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International Journal of Contemporary Business Studies 

Vol: 4, No: 6 JUNE, 2013 ISSN 2156-7506 

Available online at http://w w w.akpinsight.webs.com 

Customer Satisfaction and Online Service Quality in 

the Banking Sector in Malaysia 

Anantha Raj A. Arokiasamy 

Quest International University Perak (QIUP) 

Faculty of Business, Management and Social Sciences (FBMSS) 

No. 227, Plaza Teh Teng Seng (Level 2), 

Jalan Raja Permaisuri Bainun, 

30250 Ipoh, Perak, Malaysia. 

Page | 70 

Dr. Abdul Ghani Kanesan bin Abdullah, Associate Professor 

School of Educational Studies 

University Science Malaysia (USM) 

11800 Penang, Malaysia. 

ABSTRACT 

Online banking and customer satisfaction is gaining momentum in Malaysia in 

the last decade. The purpose of this study is to understand and analyze the impact 

of E-SERVQUAL model on customer satisfaction in a leading bank in Malaysia. 

Five service quality dimensions namely tangibles, reliability, responsiveness, 

assurance and empathy have been chosen based on SERVQUAL model by 

Parasuraman et al., (1988). These variables have been tested to explore the 

relationship between customer satisfaction and online service quality. Around 51 

respondents participated in this study through a structured self-answered 

questionnaire and Statistical Package for Social Sciences (SPSS) was used to 

analyze the correlation between service quality and customer satisfaction. Finally 

the study explored empathy, reliability and responsiveness as having contributed 

significantly to customer satisfaction of the bank‟s online banking. 

Keywords: Customer satisfaction, online banking, SERVQUAL, and service 

quality dimensions. 

1.0 INTRODUCTION 

Online service or e-service has witnessed an explosive growth in the past decade especially in 

the service sector in Malaysia. In particular the internet has been instrumental in providing e- 

services to customers from the banking sector. Compared to phone banking or walk-in outlets 

and over-the-counter transactions at banks, online banking services have become an attractive 

alternative among customers recently (Kenova and Jonasson, 2006). Internet banking helps 

banks to build and maintain close relationships with their customers, reduces operating and fixed 

costs and achieves more efficient and enhanced financial performance (DeYoung et al., 2007 as 

cited in Rod et al. 2009). From the customers‟ point of view, online services offer a wider array 

of benefits such as ease of use; reduce service or transaction charges and enhanced control 

(Scullion and Nicholas, 200). Many banks over the years have tried to provide quality of online 

C opyright © 2 0 13. A cademy of Knowledge P rocess




services to satisfy the needs of their customers. It is now a key variable in maintaining customer 

satisfaction. These banks are introducing internet banking as an assurance to their customers that 

they will be able to maintain a competitive quality of service in the future, in efforts to avoid 

losing their customers (Rod et al. 2009). Offering internet banking is no longer regarded as a 

competitive advantage but a competitive necessity (Gan et al., 2006, as cited in Rod et al. 2009). 

The main purpose of this study was to investigate the customers‟ perceptions towards online 

service quality offered by a leading bank in Malaysia. 

Page | 71 

2.0 LITERATURE REVIEW 

2.1 Service Quality 

Service quality is generally perceived to be a tool that can be used to create a competitive 

advantage and therefore, substantial research into service and service quality has been 

undertaken in the last 20 years. Bitner et al. (1990) define service quality as “the consumers‟ 

overall impression of the relative inferiority/superiority of the organization and its services.” The 

most common definition of service quality is the discrepancy between consumer‟s expectations 

and perceptions of the service received. Accordingly, service quality is defined as how well a 

delivered service level matches customer‟s expectation. Parasuraman et al. (1988, 1991) 

identified more detailed dimensions of service quality and developed a well-known instrument, 

called SERVQUAL, to measure customer‟s perceptions and expectations from service. The 

SERVQUAL instrument consists of five underlying dimensions, with two sets of 22 item 

statements for the „expectation‟ and „perception‟ sections of the questionnaire. Perceived service 

quality is measured by subtracting customer perception scores from customer expectation scores, 

both for each dimension and overall. The five dimensions of SERVQUAL are (Parasuraman et 

al., 1988, 1991): 

(1) Tangibles, which pertain to the physical facilities, equipment, personnel and 

communication materials. 

(2) Reliability, which refers to the ability to perform the promised services dependably and 

accurately. 

(3) Responsiveness, which refers to the willingness of service providers to help customers 

and provide prompt service. 

(4) Assurance, which relates to the knowledge and courtesy of employees and their ability to 

convey trust and confidence. 

(5) Empathy, which refers to the provision of caring and individualized attention to 

customers. 

Since the SERVQUAL was developed in 1988, various researchers have recognized that both the 

instrument itself and the conceptualization of service quality may benefit from further refinement 

(for example, Finn and Lamb 1991, Lee and Hing 1995). They have argued that the SERVQUAL 

instrument needs to be customized to the specific service area. Cronin and Taylor (1992) have 

developed instruments to measure service quality based only on customer perceptions. After 

many studies have examined the suitability of SERVQUAL in measuring service quality in 

different types of service, they tried to adapt the original SERVQUAL items to various service 

contexts by slightly changing the original items. The SERVQUAL, however, does not embrace the 

unique facets of online service quality, such as customer-to-Web-site interactions, since this 

instrument was constructed based mainly on customer-to-employee interactions (Cai and Jun, 2003). 





Despite SERVQUAL as an instrument to measure quality has been widely accepted and several 

studies have attempted to address the key attributes of services quality, many researchers express the 

need that the SERVQUAL should be customized to the specific service area (Han and Beak, 2004). 

2.2 Online Service Quality 

During the past several years, some conceptual and empirical studies have attempted to address 

the key attributes of service quality directly or indirectly related to online service and, 

SERVQUAL has been widely accepted and used in measuring Information System service 

quality (Van Dyke et al., 1999). Yang & Jun (2002) redefined the traditional service quality 

dimensions in the context of online services, and suggested an instrument consisting of seven 

online service dimensions (reliability, access, ease of use, personalization, security, credibility, 

and responsiveness). In addition, Barnes & Vidgen (2002) introduced a method for assessing the 

service quality of e-commerce web-sites, called WebQual. Despite the increased aware of online 

services, but still there is the problem of how the quality of online services is defined, which its 

determinants are and how it can be actually measured (Kenova and Jonasson, 2006). The quality 

of e-service is an essential issue to develop a valid scale. The growth of e-commerce in the 

global and regional markets creates a special interest in the measuring of e-service quality and 

also in the investigation of the dimensions of e-service (Mekoves et al., 2007). 

Page | 72 

Considerable studies have been conducted focusing on the measurement and evaluating online 

service quality. Despite the valuable contribution of these scales, the SERVQUAL scale 

developed by Parasuraman, Zeithaml and Berry has received a considerable attention. Yang 

(2001) argues that the primary value of SERVQUAL lies on its powerful benchmarking, 

diagnostic and perspective tools. As stated earlier, the SERVQUAL scale does not best fit the 

online services and therefore many studies have tried to extend its conceptualization to the 

electronic context. Lee and Lin (2005) maintain that most research on e-service quality 

measurement has focused on rewording the SERVQUAL scale items. 

2.3 E-Banking 

The concept of electronic banking has been defined in many ways. Daniel (1999) defines 

electronic banking as the delivery of banks' information and services by banks to customers via 

different delivery platforms that can be used with different terminal devices such as a personal 

computer and a mobile phone with browser or desktop software, telephone or digital television. 

Pikkarainen et al (2004) define internet banking as an "internet portal, through which customers 

can use different kinds of banking services ranging from bill payment to making investments". 

With the exception of cash withdrawals, internet banking gives customers access to almost any 

type of banking transaction at the click of a mouse (De Young, 2001). Indeed the use of the 

internet as a new alternative channel for the distribution of financial services has become a 

competitive necessity instead of just a way to achieve competitive advantage with the advent of 

globalization and fiercer competition (Flavián et al, 2004; Gan and Clemes, 2006). 

Banks use online banking as it is one of the cheapest delivery channels for banking products 

(Pikkarainen et al, 2004). Such service also saves the time and money of the bank with an added 

benefit of minimizing the likelihood of committing errors by bank tellers (Jayawardhena and 

Foley, 2000). Robinson (2000) believes that the supply of internet banking services enables 

banks to establish and extend their relationship with the customers. There are other numerous 





advantages to banks offered by online banking such as mass customization to suit the likes of 

each user, innovation of new products and services, more effective marketing and 

communication at lower costs (Tuchilla, 2000), development of non-core products such as 

insurance and stock brokerage as an expansion strategy, improved market image, better and 

quicker response to market evolution (Jayawardhena and Foley, 2000). Wise and Ali (2009) 

argued that many banks want to invest in ATMs to reduce branch cost since customers prefer to 

use them instead of a branch to transact business. The financial impact of ATMs is a marginal 

increase in fee income substantially offset by the cost of significant increases in the number of 

customer transactions. The value proposition however, is a significant increase in the intangible 

item "customer satisfaction". The increase translates into improved customer loyalties that result 

in higher customer retention and growing organization value. Internet banking is a lower-cost 

delivery channel and a way to increase sales. 

Page | 73 

2.4 Customer satisfaction and service quality 

Since customer satisfaction has been considered to be based on the customer‟s experience on a 

particular service encounter, (Cronin & Taylor, 1992) it is in line with the fact that service 

quality is a determinant of customer satisfaction, because service quality comes from outcome of 

the services from service providers in organizations. Another author stated in his theory that 

“definitions of consumer satisfaction relate to a specific transaction (the difference between 

predicted service and perceived service) in contrast with „attitudes‟, which are more enduring 

and less situational-oriented,” (Lewis, 1993, p. 4-12) This is in line with the idea of Zeithaml et 

al (2006, p. 106-107). Regarding the relationship between customer satisfaction and service 

quality, Oliver (1993) first suggested that service quality would be antecedent to customer 

satisfaction regardless of whether these constructs were cumulative or transaction-specific. 

Some researchers have found empirical supports for the view of the point mentioned above 

(Anderson & Sullivan, 1993; Fornell et al 1996; Spreng & Macky 1996); where customer 

satisfaction came as a result of service quality. In relating customer satisfaction and service 

quality, researchers have been more precise about the meaning and measurements of satisfaction 

and service quality. Satisfaction and service quality have certain things in common, but 

satisfaction generally is a broader concept, whereas service quality focuses specifically on 

dimensions of service. (Wilson et al., 2008). Although it is stated that other factors such as price 

and product quality can affect customer satisfaction, perceived service quality is a component of 

customer satisfaction (Zeithaml et al. 2006, p. 106-107). This theory complies with the idea of 

Wilson et al. (2008) and has been confirmed by the definition of customer satisfaction presented 

by other researchers. The below figure shows the relationship between customer satisfaction and 

service quality. The author presented a situation that service quality is a focused evaluation that 

reflects the customer‟s perception of reliability, assurance, responsiveness, empathy and 

tangibility while satisfaction is more inclusive and it is influenced by perceptions of service 

quality, product quality and price, also situational factors and personal factors. (Wilson, 2008, p. 

78). Yang (2001) found a positive relationship between online quality service and customer 

satisfaction based on five dimensions of e-service quality: care/help, ease of use, reliability, and 

product portfolio. Mobarek (2007) in his study about e-banking and customer satisfaction proved 

that customers are generally satisfied with e-banking services as a whole. Nupur (2010) arrived 

at the conclusion that there is a relationship between customer satisfaction and in e-banking and 





the five dimensions of SERVQUAL scale: reliability, responsiveness, assurance, empathy, and 

tangibles. 

Figure 2.1: Customer perceptions of quality and customer satisfaction 

(Wilson et al., 2008, p. 79) 

Page | 74 

Reliability 

Responsiveness 

Assurance 

Empathy 

Tangibles 

Service 

Quality 

Product 

Quality 

Situational 

Factor 

Customer 

Satisfaction 

Price 

Personal 

Factor 

Literature review explored showed substantive role of customer satisfaction and service quality, 

e-banking, online service quality and service quality. Therefore this study aims to address the 

relationship between online service quality and customer satisfaction for a leading bank in 

Malaysia. 

3.0 METHODOLOGY 

3.1 Research Framework and Hypotheses 

For the measurement of impact of online banking on service quality, a model named 

SERVQUAL was developed by Parasuraman (1988). The model consists of ten components. 

SERVQUAL provides a technology for measuring and managing service quality. In their 1988 

work these ten dimensions were reduced to five dimensions as follows: 

Dimensions 

Items in Scale 

1 Reliability 4 

2 Assurance 5 

3 Tangibles 4 

4 Empathy 5 

5 Responsiveness 4 





Figure 3.1: Proposed Theoretical Model 

Service Quality 

Dimensions 

(SERVQUAL) 

(Independent Variables) 

Assurance 

Customer Satisfaction 

Online Banking 

(Dependent Variable) 

Page | 75 

Empathy 

Responsiveness 

Reliability 

Tangibles 

3.2 Hypotheses of the Study 

The hypotheses of the study are developed as below: 

H 1 : 

H 2 : 

H 3 : 

H 4 : 

H 5 : 

There is a significant relationship between assurance and customer satisfaction. 

There is a significant relationship between empathy and customer satisfaction. 

There is a significant relationship between tangibles and customer satisfaction. 

There is a significant relationship between reliability and customer satisfaction. 

There is a significant relationship between responsiveness and customer 

satisfaction. 

3.3 Sample Selection Method 

The target population of the study comprised of the general public within the city of Perak, 

Malaysia. The survey was targeted to the users of online banking services at a leading bank in 

Malaysia. A total of 85 questionnaires were randomly distributed to all walk-in customers at the 

selected outlet at the bank in Perak over a period of one week. The respondents were asked to 

apprise their feelings and emotional bonding with the services rendered by the bank. 





3.4 Research Design 

Quantitative research method is adopted in this research. This technique studies large group of 

people and making generalizations from the samples being studied to broader group beyond 

these samples. Commonly used methods of research design are exploratory, descriptive and 

explanatory studies. The purpose of this study was to investigate the customers‟ perceptions 

towards online service quality of the bank. 

Page | 76 

4.0 DATA ANALYSIS 

A total of 85 sets of questionnaires were distributed to the potential respondents and a total of 63 

questionnaires were collected. Out of this, 12 sets of the questionnaires were considered 

unusable because over 25 percent of the questions in Part 1 – Section A of the questionnaire 

were not answered (Sekaran, 2003). It was assumed that the respondents were either unwilling to 

cooperate or not serious with the survey. Therefore, only 51 usable sets of collected 

questionnaires were used for the data analysis. Thereby, the response rate was 60 percent. 

Section A collects the respondents‟ demographic data which consists of elements such as gender, 

age, ethnicity, marital status, level of education, occupation and monthly income level. Section B 

consists of five independent variables, which is of this study‟s main purpose: to determine the 

relationship between empathy, responsiveness, tangibles, assurance and reliability and customer 

satisfaction in the online banking services provided. Each variable comprises of three to ten 

questions that are required to be answered by the respondents. The respondents were required to 

provide their rating on their perception using a 5 point Likert Scale measurement that ranged 

from 1=strongly disagree, 2=disagree, 3=neutral, 4=agree and 5=strongly agree. Pearson 

Correlation and Multiple Regression Analysis tool in Statistical Package for the Social Sciences 

(SPSS) was used to measure the relationship between variables of interest. 

4.1 Customer Profile 

Respondents form an important component of the primary data survey. Descriptive analysis was 

done to present the demographic information of the respondents. The sample size consists of 51 

respondents of the bank from mainly walk-in customers over a period of one week. The basic 

attributes of the respondents are income, age, sex, occupation, educational qualification and other 

socio-demographic information. Table 4.1 below represents a comprehensive profile of bank 

customers who had participated in this study. Based on the survey, the male respondents 

represented 32 percent of the total respondents while female respondents represented 19 percent. 

The highest proportion of respondents were Chinese (64 % or 33 respondents), followed by 

Malay (23 % or 11 respondents), Indian (11 % or 6 respondents), and others (2 % or 1 

respondents). 





Table 4.1: Demographical Profile of Respondents 

Gender Frequency Percent 

Male 32 63 

Female 19 37 

Marital Status Frequency Percent 

Married 41 80 

Unmarried 10 20 

Age Profile Frequency Percent 

Below 30 18 35 

30-40 22 43 

40-55 8 16 

55-70 3 6 

Income Frequency Percent 

Below 3k 18 35 

3k-5k 21 41 

5k-10 9 18 

Above 10k 3 6 

Type of Account Frequency Percent 

Saving 11 22 

Current 40 78 

Banking Relationship Frequency Percent 

7 yrs 

1 2 

Page | 77 

4.2 Reliability Test 

According to George & Mallery (2003), reliability is the degree to which measure are free from 

error and therefore yield consistent results. The reliability of a measure indicates the stability and 

consistency with which the instrument measures the concept and helps to assess the „goodness‟ 

of a measure (Cavana, Delahaye and Sekaran, 2001). According to Sekaran (2003), the closer the 

reliability coefficient gets to 1.0, the better it is, and those values over .80 are considered as 

good. Those values in the .70 is considered as acceptable and those reliability value less than .60 

is considered to be poor (Sekaran, 2003). All the constructs were tested for the consistency 

reliability of the items within the constructs by using Cronbach‟s alpha reliability analysis. 

Cronbach‟s Alpha values in respect of each variable are given in table 4.2 below. Respondents 

were also assured about the confidentiality as information shared in this regard would be used for 

academic and research purposes only. In conclusion, the results showed that the scores of the 

Cronbach‟s alpha for all the constructs exceeded the threshold of 0.70 indicating that the 

measurement scales of the constructs were stable and consistent. 





Table 4.2: Cronbach’s Alpha Reliability Test 

Construct Alpha Coefficient Number of Items 

Customer satisfaction 0.884 10 

Reliability 0.735 8 

Responsiveness 0.838 9 

Empathy 0.758 8 

Tangibles 0.733 8 

Assurance 0.826 10 

Page | 78 

4.3 Descriptive Statistics 

4.3.1 Pearson Correlation Coefficient 

Pearson's correlation coefficient (r) is a measure of the strength of the association between the 

two variables. According to Sekaran (2003), in research studies that includes several variables, 

beyond knowing the means and standard deviations of the dependent and independent variables, 

the researcher would often like to know how one variable is related to another. While correlation 

could range between -1.0 and +1.0, the researcher need to know if any correlation found between 

two variables is significant or not (i.e.; if it has occurred solely by chance or if there is a high 

probability of its actual existence). As for the information, a significance of p=0.05 is the 

generally accepted conventional level in social sciences research. This indicates that 95 times out 

of 100, the researcher can be sure that there is a true or significant correlation between the two 

variables, and there is only a 5% chance that the relationship does not truly exist. The correlation 

matrix between dependent variable and independent variables are exhibited in Table 4.3 below. 

The findings from this analysis are then compared against the hypotheses developed for this 

study. Table 4.3 shows the mean value depicting the overall customers‟ satisfaction. As far as 

this description analysis is concerned, customers‟ satisfaction on online banking service is above 

satisfactory level (with a mean value of 3.29 on a 5 point Likert scale). As far as the mean values 

are concerned customers are satisfied on tangibles, reliability, responsiveness, empathy and 

assurance. This satisfaction comes from easiness and availability of information on the bank‟s 

website, accuracy of service promises, quick response and the ability to get help if there is a 

problem or question and caring and individualized attention provided by web administrators. 





Table 4.3: Summary of Means, Standard Deviations and Correlation Matrix 

Variables Mean SD 

Customer 

Satisfaction 

4.13 1.03 

Customer 

Satisfaction 

Empathy 3.47 0.732 0.188** 

X1 X2 X3 X4 X5 

Page | 79 

Tangibles 3.37 0.724 0.176** 0.512** 

Reliability 3.41 0.882 0.194** 0.554** 0.482** 

Responsiveness 3.42 0.734 0.201** 0.571** 0.383** 0.497** 

Assurance 3.31 0.727 0.212** 0.632** 0.615** 0.564** 0.606** 

Note: Correlation is significant at the **0.01 level (2-tailed) 

X1=Empathy, X2=Tangibles, X3=Reliability, X4=Responsiveness, X5=Assurance 

As shown in table 4.3, the correlation matrix indicates that service quality was positively and 

moderately correlated with customer satisfaction. The highest coefficient of correlation in this 

study between service quality variables and customer satisfaction however is 0.212, which is 

below the cutoff of 0.90 for the collinearity problem. Thus, multicollinearity problem does not 

occur in this study (Hair et al., 1998). These correlations are also further evidence of validity and 

reliability of measurement scales used in this research. (Barclays et al., 1995; Hair et al., 1998). 

There was a significant positive relationship between assurance and customer satisfaction (r = 

.212, n = 51, p




this study met the assumptions required to ensure validity of its significance test (Ooi et al., 

2006). Based on Table 4.4, empathy (B = 0.261) has the strongest impact on customer 

satisfaction which is significant at 0.05 level followed by reliability (B = 0.194). The F value of 

24.726 is significant at the 0.05 level. This shows that the model is fit and the F-value is large. 

According to the result of Table 4.4, R 2 of 0.344 indicates that 34.4% of variation in customer 

satisfaction is explained by the independent variables empathy and reliability. Meanwhile, 75.3% 

of the changes in customer satisfaction are explained by other factors or variables which were 

not taken into consideration in this study. 

Page | 80 

Table 4.4: Coefficients a 

Unstandardized Standardized 

Collinearity 

Model 

Coefficients Coefficients 

t Sig. 

Statistics 

Std. 

B 

Beta Tolerance VIF 

Error 

1 (Constant) 0.348 0.293 1.187 0.237 

Empathy 0.261 0.039 0.106 2.026 0.000 0.808 1.237 

Tangibles 0.078 0.063 0.238 4.124 0.000 0.834 1.200 

Reliability 0.194 0.058 0.189 3.335 0.000 0.887 1.128 

Responsiveness 0.095 0.037 0.212 2.554 0.000 0.882 1.012 

Assurance 0.076 0.033 0.223 2.310 0.000 0.798 1.211 

R 2 0.344 

Adj. R 2 0.331 

Sig. F 

.000 a 

F-value 24.726 

a Dependent Variable: Customer Satisfaction 

5.0 CONCLUSION 

In this study, the interrelationship of studied variables including empathy, tangibles, reliability, 

responsiveness and assurance were examined by correlation analysis. The findings imply that all 

variables had mean value of greater than average on a five point Likert scale and empathy as an 

important variable had the highest mean value. In addition all studied variables had significant 

correlations with each other. The nature of banking services encourages customers to demand the 

highest possible quality. In order to achieve this, it is essential to be very close to customers to 

capture information on customer current and future expectations and perceptions. The main 

objective of this study was to examine the affect of online service quality on customer 

satisfaction. A lot of research has indicated SERVQUAL as the instrument for measure of 

service quality. SERVQUAL appears to be a consistent and reliable scale to measure online 

banking service quality. The study hopes to provide guidance and reference for the management 

of commercial banks in Malaysia. 





5.1 Managerial Implication 

It can be concluded from the study that managers and decision makers of commercial banks in 

Malaysia are avidly looking for ways to improve the elements of service quality that make the 

most contributions on determining customer satisfaction. In making such an assessment, 

managers should examine customer responses to the five dimensions of service quality used in 

this study. From the managerial point of view, service quality can be concluded as the precursor 

to customer satisfaction. Having high relative weights of different service dimensions do not 

necessarily compute to higher customer satisfaction and vice versa, this could lead to further 

improvements in the area of enhancing customer satisfaction. 

Page | 81 

Commercial banks in Malaysia will find this study relevant to their decision-making processes as 

they seek to improve their customers‟ satisfaction level while maintain customer loyalty, 

retention rates and attract new customers. Banks‟ management should therefore focus on 

providing superior quality services to their customers while maintain loyalty. 

5.2 Limitation of the Study 

Although the research findings provide some new insights to researchers, these findings should 

be viewed in light of some limitations. 51 samples from Perak may not be large enough to 

represent accurately the whole populations‟ attitude towards customer satisfaction in the online 

service quality provided by commercial banks in Malaysia. 

ACKNOWLEDGEMENT 

The author would like to acknowledge Ms. Krishnaveni Nagappan for her week long activity of 

data collection. Without her support and perseverance this study would not have been possible. 

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