependent variable when there is any change in
independent variables.

At first, it is necessary to test assumptions for
regression analysis. The principal assumption is that
there is a linearity of the relationship between
dependent and independent variables. This research
investigates the model with more than one independent
variables, the correlation among independent variables
(multi-collinearity) should be checked through
Variance inflation factor (VIF). Regression model
accept variables which have VIF smaller than 10. In
addition, it is assumed that the error terms ε are

independent, normally distributed random variables
with mean value of 0, and constant variances. As long
as these assumptions are not seriously violated,
regression model will be established.

Once regression function was given, the research can
investigate relationship between service quality and
customer satisfaction at Military bank. R-square
(coefficient of determination) will provide a
goodness-of-fit measure. With higher R-square value,
the model is higher fit for analysis.

4. Research analysis and results

4.1. Data description

Among 150 questionnaires provided to customers,
146 responses were collected. After inputting data and
screening questionnaires, there were 123 valid samples
and 23 missing samples. In survey sample, the majority
participant group has age ranging from 20 to 29 years
old. They stand at 63 people or 51.2% of the total
responses.

Figure 2: Kind of services used

</div>
(7)<div class='page_container' data-page=7>

4.2. Reliability analysis

Table 2: Reliability analysis results

Corrected
Item-Total
Correlation

Cronbach's Alpha
if Item Deleted

TANGIBLE scale: Cronbach's Alpha = .718

TAN 1 .591 .614

TAN 2 .647 .561

TAN 3 .694 .527

TAN 4 .165 .836

RELIABILITY scale: Cronbach's Alpha = .824

RELI 1 .610 .795

RELI 2 .695 .756

RELI 3 .588 .805

RELI 4 .706 .750

RESPONSIVENESS scale: Cronbach's Alpha

= .774

RES 1 .525 .746

RES 2 .555 .732

RES 3 .645 .687

RES 4 .597 .712

ASSURANCE scale: Cronbach's Alpha = .827

ASS 1 .672 .773

ASS 2 .674 .772

ASS 3 .663 .777

ASS4 .606 .803

EMPATHY scale: Cronbach's Alpha = .608

EMP 1 .256 .644

EMP 2 .312 .594

EMP 3 .491 .464

EMP 4 .532 .430

CUSTOMER SATISFACTION scale: Cronbach's

Alpha = .643

SAT 1 .478

SAT 2 .478

Table 2 shows that six scales are reliable with
Cronbach’s Alpha value greater than 0.6. Among 22
observed variables, TANGIBLE 4 and EMPATHY 1
have Corrected Item-Total Correlation of .165 and .256

which are smaller than 0.3. Thus, these two items will
be rejected. The remaining 20 observed variables have
greater than 0.3 Corrected Item-Total Correlation
values; therefore, they are accepted and will be
analyzed in the next step.

In conclusion, through reliability analysis, two items – 
TANGIBLE 4 and EMPATHY 1 – are rejected. The 
initial scale with 22 variables, now, reduces to 20 
observed variables (18 variables for service quality 
scale and 2 variables for customer satisfaction scale).

4.3. Exploratory factor analysis

4.3.1. Exploratory factor analysis for service 
quality scale

Exploratory factor analysis result at the first time for
service quality scale found that initial five components
reduce to four components extracted with eigenvalues
greater than 1. The first components namely
RELI-ASS is a combination of Reliability and
Assurance components. The other three components
are TANGIBLE, RESPONSIVENESS, and
EMPATHY. The result also rejects item ASSURANCE
4 and EMPATHY 2 because ASSURANCE 4 has two
factor loadings in which 0.515 (factor 1) is a little
greater than 0.5 but unclearly differentiates from 0.488
(factor 4); and EMPATHY 2 has smaller than 0.5
factor loadings.

</div>
(8)<div class='page_container' data-page=8>

Table 3: Reliability and factor analysis for service 
quality scale

Reliability statistics

Component No. of

Items

Cronbach’s
Alpha

RELI-ASS 7 .877

TANGIBLE 3 .836

RESPONSIVENESS 4 .774

EMPATHY 2 .695

Rotated Component Matrix

Reliability analysis at the second time indicates that all
four extracted components have greater than 0.6
Cronbach’s Alpha values which mean that data of these
four components are reliable. Besides, exploratory
factor analysis is adequate with KMO value of 0.883
and Sig. value of .000. In addition, with Cumulative %
of Variance of 66.607%, these four components

explain 66.607% of service quality variance. It is
interesting that the first components (RELI-ASS)
accounts for 41.327% of the variance; thus, it may be a
strongest components among four components
obtained here.

In conclusion, after making exploratory factor analysis, 
the service quality scale includes 16 observed 
variables, divided into 4 components namely RELI-ASS, 
TANGIBLE, RESPONSIVENESS, and EMPATHY. 
4.3.2. Exploratory factor analysis for customer 
satisfaction scale

Customer satisfaction scale includes two items.
In KMO and Bartlett's Test, KMO value measuring the
sampling adequacy equals to 0.5 with Sig. is .000.
These numbers confirm the validity of data for
exploratory factor analysis.

Table 4: Exploratory factor analysis of 
customer satisfaction scale

Component Matrix

Component
1

SATISFACTION 2 .860

SATISFACTION 1 .860

Eigenvalues 1.478

% of Variance 73.884

The analysis extracts 1 component which has
eigenvalues of 1.478 (greater than 1). Both two
customer satisfaction items define this component with
factor loadings of 0.860 (greater than 0.5) for each item.
The cumulative variance is 73.884% which means that
Component

RELI-ASS TAN RES EMP

RELI 2 .779
RELI 1 .771
ASS 3 .771
RELI 4 .692
ASS 2 .622
RELI 3 .618
ASS 1 .566

TAN 2 .869

TAN 3 .856

TAN 1 .675

RES 4 .739

RES 2 .736

RES 3 .716

RES 1 .640

EMP 3 .813

EMP 4 .804

Eigenvalu

es 6.612 1.726 1.258 1.060

% of

Variance 41.327 10.790 7.862 6.628
Cumulativ

</div>
(9)<div class='page_container' data-page=9>

this component explains 73.884% of customer
satisfaction variance.

In short, after making exploratory factor analysis, 
the customer satisfaction scale includes 2 observed 
variables, extracted to 1 component – SATISFACTION.

4.3.3. Research model – Version 2

After making exploratory factor analysis, two scale
reliability and assurance together define RELI-ASS

component. Therefore, research model is adjusted to
become research model – version 2 as following:

Figure 3: Research model – Version 2

Hypothesis H1, H3, H5 remains unchanged.
Hypothesis H6 is added for RELI-ASS
component: RELI-ASS component and customer
satisfaction have a positive relationship. That means
the higher/lower customer evaluate RELI-ASS factor,
the higher/lower level of customer satisfaction.

4.4. Regression analysis

4.4.1. Regression analysis

At first, average scores of both dependent variables
(SATISFACTION) and independent variables
(RELI-ASS, TANGIBLE, RESPONSIVENESS, and
EMPATHY) for 123 participants are calculated. Then,
it is necessary to test whether data satisfy assumptions
for regression analysis.

Pearson Correlation between SATISFACTION

and the other four components - RELI-ASS,
TANGIBLE, RESPONSIVENESS, and EMPATHY –
present positive values. That means there is a positive
linear relationship between dependent and independent
variables. Besides, the correlation among four
components is also quite strong with Pearson values of
greater than 0.3 which may lead to a multi-collinearity

situation. However, Variance inflation factor (VIF)
values of four components are very small (much
smaller than 10). Thus there will not be a
multi-collinearity situation, and regression model
accepts these variables. Moreover, ε (residual) is
normally distributed as bell shaped, with mean nearly
equal to 0 and standard deviation is 0.983 (nearly equal
to 1). These numbers do not violate the standard
normal distribution of error terms. In short, it can be 
seen that assumptions for regression model are not 
seriously violated; then, regression model will be 
established.

Table 5: Regression analysis summary 
Model Summary

Model R R Square

Adjusted R
Square

1 .805 .649 .637

Coefficients

Model

Unstandardized
Coefficients

Standardized
Coefficients

Sig.
B Std. Error Beta

(Constant) .023 .259 .931

RELI-ASS .267 .071 .267 .000

TAN .009 .058 .010 .881

RES .339 .064 .368 .000

EMP .364 .066 .355 .000

In Table model summary, adjusted R-square value
accounts for .637. This value indicates that 63.7% of

y RELI-ASS

TANGIBLE

Satisfaction

RESPONSIVE
NESS
EMPATHY

</div>
(10)<div class='page_container' data-page=10>

the variance in customer satisfaction can be explained

by four variables, namely RELI-ASS, TANGIBLE,
RESPONSIVENESS, and EMPATHY.

With coefficients presented in Table 5, regression
function is as following:

SATISFACTION = 0.267RELI-ASS +

0.10TANGIBLE + 0.368RESPONSIVENESS +
0.355EMPATHY

However, component TANGIBLE has the smallest
coefficient value of 0.010 and Sig. value of 0.881
(greater than 0.05). Thus, hypothesis H1 is not
supported and TANGIBLE does not reliably explain
customer satisfaction. TANGIBLE is eliminated from
model. Regression analysis is conduct at the second
time.

Table 6: Regression analysis – the second time 
Model Summary

Model R R Square

Adjusted
R Square

1 .805 .648 .640

Coefficients

Model

Unstandardized
Coefficients

Standardized
Coefficients

Sig.
B Std. Error Beta

(Constant) .030 .254 .907

RELI-ASS .270 .068 .270 .000

RES .341 .061 .371 .000

EMP .365 .065 .356 .000

Adjusted R-square value indicates that 64% of the
variance in customer satisfaction can be explained by
three variables, namely RELI-ASS, EMPATHY, and
RESPONSIVENESS. Hypotheses H3, H5 and H6 are
all supported. The regression function can be written as
following:

SATISFACTION = 0.270RELI-ASS +

0.371RESPONSIVENESS + 0.356EMPATHY

Positive coefficients indicate that SATISFACTION has
positive relationship with RELI-ASS,
RESPONSIVENESS, and EMPATHY.

4.4.2. Research model and hypothesis tested

result

Table 7: Hypotheses tested results

Hypotheses Result 
H6: RELI-ASS component and

customer satisfaction have a positive
relationship. That means the higher/lower
customer evaluate RELI-ASS factor, the
higher/lower level of customer satisfaction.

Supporte
d

H1: TANGIBLE component and

customer satisfaction have a positive
relationship. That means the higher/lower
customer evaluate tangible factor, the
higher/lower level of customer satisfaction.

Not
Supporte

H3: RESPONSIVENESS component

and customer satisfaction have a positive
relationship. That means the higher/lower
customer evaluate responsiveness factor, the
higher/lower level of customer satisfaction.

Supporte
d

H5: EMPATHY component and
customer satisfaction have a positive
relationship. That means the higher/lower
customer evaluate empathy factor, the
higher/lower level of customer satisfaction.

Support
ed
Figure 4: Research model result

B

a

n

k

in

g

s

er

v

ic

e

q

u

a

li

ty RELI-ASS

TAN

Satisfaction

RES

EMP

H1(not supported)

H3
H1

H5
H1
H6

0.371

</div>
(11)<div class='page_container' data-page=11>

In conclusion, by data selected from customers of 
Military Bank, this research constructed a regression 
model in which four components of service quality 
(RELI-ASS, TANGIBLE, RESPONSIVENESS, and 
EMPATHY) have statistically positive relationship with 
customer satisfaction (SATISFACTION). All 
hypotheses are supported by this result except 
hypothesis of TANGIBLE component.

5. Findings and discussions

5.1. Impact of service quality factors on customer 
satisfaction at Military Bank

The service quality factors at Military Bank are
classified into RELI-ASS, RESPONSIVENESS, and

EMPATHY. They are also service quality components
which determine customer satisfaction level. The
remaining component – TANGIBLE – which does not
show reliable statistically relationship with customer
satisfaction is discarded. The reason why can be
explained that among 123 customers in the survey
sample, there are 56 people which accounts for 45.5%
used and assessed ATM card services. Their
transactions with the bank are mainly performed
through ATM machines. Therefore, TANGIBLE
components may not have much impact on their
assessment about service quality.

The regression function which illustrates the
relationship between these three factors and customer
satisfaction is as following:

SATISFACTION = 0.270RELI-ASS +

0.371RESPONSIVENESS + 0.356EMPATHY
All hypotheses for these components are supported.
From the equation, positive coefficients show that three
factors have positive impacts on customer satisfaction.
The factor which has significant influence on overall
customer satisfaction is RESPONSIVENESS with
standardized coefficient of 0.371. This number reveals
that a unit increases (decreases) in
RESPONSIVENESS will lead to an increases
(decreases) in overall customer satisfaction by 0.371

units. That also means if Military Bank increases its
responsiveness ability in serving customers by 1 unit,
they may increase customer satisfaction level by 0.371
units.

The second important factor in determining customer
satisfaction is EMPATHY component with
standardized coefficient of 0.356. That means if the
bank increases its attention and care to each individual
customer by 1 unit, they may increase increase
customer satisfaction level by 0.356 units.

The last factor affecting on customer satisfaction is
RELI-ASS. This factor has the smallest impact among
three factors, but its standardized coefficient is still
quite high with value of 0.27. It is a combination
between the bank’s ability to perform services
accurately right at the first time and to build trust for 
customers. If the bank can increase these abilities by 1 
unit, it will contribute to an increase in overall
customer satisfaction by 0.27 units.

Adjusted R-square value of 0.64 indicates that these
three service quality component can explain 64% of
the variance in customer satisfaction. The remaining
36% can be explained by other factor such as brand’s
image, advertising activities, social responsibility, etc.
It is clear that three service quality components
together determine customer satisfaction level in
Military Bank. Although level of each factor’s impact

is different, they are all important factors which are
needed attention and further improvement.

5.2. Suggestions to improve service quality and 
customer satisfaction at Military Bank

</div>
(12)<div class='page_container' data-page=12>

establish attractive compensation policies that
increasingly motivate employees in providing services
and helping customers.

EMPATHY is the second important factor which
stresses great impact on customer satisfaction at
Military Bank. In order to increase EMPATHY, the
bank should further pay attention to each individual
customer to deeply understand their specific needs, and
then help them to choose the most suitable service. The
bank may diversify list of services to meet various
needs of customers. Besides, it should provide cares for
its customers; for example, implementing preferential
customer policies to maintain the loyalty of customers
especially; sending customers best wishes or gifts in
some special occasions such as customer’s birthday,
New Year, etc…

Last but not least, RELI-ASS (a combination of
Reliability and Assurance) is also necessary to be
improved. RELI-ASS refers to the bank’s ability to
perform services accurately right at the first time and
build trust in customer mind. Improving this factor
relies much on employees’ professional qualifications

and skills. Thus, the bank should focus on not only
attracting talents but also training them. Moreover, the
bank should continuously improve service processes to
shorten transaction time, enhance accuracy and safety
levels of all processes, then provide highest utility of
services for customers.

6. Limitations and suggestions for further research

One limitation of this study is that survey was
conducted in only one representative Transaction office
of Military Bank. Questionnaire answered by
customers are mostly based on their assessment about
service quality of this transaction office. Therefore,
some analysis and conclusions in this study can be
improved.

Another limitation is that the time to carry out survey,
collect survey data as well as analyze data was limited.
Data is described with a large amount of responses
used and assessed about ATM card services (56 people

which accounts for 45.5%). They come to transaction
office to open account or card; after that they mostly
make transactions with ATM machines. Consequently,
some participants’ assessment may be still subjective.
In further research, observation results may be
improved if survey was conducted in some
representative transaction offices from difference
regions in Vietnam. Additionally, service quality and

customer satisfaction assessment at Military Bank
would be better if data analyzed includes equal number
of assessments about different kinds of services. With
these improvements, it is expected that further studies
may have higher practical values with more objective
analysis and conclusions.

7. Conclusions

This research examined Military Bank’s services to
investigate the components of its service quality and
describe the relationship between service quality’s
components and overall customer satisfaction level.
This research conducted quantitative method and the
strategy of inquiry used was survey. The theoretical
model used was based on SERVPERF model with 22
observed items classified into 5 components of service
quality and 1 component of customer satisfaction. With
123 valid responses, data was used to make reliability
analysis, exploratory factor analysis and regression
analysis as shown in Section 4. The initial theoretical
model was replaced by a new model with 3
components of service quality (RELI-ASS,
RESPONSIVENES, and EMPATHY) and the
remaining component of customer satisfaction. The
regression analysis describes a positive relationship
between service quality components and customer
satisfaction in form of following equation:

SATISFACTION = 0.270RELI-ASS +

</div>
(13)<div class='page_container' data-page=13>

bank’s ability to perform services accurately, on time
right at the first time and ability to built customers’
trust in bank’s service, trust in employees’ professional
skills as well as serving; RESPONSIVENESS stands
for the bank’s willingness to provide services and help
customers; and EMPATHY stands for the bank’s
attention and care to each individual customer. This
result confirms the importance of service quality in
maintaining customer satisfaction. In addition,
demonstration in this study may contribute to Military
Bank managers’ awareness of service quality’s role.
Then, they may consider the value of service quality to
customer satisfaction, and allocate resources in
effective way.

References

Amit Choudhury, (2010), “Cronbach’s alpha”,

Experiment-resources.com, retrieved 29/04/2012, from 
/>

Brady, M. K., and Robertson, C. J., (2001), “Searching for a
consensus on the antecedent role of service quality and
satisfaction: an exploratory cross-national study”, Journal of

Business Research, Vol. 51 (1), pp. 53–60.

Center for the Study of Social Policy, (2007), Customer
Satisfaction: Improving Quality and Access to Services and

Supports in Vulnerable Neighborhoods, pp. 6.

Cronin, J. J., and Taylor, S. A. (1992). “Measuring service
quality: A Reexamination and extension”, Journal of

Marketing, pp. 55-68.

DeCoster, J. (1998), “Overview of Factor Analysis”,
retrieved 29/04/2012, downloaded from

Emari, H., Iranzadeh, S., and Bakhshayesh, S., (2010),
Determining the Dimensions of Service Quality in Banking
Industry: Examining the Cronroos’s Model in Iran, Journal

of Compilation, pp. 3.

Hollis Landrum et al., (2009), “Measuring information
science system service quality with SERVQUAL: Users’
perceptions of relative importance of the five SERVPERF
dimensions”, Information Science: the International Journal

of an Emerging Trans-discipline, Vol. 12, pp. 18-34.

Jay Heize, Barry Render, (2009), Operation Management

Flexible Version (9th edition), Prentice Hall, pp. 156, 168,

185-186.

Kotler Philip, Wong Veronica, Saunders John, Armstrong
Gary, (2005), Principles of Marketing (4th European edition),

Prentice Hall, pp. 539, 546, 625.

M.Muzaffar Zahoor, “SERVPERF Analysis in Banking
Services”, Karachi Institute of Economics and Technology.
Nguyen Thi Phuong Tram, (2008), “Service quality in
e-banking: Comparison between SERVQUAL model and
GRONROOS model”, University of Economics,
HoChiMinh.

Parasuraman, Valarie A. Zeithaml, & Leonard L. Berry,
(1988), “SERVQUAL: A Multiple-Item Scale for Measuring
Consumer Perceptions of Service Quality, Journal of

Retailing, Vol. 64, No. 1, pp. 12-40.

Ruyter, K., Bloemer, J., and Pascal, P., (1997), “Merging
service quality and service satisfaction: an empirical test of
an integrative model”, Journal of Service Marketing, Vol. 16 
(4), pp. 363-379.

Sanjay K Jain and Garima Gupta, (2004), “Measuring
Service Quality: SERVQUAL vs. SERVPERF Scales”,

Vikalpa, Vol. 29, pp. 25-35.

Tavakol Mohsen, Dennick Reg, (2011), Making sense of

Cronbach’s alpha”, International Journal of Medical

Education, pp. 53-55

Vanniarajan, T., Anbazhagan, B., (2007), “SERVPERF
Analysis in Retail Banking”, International Marketing

</div>

The Relationship between Service Quality and Customer Satisfaction – a Case of a Commercial Bank in Vietnam

<b>The Relationship between Service Quality and Customer Satisfaction </b>

<b>– a Case of a Commercial Bank in Vietnam </b>

<b> </b>

<b>Customer </b>

<b>satisfaction </b>

H1

<i><b> Analysing data </b></i>

<b>4. Research analysis and results </b>

<i><b>4.1. Data description </b></i>

<i>4.3.3. Research model – Version 2 </i>

<b>Figure 3: Research model – Version 2 </b>

<i><b>4.4. Regression analysis </b></i>

<i>4.4.1. Regression analysis </i>

<b>Satisfaction </b>

<i>4.4.2. Research model and hypothesis tested </i>

<i>result </i>

<b>Satisfaction </b>

<b>5. Findings and discussions </b>

Tài liệu liên quan

Tài liệu bạn tìm kiếm đã sẵn sàng tải về