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

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, TANG[r]

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

0983820460 Email: lienpt@vnu.edu.vn

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

01689931018 Email: nguyenhueminh146@gmail.com

■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

Quality is a really significant concept that is considered

as a strategic organizational weapon (Anber Abraheem Shlash Mohammad, Shireen Yaseen Mohammad Alhamadani, 2011) The importance that customers place on quality attributes is the driver of satisfaction (Vanniarajan, T., Anbazhagan, B., 2007) Therefore, to exist and develop, organizations are required to focus more and more on their service quality which will in turn result in satisfied customers and increasing

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):

- Tangible includes physical evidences of the service such as appearance of physical facilities,

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

relationship between service quality and customer satisfaction Sureshchandar et al., (2002) used a factor specific approach to test the relationship between service quality and customer satisfaction of different banks in India These critical factors used are (1) core service or service product, (2) human element of service delivery, (3) systematization of service delivery: non-human element; (4) tangibles of service – servicescapes, (5) social responsibility Questionnaires comprising 41 items in total were distributed to 452 customers from 51 different banks, and then 277 completed questionnaires from 43 banks were obtained Analysis results revealed that correlation statistics between service quality and customer satisfaction are reasonably high which demonstrated high relationships between service quality and customer satisfaction Anber Abraheem Shlash Mohammad and Shireen Yaseen Mohammad Alhamadani (2011) conducted a research about service quality perspectives and customer satisfaction in commercial banks working in Jordan The research examined level of service quality

as perceived by 260 customers and its effect on customer satisfaction with the questionnaire survey including 20 items to measure 5 dimensions of service quality (Reliability, Responsiveness, Empathy, Assurance, and Tangibles) and 5 items to measure customer satisfaction The results indicated that 5 dimensions of service quality have significant influence on customer satisfaction when 26.1% of customer satisfaction can be explained by them

Brady and Robertson (2001) conducted research about fast food restaurants in America and Latin America The results indicated that there was a certain relationship between service quality and customer

satisfaction In addition, Ruyter et al., (1997) tested the

health care service and attempted to determine the relationship between service quality and customer satisfaction The results suggested that service quality should be treated as an antecedent of customer satisfaction From these researches, it can be concluded

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):

ij

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

Tangible

Reliability

satisfaction

Assurance

Empathy

H2

H3 H1

H4

H1 H5 H1 H1

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

Exploratory factor analysis is a powerful statistical technique which is used for data reduction and summarization The sampling adequacy of factor

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

In addition, Figure 2 indicates that the largest number of participants used and assessed ATM card services This number is 56 people among 123 samples which accounts for 45.5%

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

RELIABILITY scale: Cronbach's Alpha = 824

RESPONSIVENESS scale: Cronbach's Alpha

= 774

ASSURANCE scale: Cronbach's Alpha = 827

EMPATHY scale: Cronbach's Alpha = 608

CUSTOMER SATISFACTION scale: Cronbach's

Alpha = 643

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

The service quality scale including 16 observed variables, divided into 4 components namely RELI-ASS, TANGIBLE, RESPONSIVENESS, and EMPATHY is conducted reliability analysis and factor analysis at the second time

Table 3: Reliability and factor analysis for service

quality scale

Reliability statistics

Items

Cronbach’s Alpha

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

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 2 779

RELI 1 771

ASS 3 771

RELI 4 692

ASS 2 622

RELI 3 618

ASS 1 566

Eigenvalu

Variance 41.327 10.790 7.862 6.628

Cumulativ

e Variance 41.327 52.117 59.980 66.607

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

Adjusted R Square

Coefficients

Model

Unstandardized Coefficients

Standardized Coefficients

Sig

B Std Error Beta

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

TANGIBLE

Satisfaction

RESPONSIVE

NESS

EMPATHY

H1

H3 H1 H5 H1 H6

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:

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

Coefficients

Model

Unstandardized Coefficients

Standardized Coefficients

Sig

B Std Error Beta

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:

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

d

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

ty RELI-ASS

TAN

Satisfaction

RES

EMP

H1(not supported)

H3 H1

H5 H1

H6

0.371

0.356 0.27