Relational Study of Automated Service Quality, Customer Satisfaction and Financial Performance

Internship Report
Summer 2006

A RELATIONAL STUDY ON AUTOMATED SERVICE QUALITY,
CUSTOMER SATISFACTION AND FINANCIAL PERFORMANCE IN
THE CONTEXT OF BANK ASIA LTD

Submitted by
Syed Mohammad Ashiqullah
ID: 0320454

Submitted to
Mr. Samir Mainuddin
Lecturer

Independent University, Bangladesh
August 24th, 2006

A RELATIONAL STUDY ON AUTOMATED SERVICE QUALITY,
CUSTOMER SATISFACTION AND FINANCIAL PERFORMANCE IN
THE CONTEXT OF BANK ASIA LTD

Submitted by
ID: 0320454

Submitted to
Mr. Samir Mainuddin
Lecturer

August 24th, 2006

August 24, 2006

Mr. Samir Mainuddin

Lecturer, School of Business


Dear Sir,

It is a great pleasure for me to submit the report on “A relational study on automated

service quality and customer satisfaction with the financial performance in the context of

Bank Asia Ltd.”. I am submitting this report as the part of my internship (BBA-499A) in

Bank Asia Ltd. This report will help the organization to find out related factors with their

automated service quality, customer satisfaction and financial performance.

I hope you will asses my report considering the limitations of the study. Your kind

advice will encourage me to do further research in future.

Yours Sincerely


ID # 0320454

Acknowledgement

In the preparation and finalization of this internship report, I acknowledge the

encouragement and assistance given by a number of people and institution. I am most

grateful to the Bank Asia Ltd. (Gulshan Branch) management to give me the opportunity

to complete my internship in their esteemed organization.

I would like to express my gratitude to my Supervisor Mr. Samir Mainuddin for

providing me detailed feedback and advice on this report. He always gave me his

valuable suggestions in making this study as flawless as possible. My deepest

appreciation also goes to Dr. Nadim Jahangir, Dr Arif-Al Mahmood, Mr. Muzahid

Akbar, and Mr Mohammed Imran for their overall support throughout my university life

which helped me making this report a better one.

I also want to render my special thanks to Mr. Syed Iltefath Hussain, First Vice

President & Manager, and Mr. Alamgir Hossain, Assistant Vice President & Sub-

Manager, Bank Asia Ltd. for providing all the support in the organization. Special thanks

go to the account holders and the employees of the Bank, who spared their time

generously, and took the trouble of answering a detail questionnaire and helped me to

complete my study.

Table of contents
Abstract i

1 Introduction 1

2 Problem Statement 1

3 Purpose of the study 3

4 Literature Review 4

5 Research Questions 11

6 Research Hypothesis 11

7 Conceptual Framework 11

8 Operational Definition 12

9 Research Methodology 12

9.1 Research Design 12

9.2 Sampling Method 13

9.3 Survey Instrument 14

9.4 Data Collection Procedure 15

9.5 Data Analysis 15

9.6 Result 16

9.7 Regression analysis 19

9.8 Assessment of the research hypothesis 22

10 Limitations of the Study 23

11 Significance of the Study 24

12 Recommendation 25

13 Conclusion 26

14 Timeline 26

References 27

Appendices 36

INTRODUCTION

Bank Asia symbolizes modern banking with innovative services in Bangladesh. The

Bank provides Online Banking, ATM Support, SMS and Net Banking Services in the

country. The newly developed web application is fully authentic, secured and robust.

This technology based services also provides Fund Transfer through internet,

Debit/Credit Card facility, free SMS message of special type of withdrawal from

customer accounts time to time. Aaaaa aaaaaaaa aaaaaa aaaaaaaaaa aaaaaaaaaa a a a a a a

aaa Bank Asia formed with the Bank Company Act 1991, the rules and regulation issued

by the Bangladesh Bank, the Company Act 1994, the Securities and exchange Rules 1987

and other applicable laws and regulations in 1999. The first Board of Directors of the

bank was constituted with 13 Directors. Aaaaa aaaaaaaa aaaaaa aaaaaaaaaa aaaaaaaaaa a

a a a Bank Asia is gradually setting new standards on banking sector in the matter of

social responsibilities. Bank Asia will meet the cost of ophthalmologic operations for all

children in Bangladesh who are born blind. Bank Asia has introduced scholarship

schemes for the poor and meritorious students of the rural areas for higher studies. Aaaaa

aaaaaThe recent increasing number of private banks in Bangladesh has been an alarming

threat for Bank Asia, and the organizational financial performance seems to be hampered.

Thus Bank Asia wants to investigate the related variables which have significant

relationships with financial performance.

PROBLEM STATEMENT

In an earlier study conducted by Al Hawari and Ward (2005) automated service

quality has been identified to have a significant importance in the financial performance

Automated service quality, customer satisfaction and their relationship with financial performance 2

of a bank. The current study extends the previous study and investigates weather there is

any relationship between automated service quality and customer satisfaction with the

financial performance of a bank in the context of Bank Asia, Bangladesh.

ATM, telephone banking, internet banking, price, and core service, five factors of

automated service quality of a bank are the key components of the financial performance

of a bank. In the general literature, service quality and customer satisfaction have often

been identified as significant predictors of business performance (Duncan and Elliott,

2002; Wiele et al., 2002; Yasin et al., 2004; Yeung et al., 2002). Therefore, this study

explores how perceived quality of automated service and level of customer satisfaction

are related to bank profitability. “Automated service quality” is defined as the customer’s

overall evaluation of the services provided through electronic channels, such as the

internet, telephone and ATMs (Santos, 2003). It is proposed that customer perceptions

and preferences of service quality have a significant impact on a bank’s success.

Analysing markets based on customer perceptions, designing a service delivery system

that meets customer needs, and enhancing levels of service performance are pertinent

objectives for banks to gain and retain a competitive advantage (Brown and Swarts,

1989). Service quality in the broader context has received much attention because of its

obvious relationship with costs, financial performance, customer satisfaction, and

customer retention.

The literature provides an extensive account of the relationships between service

quality, customer satisfaction, and financial performance where face-to-face interaction

between customer and employee is the only focus. Recently, however, technology has

had a remarkable influence on the growth of service delivery options (Dabholkar and


Bagozzi, 2002) and a profound effect on service marketing (Bitner et al., 2000). There are

several competitive advantages associated with the adoption of technology in service

organizations, including the creation of entry barriers, enhancement of productivity, and

increased revenue generation from new services (Fitzsimmons and Fitzsimmons, 1997).

Service quality is one of the main factors that determines the success or failure of

electronic commerce (Santos, 2003). However, automated service quality has tended to

lag behind because practitioners have focused mainly on issues of usability and

measurement of use (Buckley, 2003), with little consideration for the outcomes.

Therefore, this study will investigate weather significant relationship exist among

automated service quality, customer satisfaction and the financial performance in Bank

Asia.

PURPOSE OF THE STUDY

The purpose of the study is to present and test a model, which identifies the

relationship of, automated service quality and customer satisfaction with the financial

performance of the bank.

The rapid development of IT-based technology options advances the need for

research beyond the interpersonal dynamic of service encounters in this technology-

oriented context (Meuter et al., 2000). Parasuraman and Grewal (2000) emphasised the

importance of technology in shaping buyer-seller interactions and recommended further

investigation into the impact of technology, for example, on the service quality-value-

loyalty chain. The quality issues of automated services in the banking context are

becoming important because of their potential influence on: attractiveness, customer


retention, profitability, positive word-of-mouth, and maximum competitive advantages

(Moutinho and Smith, 2000; Nguyen and Leblanc, 1998; Santos, 2003).

Despite the theoretical background underpinning the importance of automated

service quality in customer satisfaction and profitability, empirical research is required to

examine the extent to which it enhances or diminishes these variables in this new context.

Accordingly, this paper will begin with a literature review of current theoretical

arguments, followed by a description of a model, developed by the authors, to show the

relationship between customer perceptions of automated bank services and their

profitability via customer satisfaction. Data collection methods and analysis techniques

will then be explained. The paper will conclude with an examination of the major

research findings, methodological limitations and implications for marketing planning.

The present study aims to identify the relationship of automated service quality and

customer satisfaction with the financial performance of the bank.

LITERATURE REVIEW

Automated Service Quality

There are well-established definitions of service quality within the general personal

interaction environment (Cronin and Taylor, 1992; Parasuraman et al., 1988), but

attention has recently been directed to the e-commerce environment (Santos, 2003). To

date, automated service quality research has been limited to relationship management

rather than the metrics of service quality (Buckley, 2003). Therefore, the current

literature lacks a comprehensive definition of automated service quality. Zeithaml (2002,

p. 135) defined it with specific reference to the internet defining it as “the extent to which


a web site facilitates efficient and effective shopping, purchasing and delivery”. For the

purposes of this research, however, the definition proposed by Santos (2003) has been

adopted, as it provides a more general definition of automated service quality that can be

extended beyond internet-based applications. It is “the

consumers ’ overall evaluation and judgement of the excellence and quality of e-service

offerings in the virtual marketplace”. This is applicable to the current research, as the

internet banking channel is not the only automated service delivery channel in the

banking sector. In addition to internet banking service quality, telephone banking and

ATM service quality are addressed here, within this particular service environment.

Thus, “automated banking service quality” is defined as the customer’s overall

evaluation of the excellence of services provided through electronic networks, such as the

internet, ATM, and telephone banking.

Mols (2000) argued that customer acceptance of new automated channels of service

delivery in banks may bring a dramatic change in the way retail banks build and maintain

close relationships with their customers. The introduction of new automated channels of

service delivery has made customer participation more widely possible (Dabholkar,

1994) and researchers therefore need to adopt new ways to conceptualise automated

service quality, taking into consideration the attributes of all electronic delivery channels

(Dabholkar, 1996; Meuter et al., 2000; Szymanski and Hise, 2000). A number of

marketing scholars identify ATM, internet and telephone banking as the principal

automated delivery channels for retail banking (Joseph and Stone, 2003; Joseph et al.,

1999; Radecki et al., 1997).


In the banking sector, customers tend to use these three different automated service

delivery channels in a complementary way (Dabholkar, 1996). Consequently, building a

relationship with the customer can be developed using any one of them, but more likely

in combination (Lang and Colgate, 2003; Patricio et al., 2003; Ramsay and Smith, 1999).

Customer evaluation of automated service options and their intention to use a particular

option are directly affected by perceptions of the attributes associated with a particular

option (Dabholkar, 1996). Each channel has its own attributes, which differ from the

others. The quality of each automated delivery channel shapes customers’ overall

perception of automated service quality; therefore, each delivery channel has been

considered as a factor in the proposed automated service quality construct rather than an

aggregated measurement. From a customer perspective, price is the most important

motivation for engaging in online purchases and is the most critical comparison lement

(Surjadjaja et al., 2003).

Price is considered as one of the most important determinants of automated service

(Iqbal et al., 2003). Furthermore, research reveals that online consumers are more price-

sensitive than offline consumers. In the sphere of banking, pricing problems associated

with perceptions of unfairness and non-competitiveness, such as fee charges and interest

rates, contribute to bank switching behaviour by consumers (Colgate and Hedge, 2001;

Keaveney, 1995). Consequently, price has been incorporated as an additional factor that

could influence overall customer perceptions of automated service quality.

“Core service” refers to all components of service (Kotler, 1984; Sureshchandar et

al., 2002a) and the basic products being offered and, as such, explains the “what” of a

service (Brogowicz et al., 1990). Core service has features that shape and distinguish


service quality from one service provider to another (Rust and Oliver, 1994; Schneider

and Bowen, 1995). It is an essential component of automated service (Riel et al., 2001),

as the product offerings and product information represent a set of elements that can have

a positive impact on automated service satisfaction levels (Szymanski and Hise, 2000).

Product innovation and knowledge development factors also have a significant effect on

the success of automated delivery channels (Hway-Boon and Yu, 2003). Therefore,

customer perceptions of the variety of products/services offered by a bank will be

considered as another significant factor shaping overall customer perceptions of

automated service quality. This research establishes five factors that influence

customer perceptions of automated service quality in banking services: ATM service,

internet banking service, telephone banking service, core service, and customer

perception of price.

Relationship between automated service quality and financial performance

Service quality is considered a critical measure of organisational performance. It

remains the most important issue in both the marketing literature generally, and service

marketing literature specifically (Jensen and Markland, 1996). The relationship between

service quality and financial performance has been extensively investigated theoretically

and empirically over the past few years in the traditional banking service context

(Bloemer et al., 1998; Cronin and Taylor, 1992; Sureshchandar et al., 2002a; Yavas et al.,

1997).

The literature indicates that profit-oriented service organisations and academic

researchers see service quality as a key driver of profit (Mukherjee et al., 2003).

However, few studies have explored the direct positive link between service quality and


organisational performance in the traditional service context (Duncan and Elliott, 2002;

Yasin et al., 2004). Furthermore, this relationship has not been empirically investigated in

the automated banking context. The viability of automated banking depends upon its

profitability and research has linked the success or failure of automated banking with

service quality (Santos, 2003). Since automated banking quality impacts on the attraction

of bank customers and permits banks to cut costs sharply (Mols, 1998), the quality of the

automated banking services contributes to the improvement of profitability (Moutinho

and Smith, 2000). Therefore, with respect to the effect of automated service quality on

bank profitability, it can be expected that in an automated banking service context,

service quality is positively related to bank financial performance.

Customer Satisfaction

Customer satisfaction is generally defined as a feeling or judgment by customers

towards products or services after they have used them (Jamal and Naser, 2003).

Customer satisfaction in service industries has been approached in two ways; satisfaction

as a function of disconfirmation, and as a function of perception (Davis and Heineke,

1998).

The confirmation/disconfirmation paradigm views customer satisfaction judgments

as the result of consumer perceptions of the gap between their expectation and perception

of actual performance (Parasuraman et al., 1994; Oliver, 1981). However, the

disconfirmation theory has been increasingly criticised by many marketing scholars

(Churchill and Suprenant, 1982; Teas, 1994). In particular, the latter author argued that

the different definitions of expectations and the difficulties with measurement

operationalisation have undermined these models which used


expectation concepts. Thus, there was no consistency in operationalising the expectation

part of customer satisfaction in the literature. Some authors have considered that neither

disconfirmation nor expectation had any effect on customer satisfaction (Cronin and

Taylor, 1994; Churchill and Suprenant, 1982). Some researchers demonstrated a direct

link between actual performance and satisfaction levels (Cadott et al., 1987). However, to

avoid the debate surrounding the nature of the expectation concept in measuring customer

satisfaction, this research has followed an alternative approach, which initially depended

on customers’ actual evaluations of satisfaction, rather than on the gap between

perception and expectations (Cronin and Taylor, 1994; Teas, 1994).

Relationship between customer satisfaction and financial performance

Achieving customer satisfaction is a vital target for most service firms today (Jones

and Sasser, 1995) as it leads to improved profits, word-of-mouth, and less marketing

expenditure (Reichheld, 1996; Yeung et al., 2002). Many empirical studies in the

literature have found a positive relationship between customer satisfaction and financial

performance (Wiele et al., 2002; Yeung et al., 2002; Anderson et al., 1994).

However, the authors found no studies pertaining specifically to financial

institutions. Accordingly, this study will also contribute to knowledge by investigating

this relationship within the automated service quality and banking context. Thus we can

say that in an automated banking service context, customer satisfaction is positively

related to financial performance.

Financial performance

Performance is the outcome of all of the organisation’s operations and strategies

(Wheelen and Hunger, 2002). Measuring performance accurately is critical for


accounting purposes and remains a central concern for most organisations. Performance

measurement systems provide the foundation to develop strategic plans, assess an

organisation’s completion of objectives, and remunerate mangers (Ittner and Larcker,

1998).

Although assessment of performance in the marketing literature is still very

important, it is also complicated (Pont and Shaw, 2003). While consensual measurement

of performance promotes scholarly investigations and can clarify managerial decisions,

marketers have not been able to find clear, current and reliable measures of performance

on which marketing merit could be judged. Two approaches have been adopted in the

literature to measure financial performance.

The first subjectively measures the performance of firms based on their own evaluation

and expectations or comparison with their competitors. The second is objective, based on

the absolute measure of performance such as financial ratios (Appiah-Adu, 1998).

In this study, both measures were used (Pont and Shaw, 2003) because

• Other studies adopting the two approaches found a strong association between

objective and subjective measures of performance.

• Subjective performance measures have been found to be reasonably reliable and

are widely used in international marketing and strategy literature.

• The sole use of objective performance measures, such as growth, is not an

accurate measure of firm performance (Dawes, 1999).

A combination of the two approaches maximises the advantages and overcomes the

weaknesses associated with using one only.


RESEARCH QUESTIONS

This study proposes to investigate the following questions:

1) Is there any significant relationship between Automated Service Quality (ATM,

Telephone Banking, Internet Banking, Price, and Core Service) and the Financial

Performance of a bank in the context of Bank Asia?

2) Is there any significant relationship between Customer Satisfaction and the

Financial Performance of a bank in the context of Bank Asia?

RESEARCH HYPOTHESES

The hypotheses derived from research questions are as follows:

1) There is a significant relationship between Automated Service Quality (ATM,


Performance of a bank in the context of Bank Asia.

2) There is a significant relationship between Customer Satisfaction and the

Financial Performance of a bank in the context of Bank Asia.

CONCEPTUAL FRAMEWORK

Automated Service Quality
ATM
Telephone Banking
Internet Banking
Price
Core Service
Financial Performance

Customer Satisfaction


OPERATIONAL DEFINITION

Measured Variables Operational Definitions

ATM Operationally defined by the Joseph & Stone (2003)

Telephone Banking Operationally defined by the Joseph & Stone (2003)

Internet Banking Operationally defined by the Jun & Cai (2001)

Price Operationally defined by the Colgate & Hedge
(2001)

Core Service Operationally defined by Sureshchandar et al.
(2002a)

Customer Satisfaction Operationally defined by Sureshchandar et al.
(2002b)

Financial Performance Operationally defined by Duncan & Elliot (2002,
2004)

Table: Operational Definition of Measured Variables

RESEARCH METHODOLOGY

Research Design

The conceptual framework illustrates the name of research variables and relationship

within them. In this study, the researchers are going to investigate the relationship

between automated service quality and customer satisfaction with the financial

performance of the bank in the context of Bank Asia.

Research that studies the relationship between two or more variables is also referred

to as a co relational study (Cooper & Schindler, 2003). That is why a co relational

research design has been selected in order to find out the appropriate answers of the

research questions and to test the hypotheses. The model also suggests this type of


design. Here, financial performance is considered as the dependent variable, whereas

automated service quality and customer satisfaction are considered as independent

variable.

To gather data on the research questions, the researchers used questionnaire. The

rationale behind using questionnaire to collect data is:

1) It takes less time to fill up a questionnaire. Therefore, the customers will not be

reluctant in providing accurate data.

2) Personal interview is both time and cost consuming.

3) The data gathered through questionnaire is easy to put in quantitative analysis.

Therefore, questionnaire is the most useful method to collect data for this study.

Sampling Method

There were two different types of population for this study. For this proposed study

the first population was the employees of Bank Asia Ltd. Another population was the

account holders of Bank Asia Ltd.

The sampling frame for the employees was the official register of the employees.

The researcher used systematic sampling to collect the sample for this study. In most of

the previous researches conducted on employees the researcher had used this type of

sampling (Piercy, 1995; Calleya, & Caruana, 1998). The sample size was 100 as in the

previous research which was conducted on the financial performance of banks the

researcher has chosen a sample size of 100 and found effective match (Al-Hawari &

Ward, 2005). Again, in this research the researcher used sample size of 100 because of

time limitation.


The researcher used convenient sampling to collect the second sample. A sample

consisting of 100 individual account holders of Bank Asia Ltd were selected. The reason

behind choosing non-probability sampling is that:

1) If the researcher would have gone for probability sampling for the customers, then

a sample frame would have been needed to collect and from the list, a sample would have

been drawn, which might have been larger enough to meet reasonable time and given

cost. According to Cooper and Schindler (2003), “Cost considerations influence

decisions about the size and type of sample and also the data collection methods.

2) The current researchers are going to extend the study of Al-Hawari and Ward

(2005) in which the previous researchers use the sample size of 100 and find appropriate

results as predicted. Therefore, the current researchers feel the sample size of 100 is safe

to implicate in this research. This was mainly done considering the time and cost factors

behind the research conducted.

Survey Instrument

To gather data the researcher used questionnaires. The questionnaire survey is the

most effective method for this study to collect data for this for the following reasons-

1. Respondent’s anonymity can be maintained.

2. The researcher conducted survey on a total of 200 respondents. It was not

possible to conduct personal interview because of time limitation. Therefore,

questionnaire survey was the most appropriate one for this study.

Structured questionnaires were used in this research to collect data from the

customers. In the questionnaire which was developed, there were six sections such as,

ATM, telephone banking, internet banking, price, core service and customer satisfaction.


ATM was measured by using 4 items developed by Joseph & Stone (2003). Telephone

banking was measured by using 6 items developed by Joseph & Stone (2003). Internet

Banking was measured by using 6 items developed by Jun & Cai (2001). Price was

measured by using 4 items developed by Colgate & Hedge (2001). Core Service was

measured by using 4 items developed by Sureshchandar et al. (2002a). Customer

Satisfaction was measured by using 4 items developed by Sureshchandar et al. (2002b).

All the variables were measured using a 5 point likert scale.

Data Collection Procedure

The present research is a unique one for Bank Asia Gulshan Branch. As a result,

secondary sources of data were not available for the present study. Therefore, the

researcher required primary data to investigate the research questions. To collect data

from the primary sources, the researcher thus used questionnaire survey method.

Data Analysis

Pearson’s Co relational analysis was used to find out whether any relationship exists

between the independent and dependent variables. Correlation analysis is the statistical

tool that can be used to describe the degree to which one variable is linearly related to

another (Levin & Rubin, 1998).

After collecting the data, correlation matrix for the variables were prepared and the

researcher looked for significant correlations. The researcher used Stepwise regression to

test the strength of associations between the study variables.

The Statistical Package for Social Science (SPSS) software was employed to analyze

the data collected from the actual survey.


Results

Reliability Coefficient and Descriptive Statistics

The reliability coefficients, means and standard deviations of all the constructs in the

current study are displayed in Table 2. The coefficient alphas for the different constructs

were computed using the reliability procedure in SPSS (version 12.0). Nunally (1978)

suggested that for early stages of any research the reliability of .50-.60 is sufficient. The

reliabilities of all the constructs in this study found to be above the standard set by

Nunally (1978).

Table 2

Reliability Coefficient and Descriptive Statistics of Automated Service Quality (ATM,
Telephone Banking, Internet Banking, Price, and Core Service), Customer Satisfaction,
and Financial Performance

Scale Number of Alpha M SD

Items

ATM 4 0.824 3.5800 .68154

Telephone Banking 6 0.659 3.4533 0.51251

Internet Banking 6 0.531 3.2517 0.50613

Price 4 0.787 3.1675 0.78981

Core Service 4 0.652 3.3675 0.74489

Customer Satisfaction 4 0.751 3.1650 0.70641

Financial Performance 4 0.533 3.2200 0.59382

Note: n = 100

Mean scores have been computed by equally weighting the mean scores of all the

items. On a five-point scale, the mean score for ATM is 3.58 (sd = 0.68). The mean score


for Telephone Banking is 3.45 (sd = 0.51). The mean score for Internet Banking is 3.25

(sd = 0.50). The mean score for Price is 3.2 (sd = 0.79). The mean score for Core Service

is 3.37 (sd = 0.74).

The mean scores of Automated Service Quality of Bank Asia range from 3.16 – 3.58

indicating that consumers’ perception about the automated service quality of Bank Asia is

above average. The mean score or Customer Satisfaction is 3.16 (sd = 0.70). It suggests

that these customers are more or less satisfied with Bank Asia.

The mean score for the Financial Performance is 3.22 (sd = 0.59). It suggests that the

financial performance of Bank Asia is portrays an acceptable level.

Correlation analysis

A correlation analysis was conducted on all variables to explore the relationship

between variables. Table 3 depicts the bivariate correlation procedure with a two tailed

statistical significance at two different levels, highly significant (p<.01) and significant

(p<.05).

Table 3
Correlation Matrix for Automated Service Quality (ATM, Telephone Banking, Internet
Banking, Price, and Core Service), Customer Satisfaction, and Financial Performance

ATM Tele Int. Price Core Cust. Financial
Banking Banking Service Sat. Per.
ATM 1 .657(**) .196 .301(**) -.112 .475(**) .435(**)

Telephone
Banking 1 .197(*) .356(**) .153 .486(**) .434(**)

Internet
1 .134 -.013 .125 .349(**)
Banking
Price 1 -.071 .539(**) .645(**)

Core Service 1 -.083 .134


Customer
Satisfaction 1 .597(**)

Financial
1
Performance
Note: *p < .05, **p < .01.

The result of correlation analysis for all the variables is shown in Table 3. It

examines the correlations among Automated Service Quality (ATM, Telephone Banking,

Internet Banking, Price, and Core Service), Customer Satisfaction, and Financial

Performance of Bank Asia. According to Rowntree (1981) the the classification of the

correlation “r” is as follows:

0.0 to 0.2 Very weak, negligible

0.2 to 0.4 Weak, low

0.4 to 0.7 Moderate

0.7 to 0.9 Strong, high, marked

0.9 to 1.0 Very strong, very high

It helps interpreting the strength of relationships between variables. The variables,

which had a statistical significant correlation with ATM were Telephone Banking (r =

0.66, p< .01), Price (r = 0.30, p< .01), Customer Satisfaction (r = 0.47, p< .01) and

Financial Performance (r = 0.43, p< .01). Telephone Banking, Customer Satisfaction and

Financial Performance had a moderate correlation with ATM, whereas Price portrayed a

weak correlation with ATM in Bank Asia. Telephone Banking was found to be

significantly correlated with Internet Banking (r = 0.19, p< .05), Price (r = 0.36, p < .01),

customer satisfaction (r = 0.49, p< .01), and Financial Performance (r = 0.43, p< .01).

Customer Satisfaction and Financial Performance of the bank had a moderate correlation

with Telephone Banking. On the other hand Price and Internet Banking predicted weak


and very weak correlation with Telephone Banking simultaneously. The variable

significantly correlated with Internet Banking was Financial Performance (r = 0.35, p<

.01) and it illustrated a weak correlation. Price had a significant and moderate correlation

with Customer Satisfaction (r = 0.54, p< .01), and Financial Performance (r = 0.64, p<

.01). Customer Satisfaction was significantly and moderately correlated with Financial

Performance (r = 0.59, p< .01).

In the case of Core Service no significant correlation was being found with all the

other variables of the organization.

Regression analysis

Both stepwise and entered regression were conducted to asses the relationship

between the study variables.

Stepwise regression

A stepwise regression analysis was performed to identify the relationship between

automated service quality (ATM, Telephone Banking, Internet Banking, Price, and Core

Service), customer satisfaction, and financial performance of Bank Asia.

Table 4
Stepwise regression on Financial Performance
Variables B SE B β R2 ∆R
Step 1 0.416

(Constant) 1.684
Price 0.485 0.645 0.645
Step 2 0.504 0.088

(Constant) 1.200 0.211
Price 0.342 0.064 0.455
Customer
0.296 0.071 0.352
Satisfaction

Step 3
0.564 0.06


(Constant) 0.353 0.305
Price 0.325 0.060 0.432
Customer
0.280 0.067 0.333
Satisfaction
Internet
0.293 0.080 0.249
Banking

Step 4 0.603 0.039

(Constant) -0.226 0.349
Price 0.330 0.058 0.439
Customer
0.290 0.065 0.346
Satisfaction
Internet
0.293 0.077 0.250
Banking
Core Service 0.157 0.052 0.197
Step 5 0.620 0.017

(Constant) -0.457 0.362
Price 0.325 0.057 0.432
Customer
0.237 0.069 0.282
Satisfaction
Internet
0.269 0.076 0.229
Banking
Core Service 0.166 0.051 0.208
ATM 0.130 0.064 0.150

Table 4 represents Price, Customer Satisfaction, Internet Banking, Core Service, and

ATM to have a statistical significant relationship with Financial Performance. Telephone

Banking was excluded from the above regression as it had little or no significant

relationship with Financial Performance. For every additional unit of Price, keeping all

the other variables constant, Financial performance will increase by 0.432 units.

The variable with the most significant relation with financial performance is shown

in Step 1 (Price), which has a coefficient of 0.645. Thus interpreting that, for every

additional unit of Price the Financial performance of the Bank will increase by 0.645


units. The constant suggests that in the first step if Price is zero Financial performance

will be 1.684.

Simultaneously in Step 5 we see all the five variables which has a significant relation

with financial performance. The coefficients (Table 4) here suggest that for every

additional unit of Price, keeping all the other predictors constant, Financial performance

will increase by 0.432 units. Again, for every additional unit of Customer Satisfaction,

keeping all the other predictors constant, Financial performance will increase by 0.282

units. For every additional unit of Internet Banking, keeping all the other predictors

constant, Financial performance will increase by 0.229 units. For every additional unit of

Core Service, keeping all the other predictors constant, Financial performance will

increase by 0.208 units. For every additional unit of ATM, keeping all the other

predictors constant, Financial performance will increase by 0.150 units.

The constant suggests that when all the predictors in step 5 are zero Financial

performance will be – 0.457.

Thus the five predictors together explained 62% of the variance in Financial

Performance. Price, Customer Satisfaction, Internet Banking, Core Service, and ATM

explained about 41.6%, 8.8%, 6%, 3.9% and 1.7% of the Financial Performance

respectively.

Standardized (simultaneous) analysis:

Entered (simultaneous) regression analysis was performed to identify the relationship

between automated service quality (ATM, Telephone Banking, Internet Banking, Price,

and Core Service), customer satisfaction, and financial performance of Bank Asia.


Table 5
Standardized (Simultaneous) Regression on Financial Performance
Variable B SE B β R2
.622
(Constant) -.409 .369
ATM .164 .079 .189
Telephone Banking -.081 .109 -.070
Internet Banking .274 .077 .233
Price .330 .058 .439
Core Service .179 .054 .224
Customer Satisfaction .248 .071 .295

Table 5 depicts that in Bank Asia apart from Telephone Banking the other five

predictors; Price, Customer Satisfaction, Internet Banking, Core Service, and ATM were

found to be statistically significantly related with Financial Performance. Significantly

related five predictors together explained 62%.

Assessment of the research hypothesis

Hypothesis 1:

“There is a significant relationship between Automated Service Quality (ATM,


Performance of a bank in the context of Bank Asia.”

The result of the correlational analysis states that the Automated Service Quality

(ATM, Telephone Banking, Internet Banking, and Price) in Bank Asia was significantly

correlated with their Financial Performance (r = 0.435, r = 0.434, r = 0.349, r = 0.645; p<

.01).

The stepwise regression analysis depicts that in Bank Asia Ltd, Automated Service

Quality (Price, Internet Banking, Core Service, and ATM) was found to be statistically

significantly related with Financial Performance. Price, Internet Banking, Core Service,


and ATM explained 41.6%, 6%, 3.9%, and 1.7% respectively of the Financial

Performance in Bank Asia.

The result of the standardized regression depicts that Automated Service Quality

(ATM, Internet Banking, Price, and Core Service) is positively and significantly

associated with the Financial Performance in Bank Asia. Thus all the results were in

favor of hypothesis 1 and provide support to it.

Hypothesis 2:

“There is a significant relationship between Customer Satisfaction and the Financial

Performance of a bank in the context of Bank Asia”

The result of the correlational analysis states that the Customer Satisfaction was

positively and significantly correlated with their Financial Performance (r = 0.597, p<

.01).

The stepwise regression analysis depicts that in Bank Asia Customer Satisfaction

was found to be statistically significantly related with Financial Performance. Service

Customer Satisfaction explains 8.8% of the Financial Performance in Bank Asia.

The result of the standardized regression depicts that Customer Satisfaction is

positively and significantly associated with Financial Performance in Bank Asia. Thus all

the results were in favor of hypothesis 2 and provide support to it.

LIMITATIONS OF THE STUDY

A limitation of this study is the mix of longitudinal (financial performance) and

cross-sectional (service quality and satisfaction) data. It is difficult to avoid this problem

because of the time limitation. Ideally service quality and satisfaction should be tracked

over the same period as financial performance. However, this limitation had little impact


on results due to the absence of a significant difference among ratios over the five-year

span, reflecting the stability and validity of these ratios.

This paper presents an initial phase of a sustainable research program and as such has

limited itself in terms of research design. First of all, researchers have limited access to

the related literature review due to lack of journals available on the measured variables.

As a result, researchers have limited resources to deal with. Second, data collection is

restricted within Dhaka city only, which may fail to represent the factual scenario of the

relationship between measured variable. Finally, this research was limit to Bank Asia

Gulshan Branch only rather than whole banking sector of Bangladesh. So the researchers

did not have the view on total banking sector of this country, which limits the

generalization of the findings.

SIGNIFICANCE OF THE STUDY

This study is significant for the following reasons: -

1) The findings of this research effort may have practical implications for service

providers that strive to organize their service offerings in order to accomplish their

corporate objectives.

2) The study will help or assist companies to enhance their understanding of the

actual employee service quality to the response to their work climate, so it will be easy

for the companies to make decision regarding internal marketing.

3) This research may encourage further study and provide useful guidelines for these

types of researches.


RECOMMENDATION

It is apparent that the availability of information on web sites (content), accuracy of

online transactions, ease of use, provision of updated information (timeliness),

attractiveness of bank web sites (aesthetics), and security are not the only attributes that

influence customer satisfaction. Accordingly, it is necessary for bank-marketing

strategists to find the other attributes that customers use to judge service quality, such as

navigational and visual characteristics (D’Angelo and Little, 1998), feedback and product

list sections (Lohse and Spiller, 1999), and playfulness (Liu and Arnett, 2000). Moreover,

responding more quickly to customers’ needs and providing customers with the

opportunity to help themselves via web links are other aspects which could improve

standards of internet banking quality. By doing so, banks should be more able to help

customers participate, learn and act, enjoy good two-way communication, and have a

pleasant and enjoyable experience (Rao, 2002).

Ultimately, the main focus of attention for management should be on customer

satisfaction. Identification of the various factors, besides automated service quality, is

critical to overall customer satisfaction. These factors could include traditional service

quality, value, trust, bank reputation, and image (Bloemer et al., 1998; Nguyen and

Leblanc, 1998; Ranaweera and Prabhu, 2003). A better understanding of the sequence of

the relationship between automated service quality, satisfaction, and bank profitability

could help ensure clearer targeting of limited marketing resources (Caruana, 2002). That

is a marketing planning issue.

Finally, bank mangers need to remain up to date with future trends; in other words,

they need marketing intelligence. If automated service quality converges and becomes a


standard and non-differentiated attribute among all banks, it will be easy for customers to

compare and switch from one bank to another (Evans and Wurster, 1997). If so, it will be

difficult for banks to maximize their profits out of the quality aspects of automated

services.

CONCLUSION

In view of the findings, the provision of high standards of automated service quality

and maintaining a significant level of customer satisfaction will lead to improved

financial performance. While this research found that telephone banking had no or little

significant relationship with financial performance, improvement in the quality aspects of

this dimension could enhance overall satisfaction and in turn may boost the financial

performance of Bank Asia Ltd. Finally, this research will encourage further study and

useful guidelines for these types of researches.

TIMELINE FOR THE PROPOSAL WRITING

2006 June Research proposal writing and literature review

2006 July Data collection procedure

2006 August 01 Data analysis and interpretation of findings

2006 August 15 Final redraft of complete manuscript.

2006 August 24 Submission of research paper


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Appendix 1

Research Questionnaire for the Account Holders


Scale items

Question items concerning ATM

1 2 3 4 5

Strongly Disagree Neither Agree Agree Strongly Agree

Disagree Nor Disagree

1. Bank Asia has significant numbers of ATM Booths. 1 2 3 4 5

2. The ATM Booths are at secure locations. 1 2 3 4 5

3. The ATM has a user friendly system. 1 2 3 4 5

4. The ATM functions all the time. 1 2 3 4 5


Question items concerning Telephone Banking

1 2 3 4 5



1. You are exposed to a pleasant musical background. 1 2 3 4 5

2. There are reasonable numbers of voice prompts. 1 2 3 4 5

3. The waiting time is short. 1 2 3 4 5

4. The instructions are clear. 1 2 3 4 5

5. You find the system reliable. 1 2 3 4 5

6. There are sufficient telephone banking options. 1 2 3 4 5


Question items concerning Internet Banking

1 2 3 4 5



1. All needed information are available at the Bank Asia 1 2 3 4 5

website.

2. It is easy to use. 1 2 3 4 5

3. The site provides security. 1 2 3 4 5

4. Transactions are error free. 1 2 3 4 5

5. The website is attractive. 1 2 3 4 5

6. Information are up to date 1 2 3 4 5


Question items concerning Price

1 2 3 4 5



1. Service charges are adequately explaining. 1 2 3 4 5

2. The fees are acceptable. 1 2 3 4 5

3. The fees are competitive. 1 2 3 4 5

4. Bank statements provide clear understanding of the 1 2 3 4 5

service charges.


Question items concerning Core Service

1 2 3 4 5



1. The Bank provides wide range of services. 1 2 3 4 5

2. The service features are diverse. 1 2 3 4 5

3. Most of the service options are available. 1 2 3 4 5

4. The Bank follows the most advanced technology. 1 2 3 4 5


Question items concerning Customer Satisfaction

1 2 3 4 5



1. You ate satisfied with the staff of Bank Asia. 1 2 3 4 5

2. You are satisfied with the physical surrounding of Bank 1 2 3 4 5

Asia.

3. The Bank fees are satisfactory. 1 2 3 4 5

4. The delivery service process meets your needs. 1 2 3 4 5


Appendix 2

Research Questionnaire for the Employees


Question items concerning Financial Performance

1 2 3 4 5



1. Asset utilization of Bank Asia is satisfactory 1 2 3 4 5

2. The Return on Asset for Bank Asia is satisfactory 1 2 3 4 5

3. The Return on Equity for Bank Asia is satisfactory 1 2 3 4 5

4. The business level at which Bank Asia stands is 1 2 3 4 5

satisfactory


Appendix 3

SPSS Outputs


Reliability (ATM)
Warnings

The space saver method is used. That is, the covariance matrix is not calculated or
used in the analysis.

Case Processing Summary

N %
Cases Valid 100 100.0
Excluded
0 .0
(a)
Total 100 100.0
a Listwise deletion based on all variables in the procedure.

Reliability Statistics

Cronbach's
Alpha N of Items
.824 4

Reliability (TELEPHONE BANKING)
Warnings



N %
Excluded
0 .0
(a)
Total 100 100.0


Cronbach's
Alpha N of Items
.659 6


Reliability (INTERNET BANKING)
Warnings



N %
Excluded
0 .0
(a)
Total 100 100.0


Cronbach's
Alpha N of Items
.531 6

Reliability (PRICE)
Warnings



N %
Excluded
0 .0
(a)
Total 100 100.0


Cronbach's
Alpha N of Items
.787 4


Reliability (CORE SERVICE)
Warnings



N %
Excluded
0 .0
(a)
Total 100 100.0


Cronbach's
Alpha N of Items
.652 4

Reliability (CUSTOMER SATISFACTION)
Warnings



N %
Excluded
0 .0
(a)
Total 100 100.0


Cronbach's
Alpha N of Items
.751 4


Reliability (FINANCIAL PERFORMANCE)
Warnings



N %
Excluded
0 .0
(a)
Total 100 100.0


Cronbach's
Alpha N of Items
.533 4

Descriptives
Descriptive Statistics

N Minimum Maximum Mean Std. Deviation
ATM 100 1.75 4.75 3.5800 .68154
Telephone Banking 100 2.17 4.67 3.4533 .51251
Internet Banking 100 2.17 4.67 3.2517 .50613
Price 100 1.50 5.00 3.1675 .78981
Core Service 100 1.50 4.75 3.3675 .74489
Customer Satisfaction 100 1.25 4.75 3.1650 .70641
Financial Performance 100 2.00 4.75 3.2200 .59382
Valid N (listwise) 100


Correlation

Telephone Internet Core Customer Financial
ATM Banking Banking Price Service Satisfaction Performance
ATM Pearson
1 .657(**) .196 .301(**) -.112 .475(**) .435(**)
Correlation
Sig. (2-tailed) . .000 .051 .002 .267 .000 .000
N 100 100 100 100 100 100 100
Telepho Pearson
ne Correlation .657(**) 1 .197(*) .356(**) .153 .486(**) .434(**)
Banking
Sig. (2-tailed) .000 . .049 .000 .128 .000 .000
N 100 100 100 100 100 100 100
Internet Pearson
.196 .197(*) 1 .134 -.013 .125 .349(**)
Banking Correlation
Sig. (2-tailed) .051 .049 . .185 .895 .215 .000
N 100 100 100 100 100 100 100
Price Pearson
.301(**) .356(**) .134 1 -.071 .539(**) .645(**)
Correlation
Sig. (2-tailed) .002 .000 .185 . .481 .000 .000
N 100 100 100 100 100 100 100
Core Pearson
-.112 .153 -.013 -.071 1 -.083 .134
Service Correlation
Sig. (2-tailed) .267 .128 .895 .481 . .413 .185
N 100 100 100 100 100 100 100
Custom Pearson
er Correlation
.475(**) .486(**) .125 .539(**) -.083 1 .597(**)
Satisfact
ion
Sig. (2-tailed) .000 .000 .215 .000 .413 . .000
N 100 100 100 100 100 100 100
Financia Pearson
l Correlation
.435(**) .434(**) .349(**) .645(**) .134 .597(**) 1
Perform
ance
Sig. (2-tailed) .000 .000 .000 .000 .185 .000 .
N 100 100 100 100 100 100 100

** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).

Regression (STEP WISE)
Variables Entered/Removed(a)

Variables Variables
Model Entered Removed Method
1
Stepwise
(Criteria:
Probability
-of-F-to-
enter <=
Price .
.050,
Probability
-of-F-to-
remove >=
.100).

2
Stepwise
(Criteria:
Probability
-of-F-to-
Customer enter <=
.
Satisfaction .050,
Probability
-of-F-to-
remove >=
.100).

3
Stepwise
(Criteria:
Probability
-of-F-to-
Internet enter <=
.
Banking .050,
Probability
-of-F-to-
remove >=
.100).

4
Stepwise
(Criteria:
Probability
-of-F-to-
Core enter <=
.
Service .050,
Probability
-of-F-to-
remove >=
.100).


5
Stepwise
(Criteria:
Probability
-of-F-to-
enter <=
ATM .
.050,
Probability
-of-F-to-
remove >=
.100).

a Dependent Variable: Financial Performance

Model Summary

Adjusted R Std. Error of
Model R R Square Square the Estimate Change Statistics
R Square Sig. F
Change F Change df1 df2 Change
1 .645(a) .416 .410 .45619 .416 69.746 1 98 .000
2 .710(b) .504 .493 .42268 .088 17.156 1 97 .000
3 .751(c) .564 .551 .39797 .061 13.421 1 96 .000
4 .776(d) .603 .586 .38198 .038 9.205 1 95 .003
5 .787(e) .620 .599 .37582 .017 4.139 1 94 .045

a Predictors: (Constant), Price
b Predictors: (Constant), Price, Customer Satisfaction
c Predictors: (Constant), Price, Customer Satisfaction, Internet Banking
d Predictors: (Constant), Price, Customer Satisfaction, Internet Banking, Core Service
e Predictors: (Constant), Price, Customer Satisfaction, Internet Banking, Core Service, ATM

Coefficients(a)

Unstandardized Standardized
Coefficients Coefficients

Model B Std. Error Beta t Sig.
1 (Constant) 1.684 .189 8.891 .000
Price .485 .058 .645 8.351 .000
2 (Constant) 1.200 .211 5.691 .000
Price .342 .064 .455 5.355 .000
Customer
.296 .071 .352 4.142 .000
Satisfaction
3 (Constant) .353 .305 1.160 .249
Price .325 .060 .432 5.380 .000


Customer
.280 .067 .333 4.157 .000
Satisfaction
Internet
.293 .080 .249 3.663 .000
Banking
4 (Constant) -.226 .349 -.647 .519
Price .330 .058 .439 5.699 .000
Customer
.290 .065 .346 4.485 .000
Satisfaction
Internet
.293 .077 .250 3.818 .000
Banking
Core Service .157 .052 .197 3.034 .003
5 (Constant) -.457 .362 -1.263 .210
Price .325 .057 .432 5.691 .000
Customer
.237 .069 .282 3.437 .001
Satisfaction
Internet
.269 .076 .229 3.524 .001
Banking
Core Service .166 .051 .208 3.240 .002
ATM .130 .064 .150 2.034 .045

Excluded Variables(f)

Collinearity
Statistics
Partial
Model Beta In t Sig. Correlation Tolerance
1 ATM .265(a) 3.449 .001 .331 .909
Telephone
.234(a) 2.935 .004 .286 .873
Banking
Internet
.268(a) 3.642 .000 .347 .982
Banking
Core Service .181(a) 2.388 .019 .236 .995
Customer
.352(a) 4.142 .000 .388 .709
Satisfaction
2 ATM .170(b) 2.123 .036 .212 .772
Telephone
.134(b) 1.633 .106 .164 .751
Banking
Internet
.249(b) 3.663 .000 .350 .978
Banking
Core Service .197(b) 2.838 .006 .278 .992
3 ATM .130(c) 1.692 .094 .171 .754
Telephone
.093(c) 1.191 .237 .121 .734
Banking
Core Service .197(c) 3.034 .003 .297 .992
4 ATM .150(d) 2.034 .045 .205 .749
Telephone
.043(d) .550 .584 .057 .695
Banking
5 Telephone
-.070(e) -.751 .455 -.078 .463
Banking
a Predictors in the Model: (Constant), Price
b Predictors in the Model: (Constant), Price, Customer Satisfaction
c Predictors in the Model: (Constant), Price, Customer Satisfaction, Internet Banking
d Predictors in the Model: (Constant), Price, Customer Satisfaction, Internet Banking, Core Service
e Predictors in the Model: (Constant), Price, Customer Satisfaction, Internet Banking, Core Service, ATM
f Dependent Variable: Financial Performance


Regression (SIMULTANEOUS)
Variables Entered/Removed(b)

Variables Variables
Model Entered Removed Method
1
Customer
Satisfaction,
Core
Service,
Internet . Enter
Banking,
ATM, Price,
Telephone
Banking(a)

a All requested variables entered.
b Dependent Variable: Financial Performance

Model Summary

Adjusted R Std. Error of
Model R R Square Square the Estimate Change Statistics
R Square Sig. F
Change F Change df1 df2 Change
1 .789(a) .622 .598 .37670 .622 25.503 6 93 .000
a Predictors: (Constant), Customer Satisfaction, Core Service, Internet Banking, ATM, Price, Telephone
Banking

Coefficients(a)

Unstandardized Standardized
Coefficients Coefficients

Model B Std. Error Beta t Sig.
1 (Constant) -.409 .369 -1.108 .271
ATM .164 .079 .189 2.091 .039
Telephone
-.081 .109 -.070 -.751 .455
Banking
Internet
.274 .077 .233 3.564 .001
Banking
Price .330 .058 .439 5.727 .000
Core Service .179 .054 .224 3.300 .001
Customer
.248 .071 .295 3.510 .001
Satisfaction

Relational Study of Automated Service Quality, Customer Satisfaction and Financial Performance

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