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IMPACT OF INTERNET BANKING ON

CUSTOMER SATISFACTION AND BUSINESS

PERFORMANCE

THESIS

SUBMITTED TO THE UNIVERSITY OF JAMMU

FOR THE AWARD OF THE DEGREE OF

DOCTOR OF PHILOSOPHY

IN

COMMERCE

UNDER THE SUPERVISION OF

Professor R. D. Sharma

BY

Shiffu Abrol

POST GRADUATE DEPARTMENT OF COMMERCE

UNIVERSITY OF JAMMU, JAMMU-180006

2014

Certificate

Certified that Ms. Shiffu Abrol, a registered candidate for the degree of Ph. D. in

Commerce, has completed her research work. The exact title of her thesis is “Impact of

Internet Banking on Customer Satisfaction and Business Performance”. She has

worked under my supervision and the work is worthy of consideration for the award of

degree of Doctor of Philosophy.

It is further certified that:

The title of her thesis has been approved by the Board of Research Studies

(BORS) in Commerce ;

The thesis embodies the work of the candidate herself;

The candidate has worked under my supervision for the period required under

statutes;

The candidate has got one paper, relevant with research, published in national

journal;

The candidate has put in the required attendance and delivered seminars in the

department during the period of research; and

The conduct of the scholar remained quite satisfactory during the research

period.

Professor Hardeep Chahal Professor R. D. Sharma

H.O.D. Supervisor

Department of Commerce Department of Commerce

University of Jammu, University of Jammu,

Jammu. Jammu.

Preface

Customers are the key contributors for the success and survival of any business and this

is the same for banking sector also. So, need arises not only to satisfy the customers but

also to retain them because it may lead to increased profitability and better performance

of banks.

Technology is affecting the life of every individual in the present age and internet

banking is one of the technologies which is fastest growing in banking practice now a

days. Moreover, customers are shifting from traditional banking to online banking very

rapidly because of various benefits such as cost and time effectiveness. Hence, it is

required to study carefully the increasing significance of internet banking, with its

impact on customer satisfaction and business performance. The study has been

completed under six chapters.

The first chapter deals with the conceptual analysis and historical overview of internet

banking and various factors that affect their customer satisfaction.

In the second chapter, literature has been reviewed both theoretically as well as in

tabular form. Thorough review of literature generated the research gap to be studied.

The third chapter presents details about the research design and methodology followed

in the study. It includes formulation of hypotheses on the basis of core studies,

generation of scale items, data collection technique, data purification, reliability, validity

and limitations of the study.

Fourth chapter presents the analysis of the data gathered from bank managers,

hypotheses testing and major findings. This chapter also present the evaluative analysis

of business performance.

Fifth chapter presents the analysis of the data gathered from online banking customers,

its hypothesis testing and major findings.

The last chapter comprises of major findings, perceptual gap between private and public

sector bank managers, private and public sector bank customers and further perceptual

gap between customers and managers and managerial implications.

The study is expected to be useful to all the concerned including researchers and policy

makers.

Shiffu Abrol

Acknowledgement

I acknowledge my deep sense of gratitude and sincere regards to my advisor Prof. R. D.

Sharma for his guidance, caring, patience, help and providing me with an excellent

atmosphere due to which I have been able to complete my research work. The guidance

and support, which I received from my guide shall always be a source of inspiration in

my future ambitions. I appreciate all his contributions of vast knowledge, active interest,

constant encouragement and inspiration to make my Ph. D. experience productive and

stimulating.

I am grateful to my respondents for sparing time out of their busy schedule.

My sincere gratitude to all the faculty members of Department of Commerce, University

of Jammu, Jammu for their valuable assistance and advice at every stage of my work.

I am also thankful to our Lab Assistant Miss Pooja, Librarian Mrs. Jyoti Devi, non

teaching employees of the department. My acknowledgement would be incomplete if I

do not thank to all my friends who assisted me in many respects in the completion of my

work.

I am really short of words to express my very sincere thanks to my loving parents whose

blessings are always with me and especially my loving mother in law Mrs. Promila

Sahdev, who has been so caring and supportive to me all the time. I am also grateful to

my brother in law Navneet Sahdev for supporting me during my research work.

The highest moral and physical support for research comes from my beloved Soul Mate

Puneet, who always encouraged me for my studies. I also want to thank my sweet

daughter Lareina, for her never unending support and love.

I am dedicating my thesis work to my Soul Mate Puneet and my daughter Lareina.

Finally, I am grateful to almighty God, who has always blessed me with heaven choicest

blessings and his prime power that the research got successfully accomplished.

I also take pledge to work for the good of mankind and help others.

Place: Jammu (Shiffu Abrol)

Date:

List of Tables

Table No. Title Page No.

2.1 Summary of Literature Reviewed in Tabular Form 28

3.1 Generation of Scale Items in the Schedule I for Data from

Bank Managers

74

3.2 Generation of Scale Items in the Schedule II for Data from

Customers

74

4.1 Demographic Profile of Bank Managers 130

4.2 Process of Data Reduction 130

4.3 Factorial Profile of Data Gathered From Bank Managers 131

4.4 Demographic Profile wise ANOVA Results 133

4.5 Demographic Group Wise Mean Values 133

4.6 Bank wise ANOVA Results 134

4.7 Bank wise cum Factor wise Mean Values 134

4.8 Summary of Regression Analysis Showing Impact of

Different Dimensions and Factors on Customer Satisfaction,

Customer Commitment and Business Performance

135

4.9 Results of Various CFA fit Indices 135

4.10 Reliability and Validity of Latent Constructs 136

4.11 Split half Reliability 136

4.12 Discriminant Validity of Latent Constructs 136

4.13 Various Stages of Structural Modelling 137

4.14 Results of Hypothesis Testing Through SEM 137

4.15 Profitability Measures of Jammu and Kashmir Bank (JKB) 137

4.16 Profitability Measures of Housing Development Finance

Corporation (HDFC Bank)

138

4.17 Profitability Measures of Industrial Credit and Investment

Corporation of India (ICICI Bank)

138

4.18 Profitability Measures of State Bank of India (SBI) 139

4.19 Profitability Measures of Punjab National Bank (PNB) 139

4.20 Profitability Measures of Union Bank of India (UBI) 140

4.21 Profitability Measures of Canara Bank 140

4.22 Bank wise Objective and Subjective Comparison of Business

Performance

141

5.1 Demographic Profile of Bank Customers 171

5.2 Process of Data Reduction 171

5.3 Factorial Profile of Data Gathered From Bank Customers 172

5.4 Demographic Profile wise ANOVA Results 176

5.5 Age and Qualification wise Analysis of Internet Banking

Customers

177

5.6 Occupation, Income and Length of Association wise Analysis

of Internet Banking Customers

178

5.7 Results of Various CFA fit Indices 179

5.8 Reliability and Validity of Latent Constructs 179

5.9 Discriminant Validity of Latent Constructs 179

5.10 Various Stages of Structural Modelling 180

5.11 Results of Hypothesis Testing 180

6.1 Perceptual Gap Between Private and Public Sector Bank

Managers

196

6.2 Perceptual Gap Between Private and Public Sector Bank

Customers

197

6.3 Perceptual Gap Between Online Customers and Bank

Managers

198

List of Figures

Fig. No. Title Page No.

4.1 Measurement Model of Perceived Usefulness 107

4.2 Measurement Model of Trust 108

4.3 Measurement Model of Customer Satisfaction 109

4.4 Measurement Model of Commitment 110

4.5 Measurement Model of Profitability 110

4.6 Structural Equation Model of Online Banking From Managers

Perspective

114

5.1 Measurement Model of Service Quality 162

5.2 Measurement Model of Trust 163

5.3 Measurement Model of Perceived Usefulness 164

5.4 Measurement Model of Customer Satisfaction 165

5.5 Structural Equation Model of Customer Satisfaction in online

Banking

169

List of Abbreviations

AGFI Adjusted Goodness of Fit Index

ATM Automated Teller Machine

CB Canara Bank

CFA Confirmatory Factor Analysis

CFI Comparative Fit Index

CR Critical Ratios

CV Communality Values

EFA Exploratory Factor Analysis

FL Factor Loadings

GFI Goodness of Fit Index

HDFC Housing Development Finance Corporation

ICICI Industrial Credit Investment Corporation of India

ICT Information and Communication Technology

IME Internet Mediated Environment

IT Information Technology

JKB Jammu and Kashmir Bank

KMO Kaiser Meller Olkin

MI Modification Indices

MVA Market Value Added

NEFT National Electronic Fund Transfer

NFI Normed Fit Index

PEOU Perceived Ease of Use

PNB Punjab National Bank

PU Perceived Usefulness

RBI Reserve Bank of India

RMR Root Mean Square Residual

RMSEA Root Mean Square Error of Approximation

ROA Return on Asset

ROE Return on Equity

RTGS Real Transfer Gross Settlement

SBI State Bank of India

SQ Service Quality

SRW Standardised Regression Weight

TAM Technology Acceptance Model

UBI Union Bank of India

Index

Contents Page No.

Certificate i

Preface ii

Acknowledgement iii

List of Tables iv-v

List of Figures vi

List of Abbreviations vii-viii

1) Impact of Internet Banking on Customer Satisfaction

and Business Performance- A Conceptual Analysis 1-21

2) Review of Literature 22-69

3) Research Design and Methodology 70-90

4) Impact of Internet Banking on Business Performance 91-145

5) Impact of Internet Banking on Customer Satisfaction 146-184

6) Strategy for Online Customer Satisfaction and Business

Performance 185-200

Bibliography 201-221

Annexures 222-233

Chapter 1

Impact of Internet Banking on

Customer Satisfaction and

Business Performance: A

Conceptual Analysis

Chapter 1

Impact of Internet Banking on Customer Satisfaction and Business

Performance: A Conceptual Analysis

Contents Page No.

1.1 Background 1

1.2 Internet Banking 1

1.3 Trust 2

1.4 Service Quality 3

1.5 Perceived Ease of Use 5

1.6 Perceived Usefulness 6

1.7 Customer Satisfaction 8

1.8 Commitment 10

1.9 Business Performance 12

1.10 Conclusion 14

References 15

1

CHAPTER-1

IMPACT OF INTERNET BANKING ON CUSTOMER

SATISFACTION AND BUSINESS PERFORMANCE: A

CONCEPTUAL ANALYSIS

1.1 Background

Before initiating on „Impact of internet banking on customer satisfaction and business

performance‟ an attempt has been made to summarise and synthesise the three most

relevant concepts of the study viz. internet banking, customer satisfaction and business

performance. This chapter summarises the important dimensions that directly or

indirectly measure the impact of internet banking on customer satisfaction and business

performance. These dimensions are- trust, service quality, perceived ease of use,

perceived usefulness and commitment.

1.2 Internet Banking

Technology is affecting the life of every individual both qualitatively and quantitatively

in the present age. The quick expansion of information technology has imbibed into the

lives of millions of people and introduced major changes in the worldwide economic

and business atmosphere. Technological developments in the banking sector have

speeded up communication and transactions for clients (Booz et al., 1997). Internet

banking is one of the technologies which is fastest growing banking practice now a

days. It is defined as the provision of information or service by a bank to its customers

over the internet. It is viewed as a supplemental channel used in conjunction with other

channels to provide the convenience of banking anytime from one‟s home or work,

without having to incur some of the costs associated with a branch visit like going to

the branch or waiting on lines. Online banking eliminates physical and geographic

boundaries and time limitations of banking services (Yang et al., 2007). Also as

compared with traditional banking labour is replaced by machine very significantly

(computer networks) which is low in cost and is available easily 24/7 (Wu et al., 2006).

E-banking services first emerged in the early 1990‟s, when credit card, ATM, and

telephone banking services were three major applications. During the last decade,

database, information system and other technologies were applied into banking services

at different levels. After the availability of internet facility, e-banking services are now

conducted through a secure website operated by local banks and includes online

2

enquiry, e-payments, e-transfer etc. There are two general business models to provide

online banking facilities to its customers- First one is, incumbent bank also known as

„bricks and clicks‟ model, applying online banking as an enhancement to its traditional

banking sector and integrating branches, ATM, call centres and online service into a

whole system and using e-banking as a new channel of delivering services. Whereas the

another one is known as direct bank or virtual bank or internet primary bank with no

branch offices but using internet, telecommunication network and wireless networking

to provide banking services (Xu and Zhao, 2000). Thus, providing online facility by

banks is increasingly becoming a „need to have‟ than a „nice to have‟ service (Ganesan

R. and Vivekanandan K., 2009). In India ICICI bank was the first to initiate online

banking revolution as early as 1998 under the brand name „Infinity‟. But in the current

scenario, every bank in India has the internet banking facility. Moreover, these banks

are extending their presence in rural areas also to lure more customers by educating

them with new advancement in information technology.

1.3 Trust

Service is an act or performance that one party offers to another which is essentially

intangible and does not result in the ownership of anything. Because of the service

feature of intangibility, consumers are often faced with the problem of not knowing

what to expect of a service until they consume it and hence perceive service as risky

(Coulter and Coulter, 2002). Thus, need for trust arises as it is the management of risk,

uncertainty and vulnerability and includes reliability, honesty, predictability, mutuality,

expectation where a partner is equally committed (Tayler and Stanley, 2007). Internet is

a competitive and technologically developed market presenting enormous challenges to

the banks for maintaining relations with their clients. Trust and security received

special attention in the marketing literature due to the notable influence that it has on

the attainment of long-lasting and profitable relationships (Morgan and Hunt, 1994). It

is also very important aspect in the provision of electronic services for e-commerce

environments, especially those involving directly the user‟s activities like e-bank

(Furnell and Karweni, 1999). Thus, customers perceive trust as a great challenge to

internet banking and other electronic commerce forms that include sensible

information. Trust is a very complex and multidimensional phenomenon. Traditionally

it is defined as a group of beliefs held by a person derived from his perceptions about

certain attributes. Trust is habitually related to security and risk avoidance (Stewart et

3

al., 2001). It is the trait of trusting and believing in the honesty and reliability of others.

Similarly in online context, security issue is crucial as it involves directly the user‟s

activities who have few tangible and verifiable clues regarding the service provider‟s

capabilities and intentions (Urban et al., 2001). Hence, trust in online transactions is

defined as the subjective probability with which customers believe that an online

transaction with a web retailer will occur in a manner consistent with their expectations

(Stewart et al., 2001). There are many factors which will affect customer trust in online

banking. The antecedents of trust in online banking are trusting beliefs, familiarity,

disposition of trust, institutional based trust (structural assurance and situational

normality), reputation and perceived site quality. The trusting beliefs (trust in online

banking), include benevolence, competence and integrity (Mc Knight and Chervany,

2002), which will directly relate to the trusting intentions (the intention to continue

using online banking services).

1.4 Service Quality

The digital revolution has undoubtedly changed almost every aspect of daily life as we

stepped into the twenty first century. The power of the World Wide Web and global e-

commerce is becoming more significant with the increasing number of people around

the world getting connected to the internet (Siu and Mou, 2005). There are several

competitive advantages associated with the adoption of technology in service

organisations which include the creation of entry barriers, enhancement of productivity

and increase of revenue generation from new services (Fitzsimmons and Fitzsimmons,

1997). However, developments in information and communication technology have

provided a platform by which banks can design, develop and deliver services that can

be perceived by customers as superior while accessing online channel for banking

transactions (Surjadjaja et al., 2003). Service quality is one of the main factors that

determines the success or failure of electronic commerce (Santos, 2003). It is very

important component in any banking business. Service quality is the difference between

customer expectations for the service encounter and the perceptions of the services

received (Oliver, 1980). Service quality can also be defined as „the consumer‟s overall

impression of the relative inferiority/superiority of the organisation and its services‟

(Bitner et al., 1990). Accordingly service quality is defined as how well a delivered

service level matches customer expectations. Customers perceive the quality of services

of online banking based on the performance of online delivery systems and not on the

4

processes in which the delivered service is developed and produced. Numerous studies

were carried out to conceptualise the service quality concept. It can also be defined by

the practitioners in terms of key dimensions that customers use while evaluating the

services (Lewis and Booms, 1983). The conceptualisation of service quality should

include both the service delivery process (Parasuraman et al., 1995) as well as the

service outcomes (Lehtinen and Lehtinen, 1991). In the early 1980s Nodic model was

proposed by Gronroos (1984) which defined the dimensions of service quality and

these include technical quality (what consumers get), functional quality (how consumer

gets the services) and corporate image (how consumer perceives the firm and its

services). Similarly, Lehtinen and Lehtinen (1991) offered another model with three

dimensions of service quality viz. physical, interactive and corporate dimensions.

Physical quality is about the quality of physical products involved in service delivery

and consumption interactive dimension refers to the interaction between the customers

and the service organization‟s employees. Corporate quality refers to the corporate

image as perceived by the customers. E-SERVQUAL measures website e-SQ as

perceived by customers. It is a method for measuring website e-SQ that is based on the

same principle as the original SERVQUAL method and includes some dimensions

similar to those of SERVQUAL. The E-SERVQUAL scale contains a core and

recovery scale, represented by four and three dimensions respectively. Core scale is

used to measure the customer‟s perceptions of service quality delivered by online

retailers. Recovery scale refers to specific situations, when a customer has a question or

runs into a problem (Zeithaml et al., 2002). In simpler terms, core scale refers to the

quality of the website itself, while the recovery scale is more concerned with the actual

performance of the company, rather than with website performance. Zeithaml (2002)

identifies the need for businesses to focus on e-services in their e-business, and to

understand the importance of e-service quality as a differentiating strategy. Businesses

also need to recognize that the web experience presents the brand positioning to online

consumers, and may be an important element in the establishment of trust and

relationships with customers (Zeithaml et al., 2002). The measurement tool developed

by Parasuraman, Zeithaml and Berry in 1985 to measure service quality includes ten

dimensions viz, tangibility, reliability, responsiveness, communication, access,

competence, courtesy, credibility, security and understanding which were later in 1988

reduced to five dimensions viz, tangibles, reliability, responsiveness, assurance and

empathy to measure service quality. However Zeithaml et al., 2000 provided a

5

comprehensive concept of online service quality based on pre and post service aspects.

According to them e-service is the extent to which a website facilitates efficient and

effective shopping, purchasing and delivery of products and services to users and

consumers and includes dimensions such as access, ease of navigation, security/

privacy, responsiveness, trust/assurance, site aesthetics and price knowledge, which are

significant indicators of online service quality. Further Lociacano et al., (2000)

established a scale called WEBQUAL with twelve dimensions viz. information fit to

need, interaction, trust, response time, design, intuitiveness, visual appeal,

innovativeness, flow, integrated communication, business process and substitutability.

Later Yang, Peterson and Huang in 2001 expressed online service quality to be the

function of six elements namely ease of use, content, accuracy of content, timeliness of

response, aesthetics and privacy. Wolfinbouger and Gilly (2002) have established four

dimensions namely website design, reliability, privacy/security and customer service

and found that reliability and fulfilment are the strongest predictors of customer

satisfaction and commitment. Thus, continuous improvements in the information

technology have enabled banks to provide their services in a more direct manner to

adjust their products better to the clientele‟s needs. Although banking has always been

an information business, until now information technology was mainly used to

automate administrative processes. The shift from automating to informating-using

information and its flow to inform managers provides opportunities to track a

customer‟s behavior and respond at the right time. By making effective use of these

opportunities, banks are able to transfer a great deal of transactions from branch offices

to a call-centre. Accessibility has been extended through technological developments as

well as with the introduction of new service delivery methods that allow consumers to

do business with service firms from the home and office.

1.5 Perceived Ease of Use

The internet and World Wide Web (WWW) offer bankers and customers an

opportunity with innovative new virtual environment that can hopefully stimulate and

enhance their learning and operative process. The customer intention to adopt a new

technology is primarily determined by the ease of use of the technology (Davis, 1989;

Davis et al., 1989). Perceived ease of use has been an important factor in studying

information technology acceptance and internet and World Wide Web adoption being

no exception. It refers to the degree to which a person believes that using a particular

6

system would be free of effort. This follows from the definition of „ease‟ which means

freedom from difficulty or great effort (Radner and Rothscheld, 1975). It can also be

defined as the degree to which an innovation is perceived not to be difficult to

understand, learn or operate (Rogers, 1983). Further Rogers (1983) stated that

perceived ease of use is the degree to which consumers perceive a new product or

service as much better than its substitutes. Moreover Zeithaml et al., (2002) stated that

perceived ease of use is the degree to which an innovation is easy to understand or use.

In the context of online banking, ease of use may refer to be easy to remember URL

address, a well organised format, easy site navigability and concise and understandable

contents, terms and conditions (Santos, 2003). Perceived ease of use is the consumer

perception that banking on the internet will involve a minimum of effort (Mathieson,

1991). Further, Consult (2002) noted that perceived ease of use refers to the ability of

customers to experiment with new innovation and evaluate its benefits easily. He also

states that the drivers of growth in electronic banking are determined by the perceived

ease of use which is a combination of convenience provided by those with easy internet

access, the availability of secure, high standard electronic banking functionality and the

necessity of banking services. Hence perceived ease of use is an important measure of

customer satisfaction, system adoption or information systems success (Moore and

Benbasat, 1991) and has been studied extensively in the context of information

technology adoption and diffusion. In applying this construct in online banking context,

banks should focus on website navigation and applicable functions to cater needs of

their users so that an application perceived easier to use by users than another is more

likely to be accepted by them and enhances their intention or willingness to use the

technology. If the system of using an online channel for banking transactions does not

outweigh customer deprival occasioned by factors such as impersonal communication,

technical difficulties and learning efforts, the customer may simply switch its patronage

back to traditional channel. Thus, it is apparent that a channel which is easy to use can

play a pivotal role in customer satisfaction with online banking services (Davis et al.,

1989).

1.6 Perceived Usefulness

Information technology rapidly changes the fabrics of industrial growth and

development these days and thus internet banking has become more and more

diversified and complex. Specialising is unlimited, speedy and convenient services

7

through internet banking. Moreover traditional banking in many countries including

India (Lichtenstein and Williamson, 2006) has created challenges before the bankers.

There are several factors that predetermine the consumer attitude towards internet

banking such as demographic background, motivation and behaviour towards different

banking technologies and individual preferences and expectations of new technology

(Rahmath and Abdullah, 2011). Customer attitudes towards internet banking are

influenced by the prior experience of computer and new technology (Laforet and Li,

2005) and other environmental factors (Davis, 1989). The adoption of internet banking

as a new channel for banking transactions forces customers to consider concerns about

password integrity, privacy, data encryption, hacking and the protection of personal

information (Benmati and Serva, 2007). In fact perceived usefulness, security and

privacy are the main influencing factors to accept internet banking system to conduct

banking transactions (Qureshi et al., 2008). Perceived usefulness is one of the important

components of Technology Acceptance Model (TAM) which has been widely studied

by information system researchers (Davis, 1989) and found the system enhancing job

performance of users (Alsajjan and Dennis, 2009). Usefulness refers to user‟s

assessment of the likelihood that the information will enhance their decision. It is the

subjective probability that use of internet in banking transactions would improve the

way a user could complete a given task (Laforet and Li, 2005). Further according to

Davis et al., 1992, perceived usefulness refers to consumer‟s perception regarding the

outcome of the experience. Mathwick et al., (2001) defined perceived usefulness as the

extent to which a person deems a particular system to boost his or her job performance.

Pikkarainen et al., (2004) found perceived usefulness as a determinant of actual

behaviour which encouraged the users of twenty first century banking to use more

innovative and user friendly self service technologies that give them greater autonomy

in performing banking transactions, in obtaining information on financial affairs and in

purchasing other financial products. However, Gerrard and Cunningham (2003) noted

that the perceived usefulness depends on the banking services offered such as checking

bank balances, applying for a loan, paying utility bills, transferring money abroad and

obtaining information on mutual funds. Users may use information technology because

it is appropriate for the job rather than it is convenient or useful (Goodhue and

Thompson, 1995). Thus if the functions of internet banking support are appropriate for

the user‟s job, they will use the technology. Goodhue and Thompson (1995) further

suggest two important points which influence users to use the internet technology. First,

8

it must be appropriate for the given job and secondly individual characteristics are

important because what is appropriate is determined by individuals. The concept of

absorptive capacity, consisting of three components, was proposed by Cohen and

Levinthal (1990) and has been used in many areas such as management strategies,

organisational learning and information technology acceptance. The first component is

prior knowledge which provides the basis of assessing the value of new knowledge.

The second component is knowledge internalisation ability, which internalises new

knowledge by combining it with knowledge one already has. The third and last

component is knowledge utilisation ability with which individuals can apply new

knowledge to their jobs. Thus, if we apply this absorptive capacity to internet banking,

people can use internet banking if they have prior knowledge of using computers and

the actual ability to utilize it. Perceived usefulness may increase customer loyalty,

adoption of recommendation provided by intelligent agents and intention to buy (Tam

and Ho, 2006). Hence, perceived usefulness has become a key predictor of user‟s

attitudes and intention to use a technology. As a consequence, the greater the perceived

usefulness of using electronic banking services, the more likely that electronic banking

will be adopted (Polatoglu and Ekin, 2001).

1.7 Customer Satisfaction

In any “business to customer” (B2C) type of environment, satisfying a customer is the

ultimate goal of business. It is an important theoretical as well as practical issue for

most marketers and consumer researchers because organisations sometimes do not

really understand what actually goes on in customer‟s mind (Fournier and Mick, 1999).

The concept of customer satisfaction is equally important for service organisations,

such as banks, as many of them subscribe to the fact that higher customer satisfaction

will lead to greater customer loyalty (Boulding et al., 1993) which in turn leads to

future revenue. „Customer satisfaction‟ not only means a happy customer but rather

more than that. The concept of customer satisfaction is a synthesis of two distinct

words i.e customer and his/her satisfaction. In common language, the word „customer‟

means a buyer who purchases a product or avails a service from another. „Satisfaction‟

occurs when one gets what one needs, desires, expects, deserves or deems to be one‟s

entitlement. Oliver (1980) defines customer satisfaction as product performance

equivalent to customer expectation. Oliver (1981) expressed satisfaction as a

psychological state resulting from a process of emotional and cognitive evaluation.

9

According to Hansemark and Albinsson (2004), satisfaction is an overall customer

attitude towards a service provider, or an emotional reaction to the difference between

what customers anticipate and what they receive, regarding the fulfilment of some

need, goal or desire. Kotler (1997) defined satisfaction as a person‟s feeling of pleasure

or disappointment resulting from comparing a product‟s perceived performance (or

outcome) in relation to his or her expectations. Further customer satisfaction is a

collective outcome of perception, evaluation and psychological reaction to the

consumption experience with a product or service. Haoyer and Mach Innis (2001)

expressed that satisfaction can be associated with the feelings of acceptance, happiness,

relief, excitement and delight. In a competitive marketplace, where businesses compete

for customers, customer satisfaction is seen as a key differentiator and increasingly has

become a key element of business strategy. It can also be defined as a global issue that

effects all organisations irrespective of their size, whether profit or non-profit, local or

multinational companies that have a more satisfied customer base along with higher

economic returns. Boulding et al., 1993 in turn, showed that satisfaction has a

significant effect on purchase intention. For instance, if customers are satisfied with a

particular service offering after its use, they are likely to engage in repeat purchase and

try in building line extensions (East, 1997). In availing services, there are two general

conceptualisations of satisfaction, namely, the transaction specific satisfaction and the

cumulative satisfaction (Boulding et al., 1993; Yi and La, 2004). Transaction specific

satisfaction is the customer‟s very own evaluation of his or her experience and reaction

towards a particular service encounter (Boshoff and Gray, 2004). This reaction is

expressed by the customer who experiences a product or service for the first time. On

the other hand, cumulative satisfaction refers to the consumption experience to date

(Johnson et al., 1995), an own accumulation of contacts with services provided to them.

Thus, it is from this accumulation that customer‟s establish a personal standard which is

used to gauge service quality. The proliferate use of technological convenience offered

by service providers has promoted interest in its effect on customer‟s overall

satisfaction and has given two more conceptualisation of customer satisfaction. These

are human encounter satisfaction and technological encounter satisfaction (Bitner et al.,

2000). The human encounter satisfaction, which a customer derives from an interaction

with an employee of the company, plays an important role in consumer‟s overall

satisfaction with the services of the organisation whereas technological encounter

satisfaction means the satisfaction a customer derives from the interaction with the

10

technology of the company, which plays an important role in consumer‟s overall

satisfaction. Thus, it can be inferred that satisfaction is not simply an overall evaluation

of a service experience, but an influence of different components of the service (Dixit

and Datta, 2010). The boom of internet and electronic banking has evoked several

research efforts aimed at understanding service satisfaction in relation to virtual

business environment (Yang and Peterson, 2004). Thus, the unique characteristics of

internet based services are extensive human- computer interactions and high level self

service may imply that customers perceive satisfaction from online services differently

when contrasted with their offline counterparts (Ribbink et al., 2004). With the growing

trend of information technology in banking sector, customers prefer to deal online with

their bank because of the rising trend of technology effecting quality and customer

satisfaction. Moreover, online banking facilitates cost-effective decision thinking and

applications on the part of the e-bank‟s operations and IT managers to enhance

customer service quality, develops trust in customers and boosts market share in this

expanding but increasingly competitive business area. It thus generates customer

satisfaction and also customer commitment (Liao and Cheung, 2008).

1.8 Commitment

Similar to trust, commitment is one of the most important variables for understanding

the strength of marketing relationship. Marketing relationship refers to marketing

activities that attract, develop, maintain and enhance customer relationship (Berry and

Parasuraman, 1991) for sustainable better business. It has changed the focus of

marketing orientation from interacting for short term, discrete transactional customers

to retaining long lasting intimate customer relationships. More specifically in the

banking context, marketing relationship refers to the relationship banking where it is in

the interest of the banks to establish and maintain long term bonds with their customers

and make them committed so that they can conduct their financial transactions with

their respective banks on regular basis (Ritter, 1993). Relationship banking is also an

important construct in online banking transactions. Moorman et al., (1992) define

relationship commitment as an enduring desire to maintain a valued relationship. Their

valued relationship corresponds with the belief that relationship commitment exists

only when the relationship is considered important for meaningful and long term

business. Priluck (2003) found committed customers more loyal to the organisation and

thus they may be retained by that organisation even when dissatisfied. Dwyer et al.,

11

(1987), Morgan and Hunt (1994) defined commitment as an essential ingredient for

successful long term relationship between customers and banks and it also involves

moral duty to cooperate with customers. It is a desire to have a continual relationship

and an effort to ensure its continuance or as a pledge for relational continuity between

exchange partners (Dwyer et al., 1987). It can also be defined as a psychological

sentiment of the mind through which an attitude concerning continuation of

relationship between banks and customers is formed. Similarly in the context of

internet banking, commitment can be defined as a psychological state that the user

maintains with a website, statement characterising his/her relationship with the site

having implications for the level of maintenance of the same or not, corresponding to

an affective or calculative commitment of the surfer to the site (Boulaire and Mathieu,

2000). Commitment can be affective or normative and calculated and identity. The

affective commitment refers to the customer‟s emotional attachment with the bank site

and can result from experience on the internet and through a site and the immediate

emotional gratification that it brings. In contrast normative commitment derives from a

person‟s sense of moral obligation towards the site (Allen and Meyer, 1990). Two sub

dimensions characterise affective commitment: the symbolic dimension and the

hedonistic dimension of the site. Whereas calculated commitment refers to the

cognitive process by monitoring the surfer to reach the outcome, the decision to

continue his relationship with a site and arises from convenience, such as 24 hour

access, no geographic limitation, speed of service and transaction automation. In this

perspective, the calculated commitment is characterised by three sub dimensions: the

absence of alternatives, satisfaction with the chosen site and then switching cost. Also

identity commitment to technology refers to the value that consumers place on being

perceived by others as a technologically competent individual and motivates them to

clarify vulnerabilities and substantiate the capabilities of electronic channels (Stryker

and Serpe, 1994). Thus, three forms of commitment arises: a commitment based on

emotional attachment that develops in the relationship between the surfers and the site

that expressing the emotions felt during the browsing experience and is more important

than calculated dimension which depends on the number of alternatives and switching

costs and also identity commitment which arises from social ties. Hence, customer is

committed to deal online with the bank if the bank has proved to be trustworthy and

able to offer solutions that successfully support the value generating processes of the

customer. Also for achieving customer commitment, bank‟s strategy must be customer

12

centred, long term and be based on mutual relationship benefits (Kassim and Abdullah,

2006). Chung and Kim (2003) note that online commitment is often seen as the

intention to revisit the site, intention to buy on the site and intention to recommend

others to visit the site. It is considered as an overall assessment resulting from

satisfaction and is defined as an intention to maintain valued relationship with the

bank‟s site.

1.9 Business Performance

The internet has altered the way in which many industries conduct business. Banking is

no exception to this as technology and innovative thinking changed the design and

delivery of banking services. These days banks use websites as a competitive tool to

attract new customers, improve service quality and boost overall financial performance

through regular feedback. The field of business performance measurement lacks

cohesive body of knowledge (Marr et al., 2002). Business performance measurement

from operations perspective is mainly perceived as a set of metrics used to quantify

both the efficiency and effectiveness of actions (Neely et al., 1995). From Strategic

control perspective, two different aspects of a business performance measurement can

be identified, on the one hand it reflects the procedures used to cascade down those

performance metrics used to implement strategy within the organisation (Gates, 1999).

On the other hand, a business performance measurement system is the system that not

only allows an organisation to cascade down its business performance measures, but

also provides with necessary information to challenge the content and validity of the

strategy (Ittner et al., 2003). Business performance measurement can also be defined

from management accounting perspective, that is a system of multidimensional set of

performance measures for the planning and management of a business. Thus, there are

numerous concepts of business performance. The effectiveness of organisations in

fulfilling its purpose can be defined as business performance (Bourne et al., 2003).

Although performance can have a variety of meaning (Short or long term, financial or

organisational benefits), it is broadly viewed from two perspectives (Sin et al., 2005).

According to Aggarwal, Erramilli and Dev (2003) performance represents an

input/output relationship and is a two dimensional construct based on objective and

subjective performance. Objective performance is one of the dimensions which

involves financial or market based measures such as profitability, market share, return

on equity (ROE), return on assets (ROA) and capacity utilisation. On the other hand the

13

subjective or judgemental performance involves customer or employee opinion based

measures such as customer satisfaction, institutional image, employee satisfaction,

service quality, customer commitment etc. There are numerous studies that have

examined the impact of internet banking on business performance (Hajri and Tatnall,

2007; Malhotra and Singh, 2007; Karim and Hamdan, 2010; Shaukat and Zafarullah,

2009). Hajri and Tatnall (2007) made a comparative study of internet banking in Oman

and Australia and found positive impact of internet banking on business performance

measured in terms of perceived relative advantage, organisational performance,

customer/organisational relationship and ease of use. Shaukat and Zafarullah (2009)

also examined the impact of IT on business performance on the basis of subjective

criteria and found positive impact measured in terms of customer satisfaction,

customer/supplier links, company image, job interest of employees, stakeholder‟s

confidence and inter office links/communication. Whereas Karim and Hamdan (2010)

concluded that IT has positive impact on business performance measured in terms of

ROA, ROE, market value added (MVA) and net profit margin. The marketing concept

indicates that superior judgemental performance is a pre- requisite for superior

objective performance. Narver and Slaver (1990) also elicited that to maximise long

term performance, the banks must build and maintain long run mutually beneficial

relationship with their customers. In an online banking context, there is no consensus as

to how business performance should be measured. Scholars have relied on variety of

both financial measures such as ROA (Narver and Slaver, 1990), ROE, MVA and net

profit margin (Karim and Hamdan, 2010) and sales growth (Pelham, 1999) as well as

more market specific measures as customer satisfaction, customer/supplier links

(Shaukat and Zafarullah, 2009). Thus, a lack of uniformity suggests that it becomes

necessary to categorise the performance indicators used in each study in terms of their

scope (business level or market specific) and measurement (Objective versus subjective

assessment). Business level performance was defined as any generic financial indicator

applicable at the level of a firm (eg. profits, ROA/ROE, sales growth). Market specific

performance was defined with reference to specific markets (eg. customer satisfaction

or loyalty, market share, customer commitment). The objective performance is the

outcome of business activities of the organisation whereas subjective performance

relates to the perceptions of individuals about the organisational performance and may

include customer satisfaction, employee satisfaction, and service quality. Thus, the

widespread availability of internet banking is expected to affect the mixture of financial

14

services produced and offered by banks and the resulting financial performance of these

banks depends on their assessment of the profitability of such a delivery system for

their services (Berger, 2003). In addition, banking through internet has emerged as a

strategic resource for achieving higher efficiency, control of operations and reduction

of costs by replacing paper based and labour intensive methods with automated

processes, thus leading to higher productivity and profitability (Malhotra and Singh,

2004).

1.10 Conclusion

Online globalisation, increasing use of new technologies and fast competition, forced

the banks to adopt new channels to gain competitive advantage, reduce cost, improve

financial services, enlarge customer databases to generate customer satisfaction and

commitment. Moreover, online customers are expensive to attract and difficult to retain

because it is relatively easy for customers to switch their online providers providing

additional benefits. Variables that influence customer commitment towards online

banking include service quality, trust, perceived ease of use, perceived usefulness and

satisfaction can also have a significant impact on bank‟s profitability. Thus, it becomes

important for banks to understand which variable is most important for online business,

which also affects their business performance.

15

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Chapter 2

Review of Literature

Chapter 2

Review of Literature

Contents Page No

2.1 Thematic Review of Literature 22

2.2 Research Gap 26

2.3 Summary of Literature Reviewed in Tabular Form 28

References 64

22

CHAPTER-2

REVIEW OF LITERATURE

2.1 Thematic Review of Literature

Till date limited efforts have been made to study the impact of online banking services

in Indian banking. The existing literature has been reviewed for understanding different

concepts and variables related to internet banking as well as to find out the research gap

for the present study. A lot of discussion has appeared in various researches pertaining

to various dimensions that affect the adoption of internet banking and in measuring its

impact on customer satisfaction and business performance. Therefore, in order to

concretise the research gap for the present study, the related literature has been

reviewed as under:-

As already stated, online banking primarily introduced in the early 1990’s, uses

the computer technology to give users the ability to manage their transactions on their

own more quickly and efficiently from anywhere around the world by just a click of the

mouse. Tulani et al., (2009) examined the extent of adoption and usage of internet

banking by commercial banks in Zimbabwe and found people using internet banking

for checking account balances, payment of bills and fund transfer. They also found

perceived benefits of using internet banking as cost reduction, increased loyalty and

attracting new customers. Singhal and Padhmanabhan (2008) determine utility request,

security, utility transaction, ticket booking and fund transfer as the factors influencing

users to adopt e-banking channel. Quereshi et al., (2008) evaluate factors that

manipulate the nature of customer’s towards online banking and found almost 50% of

the clients shifted from traditional banking to online banking system because of

perceived usefulness, security and privacy provided by online banks. Likewise, Azouzi

(2009) also examined the adoption of electronic banking in Tunisia and found majority

of respondents (95%) having an access to internet, but only few of them using it as a

primary banking channel. Auta (2007) empirically examines the impact of e-banking

in Nigeria’s economy and found customers are satisfied with e-banking system which

provides convenience and flexible advantages such as easy transfer, speedy transfer,

less cost and time saving benefits. Lichenstein and Williamson (2006) also provide an

understanding of how and why specific factors affect the consumer decision about

internet banking in an Australian context and found convenience as the main motivator

23

for consumers to bank online. Flavian et al., (2006) analysed how perceptions of

consumers about traditional bank influence their decision to adopt the services offered

by the same bank on the internet and found consumer trust in a traditional bank as well

as income, age and sex of the respondents as the major factors that influence consumer

decision to work with the same bank via the internet. Thus, online banking service has

recently become very effective offering sophisticated tools, including account

aggregation, stock quotes, rate alerts and portfolio managing programmes to help their

customers manage all their assets more effectively and on time (Tan and Teo, 2000).

The researchers have also focussed on various factors affecting adoption of

internet banking (Ashtiani and Iranmanesh, 2012; Eze et al., 2011; Yaghoubi and

Bahmani, 2010; Oii et al., 2010; Kashier et al., 2009). Tat et al., (2008) revealed trust

as the most important factor influencing intention to continue using the internet

banking services followed by compatibility and ease of use. Bander and Charter (2006)

also measure impact of trust on acceptance of online banking and found trust playing

an important role in increasing the usability of online banking. Wang et al., (2009)

investigated whether consumer perception of risk (perceived risk) in transacting on the

internet would have an influence on e-banking website (specific trust) and customer’s

willingness to use e-banking and found perceived risk having a direct influence on

consumer willingness to use e-banking and specific trust having a positive moderating

influence on the relationship between perceived risk and willingness to use e-banking.

In addition to this, there are numerous studies conducted by Hassan et al., 2012

Ravichandran et al., 2010; Dixit and Datta, 2010; Baskar and Ramesh, 2010; Ganguli

and Roy, 2010; Khurana, 2009; Haque et al., 2009, Yang and Peterson, 2004 indicating

that service quality of banks also affects intention to use internet banking as well as

their satisfaction. Also, Lee and Lin, 2005; Siu and Mou, 2005, You and Donthu, 2001,

Wong et al., 2008, Parasuraman et al., 1985, Parasuraman et al., 1988 develop various

dimensions of online service quality.

Moreover, Muhammad and Rana (2012) found perceived ease of use, perceived

usefulness, compatibility, innovativeness and perceived credibility influencing

customer’s intention to adopt internet banking. Similarly Wu, Chang and Lin (2012)

found trust, perceived usefulness and perceived ease of use and relative advantage

having a significant effect on customer’s behavioural intention to adopt internet

banking. Chang and Hamid (2010) also explored two factors viz. perceived ease of use

and perceived usefulness influencing behavioural intention of customer’s to adopt

24

internet banking in Taiwan. In the same manner, Yiu et al., (2007) also make an

attempt to know the adoption of internet banking by retail customers in Hong Kong and

found constructs such as perceived usefulness, perceived ease of use, perceived risk

and personal innovativeness on information technology having a positive relationship

with internet banking adoption.

Satisfying a customer in any banking business is the ultimate goal and

objective. Researchers have also focussed on impact of internet banking on customer

satisfaction (Alam and Soni, 2012; Musiime and Ramadhan, 2011; Singh and Kour,

2011). Ma (2012) finds privacy, reputation and price as the key factors affecting

customer satisfaction in online banking in China. Alam and Soni (2012) find

satisfaction of customers being generated through quick services, affordable service

charge, easiness of depositing and withdrawing money, ATM booths, account

statement over SMS/e-mail services and error free records. Zafar et al., (2012) observed

tangibility, reliability, competence and conflict handling as the constructs of service

quality generating customer satisfaction and customer loyalty. Musiime and Ramadhan

(2011) found a positive significant relationship between internet banking adoption and

customer satisfaction. Dai et al., (2011) determined the antecedents of online service

quality, commitment and loyalty in internet mediated environment (IME) and found

service content quality and service delivery quality as two important antecedents of

consumer service enjoyment, affecting their commitment and loyalty. Muhammad and

Alhamadani (2011) claimed five service quality dimensions viz. reliability,

responsiveness, empathy, assurance and tangibility as important antecedents of

customer satisfaction. Nupur (2010) examined e-banking and customer satisfaction in

Bangladesh and found the same service quality dimensions which were found by

Muhammed and Alhamadani (2011) as core dimensions of customer satisfaction. Lin

and Sun (2009) studied factors influencing satisfaction and loyalty in online shopping

on the basis of technology acceptance factors viz. perceived usefulness and perceived

ease of use, website service quality and specific hold up cost factors and conclude that

customer’s e-satisfaction will positively influence customer’s e-loyalty directly,

technology acceptance factors will positively influence customer e-satisfaction and e-

loyalty directly, website service quality can positively influence customer e-loyalty

directly, but cannot positively influence customer e-satisfaction directly. Floh and

Treiblmair (2006) identified satisfaction and trust as important antecedents of customer

loyalty. Li et al., (2006) examined the relationship between user and website with

25

commitment and trust as key mediating variables and find significant association

between intention to stick with a website and commitment and trust in the website.

Further, Fock and Koh (2006) conceptualise trust and commitment relationship in

context of internet banking and revealed higher level of trust and commitment as

significantly associated with willingness to try internet banking facilities. Luarn and

Lin (2003) observed customer satisfaction and perceived value are indirectly related to

loyalty through commitment. Riquelme et al., (2009) also examined which customer

service and online attributes predict overall satisfaction and found that satisfaction has

been generated through improving courtesy, content timeliness and product and

services offered. Khan and Mahapatra (2009) concluded that customers are satisfied

with the reliability of services provided by banks but are not satisfied with the

dimension of user friendliness. Thus, the studies indicate the necessity of measuring the

impact of trust, perceived ease of use, perceived usefulness, service quality provided by

banks online on customer satisfaction and customer commitment.

The effectiveness of organisations in fulfilling its purpose can be described as

business performance (Opara et al., 2010). In fact it represents an input/output

relationship, is two dimensional concept based on objective and subjective performance

(Hasan et al., 2010). Some researchers have focussed on measuring impact of

information technology on objective basis (Karim and Hamdan, 2010; Onay and Ozsoz,

2007; Malhotra and Singh, 2007; Siam, 2006; Guo et al., 2004). Whereas, others have

focussed on measuring impact on the basis of subjective criteria (Ahmad et al., 2010;

Shaukat and Zafarullah, 2009; Hajri and Tatnall, 2007; Jham and Khan, 2005; Lee and

Hwan, 2005). Also, Kaleem and Ahmad, 2008 observed bankers in Pakistan

considering internet banking as profitable because of minimising inconvenience,

reducing transaction costs and saving time. Uppal (2011) analyzed the performance of

Indian banks in terms of productivity and profitability in the pre and post e-banking

period and found bank’s performance better in post e-banking period than pre e-

banking period. Similarly, Kour (2012) examined the impact of IT on branch

productivity and Kashap and Sharma (2012) examined the impact on branch

productivity, labour productivity and profitability in pre and post e-banking period and

found performance of banks improving after implementation of information

technology and more particularly, mobile banking and internet banking. Thus, on the

basis of literature reviewed, there is a need to measure the impact of internet banking

on business performance on the basis of both objective and subjective criteria in pre

26

and post e-banking period. The objective performance will be measured with the help

of ROA, ROE and Net Profit margin whereas the subjective performance will be

measured through customer satisfaction, service quality offered by banks, perceived

ease of use, perceived usefulness and customer commitment.

2.2. Research Gap

Internet banking is changing the whole banking industry, having effects on banking

relationships and its performance. So this aspect cannot be undermined and need to be

researched thoroughly. The aforesaid review of literature reveals that so far impact of

internet banking on customer satisfaction together with business performance has not

been studied extensively. The most of the studies have focussed on extent of adoption

of internet banking (Tulani et al., 2009; Azouzi, 2009; Qureshi et al., 2008), some have

studied factors affecting continued usage of internet banking (Kashier et al., 2009;

Ashtiani and Iranmanesh, 2012; Eze et al., 2011). Similarly, some studies focussed on

dimensions of service quality (Lee and Lin, 2005; Siu and Mou, 2005; You and

Donthu, 2001), some have examined influence of trust and its antecedents on the

adoption of e-banking (Wang et al., 2009; Bander and Charter, 2006). In the same

manner , some have focussed on measuring impact of internet banking on customer

satisfaction and commitment (Ma, 2012; Singh and Kour, 2011) and some on business

performance (Hajri and Tatnall,2007; Malhotra and Singh, 2007; Onay and Ozsoz,

2007). Thus, most of studies were limited to either one or two aspects of internet

banking.

The proposed study aims to fill up this research gap by studying the impact of internet

banking on customer satisfaction and business performance on the basis of following

dimensions viz. trust, service quality, perceived ease of use, perceived usefulness,

customer satisfaction and commitment. Further the business performance can be

evaluated from the financial reports of the banks and from customer satisfaction and

commitment, which increase the performance of the banks as a whole.

Hence, the objectives of the study are as under;

To find the increasing significance of internet banking.

To examine the impact of trust on customer satisfaction.

To evaluate the impact of service quality on customer satisfaction and business

performance.

27

To examine the impact of perceived usefulness and perceived ease of use on

intention to use internet banking and hence customer satisfaction and employee

satisfaction.

To evaluate the impact of customer satisfaction on customer commitment.

To examine the impact of internet banking on business performance of banks to

be measured objectively as suggested by Karim and Hamdan, 2010; Onay and

Ozsoz, 2007 and subjectively as suggested by Ahmad et al., 2010; Shaukat and

Zafarullah, 2009 and further period wise as suggested by Kour, 2012 and Uppal,

2011.

28

2.1:Summary of Literature Reviewed in Tabular Form

S. No. Authors (Year) Objective of the Study Methodology Findings

Limitation/Future

Research

1. Parasuraman,

Zeithaml and Berry

(1985)

To develop model of

service quality

Conceptual paper Found ten dimensions of

service quality viz. tangibility,

reliability, responsiveness,

communication, access,

competence, courtesy,

credibility, security and

understanding

Need to develop a

standard instrument to

measure consumer’s

service quality

dimensions

2. Parasuraman,

Zeithaml and Berry

(1988)

To examine consumer

perceptions of service

quality

Data were collected

through quota

sampling from 200

respondents and

analysed through

factor analysis

Results show that service

quality can be measured

through five dimensions viz.

tangibility, reliability,

responsiveness, assurance, and

empathy

Enriched empirical

research focussing on

service quality and its

antecedents and

consequences should be

done in future

3. Tan and Teo (2000) To identify attitudinal,

social and perceived

Data were collected

from 454 respondents

Attitudinal and perceived

behavioural control factors

Online survey has

restricted the

29

behavioural control

factors that influence

adoption of internet

banking

through mailed

survey questionnaire

rather than social influence

play a significant role in

influencing intention to adopt

internet banking. Perceptions

of relative advantage,

compatibility, trialability and

risk towards using the internet

were found to influence

intention to adopt internet

banking services.

perceptions of non-

internet users

4. Yoo and Donthu

(2001)

To develop and validate

a psychometrically

rigorous instrument to

measure the perceived

quality of an internet

shopping site

(SITEQUAL)

5 point likert scaled

questionnaires were

given to 94 students

of marketing class,

out of which 69 gave

the completed form

which resulted in 207

evaluations as each

participant evaluated

three sites. Both EFA

Four dimensions viz. ease of

use, aesthetic design,

processing speed and security

have appropriate reliability

and validity in every aspect,

showing site quality as directly

linked to site performance

The participants

measure only consumer

goods sites. Thus, other

sites need to be taken

into consideration and

SITEQUAL dimensions

of technical aspects of

web design should also

be examined

30

and CFA were used

to analyse the data

5. Luarn and Lin

(2003)

To examine antecedents

that influence loyalty

Data were collected


who used online

travelling services

and video on demand

through Quota

sampling and

analysed through

multiple regression

analysis

Trust, customer satisfaction,

perceived value and

commitment are separate

constructs that combine to

determine loyalty with

commitment exerting a

stronger influence than trust,

customer satisfaction and

perceived value. Also


perceived value are indirectly

related to loyalty through

commitment

Study is limited to only

two e-service categories

and targeted specific

consumer group

6. Guo et al., (2004) To examine the lagged

effect between

customer satisfaction

and profitability

Data on customer

satisfaction is

gathered from

American customer

Past satisfaction having a

positive effect on current

profitability and past

profitability affects

Empirical study should

be conducted in future

31

satisfaction index

(ACSI) and data on

sales and other

variables of interest

such as Return on

Assets (ROA) are

extracted from

sources such as

compustat for the

companies whose

satisfaction scores

are reported in the

ACSI database


7. Yang and Peterson

(2004)

To examine customer

perceived value,

satisfaction, loyalty and

the role of switching

costs

Data were collected

from web based

survey randomly

selected from an e-

mailing list of 4000

respondents provided

by an e-mail broker,

Customer loyalty can be

generated through improving


offering high product/service

value

The study is too limited

in scope as only limited

factors were taken

32

from which only 235

gave the final

response. Both EFA

and CFA were used

to analyze the data

8. Lee and Lin (2005) To examine the

relationship among e-

service quality

dimensions and overall

service quality, customer

satisfaction and

purchase intentions

Data were collected

from 297 online

customers and

analysed with the

help of CFA and

SEM

Website design, reliability,

responsiveness and trust affect

overall service quality and

customer satisfaction which in

turn significantly affects

customer purchase intentions.

However, the personalisation

dimension is not significantly

related to overall service

quality and customer

satisfaction

Different methodologies

such as longitudinal

studies, focus groups

and interviews should

be used in future to

examine the same

relationship

9. Siu and Mou

(2005)

To examine e-banking

service quality on the

basis of four dimensions

viz. credibility,

Data have been

gathered from 195

respondents who are

actually users of

All dimensions except

security are found to be

important in determining

overall service quality. Also

E-banking service

quality was tested in

Hong Kong with limited

sample. Hence, it does

33

efficiency, problem

handling and security

internet banking in

Hong Kong .One –

way ANOVA, T-test

and multiple

regression analysis

were used as

statistical tool for

analysis

credibility, problem handling

and security having significant

impact on customer

satisfaction and it is also found

that security and efficiency are

significantly associated with

future consumption behaviour

not give general picture

of e-banking

10.

Jham and Khan

(2005)

To examine the impact

of customer satisfaction

on performance of

Indian banks by

considering various

services provided by

banks viz. traditional

facilities, multichannel

banking and internal

marketing

Data were collected

from 560 customers

through probability

systematic sampling

from five banks viz.

SBI, PNB, HDFC,

ICICI and IDBI and

analysed through

factor analysis,

ANOVA and

regression analysis

Result concludes that

performance of the bank is

positively linked to


Selection of data from

only one industry

thus, limits the ability

to extrapolate the

findings of the

research to other

industries

34

11. Lee and Hwan

(2005)

To examine the

relationship between

service quality, customer

satisfaction and

profitability

Conceptual paper Perception quality is an

antecedent of attitude, service

quality is an antecedent of

customer satisfaction,

customer satisfaction directly

affects purchase intention and

customer satisfaction is an

antecedent of profitability

Empirical research

should to conducted in

future

12. Floh and

Treiblmair (2006)

To examine antecedents

of online loyalty such as

trust, quality of the

website, quality of the

service and overall

satisfaction

Data were collected

from 2000 customers

of an Austrian online

bank and analysed

through SEM

Results show that satisfaction

and trust are important

antecedents of loyalty

The results of the study

cannot be generalized

because of the biasness

of the sample

13. Fock and Koh

(2006)

To examine trust and

commitment relationship

in the context of internet

banking

Data were collected

from 300

undergraduate

students from

Singapore and

analysed by applying

Higher level of trust and

commitment are significantly

associated with greater

willingness to try internet

banking. They further found

security, ethics, privacy,

This study focuses on

measuring perceptions

of trust rather than

actual trustworthiness of

internet banks. Further

only nine antecedents

35

regression analysis openness, the speed of

response, quality of

information, regulatory

control, technology

advancement and reputation as

determinants of trust

are considered factors

that affect trust, there

may be more

antecedents to trust and

willingness to try

14. Siam (2006) To examine the effects

of electronic banking

services on bank’s

profitability in Jordan

Data were gathered

from 20 commercial

banks which have

developed their sites

in Jordan and


correlation analysis

Electronic banking services

having a negative effect on

bank’s profitability in the short

run and positive effect on

bank’s profitability in the long

run

Study has been

conducted in Jordan city

only

15. Lichenstein and

Williamson (2006)

To examine specific

factors affecting

consumer decision in

Australian Banking

context

Conceptual paper Convenience is the main

motivator that influences

customers to bank online.

Empirical study should

be conducted in future

16. Flavian (2006) To examine how

consumers’ perceptions

Data were randomly

collected from 633

Consumer trust in a traditional

bank as well as income, age

The study was based on

perceptions of only

36

of their traditional banks

influence their decision

to adopt the services

offered by the same

banks on the internet

bank customers and

analysed through

Binomial Logistic

Regression process

and sex are factors that

influence their decision to

work with the same bank via

the internet

Spanish speaking

persons

17. Bander and Charter

(2006)

To measure the impact

of trust on acceptance of

online banking

Conceptual paper Trust plays an important role

in increasing the usability

under the online banking

environment

Trust should be

considered in addition to

perceived usefulness

and perceived ease of

use

18. Li et al., (2006) To examine the

relationship between

user and website with

commitment and trust as

key mediating variables

Data were collected

from 239 graduate

and post graduate

students and analysed

by using partial least

square

There exists significant

association between intention

to stick with a website and

commitment to and trust in the

website

This study positioned

and measured

commitment and trust as

uni dimensional

concepts, whereas other

studies recognize these

two concepts as

multidimensional

19. Hajri and Tatnall

(2007)

Made a comparative

study of internet

Data were collected

through interviews

The findings reported in

this study suggested that

More factors should be

considered for future

37

banking in Oman and

Australia

with bank managers

in each country

about the

perceptions of four

factors that might

have affected their

decisions to adopt

or not to adopt

internet

technologies

four perceptions of bank

managers towards the

internet: perceived relative

advantage, organisational

performance, customer /

organisational relationship

and ease of use can assist in

drawing out enablers and

inhibitors to the adoption of

internet technology for both

Oman and Australia

studies

20. Malhotra and Singh

(2007)

To examine the

current state of

internet banking in

India and its

implication for the

Indian banking

industry. They also

analysed the

performance of an

The data were

collected from the

RBI financial

statements and

income expense

reports. The

internet related

details were drawn

from a survey of 85

Result show that nearly

57% of the Indian

commercial banks are

providing transactional

internet banking services.

The invariable analysis

indicates that internet banks

have better operating

efficiency ratios and

Sample size is small

38

internet banking

group in comparison

to non-internet

banking group and

impact of internet

banking on business

performance and risk

scheduled

commercial bank’s

websites in June

2007. A number of

financial ratios

have been used to

measure the

performance of

banks

profitability as compared to

non-internet banks. Also

internet banks rely more

heavily on core deposits for

funding than non-internet

banks do. The multiple

regression results reveal

that the profitability and

offering of internet banking

do not have any significant

association. However, on

the other hand, internet

banking has a significant

and negative association

with risk profile of banks,

which shows that the


banking has not increased

the risk profile of banks.

21. Onay and Ozsoz To examine the In fact thirteen The adoption of internet Other parameters

39

(2007) impact of internet

banking on financial

performance and

profitability of

Turkish banks

banks adopted

internet banking in

Turkey between

1996 and 2005.

Bank profitability

has been measured

in terms of return

on bank assets

(ROA), a ratio of

bank’s profits to

total assets, and

return on equity

(ROE)

banking does not seem to

have a significant impact on

the performance of Turkish

banks measured in terms of

ROA, ROE and margin in

the year of internet

adoption rather in the

following year the bank

registered a significant

decrease in the profitability

because of increase in IT

expenditure by adopting

new technology. However

in the 2nd

and 3rd

years

following the adoption of

technology, there was a

positive coefficient of the

variable on the ROE only,

showing positive impact on

bank profitability and

should be taken into

consideration for

future research

40

internet adoption

22. Yiu et al., (2007) To examine adoption of

internet banking by

retail customers in Hong

Kong

Data were collected


through telephone

survey and analysed

by adopting T-test

and Pearson

correlation techniques

Constructs such as perceived

usefulness, perceived ease of

use, perceived risk and

personal innovativeness on

information technology have a

positive relationship with

internet banking adoption

Sample size is small

23. Auta (2007) To examine the impact

of e-banking in

Nigeria’s economy

Data were collected

from 750 customers

of 25 commercial

banks in Nigeria and

analysed through

Kaiser Meyor Olkin

(KMO) approach and

Bartlett’s test of

sphericity to extract

independent variables

associated with e-

banking

Customers are satisfied with e-

banking system providing

convenience and flexible

advantages such as easy

transfer, speedy transaction,

less cost and time saving

benefits to its customers

Data is collected from

only urban city of

Nigeria

41

24. Singhal and

Padhmanabhan

(2008)

To examine factors

responsible for internet

banking

Data were collected

through mailed

questionnaires from

61 respondents and

analysed through

SPSS

Majority of respondents are

male and the factors responsible

for internet banking are utility

request, security, utility

transaction, ticket booking and

fund transfer

25. Qureshi et al.,

(2008)

To study factors that

manipulate nature of

customers towards

online banking and their

growing tendency

towards online financial

institutions in Pakistan

Primary data were

collected through

mail survey and

telephonic

interviewing whereas

secondary data has

been obtained from

the websites of the

State Bank of

Pakistan

50% of the clients shifted

from traditional banking to

online banking system because

of perceived usefulness,

security and privacy provided

by online banks

The study is based on

limited data input and

also important

demographic

background of the

customers has not been

taken into account

26. Tat et al., (2008) To examine predictors

of intention to continue

using internet banking

services on the basis of

The data were

collected from 204

residents in Klang

Valley, Malaysia who

Trust as the most important

factor influencing the intention

to continue using the internet

banking services followed by

However, the results

cannot be generalized as

the other predictors such

as the perceived risk,

42

trust, compatibility and

ease of use

were users of internet

banking services.

Pearson correlation

analysis and multiple

regression analysis

were used for

drawing inferences

compatibility and ease of use usefulness and relative

advantage that can

influence the criterion

variable are not taken

into account

27. Wong et al., (2008) To examine the role of

traditional service

quality in an e-banking

environment

Data were collected


through online survey

and analysed through

Quadrant analysis

Five service quality

dimensions viz. reliability,

responsiveness, assurance,

empathy and tangibles has not

changed dramatically over the

years, but large discrepancies

were found between customer

expectations and their

perceived performance of

traditional banking services

The data collection is

limited to the Australian

context where the

Australian’s internet

maturity is quite solid

28. Kaleem and Ahmad

(2008)

To examine bankers’

perception of the

potential benefits and

Data were collected

from 207 bank

employees from 15

Bankers consider ‘minimizing

inconvenience’, ‘ minimizing

cost of transaction’, and ‘time

Demographic

characteristics should

also be used as

43

risks attitude with

electronic banking in

Pakistan

major commercial

banks operating in

Lahore and analysed

via frequency and

mean score analysis

saving’ as important benefits

and chances of government

access, chances of fraud and

lack of information security to

be vital risk associated with

electronic banking

parameters for further

analysis

29. Tulani et al., (2009) To examine the extent of

adoption and usage of

internet banking by

commercial banks in

Zimbabwe and the

challenges they face in

this respect

A structured

questionnaire was

used in 16

commercial banks in

Zimbabwe, while

only 12 filled and

returned the

questionnaire. SPSS

version 10 was used

as a statistical

analysis tool for

drawing inferences

Majority of the banks in

Zimbabwe have adopted

internet banking, usage

levels have remained

relatively low, as not many

customers are using this

innovation in Zimbabwe.

The main usage of internet

banking has been for

checking account balances,

payment of bills and fund

transfer. Important

perceived benefits of using

internet banking were cost

The study indicates

the necessity of

improving marketing

efforts by initiating

awareness

programmes to raise

customer awareness

and interest in

internet banking and

also the government

must, through the

Reserve Bank of

Zimbabwe (RBZ),

increase investment in

44

reduction, increased loyalty

and attracting new

customers and the

challenges for adoption of

internet banking are

compatibility with legacy

systems followed by cost of

implementation and

security concerns

education and

infrastructure

development to

enable more firms and

consumers to adopt

the innovation

30.

Azouzi (2009) To examine the extent

of adoption of

electronic banking in

Tunisia

Data were

collected through

questionnaire and

personal interviews

from 84

respondents

selected from

schools,

universities and

households having

a current account in

Results show majority of

respondents (95%) having

access to internet but only

few of them use it as a

primary banking channel. In

fact 52.4% of the

respondents prefer to go

directly to bank and

continue to emphasize their

linkage to traditional

banking. It is due to the fear

Although the study

has come up with the

findings of far

reaching significance

both in literature and

practice yet it cannot

be generalised due to

its limited data input

and that too from

respondents working

primarily in

45

bank

of transactions error or

hackers that alienate

Tunisian customer’s from

using online banking

educational

institutions

31. Kasheir et al.,

(2009)

To examine the factors

affecting continued

usage of internet

banking among

Egyptian customer’s

Data were collected

from 65 respondents

conveniently and

analysed through

multiple regression

and ANOVA

Perceived ease of use was

found to be the strongest

predictor of intention to

continued usage of internet

banking services and

demographic variables having

no significant effect on the

same

Size of sample and

strategy of data

collection are the major

limitations of the study

32. Wang et al., (2009) To analyse customer

perception of risk in

transacting on the

internet and their

willingness to use e-

banking

Data were collected


including

administrative and

academic staff from

ten departments

across the five

Perceived risk having a direct

influence on consumer’s

willingness to e-banking and

specific trust having a positive

moderating influence on the

relationship between perceived

risk and consumer willingness

Non- probability

sampling technique has

been used which

restricts the

generalisability of

results

46

faculties of large

Australian University.

Hierarchical

moderated regression

analysis was used to

analyse the data

to use e-banking

33. Khurana (2009) To identify the customer

preferences towards

online banking and

various service quality

dimensions that affect

customer satisfaction in

internet banking

Primary data were

collected from 100

internet banking users

of Hissar district by

convenience sampling


ANOVA and F-test

Service quality dimensions

such as efficiency,

responsiveness, fulfillment,

privacy of personnel

information and easiness to

use are the core dimensions of

internet banking affecting


The data have been

obtained from one

district only and that too

from limited

respondents

34. Haque et al., (2009) To study factors

determining the

Malaysian Banking

consumers perception on

e-banking transactions

Structured

questionnaire has

been used to collect

data from 230

respondents and

Protected transactions having

significant impact on

customers perception about e-

banking security, followed by

service quality and regulatory

Banks must invest in

technology research

through which greater

prevention and

protection tools can be

47

analysed through

factor analysis and

SEM

framework issues innovated

35. Lin and Sun (2009) To examine factors

influencing satisfaction

and loyalty in online

shopping on the basis of

technology acceptance

factors (perceived

usefulness and perceived

ease of use), website

service quality and

specific hold up cost

factors

Data were collected

from 221 online users

through snowball

sampling technique


AMOS and SEM

Customer e-satisfaction will

positively influence customer

e-loyalty directly, technology

acceptance factors will

positively influence customer

e-satisfaction and e-loyalty

directly, website service

quality can positively

influence customer e-loyalty

directly, but cannot positively

influence customer e-

satisfaction directly

Wider range of

constructs such as

cultural and social

factors affecting e-

satisfaction and e-

loyalty are also need to

be studied

36. Riquelme et al.,

(2009)

To examine which

customer service and

online attributes predict

overall satisfaction,

The sample was

drawn from one of

the main banks in

Kuwait. Multiple

Satisfaction being generated

through improving courtesy,

content timeliness and

products and services offered.


the data pertaining to

only one bank

48

determined if satisfied

customers use more

online banking features

than not satisfied

customers and to

identify the

characteristics of less

satisfied customers

regression and

discriminant analysis

were used to analyse

the data

This shows that companies

that offer a wide product

portfolio and relevant website

content accompanied by

prompt and courteous response

create satisfaction online

37. Khan and

Mahapatra (2009)

To examine quality of i-

banking services in India

from customer

perspective

Data were collected

from various target

groups consisting of

ten e-banking users

and the managers of

four banks including

public sector, private

sector and foreign

banks and analysed

with the help of

regression analysis

Customers are satisfied with

the reliability of the bank

services but are not satisfied

with the dimension of user-

friendliness. The two

dimensions viz-

privacy/security and fulfilment

are not contributing

significantly towards the

overall service quality

The results cannot be

generalised as the

service quality of e-

banking has been tested

in urban India and that

too from limited sample

only

38. Shaukat and To examine the The data were IT having positive impact In fact the number of

49

Zafarullah (2009) impact of IT on

organisational

performance with

respect to different

performance

indicators of Pakistani

manufacturing and

banking sectors during

1994-2005

collected through

in-depth interviews

and field surveys of

48 companies, 24 in

manufacturing

sector (12 local and

12 foreign) and 24

in banking sector

(12 local and 12

foreign). The

participants in the

study were the

operative staff and

managers of

finance. T-test and

one way ANOVA

have been used to

draw inferences

on organisation in terms of

customer satisfaction,

customer/supplier links,

company image, job interest

of employees, stakeholders,

confidence and inter office

links/communication. Also

the performance of the

banking sector outstrips the

performance of the

manufacturing sector. In the

banking sector local

companies are taking the

lead, while in

manufacturing companies

multinationals are at top

manufacturing

companies taken is

too small though

chosen randomly

39. Yaghoubi and

Bahmani (2010)

To study factors

affecting adoption of

Data were randomly

collected from 349

Intention to use online banking

is positively affected by

Research domain is too

limited

50

online banking in

Isfahan Province of Iran

selected customers


SEM

perceived behavioural control

and perceived usefulness

40. Oii et al., (2010) To examine the factors

that affect the adoption

of online banking in

Vietnam

Data were collected


and analysed on the

basis of correlation

and multiple

regression analysis

Perceived usefulness, trust,

and government support are

positively associated with the

intention to use online banking

in Vietnam. Contrary to the

technology acceptance model,

perceived ease of use was

found insignificant

Sample is too small

41. Ravichandran et

al., (2010)

To examine the

influence of service

quality on banking

customer behavioural

intentions

Data were collected

from 102 customers

from two major

public sector banks of

Tirchirapalli city of

Tamil Nadu, India


univariate analysis

Tangibility, responsiveness

and empathy dimensions play

an important role in predicting

customer behavioural intention

The findings of the

study cannot be

generalised as it is based

on consumer perception

only

42. Dixit and Datta To identify the Data were collected Factors such as perceived However, the study is

51

(2010) perceived service quality

dimensions of self

service technology

(internet banking) and

its impact on customer

satisfaction and loyalty

in internet banking


of internet banking

users from the states

of Rajasthan and

Uttar Pradesh in

India. Descriptive

statistics and

correlation were used

through SPSS to

know the perceived

service quality of

internet banking and

level of satisfaction

among customers in

India

value, perceived service

quality, customer satisfaction

and their loyalty having a

significant impact on customer

acceptance of internet banking

based on two states

only, thus not true

representative of whole

of India

43. Baskar and Ramesh

(2010)

To examine the linkage

between online banking

service quality and


Data were collected

from 400 randomly

selected customers

from 42 banks

through systematic

Results show online banking

service quality having a

significant positive impact on


The findings of the

study are not conclusive

because the data have

been drawn from only

one segment viz.

52

sampling. Multiple

regression analysis

was used to analyse

the data

customer’s

44. Ganguli and Roy

(2010)

To identify the generic

service quality

dimensions of

technology based

banking and also to

examine the effect of

these dimensions on


and loyalty


the data collected

from 336

undergraduate

students of University

in the Massachusetts

State of USA and

analysed through

EFA, CFA and SEM

Customer services, technology

security and information

quality, technology

convenience and technology

usage easiness and reliability

were identified as four generic

service quality dimensions. It

was also found that customer

service and technology usage

easiness and reliability have

positive and significant impact

on customer satisfaction and

loyalty

The findings of the

application of the

service quality

dimensions cannot be

relevant to e-banking as

only generic dimensions

were taken

45. Chang and Hamid

(2010)

To investigate internet

banking adoption among

Taiwanese banking

Data has been

collected from 203

respondents from

Perceived ease of use and

perceived usefulness are the

two factors influencing

More factors are taken

into consideration for

future study

53

customer’s Taiwan and analysed

by applying chi-

square test and

regression analysis

behavioural intention to adopt

online banking

46. Nupur (2010) To examine the impact

of e-banking variables

on customer satisfaction

in Bangladesh

Data were collected

from 400 randomly

selected respondents

out of whom only 250

gave the complete

response. Regression

analysis and ANOVA

were used to analyse

the data

Reliability, responsiveness,

assurance, empathy, and

tangibility are core service

quality dimensions for

customer satisfaction in e-

banking and out of them only

reliability, responsiveness and

assurance having more

contribution to customer

satisfaction

Data have been

collected from urban

areas of Bangladesh and

no bank wise position is

made

47. Opara et al., (2010) To investigate impact of

technology on

relationship marketing

orientation and business

performance of Nigerian

banks

Data were collected

from 409 employees

of 123 bank branches

operating in Port

Horcourt and

analysed with the

Technology exists as a

moderating variable in the

relationship marketing

orientation and business

performance relationship of

the Nigerian banks

The data has been

gathered from only

employees of bank

54

help of SPSS

48. Ahmad et al.,

(2010)

To examine relationship

between customer

satisfaction and

performance of

conventional banks

operating in Pakistan

Data were gathered

from self developed

questionnaire

administered to 864

customers through

simple random

sampling from 72

branches of National

Bank of Pakistan,

Muslim Commercial

Bank and Askari

Bank operating in

Pakistan and have

been analysed by

using Pearson

correlation and the

magnitude of

relationship is

assessed by

There is a significant positive

relationship between customer

satisfaction and performance

of conventional bank. Also

customer satisfaction helps to

increase the bank performance

due to greater profitability,

increased market share and

more return on investment.

Similarly customer satisfaction

generates positive outcomes

for long term profitability

Respondents from one

location is selected

55

regression analysis

49. Karim and Hamdan

(2010)

To examine the effects

of information

technology on the

Jordanian banking

industry

Data has been

gathered from 15

Jordanian banks for a

period of five years

Findings revealed that IT

having a positive impact on

business performance

measured in terms of ROA,

ROE, market value added and

net profit margin

Other Measures should

be adopted in future

research

50. Eze et al., (2011) To examine factors

influencing use of

internet banking services

among Young

Malaysian Adults

Data were collected

from 310 young

participants through

convenience sampling


multiple regression

analysis

Factors such as perceived ease

of use, perceived usefulness,

relative advantage, self

efficacy, perceived credibility

and trialability tend to

influence customer attitude to

adopt internet banking services

Respondents only from

one location and that too

conveniently have been

selected

51. Musiime and

Ramadhan (2011)

To examine the factors

that influence customer

adaptation of internet

banking as well as to

examine the relationship

Data were collected

from 351 customers

of Kampala city

through stratified

sampling and

There is a significant positive

relationship between internet

banking and customer

satisfaction

Future research should

focus on determining

the needs, issues and

demands of the

customers

56

between internet

banking service,

customer adoption and


analysed through

descriptive analysis,

factor analysis and

multiple regression

analysis

52. Singh and Kour

(2011)

To examine factors

having impact on


Data were collected


through convenience

sampling. 114

respondents were

selected for each of

four banks viz. SBI,

PNB, ICICI and

HDFC and analysed

through factor

analysis, multiple

regression analysis

and Pearson’s

coefficient correlation

Customer satisfaction in a

universal banks is influenced

by seven factors viz. employee

responsiveness, appearance of

tangibles, social responsibility,

services innovation, positive

word of mouth, competence

and reliability

The major limitation of

the study is the

collection of data from

only Chandigarh for

which the results do not

have general

applications to different

banks in the same sector

and the same banks in

different city of India

53. Dai et al., (2011) To examine the Data has been Service content quality and Findings cannot be

57

antecedents of online

service quality,

commitment and loyalty

in internet mediated

environment (IME)

collected through

online survey from

772 persons who use

IME services such as

internet banking

services, online

purchases, online

entertainment

services etc and

analysed through

ANOVA and SEM

service delivery quality are

two important antecedents of

consumer service enjoyment

that further affect their

commitment and loyalty

generalized because

majority of the

responses are from

young population

54. Mohammad and

Alhamadani (2011)

To examine the level of

service quality of

commercial banks in

Jordan and its effect on

customer satisfaction on

the basis of

SERVQUAL model

proposed by

Parasuraman et al.,

Data were collected

from 260 randomly

selected customers

from thirteen

commercial banks of

Jordan and analysed

through multiple

regression analysis

Five dimensions of service

quality viz. reliability,

responsiveness, empathy,

assurance and tangibles are

important antecedents of


The results cannot be

generalized because the

sample is small and that

too limited to customers

living in Irbid city

(located north of

Jordan). Secondly, the

study did not take into

account the potential

58

(1988) differences in

customer’s culture.

55. Uppal (2011) To examine the

performance of banks

in terms of

productivity and

profitability in pre and

post e-banking period

Nine banks viz.

SBI, BOB, Canara

Bank, HDFC,

ICICI,UTI,

Citibank, Standard

Chartered and

HSBC have been

selected on the

basis of their

market share in

2003-04 and

analysed with the

help of various

ratios

Findings revealed that

performance of all banks

under study is much better

in post e-banking period.

The performance of foreign

banks is at the first position

followed by private and

public sector banks

Other aspects such as

corporate governance,

reforming capital

structure need to be

covered in future

56.

Ashtiani and

Iranmanesh (2012)

To examine factors

affecting adoption of

electronic banking.

A random sample of

363 M.S. students in

Islamic Azad

University of Arak

Results show positive word of

mouth and trust in bank having

a direct effect while perceived

competence having an indirect

This study is based on

perceptions from only

students of an Islamic

University

59

were obtained

through structured

questionnaire and

analysed through

SEM technique

effect on electronic banking

adoption

57. Hassan et al.,

(2012)

To examine

determinants that mainly

affect the customer

service quality

perception of internet

banking amongst

different age groups of

boths male and female

Data were collected

from 120 internet

banking users and

analyzed by applying

Chi-square test

Web site design, trust,

security, product

diversification, credibility,

collaboration, access and

communication strongly affect

the customer perception about

the quality of internet banking

services

Data has been collected

from customers of one

particular region

58. Muhammad and

Rana (2012)

To examine factors that

are distressing the


banking services among

adult students in

Kingdom of Saudi

Arabia

Data were collected

from 150 adult

students of Saudi

Arabia and analysed

with the help of T-test

and correlation

Perceived ease of use,

perceived usefulness,

compatibility and

innovativeness and perceived

credibility tend to influence

customers to adopt internet

banking whereas trialibility

Only adults were chosen

for the purpose of study

60

did not influence adoption of

internet banking

59. Wu et al., (2012) To examine perceived

usefulness and perceived

ease of use while

incorporating relative

advantage, website

quality, knowledge and

support, information

quality and trust as new

constructs in predicting

customer’s behavioural

intention of using online

banking

Quota sampling was

used to collect data

from 465 customers

from 31 domestic

banks and 15

questionnaires were

administered to each

bank. Multiple

regression analysis

was used to represent

the difference

between users and

potential users

behavioural intention

of using online

banking in Taiwan

The findings revealed that trust

demonstrated a strong effect

on customer’s behavioural

intention for both potential

user group and user group.

Also apart from perceived

usefulness and perceived ease

of use, relative advantage also

had a significant effect on

customer’s behavioural

intention

Data has been collected

from respondents of

Taiwan only

60. Alam and Soni To study customer Data were collected There is a significant variation Customer satisfaction of

61

(2012) satisfaction of internet

banking in Vadodara

city of India

from 250 bank

customers and

analysed with the

help of ANOVA and

multiple regression

analysis

in the level of satisfaction

among internet banking users

which depends upon

reliability, responsiveness,

security, ease of use and

tangibles. Further they also

claimed that satisfaction

comes from quick services,

affordable service charge,

easiness of depositing and

withdrawing money, ATM

booths, Account statement

over SMS/ e-mail services and

error free records

a particular bank is not

analysed.

61. Ma (2012) To examine factors of

service quality that

influence customer

satisfaction

Data were collected

from 198 Chinese

customers and

analysed through

SEM

Privacy, reputation and price

are the key factors that affect

customer satisfaction in

internet banking services

This study solicited

perceptions from only

Chinese customers

62. Zafar et al., (2012) Aims to explore

common constructs for

Data has been

gathered from 192

Tangibility, reliability,

competence and conflict

This study is based upon

easy sampling

62

quality of banking

services which influence


and also to examine the

impact of customer

satisfaction on customer

loyalty in the context of

banking relationships

customers from

Rawalpindi/

Islamabad, Lahore

and Karachi

conveniently and


AMOS and SEM

handling are the constructs of

service quality that generate


customer loyalty

processes, which

prohibit general nature.

A random probabilistic

sampling method can

provide results that are

more accurate

63. Kashyap and

Sharma (2012)

To examine the

performance of

scheduled commercial

banks (SCBs) in terms

of labour productivity,

branch productivity

and profitability in pre

and post e-banking

period

All SCBs have been

taken into

consideration with

division of period

between pre e-

banking period

(1991-1999) and

post e-banking

period (2000-2009)

Results show that

performance of all banks

improved after the

introduction of IT Act,

1999, in terms of capital

deposits, branch

productivity and Net profit

More aspects should

be covered for future

research

64. Kour (2012) To examine the

impact of IT on

branch productivity

Indian banking

industry is taken as

universe with

Findings indicate that IT

along with other factors is

improving the productivity

Same methodology

may be used to study

the impact at

63

partially IT

oriented banks and

fully IT oriented

banks. The analysis

is done by dividing

the period into two

viz pre e-banking

(1996-97 to 2000-

01) and post e-

banking (2001-02

to 2006-07)

at an excellent rate and

fully IT oriented banks are

the most beneficiaries

whereas partially IT

oriented banks though

proved increase in

productivity in the post e-

banking period but still not

harmonized with fully IT

oriented banks

individual bank level

64

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International Journal of Information Management, 27(1), 336-351.

Yoo Boonghee and Naveen Donthu (2001). Developing a scale to measure the

perceived quality of an internet shopping site (SITEQUAL). Quartely Journal of


69

Zafar Mohsin, Sana Zafar, Aasia Asif, Ahmed Imran Hunjra and Mustaq Ahmad

(2012). Service quality, customer satisfaction and loyalty: An empirical analysis

of banking sector in Pakistan. Information Management and Business Review,

4(4), 159-167.

Chapter 3

Research Design and

Methodology

Chapter 3

Research Design and Methodology

Contents Page No

3.1 Nature and Scope of the Study 70

3.2 Hypothesis Formulation 70

3.3 Collection of Data 73

3.4 Generation of Scale Items 73

3.5 Data Collection Forms and Sample Design 74

3.6 Scale Purification 75

3.7 Statistical Tools Applied 76

3.8 Scale Validation 77

3.8.1 Confirmatory Factor Analysis 77

3.8.2 Structural Equation Model 77

3.9 Reliability 82

3.9.1 Internal Consistency Reliability 82

3.9.2 Construct/ Composite Reliability 82

3.9.3 Split Half Reliability 82

3.10 Validity Criterion 83

3.10.1 Face Validity 83

3.10.2 Construct Validity 83

3.10.3 Discriminant Validity 83

3.11 Limitations 83

References 85

70

CHAPTER-3

RESEARCH DESIGN AND METHODOLOGY

The various aspects of research design and methodology viz. nature and scope of the

study, hypothesis formulated, data collection forms, sample design, statistical tools

used etc are summarised as under:-

3.1 Nature and Scope of the Study

The present study is both descriptive and evaluative in nature and examines the impact

of various factors that lead to customer satisfaction in internet banking. The study also

measures the impact of internet banking on performance of both public and private

sector banks operating in Jammu city. This study is based on data gathered from

managers and customers of banks operating in Jammu city. The research work will

provide useful insights to bankers, policy makers and researchers in framing policies

that can induce customers to use internet services in banking operations with both

satisfaction to them and gainful business to bankers.

3.2 Hypothesis Formulation

The most important aspect of customer satisfaction is its significant impact on the

repurchase intentions for a product or service. In fact satisfaction is a predictor of

commitment. Chiou (2004) found overall satisfaction of consumers for internet access

positively influencing their commitment. The existing literature particularly indicates a

positive relationship between satisfaction and commitment. Higher satisfaction with

regard to banking operations, including online banking, increases the attractiveness of

relationship to customers and hence their commitment to the relationship with the

banks (Morgan and Hunt, 1994). Thus, customers are more likely to resort to the same

website in the future, to resist in the face of competing alternatives and generate

positive word of mouth. Allagui and Temessek (2004) showed that the more customers

are satisfied with their experience with a provider of e-service, the more committed

they will be. Therefore, it is reasonable to predict that customers who are satisfied with

the internet banking make greater reuse. Thus, it is hypothesized that:-

H1: Customer satisfaction influences commitment in online banking.

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The concept of trust has often been associated with the achievement of long-lasting and

profitable relationships (Anderson and Marus, 1990). Customer attitudes towards

internet banking are driven by trust, which plays an important role in increasing

usability within internet banking environment. The issue of trust is more important in

online as opposed to offline banking because transactions of this nature contain

sensitive information and parties involved in the financial transactions are concerned

about access to critical files and information transferred via the internet (Alsajjan and

Denis, 2006).Trust has been defined as the degree of confidence or certainty the

customers have in exchange option. It has been recognized as an important antecedent

in most models dealing with relationship that include loyalty and satisfaction as

dependent variables (Schaupp and Belanger, 2005). Razzaque and Boon (2003) for

instance, found a significant effect of trust on satisfaction in context of channel

relationship. We expect e-trust not only to have a direct impact on commitment but also

to have indirect influence through e-satisfaction. Thus, it is hypothesized that:-

H2: Trust in online banking positively affects customer satisfaction.

Both service quality and satisfaction are constructs resulting from the comparison of

expectations and performance. Kotler and Armstrong (2012) preach that satisfaction is

the post-purchase evaluation of products or services. The studies of Gilbert and

Veloutsou (2006), Sulieman (2011) and Buttle (1996) find service quality leading to

customer satisfaction. Whereas studies conducted by Han and Baek, 2004; Yang and

Fang, 2004 found service quality positively related to customer satisfaction in an online

environment. Intuitively, the more positive customer perception of online service

quality, the better their overall satisfaction with the bank which leads to greater

profitability of the banks (Gustafsson and Johnson, 2002; Rust, Moorman and Dickson,

2002). Further, to achieve a high level of customer satisfaction, most researchers

suggest that a high level of service quality should be delivered by the service provider

as service quality is normally considered as antecedent of customer satisfaction. As

service quality improves, the probability of customer satisfaction increases, which leads

to higher levels of customer loyalty and subsequently resulting in greater profitability

of the firm or bank. Thus, quality was one of the dimensions on which satisfaction was

based, satisfaction was also one potential influence on future quality perceptions

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(Clames, 2008). Service quality is an important tool to measure customer satisfaction

(Hozlina, 2011). Thus, it is hypothesized that:

H3: Service quality of online banking positively affects customer satisfaction.

H4: Service quality of online banking influences profitability of banks.

Cooper (1997) found that ‘ease of adoption’ is one of the important predictors that may

affect a customer intention. Perceived ease of use is defined as the degree to which an

individual believes that using computer or computerized system will be free from

physical and mental efforts (Davis, 1989). According to Teo (2001), if a system is easy

to use, it requires less effort on the part of users, thereby increasing the likelihood of

adoption and usage. Consult (2002) affirmed that drivers of growth in electronic

banking are determined by the perceived ease of use which is a combination of

convenience provided to those with easy internet access, the availability of secure, high

standard electronic banking functionality and the necessity of banking services, which

influence a customer intention to adopt that technology and improves job performance.

Moreover, bank managers also perceive that a technology if easy to use, could improve

their performance at work, which further improves their organisational performance

(Hajri, 2008). Thus, the following hypotheses were framed are:-

H5: Perceived ease of use positively affects behavioural intention to use online

banking.

H6: Perceived ease of use positively affects business performance.

Perceived usefulness is also an important antecedent of computer utilization (Davis et

al., 1989 and Igbaria Iivari, Morgann, 1995). Davis (1989) defined perceived usefulness

as the degree to which an individual believes that using the system will enhance his/her

job performance. It also suggests that using computers in work place would increase

user’s productivity, improves job performance and enhances job effectiveness and

usefulness. The importance of perceived usefulness has been widely recognized in the

field of electronic banking (Guriting and Ndubisi, 2006; Laforet and Li, 2005).

According to them, usefulness refers to the subjective probability that using the

technology would improve the way a user could complete a given task. Further, the

relationship between perceived usefulness and behavioural intention on online banking

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is based on theoretical argument (Wang et al., 2003 and Guriting and Ndubisi, 2006).

Wang et al., 2003 found a positive effect on behavioural intention to use online banking

whereas Guriting and Ndubisi (2006) found perceived usefulness significantly

determining behavioural intention to use online banking. Thus, the next hypotheses

are:-

H7: Perceived usefulness positively affects behavioural intention to use online banking.

H8: Perceived usefulness positively affects business performance.

3.3 Collection of Data

Both primary and secondary sources, relevant for gathering requisite information

pertaining to the research problem in hand, have been used in the study. First hand

information has been collected through well structured schedule from bank managers,

144 (Annexure 1) and from bank customers, 410 (Annexure 2). The secondary data

have been gathered from books and journals viz. Journal of Internet Banking and

Commerce, Journal of Banking and Finance, International Journal of Bank Marketing,

E-service Journal, Journal of Marketing, etc. Further, to measure bank performance,

various annual reports of bank and statistical tables issued by RBI have been studied for

acquiring the relevant information.

3.4 Generation of scale items

The process of generating scale items was finalised after reviewing the existing

literature and detailed discussion with subject experts. Two schedules were constructed

for collecting the requisite information from the respondents. The schedule for data

from bank managers consisted of nine sections viz. general information, peripheral

services provided by their respective banks, trust (19 statements), commitment (20

statements), service quality (20 statements), perceived ease of use (6 statements),

perceived usefulness (8 statements), customer satisfaction (19 statements) and profit

emphasis (8 statements). The schedule for data from customers also consisted of nine

sections viz. general information, peripheral services that customers avail from their

banks, trust (20 statements), commitment (7 statements), service quality (25

statements), perceived ease of use (10 statements), perceived usefulness (11

statements), behavioural intention (6 statements) and lastly customer satisfaction (20

statements). Following literature has been reviewed for generation of scale items:-

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3.1:Generation of Scale Items in the Schedule I for Data from Bank Managers

Trust and Commitment The items relating to trust were taken from Crosby,

Evans and Cowles, 1990; Wong et al., 2009 etc. While

items pertaining to commitment were taken from

Anderson and Weitz, 1992; Morgan and Hunt, 1994 etc

Service Quality The items relating to service quality have been gathered

from the literature like Sang Lin Han and Seung Baek,

2004; Parasuraman et al., 1985; Parasuraman et al., 1988;

Yang and Peterson, 2004; Lee and Lin, 2005 etc.

Perceived Ease of Use

and Perceived

Usefulness

The items relating to these constructs were gathered from

Adam et al., 1992; Venkatesh and Davis, 1996 etc.

Customer Satisfaction The items of customer satisfaction were taken from

Fornell, 1992; Singh and Komal, 2009; Floh and

Freiblmair, 2006; Fock and Koh, 2006 etc.

Profit Emphasis The items of profit emphasis to measure business

performance of banks were gathered from Deng and

Dart, 1992; Narver and Slaver, 1990; Lee and Hwan,

2005.

3.2:Generation of Scale Items in the Schedule II for Data from Customers

Trust and

Commitment

Mc Knight et al., 2000; Pavlou, 2003, Suh and Han, 2003

etc.

Service Quality Chinh et al., 2008; Yang et al., 2004, Khan and

Mahapatra, 2009 etc.

Behavioural

Intention, Perceived

Ease of Use and

Perceived Usefulness

Zeng et al., 2009; Cheng et al., 2006; Khurana, 2009; Iman

et al., 2006 etc.

Customer Satisfaction Zeng et al., 2009; Minjoon et al., 2003; Wang et al., 2001

etc.

3.5 Data Collection Forms and Sample Design

The required information pertaining to internet banking was gathered from various

bank managers and customers residing in Jammu city through specifically developed

schedules (Annexure 1&2). Census method was used to collect responses from the

selected bank managers. In total 173 branch and loans and advances managers of

various public and private sector banks operating in Jammu city were contacted, out of

whom 144 responded properly. In order to finalise the initial schedule and to determine

appropriate sample size of customers, a pilot survey was conducted in June 2010, on 30

internet banking customers residing in Channi Himmat Colony of Jammu city. For

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selection of final sample, a list of households was obtained from the office of J&K

Housing Board, which consisted of approximately 3218 households. The mean value

(4.07) and variance (0.515) in the population values arrived from the results of

pretesting were used to determine the final sample size with the help of following

formula:

N= (square of standard deviation) × (square of Z)/Square of D

Here value of Z=1.96, where confidence level is 95%

D=+- 0.05 (Level of Precision)

Therefore n= square of 0.51538 × square of 1.96/ square of 0.05

= 0.2656165 × 3.8416/ 0.0025

= 408

This resulted in determining the minimum sample size required for the study (Burns

and Ronald, 2006), which came to be 408 and then rounded off to 410. These 410

respondents were selected from list of J&K Housing Board, Jammu through systematic

random sampling technique. The first house was selected purely on random basis and

thereafter every 8th

house was picked up for the collection of required data. One of the

family members from each house selected, who had done maximum online banking

transactions, was requested to supply information through the aforesaid schedule.

3.6 Scale Purification

The multivariate data reduction technique of factor analysis has been used with the help

of 17.0 version of SPSS, which is most appropriate for the present study, as it involves

the study of interrelationships among variables in an effort to find a new set of

variables fewer in number than the original ones (Stewart, 1981). The study used

principal component analysis with a varimax rotation, for obtaining scores on a larger

set of measured variables and reducing them to scores on a smaller set of composite

variables that retain maximum information from original variables (Fabrigar et al.,

1995). Varimax rotation method has been used as it is among the best and most

commonly used orthogonal rotation procedures (Stewart, 1981). Further, there exists an

interaction effect between sample size, level of communalities and degree of over

determinedness of factors, such that when factors are highly over determined and

communalities are high (above .60), sample size has less impact on quality of results

(Tucker et al., 1969). Thus, when communalities are low, the role of sample size and

over determination becomes more important (MacCallum et al., 1999). Therefore,

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present study aimed at reducing the number of variables by focussing on high

communalities and on high reliabilities (Fabrigar et al., 1995). For describing the

underlying factor structure, the eigen value equal to or more than one criterion has been

used to determine the number of components to be extracted for further analysis

(Stewart, 1981). The test of appropriateness of factor analysis has been verified

through KMO measure of sampling adequacy, where value greater than 0.50 is

acceptable, between 0.50 to 0.70 is mediocre and 0.70 to 0.80 is good, 0.80 to 0.90 is

great and above 0.90 is superb (Malhotra, 2007), which indicates its relevance for

further analysis. Further, Bartlett Test of Sphericity, which is also known as zero

identity matrix, has been used to determine correlation among the variables (Hair et al.,

1995, p.374).

3.7 Statistical Tools Applied

The information obtained through the schedule has been processed and suitably

analyzed in order to bring out precise results with the help of appropriate tools. The

analysis has been carried out with the help of mean, standard deviation, and frequency

distribution. Mean has been used in order to know the value of each observation.

Further, standard deviation has been analysed to work out the amount of variations in

the respondent’s views (Beri, 2008, p.223). The frequency distribution provides much

more concise portrayal of the data (Tull and Hawkin, 1993). Simple Regression has

been used to find out the impact of various independent variables on dependent

variables. ANOVA has been used to examine differences between three or more

variables (Malhotra, 2007). Confirmatory Factor Analysis has been used for scale

validation. For testing the hypotheses, Regression analysis and SEM have been used.

Validity of scale has been established through content, convergent and discriminant

validity. The scores obtained through Likert scale were classified into three groups,

viz., ‘below average’ (1-2), ‘average’ (3), and ‘above average’ (4-5) to make

interpretation more lucid (Churchill, 1988, p.325). The reliability and the internal

consistency of data collected have been judged through tests like the split half and

Cronbach’s alpha values.

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3.8 Scale Validation

3.8.1 Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) is a statistical technique used to verify the factor

structure of a set of observed variables. CFA allows the researcher to test the

hypothesis that a relationship between observed variables and their underlying latent

constructs exists. After purifying the scale items using EFA and reliability analysis, the

final factors that emerged from EFA were confirmed through CFA. To further refine all

measures for CFA analysis, measurement models were estimated using maximum

likelihood estimation (AMOS). It is a way of testing how well measured variables

represent a smaller number of constructs. In CFA no distinction is made between

exogenous and endogenous constructs, hence it is an interdependence technique like

EFA. CFA is different from exploratory factor analysis, as in EFA all measured

variables are related to every factor by a factor loading estimate. However in CFA,

researcher has to assign variables to each factor on the basis of preconceived theory.

The following measures have been used to assess the fit between the obtained solution

and the assumed model – Root Mean Square Error of Approximation (RMSEA),

Adjusted Goodness of Fit Index (AGFI), Comparative Fit Index (CFI), Normed Fit

Index (NFI) and Chi-Square (π2) /degrees of freedom (df).

3.8.2 Structural Equation Modelling

Exploratory Factor Analysis (EFA) explores the data and provides the researcher with

the information about how many factors are needed to best represent the data. Thus, in

EFA factors are derived from statistical results, not from theory. While Confirmatory

factor Analysis (CFA) is used to provide a confirmatory test to our measurement

theory, where researcher has prior information of the factor loadings representing the

actual data (Hair et al., 2009). SEM model often involves both a measurement theory

and a structural theory.

SEM has become one of the most widely applied data analytic techniques in the

business research because of its ability to assess simultaneously the fit of the

measurement models and the structural model. Where measurement models test

relationships (i.e., paths) between the measured (manifest) variables and the construct,

i.e., latent variables; structural model specifies relationships between latent variables of

interest (composite measures). One of the major benefits of using SEM technique is

that it allows concurrent assessment of both reliability and validity by applying CFA.

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Moreover, it can handle various kinds of relationships where an independent variable in

one relationship becomes a dependent model in other relationships. Thus, it can be

concluded that SEM is a more appropriate technique as compared to Factor Analysis

and Regression Analysis.

Goodness of Fit Indices

Goodness of fit refers to the ability of a model to reproduce the data (usually the

variance – covariance matrix). A good fitting model is one that is reasonably consistent

with the data and so does not require re-specification. In addition, a good fit

measurement model is required before interpreting the casual paths of the structural

model.

Parameter estimates must be carefully examined to determine if one has a good model

estimates, it should have good fitting model too. Also it is important to realize that one

might obtain a good fitting model, yet it is still possible to improve the model and

remove specification error. Measurement model’s validity depends on the goodness of

fit (GOF) of the model. GOF indicates how well the specified model reproduces the

covariance matrix among the indicators items (i.e., similarity of observed and estimated

covariance matrix). The model fit compares theory to reality as represented by the data.

If the proposed theory is perfect, the estimated covariance matrix would be the same,

thus the closer the values of these two matrices, the better the model is said to fit. GOF

can be measured in following ways:

Absolute Fit Measures

Absolute fit indices determine how well a priori model fits the sample data and

demonstrate which proposed model has the most superior fit. These measures provide

the most fundamental indication of how well the proposed theory fits the data. Unlike

incremental fit indices, their calculation does not rely on comparison with a baseline

model but is instead a measure of how well the model fits in comparison to no model at

all (Joreskog & Sorbom, 1993). Included in this category are the Chi-Square test,

RMSEA, GFI, AGFI, RMR and SRMR.

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Chi-square statistics )2(

The Chi-Square value is the traditional measure for evaluating overall model fit and

assesses the magnitude of discrepancy between the sample and fitted covariance

matrices (Hu and Bentler, 1999). A good model fit would provide an insignificant

result at a 0.05 threshold (Barrett, 2007), thus the Chi-Square statistic is often referred

to as either a ‘badness of fit’ or a ‘lack of fit’ measure. Chi-square statistics is the

fundamental measures used in SEM to quantify the differences between the observed

and the estimated covariance matrices. A large value of chi-square relative to the

degrees of freedom signifies that the observed and estimated matrices differ

considerably. Statistical significance levels indicate the probability that these

differences are solely due to sampling variations. Thus, the p-value of chi-square test

should be large, indicating no statistical differences between the matrices. While the

Chi-squared test retains its popularity as a fit statistic, there exists a number of severe

limitations in its use. First, this test assumes multivariate normality and severe

deviations from normality may result in model rejections even when the model is

properly specified. Second, because the Chi-square statistic is in essence a statistical

significance test it is sensitive to sample size, which means that the Chi-square statistic

nearly always rejects the model when large samples are used (Bentler & Bonnet, 1980;

Joreskog & Sorbom, 1993). On the other hand, where small samples are used, the Chi-

Square statistic lacks power and because of this may not discriminate between good

fitting models and poor fitting models (Kenny & McCoach, 2003).

Goodness-of-fit Index (GFI)

The Goodness-of-Fit statistic (GFI) was created by Joreskog & Sorbom (1993) as an

alternative to the Chi-Square test. It calculates the proportion of variance that is

accounted for by the estimated population covariance. By looking at the variances and

covariances accounted for by the model it shows how closely the model comes to

replicating the observed covariance matrix (Diamantopoulos & Siguaw, 2000). This

statistic ranges from 0 to 1. When there are a large number of degrees of freedom in

comparison to sample size, the GFI has a downward bias. In addition, it has also been

found that the GFI increases as the number of parameters increases (MacCallum et al.,

1999) and also has an upward bias with large samples (Miles & Shevlin, 1998).

Traditionally an omnibus cut-off point of 0.90 has been recommended for the GFI.

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However, simulation studies have shown that when factor loadings and sample sizes

are low a higher cut-off of 0.95 is more appropriate (Miles and Shevlin, 1998).

Adjusted GFI (AGFI)

Related to the GFI is the AGFI, which adjusts the GFI based upon degrees of freedom,

with more saturated models reducing fit. Thus, more parsimonious models are preferred

while penalized for complicated models. In addition to this, AGFI tends to increase

with sample size. As with the GFI, values for the AGFI also range between 0 and 1 and

generally the values of 0.90 or greater indicate well fitting models.

Root mean square residual (RMR) and standardized root mean square residual

(SRMR)

The RMR and the SRMR are the square root of the difference between the residuals of

the sample covariance matrix and the hypothesized covariance model. The range of the

RMR is calculated based upon the scales of each indicator. Therefore, if a questionnaire

contains items with varying levels (some items may range from 1-5 while others range

from 1-7) the RMR becomes difficult to interpret. The standardized RMR (SRMR)

resolves this problem and is therefore much more meaningful to interpret. Values for

the SRMR range from 0 to 1.0 with well fitting models obtaining values less than .05

(Byrne, 1998; Diamantopoulos and Siguaw, 2000), however values as high as 0.08 are

deemed acceptable (Hu and Bentler, 1999). An SRMR of 0 indicates perfect fit but it

must be noted that SRMR will be lower when there is a high number of parameters in

the model and in models based on large sample sizes.

Root Mean Square Error of Approximation (RMSEA)

The RMSEA was first developed by Steiger (1990). The RMSEA tells us how well the

model, with unknown but optimally chosen parameter estimates would fit the

population covariance matrix (Byrne, 1998). In recent years it has become as ‘one of

the most informative fit indices’ (Diamantopoulos and Siguaw, 2000).

Recommendations for reducing RMSEA cut-off points have been made in the last

fifteen years. Until the early nineties, a RMSEA in the range of 0.05 to 0.10 was

considered an indication of fair fit and values above 0.10 indicated poor fit (MacCallum

et al., 1999). It was then thought that a RMSEA between 0.08 to 0.10 provides a

mediocre fit and below 0.08 shows a good fit (MacCallum et al., 1999). However, more

81

recently, a cut off value close to 0.06 (Hu and Bentler, 1999) or a stringent upper limit

of 0.07 seems to be the general consensus amongst authorities in this area. One of the

greatest advantages of the RMSEA is its ability for a confidence interval to be

calculated around its value (MacCallum et al., 1999). This is possible due to the known

distribution values of the statistic and subsequently allows for the null hypothesis (poor

fit) to be tested more precisely (McQuitty, 2004). It is generally reported in conjunction

with the RMSEA and in a well-fitting model the lower limit is close to 0 while the

upper limit should be less than 0.08.

Incremental Fit Indices:

It is also known as comparative or relative fit indices (McDonald & Ho, 2002). These

are a group of indices that do not use the chi square in its raw form but compare the chi

square value to a baseline model.

Normed Fit Index (NFI)

This statistic assesses the model by comparing the 2 value of the model to the 2 of

the null model. The null/independence model is the worst case scenario as it specifies

that all measured variables are uncorrelated. Values for this statistic range between 0

and 1 with Bentler & Bonnet (1980) recommending values greater than 0.90 indicating

a good fit. More recent suggestions state that the cut off criteria should be NFI .95

(Hu & Bentler, 1999). A major drawback to this index is that it is sensitive to sample

size, underestimating fit for samples less than 200 (Mulaik et al., 1989), and is thus not

recommended to be solely relied on (K.Line, 2005). This problem was rectified by the

Non-Normed Fit Index (NNFI, also known as the Tucker-Lewis index), an index that

prefers simpler models. However in situations where small samples are used, the value

of the NNFI can indicate poor fit despite other statistics pointing towards good fit

(K.Line, 2005; Tabachnick and Fidell, 2007). However, Hu and Bentler (1999) have

suggested NNFI 0.95 as the threshold.

Comparative Fit Index (CFI)

The Comparative Fit Index (CFI) is a revised form of the NFI which takes into account

sample size (Byrne, 1998) that performs well even when sample size is small

(Tabachnick and Fidell, 2007). Like the NFI, this statistic assumes that all latent

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variables are uncorrelated (null/independence model) and compares the sample

covariance matrix with this null model. As with the NFI, values for this statistic range

between 0.0 and 1.0 with values closer to 1.0 indicating good fit. A cut-off criterion of

CFI 0.90 was initially advanced. However, recent studies have shown that a value

greater than 0.90 is needed in order to ensure that misspecified models are not accepted

(Hu & Bentler, 1999). From this, a value of CFI 0.95 is presently recognized as

indicative of good fit (Hu & Bentler, 1999). Today this index is included in all SEM

programmes and is one of the most popularly reported fit indices due to being one of

the measures least affected by sample size.

3.9 Reliability

3.9.1 Internal consistency reliability: It refers to the extent to which items inter

correlate with one another. Internal consistency implies that multiple items measure the

same construct, and inter correlate with one another. In contrast, low inter-item

correlations indicate that some items are not drawn from the appropriate domain and

produce unreliability (Churchill, 1979). The commonly accepted measure of internal

consistency reliability is Cronbach’s coefficient alpha. The value of an alpha of 0.60 is

the minimum acceptable standard for demonstrating internal consistency (Gerrard and

Cunningham, 2004).

3.9.2 Construct/composite reliability: It is the measure of reliability and internal

consistency of the measured variables representing latent construct. It is computed from

the squared sum of factor loadings for constructs and the sum of the error terms for a

construct (Hair et al., 2009).

CR= (Sum of standardized loadings)2/ (Sum of standardized loading) 2 + Sum of error

terms.

The rule of thumb for CR is .70 or higher (Fornell and Larcker, 1981).

3.9.3 Split- Half reliability: A measure of consistency where data is split in two equal

halves and the scores for each half of the test is compared with one another to examine

if the variation in both the halves is within the range of sampling error (Tull and

Hawkins, 1993, p.316).

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3.10 Validity Criterion

3.10.1 Face /content validity: The content/face validity of the construct was assessed

through review of literature and discussions with the subject experts, and managers of

different banks.

3.10.2 Construct validity: It is the extent to which a set of measured items accurately

reflects the theoretical latent construct. It deals with the accuracy of measurement,

evidence of which provides confidence that the items measured from the sample

represent the actual true score that exists in the population.

3.10.2.1 Convergent validity: Convergent validity refers to the extent to which the

measures correlate with other measures that were designed to measure the same thing.

High correlations indicate that the scale is measuring its concept (Hair et al., 2009). It

can be measured in the following ways:-

3.10.2.1 a Factor loadings: High factor loadings i.e., above 0.50 or ideally 0.70 or

higher, indicate level of convergence.

3.10.2.1 b Variance extracted: In CFA, the average percentage of variance extracted

(VE) is a summary indicator of convergence. AVE is calculated by using

standardized loadings, which as under:

AVE = Sum of Squared Standardised Factor Loadings / Number of Items

If AVE comes above 0.50, convergent validity gets established.

3.10.3 Discriminant Validity: Discriminant validity refers to the extent to which the

measures differ from other measures designed to measure different concepts. It can be

examined through the evaluation of the Variance extracted (VE). Fornell and Larcker

(1981) highlighted the importance of evaluating the discriminant validity of the

construct used in the research. They suggested that the variance extracted for each

construct should be greater than squared correlations between constructs.

3.11 Limitations

All the possible efforts have been made to maintain objectivity, validity and reliability

of the study, yet certain limitations do exist which could not be ignored and are

required to be kept in mind whenever its findings are considered for policy formulation

or for future study. These are as follows:-

1. The data collected pertain only to four public and three private sector banks

operating in Jammu city.

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2. The study has measured perceptions of bank managers and customers about

internet banking which might have been guided by their likes and dislikes.

3. Due to privacy involved in banking transactions, bank managers might have

hesitated to share correct information about their bank’s operations. This has

also led to the element of subjectivity in their responses.

4. Due to non availability of foreign banks in Jammu city, no information could be

gathered regarding their online operations.

5. Due to larger number of variables involved in measuring the impact of internet

banking, some variables got missed out such as perceived benefits, perceived

credibility, and loyalty as a whole.

85

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Chapter 4


Business performance

Chapter 4

Impact of Internet Banking on Business Performance

Contents Page No

4.1 Introduction 91

4.2 Data Collection 93

4.3 Scale Generation 93

4.4 Profile of Respondents 94

4.5 Various Services Provided by Different Banks 94

4.6 Factor Analysis 94

4.7 Demographic Background wise Analysis 98

4.7.1 General Information 98

4.7.2 Age Wise Analysis 98

4.7.3 Qualification Wise Analysis 98

4.7.4 Length of Service Wise Analysis 99

4.8 Bank Wise Analysis 99

4.9 Testing of Hypothesis (Regression Analysis) 102

4.10 Confirmatory Factor Analysis 105

4.11 Reliability 111

4.12 Validity 111

4.13 Structural Model 112

4.14 Testing of Hypothesis (SEM) 114

4.15 Business Performance of Indian Banks 115

4.16 Conclusion 129

References 142

91

CHAPTER-4

IMPACT OF INTERNET BANKING ON BUSINESS

PERFORMANCE

4.1 Introduction

Efforts have been made to work out the nature and extent of internet banking in India

and its impact on customer satisfaction and business performance among public and

private sector banks viz. SBI, PNB, UBI, Canara Bank, J&K Bank, ICICI Bank and

HDFC Bank from the perspective of bank managers. The chapter also shows the effect

of demographic background like age, education, length of service of bank managers on

adoption of internet banking.

Today banking is highly information intensive activity that relies heavily on

information technology (IT) to acquire, process and deliver the information to all the

relevant customers (Seitz and Stickel, 1998). The banking business has changed

dramatically over the past 25 years due to technological changes. These technological

changes forced banks to deploy information technology to offer multiple service

channel to serve customers and satisfy their needs. By strategically utilising

information technology to optimise operational performance, banks have continued

some functions with traditional bank branch based channel and enhanced their

functionality by introducing alternative informational technological based service

channels, such as automated teller machine (ATMs) and internet banking (Banker and

Natarajan, 2008). The adoption of information and communication technology in

banking sector improves customer services, facilitated accurate records, provide for

home and office banking services, ensures convenient business hours, prompt and fair

attention and enhances faster services, which consequently improves bank image and

leads to a wider, faster and efficient banking operations (Akinbola and Agboola, 2005).

Laudon and Laudon (1991) observe that bank managers cannot ignore information

systems because it plays a critical role in enhancing efficiency of the organisation.

Information and communication technology directly affects how managers decide, how

they plan and what products and services are offered by them. It has continued to

change the way banks and their corporate relationships are organised worldwide and

the variety of innovative devices available to enhance the speed and quality of service

delivery. Woherem (2000) claimed that only banks that overhaul the whole of their

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payment and delivery systems and apply ICT to their operations are likely to survive

and prosper in the new millennium. Internet banking is the latest in the series of

technological wonders of the recent past. ATMs, Telebanking, Internet banking, credit

cards and debit cards have emerged as effective delivery channels for traditional

banking products. Internet banking is the latest channel which opens new horizons for

banks and enables them to move from local to global frontiers (Mavri and Ioannou,

2006). Internet banking refers to the system that enables bank customers to get access

to their accounts and general information on bank products and services through the use

of bank’s website, without the intervention or inconvenience of sending letters, faxes,

original signatures and telephone confirmations. It provides universal connection from

any location worldwide and is universally accessible from any internet linked

computers (Bradley and Stewart, 2003; Perumal and Shanmugan, 2004; Tulani et al.,

2009). From bank’s perspective, internet banking is more efficient than using any other

distribution channel because banks are looking for an increased customer base. Using

multiple distribution channels increases effective market coverage by enabling different

products to be targeted at different demographic segments (Wang et al., 2003). Banks

consider that developing web based systems or establishing intranets to support internet

based activities will reduce costs and increase productivity. It can also be considered as

a way for attaining business benefits (value) by breaking down barriers of time and

distance between the supply and demand (Shih, 2003). Also gathering necessary

information is one of the main reasons that banks use the internet in daily work (Soh et

al., 1997). Introducing internet in dealing with banking services provides a convenient

and effective way to manage finances. It means less staff members, smaller

infrastructure demands, compared with other banking channels (Fredriksson, 2005).

Moreover another reported advantage of applying e-banking service is that increased

use of internet banking may actually reduce identity fraud. The customers can check

and examine their transactions of different accounts more easily and frequently, which

is easier to access to paper statements to expose identity theft (Herington and Weaven,

2007). A study about the e- banking over 1999- 2006 shows that the application of e-

banking can improve bank’s performance in terms of the growth in assets, reduction in

operating expenses and portfolio enhancement (Dandapani et al., 2008). Moreover, it

also helps banks achieve the objectives of higher customer acceptance and satisfaction,

higher profitability and enhance competitive advantages (Shih, 2003). Thus, with the

use of internet banking, it is possible for banks to offer a number of banking services,

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such as creating an account, fund transfer, bill payment and money management of

services 24 hours a day. Taking in account these developments, it is evident that service

researchers need to pay more attention to consumer evaluations of technology based

services (Parasuraman and Grewal, 2000) for their survival and also taking measures to

increase their productivity, quality of services and competitive abilities which create

new customer base and generate more revenue to the business (Aghdasi et al., 2006).

Thus, the main objective of this chapter is to study, analyse and assess the efforts being

made by bank managers in enhancing internet banking and also to assess the effect of

these services in enhancing business performance of banks from the period it is

implemented to the period of its maturity.

4.2 Data Collection

The data for the present study have been obtained from both secondary and primary

sources. The secondary data obtained from various available journals such as Journal of

Internet Banking and Commerce, Journal of Banking and Finance, Journal of

Marketing, E-service Journal, different books. Also for measuring business

performance of banks, their respective annual reports and statistical tables issued by

RBI have been used to draw inferences. The primary data were collected from 144

bank managers of respective banks in Jammu city. In all 173 bank managers were

contacted, but out of them only 144 responded properly.

4.3 Scale Generation

The primary data were collected through specifically developed schedule (Annexure -1)

on the basis of the available literature (Mc. Knight et al., 2002; Jap and Ganeshan,

2000; Morgan and Hunt, 1994; P.Munhurrun and P.Naidoo, 2000 etc) and discussion

with experts in the related fields of the study. It comprised of 8 items of general

information, 13 items of peripheral services that banks provide to their customers and

100 items based on 5 point Likert scale (5 ---1) i.e ranging from strongly agree (5)

to strongly disagree (1) (Malhotra, 2007, p.274) covering the entire domain of the

study, purified by data purification process through factor analysis which finally

resulted into 30 items grouped under eight dimensions of internet banking.

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4.4 Profile of Respondents

The demographic and some general information including the age, qualification, length

of service with their respective jobs has been gathered. Out of total respondents, 68%

are male and the remaining are female. The age of respondents has been categorised

into three heads viz. Below average, Average and Above average. The average age of

respondents came up as 44 years and more than half i.e 59% respondents fall in above

average age. Majority of the respondents belong to graduate category (43%), followed

by post graduate (29%) and professionals (28%) (Table: 4.1). Majority of respondents

are from J&K bank because its branches are more in number as compared to other

banks operating in Jammu city. Also majority of respondents i.e 67% have working

experience of more than 15 years with their respective banks.

4.5 Various Services Provided by Different Banks

Almost all the banks viz. SBI, PNB, UBI, CANARA, J&K Bank, ICICI Bank and

HDFC Bank provide ATM, credit card, debit card, electronic transfer, tele banking,

internet banking, 24 hours banking, anywhere banking facilities to their customers.

Approximately 50% of respondents find their bank providing facilities for

stocks/shares, foreign exchange. Majority of the respondents observe that with the

development of ATM, debit card, credit cards and electronic funds transfer, the

respective bank branches have withdrawn providing home banking and traveller’s

cheque facility to their customers.

4.6 Factor Analysis

The technique of Factor Analysis has been used through Statistical Package for Social

Sciences (SPSS 17 version) with Principal Component Analysis along with varimax

rotation for summarisation of the total data into minimum factors. The statements

having factor loadings less than 0.5 and eigen values less than 1 were ignored for the

subsequent analysis (Hair et al., 1995). As stated earlier, the schedule comprised of 100

items consisting of various dimensions of internet banking and after applying factor

analysis, 30 statements got converged into eight factors with 76.202 of variance

explained. The eight factors are F1 (Perceived Usefulness), F2 (Trust), F3 (Customer

Satisfaction), F4 (Commitment), F5 (Better Facilities), F6 (Service Quality), F7

(Perceived Ease of Use), F8 (Profitability). Thus, major findings of factor analysis have

been summarised as under:

95

Factor 1: Perceived Usefulness

First factor comprised of eight items of perceived usefulness viz., ‘helps to accomplish

tasks quickly’, ‘improves job performance’, ‘enhances effectiveness of job’, ‘easier to

do job’, ‘www useful’, ‘transaction is advantageous’, ‘relevant information is easily

available’, ‘enhances effectiveness in banking career’. About 96% of respondents feel

that by using online banking channel, it is very easier to do job (MS: 4.36) which

enhances the time and cost saving benefits and consequently enables the bankers to

support the customer order more efficiently and effectively (Novak et al., 1999).

Moreover 93% of respondents find online banking transactions advantageous (MS:

4.36), more innovative and user friendly self service technology, extending bankers

greater autonomy in performing various banking transactions (Pikkarainen et al., 2004).

On the whole all this enhances effectiveness in on the jobs and career prospects of

bankers (MS: 4.5). Moreover bankers were most likely to use computer if it improves

their job performance, increases productivity on the job, enhances effectiveness and

provides information that would lead to better decision and enables them to accomplish

tasks more quickly (Selamat et al., 2009).

Factor 2: Trust

Trust comprising of five variables viz., ‘strong commitment to security measures’,

‘transaction information is protected during a connection’, ‘bank web page offers all

the relevant information about products and services’, ‘does not allow any third person

to access customer’s personal information’, and ‘bank’s log in process is secure’. About

97% of respondents are quite satisfied with the online banking system as their bank

does not allow any third person to access customer’s personal information (MS: 4.54).

Moreover, the respondents also observe their bankers having strong commitment to

security measures (MS: 4.56) as they ensure that a transaction information is protected

during connection (MS: 4.51). Thus, to conclude, banks must convince their customers

about adequate security and safeguards on the websites available such as user

identification and coding of the transmitted data need to be used to ensure security at

transaction level. Also security in this context includes secure transactions as well as

secure front end and back end system (Turban et al., 2000).

96

Factor 3: Customer Satisfaction

Customer satisfaction, being most important to every bank, comprised of five items

viz., ‘clear transaction and price information’, ‘accurate and up to date information’,

‘privacy and security’, ‘customer order fast enough’, ‘satisfied with online payment

system’. Here, respondents are more satisfied with the privacy and security to customer

transaction (MS: 4.48) followed by accurate and up to date information (MS: 4.40) and

online payment system provided by banks which deals with customer order fast enough

(MS: 4.32). Thus, to create customer satisfaction, online banks must adopt personalised

aspect of the service, that is what customers want and act as per their demand by

encompassing proper security measures in delivering services to customers. Further, to

attract more customers to deal online banks must feed their websites with richer

contents such as corporate profile, product and pricing information, interest rates etc

(Cronin, 1998).

Factor 4: Commitment

This factor, named as commitment, comprised of four variables viz., ‘economically to

be a customer of your bank’, ‘commitment is due to reasonable price of bank’,

‘commitment is due to bank’s performance’, ‘customers are committed to buy from

your bank’. Majority of respondents remain committed to buy from their bank because

of their performance (MS: 4.12), high customer satisfaction and reasonable price (MS:

4.05). Hence banks which offer wide range of products and services through internet at

reasonable price creates customer satisfaction as well as customer commitment

(Hamadi, 2010). Also to achieve customer commitment, a bank strategy must be

customer centred, long term and based on the consideration of mutual relationship and

common benefits (Kassim and Abdullah, 2006).

Factor 5: Better Facilities

Better Facilities comprising of two variables viz., ‘deposits have increased by using

online system’ and ‘profits have increased due to facilities to customers’. Factor five

shows 80% of respondents satisfied with online system for banking transactions (MS:

4.02) because it enables the users to initiate various transactions such as transferring

money between accounts or making payments, pay bills, application for loans and

credit card bills online. Thus, it enables the banks to become market leaders by offering

97

large umbrella of services and earning huge profits by providing better and additional

facilities to customers (Hickman, 1999).

Factor 6: Service Quality

Factor six comprised of two variables of service quality viz., ‘bank has upto date

equipment and technology’ and ‘bank provides online services to its customers’.

Results show that about 97% of respondents are quite satisfied with online services for

conducting various banking transactions (MS: 4.53). Hence, banks must focus on how

to improve online services to attract potential customers and how to retain current

customers by encompassing all clues and encounters that occur before, during and after

the transactions (Zeithaml, 2002).

Factor 7: Perceived Ease of Use

Perceived ease of use is associated with the user friendliness of the website which

includes two items viz., ‘interaction on web pages clear and understandable’, ‘easy to

become skilful at navigating the web pages’. Results show about 92% of respondents

feeled skilled at navigating the web pages (MS: 4.34) followed by easy interaction on

web pages, which is clear and understandable (MS: 4.31). In this context banks should

try to develop their internet banking site and interface easier to use. Moreover, if

possible, banks could also provide practical training sessions for customers at their

branches on usage of internet banking interface which helps non-online banking users

also to adopt the technology (Wu et al., 2012).

Factor 8: Profitability

This factor consists of two items of Profitability viz., ‘profit potential of major

customers’, ‘profit potential of various schemes’. Results show that about 92% of

respondents find their bank administrators quickly determining the profitability of

various schemes (M S: 4.33), as well as gains to customers (4.31), which is easily

available from their financial reports.

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4.7 Demographic Background wise: Analysis

4.7.1 General Information

The survey conducted to assess the impact of online banking on customer satisfaction

and business performance on the basis of information from bank managers highlights

that majority of respondents are from J&K Bank followed by SBI, PNB, ICICI Bank,

HDFC Bank, UBI and Canara Bank. The proportion of male respondents came up as

68%. About half of the respondents were graduate and have working experience of

more than 15 years on different positions in their respective banks. Thus, status of

online banking on the basis of background of respondents is given as under:-

4.7.2 Age wise Analysis

As already stated the average age of respondents came up as 44 years. Respondents

were classified into three groups of age viz. below average, average and above average.

Maximum number of respondents (59%) fall under above average category, followed

by below average (38.2%) and average age group (2.8%). ANOVA analysis was used

to find out the effect of demographic background like age on internet banking from two

aspects i.e satisfaction and business performance. The results of ANOVA indicate no

significant difference between the mean scores of respondents under these three groups

(F= .049, sig> .05). On further analysis, when ANOVA was applied factor wise, it

becomes evident that out of eight factors, only one factor i.e ‘profitability’ is significant

(F=4.548, sig <.05) (Table 4.4). The respondents belonging to all the three groups

attributed same responses towards eight factors. Almost all the factors viz. ‘perceived

usefulness’, ‘trust’, ‘customer satisfaction’, ‘commitment’, ‘better facilities’, ‘service

quality’, ‘perceived ease of use’ and ‘profitability’ accorded above average mean

values. Thus, it can be concluded that majority of the respondents are highly satisfied

with the services provided by their respective banks and they also feel a strong

attachment with their bank by having trust and they feel very easy to do transactions

online with their banks which further improves their job performance (Odumeru, 2010).

4.7.3 Qualification- wise Analysis

Qualification has been divided into three groups viz. Graduate, Post Graduate and

Professional. The first group contains majority of the sampled respondents (62)

followed by second group (42) and third group (40). ANOVA results indicate no

significant difference between mean scores of these three groups (F= 0.195, sig >.05).

99

On further analysis, it became evident that out of eight factors only one factor ‘trust’ is

significant (F= 3.445, sig < .05). The respondents belonging to these three groups

attributed same responses towards eight factors. They accorded above average mean

values towards eight factors viz. ‘perceived usefulness’, ‘trust’, ‘customer satisfaction’,

‘commitment’, ‘better facilities’, ‘service quality’, ‘perceived ease of use’ and

‘profitability’. Out of these eight factors perceived usefulness and service quality

accorded almost highest above average mean scores. Thus, it becomes clear that there

is not much difference between responses of these three groups. All the respondents

having different qualifications find their banks giving better services to their customers,

which creates customer satisfaction and hence profitability.

4.7.4 Length of Service wise Analysis

The length of service wise bank managers have been segregated into four segments viz.

below 5 years, 5-10 years,10-15 years and above 15 years of experience (Table 4.5 ).

Majority of respondents are having their job experience of more than 15 years.

ANOVA results indicate no significant difference in the mean scores of these four

groups (F=.218, sig>.05). On further analysis, it becomes apparent that out of eight,

only one factor i.e, ‘better facilities’ is found to be significant at 5% level of

significance (F=2.59, sig<.05). The respondents belonging to all the four groups

attributed almost same responses towards the eight factors. However, there exists

significant difference among respondents having working experience of less than 5

years, 5 to 10 years and within 10-15 years. Respondents having working experience of

10-15 years feel that their bank provides better services to its customers online as

compared to respondents having working experience of 0-10 years. It means

respondents whose usage of internet banking is more than 10 years can influence their

customers to adopt the latest technology which is significantly influenced by perceived

usefulness and perceived ease of use (Yu and Lo, 2007).

4.8 Bank Wise Analysis

The various banks taken for research purpose include both public sector and private

sector banks. The public sector banks are SBI, PNB, UBI and Canara Bank. On the

other hand the various private sector banks are J&K Bank, ICICI Bank and HDFC

Bank. ANOVA was used to know difference existing in the mean satisfaction of

respondents belonging to different banks and it was found to be significant (F=2.519,

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sig<.05). Moreover, significant difference exists between respondents with regard to

three factors viz. commitment (sig=.020), better facilities (sig=.001), service quality

(sig=.002). (Table: 4.6). Thus, each group of different bank has been analysed

separately (Table 4.7).

J&K Bank

This group accorded maximum mean scores towards two factors viz. ‘perceived

usefulness (4.41)’and ‘Trust (4.46)’. Above average mean scores were attributed to the

remaining six factors viz. ‘customer satisfaction (4.29)’, ‘commitment (4.19)’, ‘better

facilities (4.10)’, ‘service quality (4.36)’, ‘perceived ease on use (4.24)’ and

‘profitability (4.29)’. Thus, it can apprehended that managers of J&K bank are highly

satisfied with their bank as it is the leading bank in J&K state, providing latest

technology that changed the way to carry on their financial transactions. Further, they

also find that their bank is providing relevant information about all products and

services to their clients online and ensured them that their needed information is

protected during a connection. Also they do not allow any third person to access their

client’s information online. Moreover, the respondents of this bank observe using

online channel in doing banking transactions as easy which enhances their effectiveness

in banking career (Abukhzam and Lee, 2010).

SBI Bank

The bank accorded highest mean scores towards six factors viz. ‘customer satisfaction

(4.51)’, ‘trust (4.57)’, ‘perceived usefulness (4.50)’, ‘better facilities (4.51)’,

‘profitability (4.50)’ and ‘perceived ease of use (4.46)’. The remaining two factors viz.

‘commitment (3.90)’ and ‘service quality (3.75)’ received average level of mean

values. Thus, it can be concluded that respondents of this bank are highly satisfied with

all aspects of internet banking. This may be due to the reason that their bank’s online

server is secured, which provides privacy and security to customers. Moreover, the

respondents of this bank also feel that their banks create customer satisfaction but their

commitment level is low due to average level of quality of services provided by bank.

PNB Bank

The respondents from PNB accorded above average mean values for six factors viz.

‘perceived usefulness (4.50)’, ‘trust (4.44)’, ‘customer satisfaction (4.33)’, ‘service

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quality (4.50)’, ‘perceived ease of use (4.42)’ and ‘profitability (4.27)’. The remaining

two factors viz. ‘commitment (3.76)’ and ‘better facilities (3.70)’ accorded just slightly

above average mean values. Thus, it becomes evident that respondents of the bank are

highly satisfied with online services which is easier to use and helps them to

accomplish their tasks quickly such as seeking relevant information about clients and,

thus, enhances effectiveness in their respective jobs (Shih, 2003). However, the

respondents of the bank feel that their profits have been also increased by providing

better facilities to their customers.

ICICI Bank

The respondents from the bank under reference accorded almost above average mean

values to all the eight factors viz. ‘perceived usefulness (4.19)’, ‘trust (4.65)’,

‘customer satisfaction (4.40)’, ‘commitment (4.38)’, ‘better facilities (4.05), ‘service

quality (4.83)’, ‘perceived ease of use (4.44)’ and ‘profitability (4.27)’. The

respondents find their bank having upto date equipment and technology and they

provide better online services to their customers. Further, they feel that their customer’s

information is being protected while doing online transaction and their bank does not

allow any third person to access any customer’s personal information.

HDFC Bank

The bank accorded highest mean values for six factors viz. ‘trust (4.80)’, ‘service

quality (4.78)’, ‘perceived ease of use (4.71)’, ‘customer satisfaction (4.68)’, ‘perceived

usefulness (4.55)’ and ‘profitability ((4.71)’. The remaining two factors viz.

‘commitment (4.10)’and ‘better facilities (3.14)’ accorded less mean values. Thus, it is

evident that respondents of this bank have trust in their bank’s online services followed

by better service quality. The bank has strong commitment to security measures which

ensures that transaction information is protected during a connection. Moreover, the

respondents of this bank are moderately satisfied with increase in deposits by providing

online services to its customers.

UBI Bank

The bank accorded highest mean values for three factors viz. ‘trust (4.51)’, ‘perceived

usefulness (4.12)’, ‘service quality (4.07)’. Only one factor viz. ‘commitment (2.86)’

received less than average mean values. The remaining four factors received slightly

102

above average mean values viz. ‘customer satisfaction (3.85)’, ‘better facilities (3.07)’,

‘perceived ease of use (3.92)’ and ‘profitability (3.92)’. Thus, it is evident that

respondents of the bank are more satisfied towards security measures followed by the

relevant information about all products and services online which enables their

customers further to deal online. The respondents of this bank are least satisfied with

the measure commitment. Though the respondents have trust in dealing online and they

find it easier to do their job but their commitment level is low due to time taken in

conducting online transactions.

Canara Bank

The bank under reference accorded above average mean values for six factors viz.

‘perceived usefulness (4.53)’, ‘customer satisfaction (4.10)’, ‘commitment (4.12)’,

‘perceived ease of use (4.25)’, ‘trust (4.35)’ and ‘profitability (4.12)’. The remaining

two factors viz. ‘better facilities (3.87)’ and ‘service quality (3.75)’ accorded just

slightly above average mean values. Thus, to conclude respondents of this bank are

more satisfied with security measures provided by their bank. The respondents also find

using online channel enabling them to accomplish their tasks quickly, which improves

their job performance and thus enhances their effectiveness in banking career.

Moreover, managers found work productivity mainly depending on the system

effectiveness in searching for information and were more interested in using the

internet if it was very easy to use (Davis et al., 1989).

4.9 Testing of Hypothesis Through Regression Analysis

H1: Customer satisfaction influences commitment in online banking

O1: To measure the impact of customer satisfaction on customer commitment.

To measure the impact of customer satisfaction on customer commitment, linear

regression analysis was used, which shows value of R as 0.414, reflecting about 41%

association existing between customer satisfaction and commitment. Also R-square is

equal to 0.171, meaning thereby 17% variation between customer satisfaction and

commitment. The table further indicates the value of adjusted R-square which is equal

to 0.165 i.e any time another independent variable is added to regression models, the R-

square will increase. The regression model in ANOVA table reflects the overall model

significantly different from 0 (F ratio= 29.324, p=.000). This probability implies that

103

there are .000 chances the regression model results come from the population, where

the R-square is 0.00 i.e there are .000 chances out of 1000, that the correlation

coefficient is 0.00. Also, to examine whether satisfied customers remain committed to

deal online, information provided in the coefficient table has been examined. The

standardised beta values reveal that customer satisfaction has a beta coefficient of

0.414(t=5.414), which is significant (0.000). Hence, the above stated hypothesis is

accepted.

H2: Service quality of online banking influences profitability of banks.

O2: To find out the impact of service quality of online banking on profitability of banks.

Linear regression analysis was used to find out the impact of online banking service

quality on profitability of banks. The results revealed the value of R as 0.283, which

reflects 28% association existing between service quality and profitability of banks.

Also the value of R-Square is 0.08, which means 8% of variation between profitability

and service quality of banks. The table further indicates that adjusted R Square is 0.073

i.e any time another independent variable is added to regression model, the R- Square

will increase. The regression model in the ANOVA table reflects that the overall model

is significantly different from 0 (F ratio =12.319, p=0.001). This probability level

implies that there are 0.001 chances the regression model results come from a

population where the R –Square is 0.00 i.e there are 0.001 chances out of 1000, that the

correlation coefficient is 0.00. Further, to determine if service quality is a significant

predictor of profitability of banks, information provided in the coefficient table has

been examined. The standardised coefficient beta values reveal that service quality has

a beta coefficient of 0.283 (t=3.510), which is significant (0.001), implying service

quality of online banking having a strong and significant impact on profitability of

banks. Thus, the stated hypothesis is accepted.

H3: Trust in online banking positively affects customer satisfaction.

O3: To measure the impact of trust on customer satisfaction.

To measure the impact of trust on customer satisfaction, linear regression analysis was

worked out which shows the value of R as 0.434, reflecting thereby 43% association

existing between customer satisfaction and trust. Also R-Square is equal to 0.188,

which means 18% variation between trust in online banking and customer satisfaction.

The table further indicates the value of adjusted R-Square which is equal to 0.182 i.e

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any time another independent variable is added to regression models, the R- Square will

increase. Further the regression model in the ANOVA table reflects the overall model

significantly different from 0 (F ratio=32.902, p=.000). This probability implies that

there are 0.000 chances the regression model results come from the population, where

the R-Square is 0.00 i.e there are 0.000 chances out of 1000, that the correlation

coefficient is 0.00. Also, to determine whether trust in online banking generates

customer satisfaction, information provided in the coefficient table has been examined.

The standardised beta values reveal that trust has a beta coefficient of 0.434 (t=5.736),

which is significant (0.000). Hence the above stated hypothesis is also accepted.

H4: Service quality of online banking influences customer satisfaction.

O4: To measure the impact of online service quality on customer satisfaction.

In order to prove the above hypothesis, again simple linear regression analysis was

worked out which shows value of R as .348, reflecting 34% association between

service quality and customer satisfaction. Also R-square for the model is .121, showing

that 12.1% variation between customer satisfaction and service quality. The table also

indicates that the adjusted R-square for the model is.115. Anytime another independent

variable is added to regression model, the R-square will increase. The regression model

in the ANOVA table reflects the overall model significantly different from 0 (F-

ratio=19.559, p=.000). Further, to determine whether service quality of online banking

influences customer satisfaction, information provided in the coefficient table has been

examined. The standardised coefficient beta values reveal that SQ has a beta coefficient

of 0.348 (t=4.423), which is significant (.000). Thus, service quality significantly

affects customer satisfaction. Hence, the hypothesis is accepted.

H5: Perceived ease of use of online banking will have a positive effect on bank’s

profitability.

O5: To measure the effect of perceived ease of use on profitability of banks.

The relationship between perceived ease of use and profitability of banks has been

measured with the help of regression analysis. The value of R is equal to 0.340 which

shows 34% correlation between perceived ease of use and profitability of banks. The

value of coefficient of determination (R-square) figured out at 0.116, which indicates

12% variation in perceived ease of use and profitability of banks. Adjusted R- Square

for the model is 0.109. Anytime another independent variable if added to regression

105

model, the R- Square will increase. The value of F is 18.550 (0.000). The coefficient

table has been examined to work out the beta value which came as 0.340 (t= 4.307),

which is significant. Thus, the stated hypothesis is accepted.

H6: Perceived usefulness will have a positive effect on bank’s profitability.

O6: To measure the effect of perceived usefulness on profitability of banks.

To measure the effect of perceived usefulness on profitability of banks, again linear

regression analysis was worked out. According to the model summary table (Table:

4.8), the value of R as 0.470 which reflects 47% association between dependent and

independent variables. Also R- Square for the model is 0.221. This shows 22.1%

variation between profitability and perceived usefulness of managers. The table also

indicates that the adjusted R- Square for the model is 0.215. Anytime another

independent variable if added to regression model, the R-Square will increase. The

regression model in the ANOVA table reflects the overall model significantly different

from 0(F- ratio=40.224, p=.000). This probability level implies that there are .000

chances the regression model results come from a population where the R-Square is

0.00 i.e, there are .000 chances out of 1000 that the correlation coefficient is 0.00.

Further to determine whether perceived usefulness significantly predicts profitability of

banks, information provided in the coefficient table has been examined. The

standardised coefficient beta values reveal that perceived usefulness has a beta

coefficient of 0.470(t=6.342), which is significant (0.000). Thus, perceived usefulness

is significantly related to profitability of banks. Hence, the hypothesis is accepted.

4.10 Confirmatory Factor Analysis

A confirmatory factor analysis (CFA) using AMOS 16 was applied to test the

theoretical model and hypothesis (Nguyen, 2007) vis-a-vis to assess fitness, reliability

and validity of measurement models for different constructs in the study. The various

resulting measurement models are as follows:-


The first order confirmatory factor analysis model for construct ‘perceived usefulness’

was designed to test the relationship between eight variables and main construct viz.

perceived usefulness (Fig: 4.1). The model presented eight observed indicators. The

number of observed variances 36 [8(8+1)/2] was 36 and the number of estimated

106

parameters in the model was 16 (8 regression weights and 8 variances). Thus, based on

t-rule, the first order confirmatory factor analysis model for perceived usefulness was

over identified and tested with 20 degree of freedom (36-16= 20). Model has been

found to be appropriate as the values are fit under the threshold criteria (chi-square/df=

1.581, RMR= 0.19, GFI= 0.962, AGFI= 0.909, TLI= 0.977, CFI= 0.988 and RMSEA=

0.064) and valid as indicated through AVE, which came to be 0.51, higher values of

standardised regression estimates of each indicator and lastly through construct

reliability, which came to be 0.937.

107

Fig 4.1: Measurement Model of Perceived Usefulness

Trust

First order confirmatory factor analysis resulted into five indicators of the construct.

The number of observed variances [5(5+1)/2] was 15 and number of parameters in this

Perceived use

pu1

e1

.76

1

pu2

e2

.79

1

pu3

e3

.80

1

pu4

e4

1

pu5

e5 .73 1

pu6

e6

.70

1

pu7

e7

.70

1

pu8

e8

.85

1

.21

.17

.15

.13

.07

108

model was 10 (5 regression weights and 5 variances). Similarly based on t-rule, the

model was tested with 5 degree of freedom (15-10). All these indicators obtained factor

loadings above 0.5, thus revealing convergent validity of the model. Construct validity

was also established through average variance extracted and construct reliability, whose

values came up as 0.61 and 0.938 respectively. The model was of good fit (CMIN/df=

0.472, RMR= 0.006, GFI= 0.996, AGFI= 0.981, TLI=1.013, CFI=1.000 and RMSEA=

0.012).

Fig 4.2: Measurement Model of Trust

Customer Satisfaction

This model resulted into five indicators viz. clear transaction and price information,

accurate and up to date information, privacy and security, customer order fast enough

and online payment system. Model has been found to be appropriate (chisquare/df=

1.329, RMR= 0.010, GFI= 0.989, AGFI= 0.947, TLI= 0.991, CFI= 0.997 and

RMSEA= 0.048) and valid as AVE= 0.60 and construct reliability= 0.90.

TRUST

t1 e1

.80 t2 e2

.85

t3 e3 .76

t4 e4 .83

t7 e5

.67

.06

.08

109

Fig 4.3: Measurement Model of Customer satisfaction

Commitment

This model consisted of four indicators viz. economically to be a customer, customers

are committed, reasonable price, and committed because of performance. All model fit

indices were sufficiently satisfied with their related thresholds. The model fits the data

with CMIN/df= 1.057, RMR= 0.017, GFI= 0.993, AGFI= 0.964, TLI= 0.999, CFI=

1.000 and RMSEA= 0.020. The model has also been proved to be valid as indicated

through AVE which came to be 0.653, higher values of standardised regression weights

of each indicator, high construct reliability (0.818) which was assessed from the

construct loadings and error variances (Hair et al., 2009).

cust sat

cs14e1

.79cs15e2

.57cs16e3

.83

cs17e4 .84

cs18e5

.75

.22

.33

110

Fig 4.4: Measurement Model of Commitment

Profitability

This model consisted of four variables viz. ‘increased deposits’, ‘increased profits’,

‘profitability of various schemes’, and ‘profitability of customers’. The model fits the

data with CMIN/df= 1.021, RMR= 0.016, GFI= 0.997, AGFI= 0.985, TLI=1.000,

CFI=1.000 and RMSEA= 0.023 and valid as AVE= 0.464 and construct reliability=

0.839

Fig 4.5: Measurement model of Profitability

Service Quality and Perceived ease of use

CFA has not been run on these two factors as only two items remained after

exploratory factor analysis. Thus, only aggregate mean values are taken for structural

profitability

pe1

e1

.76

1

pe2

e2

.93 1

pe3

e3 .53 1

pe4

e4

.67

1

.35

commitment

c10 e1

.74 c11 e2

.95

c12 e3 ..76

c13 e4

.75 .29

111

equation modelling. But the validity could be assessed through AVE and construct

reliability which came to be 0.695 and 0.854 in case of perceived ease of use and 0.536

and 0.823 in case of service quality.

4.11 Reliability

To check the reliability, Cronbach Alpha and Split half values have been worked out

(Malhotra, 2007; p.285) twice i.e before and after factor analysis by dividing the

respondents into two equal halves. The data were found reliable before the factor

analysis as mean values of both the groups (Group 1= 4.34 and Group 2=4.31) are

almost similar. Similarly after factor analysis, the data were proved quite satisfactory in

terms of split half reliability as mean scores obtained from both groups of respondents

are satisfactory (Group 1= 4.35 and Group 2= 4.33). Moreover, Cronbach Alpha values

also proved reliable before and after factor analysis as it came to be 0.965 and 0.919

respectively (Table 4.11). Reliability is also an indicator of convergent validity. The

rule of thumb for reliability estimate is 0.70 or higher and reliability in the present case

is established as it is above 0.70 in all the cases.

CR= (Sum of standardised loadings)2/ (Sum of standardised loadings)2+Sum of error

variance terms

4.12 Validity

1. The content validity was duly assessed by reviewing the literature and

discussion with experts and researchers working on similar topics.

2. The construct validity measuring the extent to which a single scale measures

the same construct has been examined through Factor analysis. An eigen

value equal to one is taken as criterion for significance of a factor. Eigen

values of all the factors are greater than one, indicating strong construct

validity. It can also be established through convergent validity.

3. The items that are the indicators of a specific construct should converge or

share a high proportion of variance in common, which is known as convergent

validity. The various ways to estimate the relative amount of convergent

validity among item measures are as under;

3 a. Factor Loadings: High factor loading, i.e., above 0.50 or ideally 0.7 or

higher indicates higher level of convergence. Convergent validity gets

112

established in the present study as majority of factor loadings came out

to be above 0.50 (Table: 4.3).

3b. Variance Extracted: In CFA, the average percentage of variance

extracted (VE) among a set of construct items is a summary indicator

of convergence. VE is computed as the total of all squared standardised

factor loading divided by number of items. VE should be 0.50 or

greater to suggest adequate convergent validity and in our case VE for

all the constructs came to be above 0.50 (Table: 4.10).

4. Discriminant validity: It is the extent to which a construct is truly distinct

from other constructs. High discriminant validity provides evidence that a

construct is unique and captures some phenomena, which other measures do

not. Discriminant validity was assessed with the variance extracted test

recommended by Fornell and Larcker (1981), where variance extracted should

be greater than the squared correlation between the constructs and this

condition has been fully satisfied by all the constructs (Table: 4.12).

4.13 Structural Model

Structural Equation Modelling, a statistical technique for testing and estimating causal

relations, represents relationship between latent constructs. It can be expressed in the

terms of a structural model that represents the theory with a set of structural equations

and is usually depicted through a visual diagram. Structural model emphasises on the

relationship between the latent constructs and measured variables. Structural model can

be either recursive or non-recursive. A recursive model is one in which all the paths

between the constructs proceed only from one predictor to dependent or outcome

construct i.e no feedback loop exists in it. In non-recursive model, feedback loop does

exist (Hair et al., 2009).

Initially a recursive model was proposed with seven constructs viz. SQ,

TRUST, PEOU, PU, CS, CMT and BF. It was proposed that service quality influences

trust, which in turn affects customer satisfaction, commitment and business

performance. Further PEOU and PU of employees affect business performance. Thus,

on the whole CS is not only predicted through service quality and trust but also through

PEOU and PU. However, this model was not found to have an appropriate fit as chi-

113

square statistic came to be 6.976, GFI= 0.886, AGFI= 0.710, RMR= 0.085, CFI=

0.776, TLI= 0.572 and RMSEA= 0.204, hence revealing a poor fit.

In order to get a model with good fit, some significant relationship of perceived

ease of use and customer satisfaction were established which reduces the chi-square

statistics to 5.137, GFI= 0.915, AGFI= 0.761, CFI= 0.859, TLI= 0.703, RMR= 0.061

and RMSEA= 0.170. Kumbhar (2011) proved that perceived ease of use is an important

factor that generates customer satisfaction in an e-banking context. Hamadi (2010) also

established a relationship between perceived quality and satisfaction, wherein perceived

ease of use is measured through perceived quality which influences satisfaction and

hence commitment. Alam and Soni (2012) also support the relationship between PEOU

and CS, thus giving a theoretical support for PEOU and CS relationship.

Again relationship of perceived usefulness and customer satisfaction were

added to the model, which further reduced the chi-square to 3.487, GFI= 0.942, AGFI=

0.821, TLI= 0.822, CFI= 0.924, RMR= 0.050 and RMSEA= 0.132. Musiime and

Ramadhan (2011) also support the relationship between customer adoption to internet

banking, which is influenced by PEOU and PU and CS.

In the next phase, relationship between trust and commitment is established to

get better model fit as compared to the previous one. This relationship is established not

because of the modifications recommended but also due to the availability of a sound

theoretical support. Lee (2007) found trust in a bank influencing customer satisfaction

and hence commitment. Durkasree and Ramesh (2011) concluding customer

satisfaction being influenced by perceived tangibility, trust and confidence and

ordering. Casolo et al., (2007) also found positive relationship between trust and

relationship commitment.

The last phase of modification indices led to the addition of one more

relationship between service quality and profitability (Lee and Hwan, 2005). The final

model has been found to have a good fit, as its chi square statistics came to be 1.83,

GFI= 0.976, AGFI= 0.903, TLI= 0.940, CFI= 0.980, RMR= 0.036 and RMSEA= 0.076

(Table:4.13).

114

Fig 4.6: Structural Equation Model of Online Banking from Managers Perspective

Key: Sq=service quality, t=trust, peou= perceived ease of use, pu= perceived

usefulness, cs= customer satisfaction, c=commitment, bf= business performance

4.14 Testing of Hypothesis

HO1: Customer satisfaction influences commitment in online banking.

It becomes evident from the SEM results that CS positively affects Commitment (.404)

and is significant, thus accepting our first hypothesis.

HO2: Service quality of online banking influences profitability of banks.

This hypothesis also stands accepted as effect of service quality on business

performance is significant but not too much high (.228).

HO3: Trust in online banking positively affects customer satisfaction.

The direct effect of trust on customer satisfaction is significant and is positive (.363),

thus accepting the stated hypothesis.

sq

t

peou

pu

cs

c

bf ep

.38

.22

.08

.36

.48 .72

.40

.44

e4

e5

e6

e7

.34

.22

.19

.36

.20

e9

e10

.55

.97

115

HO4: Service quality of online banking influences customer satisfaction.

As it is clear from the path analysis of SEM that there exists significant and positive

effect of service quality on customer satisfaction, thus accepting the hypothesis.

HO5: Perceived ease of use of online banking will have a positive effect on banks

performance.

This hypothesis is tested by introducing unobserved variable viz. employee

performance in the path diagram. Employee performance is measured through two

constructs viz. perceived ease of use and perceived usefulness, which effects business

performance. From the path diagram, it is observed that employee performance

measured through perceived ease of use is significant (.546) which further effects

business performance (.72), thus accepting the hypothesis.

HO6: Perceived usefulness of online banking will have a positive effect on banks

performance

This hypothesis also stands accepted as employee performance measured through

perceived usefulness is significant and positive (.978), which further effects business

performance (.72).

HO7: Customer satisfaction positively affects business performance of banks.

This hypothesis also stands proved as there exists direct effect between customer

satisfaction and business performance which is significant and high (.436).

4.15 Business Performance

Facing continuously changing and highly competitive business environment, banks

have invested heavily in information technology (IT) to enhance operating efficiency

and sustain competitive advantage (Banker and Natarajan, 2008). The effectiveness of

organisations in fulfilling its purpose can be seen in terms of their business

performance. It can also refer to either the ends (results) or the ‘means’ that produce the

end (Epstein, 2004). Performance is an important variable which helps in determining

the status of an organisation as compared to its competitor in an economy. It is in this

context bank managers must deal with performance on two dimensions, its level

(return) and the variation in that level (risk). However, performance has traditionally

been studied only in terms of return (David B, 1987). Although performance can have a

116

variety of meanings (short or long term, financial or organisational benefits), it is

broadly viewed from two perspectives viz. objective and subjective (Sin et al., 2005).

The objective performance involves financial or market based measures such as

profitability, market share, return on equity (ROE), return on asset (ROA), return on

investment (ROI) and capacity utilisation. Whereas subjective performance can be

measured through customer satisfaction, service quality, institutional image, customer

commitment etc (Aggarwal, Erramilli and Dev, 2003). Moreover, business performance

can be measured in terms of its capacity to generate sustainable profitability. It is a

bank’s first line of defence against unexpected losses, as it strengthens its capital

position and improves future profitability through the investment of retained earnings.

Hence, the profitability or objective performance measures used in this study include

the net profit, rate of return on assets (ROA), the rate of return on equity (ROE) (M.

Bashir, 1999). The rate of return on assets (ROA) is the most comprehensive

accounting measure of bank’s overall performance. It is defined as net income over

total assets, it shows the profit earned per rupee of assets. It is an indicator of bank’s

efficiency and a measure of the bank’s ability to earn from its total operations. Also it

gauges how effectively a bank uses its financial or real investments to generate profits.

The other variable viz. return on equity (ROE) reflects how effectively a bank

management is using shareholder’s investment. It is defined as net income divided by

average equity and measures bank accounting profits per rupee of book equity capital.

The bank’s return on equity needs to be greater than its cost of equity as it tells the bank

shareholders how much the institution is earning on the book value of their investment

(Goudreau, 1992). Thus, return on assets measures profitability from the point of view

of the overall efficiency of a bank’s use of its total assets, return on equity captures

profitability from the shareholder’s perspective. Thus, higher the ratio better it is. The

subjective performance of banks is measured with the help of online service quality,

trust, customer satisfaction and their commitment for using online services in future

from both customer’s perspective as well as from manager’s perspective. Further, to

evaluate outgrowth of business on account of internet banking services in their

operations, the performance of banks will also be evaluated by considering period

between 1990-95 as pre e-banking period and then comparing it with three different

stages of IT development viz. period between 1996-2000 (First stage), 2001-05 (middle

stage) and 2006-2012 (Advanced stage) and between banks also (Kour, 2012; Kashap

and Sharma, 2012; Uppal, 2011).

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4.15.1 Business Performance of J&K Bank

The Jammu and Kashmir bank (JKB), incorporated on 1-10-1938, has a potential

growth prospect in terms of net profit, return on assets, return on equity, deposits and

advances. For examining the impact of internet banking on financial performance of

JKB, the aforesaid financial indicators have been used by comparing it’s business

performance before and after application of internet banking. The average net profit of

the bank before the implementation of internet banking services (1990-95) came to Rs.

1695 lakhs while in the financial year 1998-99, JKB entered into an agreement with

IBA to provide ATM facilities and in year 1999-2000, the bank had tied up with

Infosys Technologies to offer internet banking services to their customers. Thus, in the

first year of developing information technology, the net profit of bank increased by

69% (Rs.5037 lakhs in 1997-98 to Rs. 8545 lakhs in 1998-99). As such customers find

it convenient to withdraw their money easily through ATMs and are also able to check

their account balances. In the second stage of development of internet banking

facilities viz. period from 2001-05, the average net profit came to Rs. 25730 lakhs

(330% increase during five years). It was in this period that the bank had widened its

scope for providing multiple services to its customers. In year 2003-04, the bank started

RTGS payment system and credit card facilities, enabling the customers to transfer

funds and make hassle free cash payment without having their debit balances in their

accounts. Further in year 2005-06, the banks started providing easy payment of various

bills like electricity, insurance premiums etc to their customers and in year 2010-11, the

bank, thus, had integrated with more than 900 online merchants like Airtel, Make My

Trip, Metlife etc to provide various online bill payment and shopping facilities to its

customers, encouraging them to use more online banking facilities. In the same year,

the bank also started ‘SMS Alert’ facility that enabled the customers to receive prompt

information about their transactions via SMS on their mobiles. All this facilitated an

increase of net profit to Rs 80334 lakhs in 2011-12. It is also exhibited that return on

assets which is equal to net profits to working funds also shows a rising trend (1.04%

in 1990-91 to 1.145% in 2011-12), however with little fluctuations. The return on

assets during 1991-92 fell due to economic crises whereas in 2004-05, it fell due to

insulated effects of inflation and hardening of interest rates. Similarly, the return on

equity (ROE), that measures how effectively a bank management is using its

shareholders investment also improved significantly from 14.26% in 1990-91 to

21.22% in 2011-12. Further, JKB has been a quite successful bank so far as its fund

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based business is concerned. Its total advances and deposits for the period under

reference (after implementing internet banking services) also shows a rising trend from

Rs. 4762.90 crore and Rs. 11168.08 crores respectively in the year 2001 to Rs

330774.215 crores and Rs. 533469.016 crores in 2011-12. Similarly, the subjective

performance of JKB in the form of customer satisfaction is high as their customers are

satisfied with online banking services viz. up to date information related to their

banking transactions and privacy and security to their dealings. The level of customer

trust and commitment is also high in JKB which may be due to timely fulfilment of

transactions or due to open communication between customers and bank administrators

and easy solution for all online problems. In addition to this, the level of employee

performance is also high because managers find the adoption of online facilities making

it easier to do their job and consequently enabling them to support customer order fast

enough (Novak et al., 1999). The administrators are also able to determine quickly the

profitability of various schemes and customers and hence it increases the visibility of

the bank in the market. Almost all managers of all the branches are quite satisfied with

internet facilities given to customers. Moreover, the reasonable and transparent charges

levied by bank in delivering online services, attract customers in dealing online. It is in

this context to evaluate online effectiveness of JKB with financial performance, a

comparison has been made between various dimensions of the study with the profits of

the bank from both banker’s perspective as well as from customer’s perspective (Table:

4.22). Managers of JKB provide above average level of online service quality (MS:

4.35) and trust (MS: 4.42) to customers in context of online transactions. Further, the

level of customer satisfaction (MS: 4.26) and customer commitment (MS: 4.18)

measured through managers’ responses indicate above average mean scores, matching

with the increase of net profit to 30% (From Rs. 61526 lakhs in 2010-11 to Rs. 80334

lakhs in 2011-12) in one year and average increase of 75% in six years time period

(2006-12). But, when these responses are compared with customers responses and with

other banks, it reveals that JKB just provides average level of service quality (MS:3.69)

and trust (MS:3.89), although the level of customer satisfaction (MS: 4.04) and

customer commitment (MS: 3.91) are quite satisfactory, indicating that proportion of

percentage change in profit of JKB due to online effectiveness is less as compared to

other banks like HDFC Bank and ICICI Bank, thus activating the administrators of

JKB to deliver exceptional online services such as online transfers, payment of bills

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with out much loss of time to attract customers in dealing online. All this helps in

meeting customers’ financial requirements and hence increases profitability of bank.

4.15.2 Business Performance of HDFC Bank

Housing Development Finance Corporation (HDFC) Bank, a private sector bank

incorporated in August 1994, has a nationwide network with 3062 branches and 10743

ATMs. With the help of updated and advanced technology, its business performance is

improving day by day and is significantly high when compared with other two private

sector banks viz. J&K Bank and ICICI Bank. Today its net profit is as high as Rs.

514178 lakhs over a period of last one and half decades. The average net profit for the

initial period (1995-2000) came to be Rs 6628 lakhs followed by Rs 41396 lakhs during

2001-05, registering average growth rate of 524% in between two different periods of

development (Table: 4.16). However, its net increase rate is lowest in comparison to

ICICI bank but higher from all other banks under study. In the initial period, the bank

provides debit card and phone banking facilities, later in year 2001 the bank provided

online banking and credit card to its customers. Furthermore, the average net profit for

the advanced period (2006-12) came to be Rs.255565 lakhs, 517% increase from the

previous period. It was in this period that bank provided online transfers, online

ticketing, payment of various bills, VBV facility for online shopping to customers and

thus it was ranked top ranking one in the private sector banking in India in 2010. The

ROA and ROE also show rising trend from 1.46% and 17.26% in 1995-96 to 1.77%

and 18.69% in 2011-12 with wide fluctuations. But when it is compared on average

business performance basis, it is found that although ROA in second period falls but

ROE stands rising (1.4%), reflecting stable returns to the equity shareholders. A further

analysis exhibited that the bank’s total deposits and advances also increased (Table:

4.16). Further, when performance is measured subjectively, it is found HDFC Bank

also follows customer oriented philosophy by delivering exceptional service quality and

create satisfied customers. Customers of the bank are satisfied with the availability of

advanced services and have trust in conducting online transactions. The bank provides

all relevant information about products and services available online and ensures that

its login process is secure. HDFC Bank is a hub of modern facilities and provides

security and privacy to customer transactions by employing event detection technology

such as customer messaging for online transactions. Similarly, the bank also

implemented digital certificates based security engine for its corporate internet banking

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customers. The debit and credit card holders of HDFC bank are also secured by

powerful proactive risk manager technology solution, it provides SMS alerts and

prompt customer service call on detecting abnormal usage behaviour. All this prevents

frauds and minimises losses to customer, if the card is stolen. Moreover, bank has up to

date technology and equipment helps to improve its products, processes and services

and thus helps the administrators meet customer need by having 360 degree view of its

customers online. The bank also takes steps to improve the effectiveness of its redressal

mechanism across the delivery channel. Managers of bank observe quality of online

services (MS: 4.78) and level of trust (MS: 4.79) being highest among HDFC Bank

followed by level of customer satisfaction (MS: 4.68) and customer commitment (MS:

4.08). They are also satisfied with internet facilities in their operations, thus enabling

them to do their work efficiently and effectively. On the other hand, customers are

satisfied with quality of services (MS: 4.22) and security in dealing online enhances

trust (MS: 4.50), thus, leading to 32% increase in net profit in one year and 517%

increase in six years time period (2006-12). On the whole, the study reveals that bank

fulfils all the promises it makes to its customers, which ultimately gives a feeling of

trust. Customers have full confidence on bank’s reliability but are moderately satisfied

(MS: 3.60) and committed (MS: 2.96) to online services. This may be attributed to the

fact that the adoption of same online facilities provided by other public sector banks at

reasonable cost reduces the commitment level of its customers. Similarly delivery of

better online services and adoption of latest online security mechanisms are the leading

factors which increase the overall performance of the bank (517% average increase in

net profit), being the highest level of growth among all banks under study.

4.15.3 Business Performance of ICICI Bank

Industrial Credit Investment Corporation of India (ICICI) Bank, the second largest and

leading private sector bank, has a wide network of 2533 branches and 6800 ATMs in

India. It is the first bank which started its internet banking in India in year 1998 and at

present about 70% of its customers are conducting transactions online. ICICI bank, is a

type of private company engaged in providing a wide range of banking and financial

services including commercial banking and treasury operation. The bank starts its

online transfers as soon as in year 1998. Further, in year 1999, the bank used latest

technology for online networking of all its ATMs and provides debit and credit card

facility in the following year. Moreover, in the second period of advancement, ICICI

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Bank provides all online facilities including e-cheque for its internet banking users. The

objective performance of ICICI bank indicates that like other banks, its average net

profit increased from Rs 6628 lakhs to Rs 105357 lakhs registering growth rate of

1812% from one period to another. Thus adoption of new and innovative technology

like online banking is the most important factor for such a growth of a bank. The other

performance measures such as ROA also increased significantly from 0.82% in 2001 to

1.50% in 2012, whereas the ROE shows fluctuating trend. The average deposits and

advances also increased significantly with the adoption of latest technology. Similarly,

when performance is measured subjectively, it is found that both managers and

customers are satisfied with ICICI Bank for having up to date equipment and

technology. In addition to this, ICICI Bank focuses on delivering high tech quality

services (MS: 4.37) to customers for meeting their current requirements. The level of

trust and customer satisfaction is also high in ICICI Bank. Customers are also satisfied

for online payments such as transfer of funds and in paying certain utility bills. Besides,

ICICI Bank also provides privacy and security to customer transactions enabling them

to remain committed for dealing online. Managers of ICICI Bank also become skilful at

their respective banking job, enabling them to retrieve their client’s information quickly

and thus enhances their effectiveness in banking business. Also with the use of internet

facilities in their banking operations, the administrators are able to determine quickly

the profitability of various schemes as well as of various customers online. Likewise,

mangers of ICICI Bank also believe that they provide better quality online services

(MS: 4.75), generating higher level of customer satisfaction (MS: 4.56) and customer

commitment (MS: 4.35). Whereas customers find although the quality of online

services being highest and quickest among ICICI Bank (MS: 4.37), leading to their

satisfaction (MS: 4.11), but their promises to use these services in future is not certain.

Thus, on the whole, ICICI Bank’s business performance improves significantly from

one period to another and then shows steady growth. Hence, bank managers are

required to constantly review their banking operations and reduce service charges to

attract more customers to deal online. In addition to this, the bank must take steps

focussing more on its service quality and customer convenience to increase its overall

business.

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4.15.4 Business Performance of SBI

The initially known as imperial bank of India, the State Bank of India constituted on 1st

July 1955, is the country’s oldest and largest bank and a premier institution in terms of

balance sheet size, number of branches, market capitalisation and profits, which goes

on momentous phase of change and transformation. The bank is changing its outdated

front and back processes to modern customer friendly processes to improve the total

customer experience. To measure the impact of internet banking on SBI’s financial

position, the same parameters have been used by comparing its business performance

before and after the period of internet banking implementation The average net profit

for the period (1990-95), when bank operations were usually manual and employees

used only mainframe or mini computers for reconciliation and fund settlement process

came to be Rs.55836 lakhs. In the year 1997, SBI had tied up with VISA and Master

Card to provide debit card facilities to customers which increased the net profit by 37%

(Rs 134925 lakhs in 1996-97 to Rs 186120 lakhs in 1997-98). Further in year 1999,

SBI provided credit cards to its customers, enabling them to do shopping and withdraw

cash without having debit balances in their accounts. Thus, by comparing the average

net profit before and first stage of information technology development, it is found that

average net profit in year 1996-2000 came to be Rs 142428 lakhs, indicating 155%

increase in profit in five years by providing modern facilities like debit and credit card.

These facilities also attract more customers to avail banking services by depositing their

savings in SBI and getting interest on one hand and convenience of payment anytime

and anywhere at the other hand. In the second stage of development of information

technology viz. period from 2001-05, the average net profit came to be Rs. 302527

lakhs (112% increase during five years). In the year 2001-02, almost all branches of

SBI were computerized and worked on core banking solution. Further in year 2004-05

first mobile ATM was launched in remote areas and tourist locations to provide

convenience to customers at far off places. In the same year, RTGS and NEFT facility

were also provided to customers to transfer funds from one place to another. In the

advanced stage of information technology viz. period from 2006-12, the average profit

came to be Rs. 770511 lakhs i.e. 155% further increases over the previous stage. In the

year 2006-07, SBI provided the facility of payment of various bills while in year 2008-

09, internet banking facility was provided to corporate customers. All this is said to

have increased the net profit to 35% (Rs 672919 lakhs in 2007-08 to Rs. 912123 in

2008-09). Further in year 2011-12, SBI also started cash deposit ATM facility at some

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of the ATMs to deploy large number of cash deposit machines (Bunch Note Acceptors)

to provide customer convenience to deposit cash 24*7. The return on assets of SBI also

shows rising trend from 0.44% in 1990-91 to 0.89% in 2011-12. Similarly, the return

on equity also increased from 13.28% in 1990-91 to 15.72% in 2011-12 with certain

fluctuations. But when before and after information technology implementation period

compared, it found 70% increase in ROA and 36% increase in ROE in first stage and

12% and 5.21% increase in second stage and further 12% increase in ROA and fall of -

10% in ROE in advanced stage of information technology development (Table 4.18).

The other variables like total deposits and advances have also been analysed. The total

deposits of SBI increased from Rs 96395 crores in 1995-96 to Rs 1043647 crores in

2011-12. The total advances of SBI also increased from Rs 59825 crores in 1995-96 to

Rs. 867578 crores in 2011-12. The subjective performance of SBI reveals that like

JKB, PNB, SBI are also customer oriented bank. The level of customer satisfaction and

commitment is high as compared to other public sector banks operating in city.

Customers are satisfied with security and privacy of online transactions as well as with

online payment system that enables them to transfer funds and in paying bills of

different utilities. Managers of SBI find both deposits as well as profits increasing due

to provision of online banking services to its customers. For instance, the effectiveness

of managers also increases by using online systems and they feel very easy and

comfortable in doing their bank jobs. Further to evaluate performance in terms of

online effectiveness, a comparison has been made between subjective and objective

evaluation of business performance. Managers of bank observe that they provide

customer oriented services creating customer satisfaction (MS: 4.50) and customer

commitment (MS: 3.90). The quality of online services delivered is of moderate level

(MS: 3.75) but the level of trust created by bank in the mind of customers shows

highest mean scores (MS: 4.57), as compared to other public sector banks. This all

leads to 42% increase of net profit in one year (Rs 826401 lakhs in 2010-11 to Rs.

1170732 lakhs in 2011-12), highest among all other banks under study and on an

average 154% increase in six years time period (2006-12). But when these responses

are compared with customer responses, it is evident that customers are highly satisfied

(MS:4.28) and committed (MS:4.16) with online banking of SBI as compared to other

public sector banks and are averagely satisfied with quality of online services

(MS:3.64) and trust (MS:3.94). Hence, it is exhibited in Table No.4.22 that although

the current performance is better in relative terms, poor growth prospect adversely

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affects the value of firm, which means that the average proportion of percentage change

in profit due to online effectiveness (154% increase in advanced stage) is less as

compared to other public sector banks like PNB and UBI. Thus, managers are required

to give preference to customer interest and provides them with latest online services to

make them committed to deal online by rolling out its own network of automated teller

machines as well as developing anytime- anywhere banking services through internet

and other technologies. At last, customer focus and delivering of better service quality

and problem solving approach must be the driving forces behind SBI’s operations and

the bank must adapt itself to latest information technology to cater the diverse needs of

online customers.

4.15.5 Business Performance of PNB

Punjab National Bank, the second largest bank of India, also shows growth prospects

year after year and delivers value to its customers and shareholders. The average net

profit of PNB before implementation of internet banking services (1990-95) came to be

Rs. 17960 lakhs. In the year 1999-2000, PNB started providing debit and credit card

facilities to their customers and had tied up with Infosys for a centralised banking

solution. This in turn increased the average net profit by 55% in the first period and by

213% in the next period of development of advanced technology. In the same period,

the bank also widened its scope for providing RTGS, NEFT facilities to their customers

for transfer of funds. Furthermore, in year 2005-06, the bank had tied up with Indian

Airlines for online booking of Air tickets while in the preceding years, the bank had

tied up with various online merchants like BSNL, LIC etc to provide online payment of

premiums and bills to facilitate customer service which further increased the average

net profit to 278%. It is also exhibited in table that ROA has significantly gone up from

0.64% to 1.19% in year 1991 to 2012. The ROE also increased significantly from

12.87% to 19.80% in the same period. In this way, it seems that profitability of bank is

quite satisfactory and bank will continue its focus on sustaining high earning

performance and keeping strict control on costs and revenue maximisation by adopting

latest information technologies in delivering services to its customers and thus

increases returns to its shareholders. The subjective performance of PNB reflects that

the level of customer satisfaction is high because PNB offers complete e- bouquet of

internet banking services to around 11 lac corporate internet banking users. Also PNB’s

internet banking is witnessing a steady shift of customers for transfer of funds, inter-

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bank remittances and payment towards various services. For Punjab National Bank,

customer is the king and to satisfy him is the main motivating factor which induces

them to offer wide array of services through internet. The level of quality services

delivered online is also high in PNB as compared to other public sector banks. PNB

tries its best to provide error-free services in order to meet its objective of customer

satisfaction. It also adopts problem solving approach in delivering online services to

their customers and tries their best to give accurate representation to it. This shows that

PNB always has customer interest in mind and they always provide user friendly

service, competitive and seamlessly integrated across channels. In addition to this, the

manager’s performance measured in terms of perceived usefulness and perceived ease

of use is also high in PNB bank. Managers of PNB feel that with the implementation of

internet facilities in their banking operations, it becomes very easy for them to do their

job which helps to accomplish their tasks quickly and hence improves their efficiency

and effectiveness in banking career. Moreover, they also find interaction with web

pages clear and understandable and hence become skilful at navigating the web pages

of their bank’s site. Similarly, managers also revealed that they provide better quality

online services (MS: 4.50), creating customer satisfaction (MS: 4.36) and customer

commitment (MS: 3.77). Whereas, customers of PNB find level of trust (MS: 4.08) and

online service quality (MS: 3.93) as the influential factors motivating them to use

advanced services of bank. Moreover, the level of customer satisfaction (MS: 3.94) and

customer commitment (MS: 4.06) are highest from UBI and Canara Bank but lowest

from SBI. It is also consistent with the results measured objectively, reflecting

percentage of increase in one year time period is highest when compared with UBI and

CB and lower than SBI. But when it is compared on an average performance, it is

found that PNB leads in terms of percentage growth in profits from all other public

sector banks under study (Table: 4.22). On the whole, PNB’s customer oriented

philosophy indicates that the bank provides accurate and up to date information of

various transactions conducted online which helps them to make better financial

decisions regarding their banking transactions. The bank has taken adequate steps in

strengthening their anti- phising mechanism and monitoring process thereof to prevent

online frauds. PNB also implemented ‘site to user functionality of transaction

monitoring solution (IBS shield)’ for securing the interest of the internet banking

customers. Thus to conclude, Punjab National Bank, which figured as one of the top

five banks in India according to ‘The banker’ magazine, London will continue to make

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investments in technology, new products, risk management and towards expanding

franchise value. This investment will facilitate the bank to retain competitive

advantage. Further PNB has worked assiduously to build its front line position,

constantly reinvesting itself to keep pace with the changing banking landscape and

customer preferences. While successfully managing change, the bank has remained

deeply rooted in the principles of good banking. Resultantly, the fundamentals of the

bank have strengthened the bank to meet the challenges and touch new frontiers in

business growth and performance in future. Also the transactions conducted through

alternative delivery channels (ADC) such as ATM/Debit card/RTGS/NEFT etc

registered considerable growth as more than 28% of the transactions are conducted

through ADC mode. For maintaining customer satisfaction, PNB also provides

customer compensation policy to compensate customers for the losses suffered by them

due to deficiency in customer services. Thus, the efforts of the bank for providing best

value for money indicates that customers find worth dealing with this bank both

socially and financially.

4.15.6 Business Performance of Union Bank of India

Union Bank of India (UBI), the country’s fifth largest bank in terms of its size, also

shows momentous growth in terms of net profit, ROA and ROE. As similar to other

banks, the average net profit of Union Bank of India increased by 70.79%, from 9458

lakhs in 1990-95 to 16154 lakhs in 1996-2000. In the next period of advancement, the

bank had tied up with two IT companies to develop core banking solution and by the

end of year 2002, the bank launched core banking solution providing ‘anytime

anywhere banking’. In addition to this, the bank also launched Union bill pay, a

convenient utility bill payment service for the convenient of its customers. Further, in

year 2005, the bank started providing international debit and credit card in association

with VISA to its customers. Thus, provision of all these facilities further increased the

average net profit by 203% in the next subsequent period. Moreover, in advanced stage

of development, the bank used all alternate delivery channels such as ATMs, internet

banking, SMS banking etc as important tools to optimize customer satisfaction, leading

to further average 207% increase in profit from the previous period (Table:4.20). The

ROA and ROE also increased significantly except in year 2005-06 and 2011-12. Both

of the ratios fall because of sharp rise in assets for expansion in year 2005-06 and

further because of slackened business growth in 2011-12. The subjective performance

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of bank reveals that its managers find their bank having up to date equipment and

technology to offer online banking services to its customers. They are also satisfied

with security system of the bank for conducting online banking transactions such as

NEFT, RTGS etc. The bank managers also feel that with the implementation of online

facilities, they are able to accomplish their tasks quickly and find their banking job easy

and advantageous. On the other hand, customers are satisfied (MS: 3.92) and

committed (MS: 3.26) to online services, as the quality of delivered services (MS: 3.21)

is slow and not as competent as PNB, leading to average level of growth (207%) in

profits of bank. Thus, to conclude, its business performance is improving year after

year. For improving customer satisfaction and their commitment to these services, bank

must try to provide wide array of services delivered with relevant speed to meet the

requirements of various customers.

4.15.7 Business Performance of Canara Bank

Canara Bank, incorporated in 1906 and nationalised in 1969, also takes initiative to

remain customer focussed. Like other banks, Canara Bank also shows higher profits in

post e-banking period as compared to pre e-banking period, having positive impact on

technology (Uppal, 2011). In the second period of advancement (2001-05), Canara

Bank undertakes several technology initiative to fulfil advanced customer needs. It was

in the year 2003-04, that the bank had started its internet banking and further in year

2004-05, almost all the branches of bank were computerized and working on core

banking solution. In the next phase of e-banking period, the bank provides mobile

banking, online transfer, pass book printing self service and financial supply chain

management facility to its corporate customers. The rate of return on asset of Canara

bank also shows rising trend from 0.43% in 2000-01 to 1.42% in 2010-11 and then falls

to 0.95% in 2011-12. Similarly, the return on equity also shows the same result as it

increases from 10.54% in 2000-01 to 23.20% in 2010-11 and then declines to 18.35%

in 2011-12. This sharp decline in both the parameters is not due to growth in

information technology but due to slackened business growth and increase of stressed

assets at the industry level. Thus, in spite of all these stressed conditions, the bank

shows robust performance on the business front, coupled with unprecedented gains in

profits and profitability, continued buoyancy in core business operations and cost

containment, thus helped the bank to sustain and enhance top line earnings while

maintaining a stronger bottom line. The bank also shows growth in terms of its number

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of branches, ATMs and increased online customers. Its subjective performance reveals

that Canara bank is also customer oriented and generates customer satisfaction by

providing privacy and security to all banking transactions. The bank also provides its

customers all the relevant information about all products and services in their respective

websites. Similarly, when performance of managers of Canara bank is evaluated, it is

found that they find it very easy to do their job by implementing internet facilities in

their operations. Further, they also find interaction with web pages clear and

understandable and thus become skilful in navigating the web pages of their bank’s site,

thus enhancing their effectiveness in their respective jobs as well as in their banking

career. Similarly, like other banks, they also believe that both deposits and profits have

enhanced due to online banking facilities. In addition to this, when these responses are

compared with customer responses, it is found that customers are moderately satisfied

(MS: 3.65) and committed (MS: 3.54) with online operations of Canara bank.

Moreover, customers find although the charges levied by bank are less as compared to

private sector banks but the quality of online services is of average value (MS: 3.69),

thus reflecting, almost average business growth (165%) as compared to other banks

under study. On the whole, it is found that this bank shows almost average

improvement in terms of profitability and customer satisfaction.

4.15.8 Overall Business Performance of Indian Banks

The financial performance of various public sector banks reveals that State Bank of

India, which is the first largest bank of the country, leads all the banks in terms of

profitability followed by Punjab National Bank, Canara Bank and Union Bank of India.

In spite of higher profits, SBI does not provide greater returns on assets and equity. The

higher returns among public sector banks is provided by PNB followed by Canara Bank

and UBI. Similarly, when the financial performance of private sector banks is analysed,

it is found that ICICI Bank leads in terms of profitability followed by HDFC Bank and

Jammu and Kashmir Bank. The highest return on equity is provided by J&K Bank

followed by HDFC Bank and ICICI Bank whereas the highest return on assets is

provided by HDFC Bank followed by J&K Bank and ICICI Bank. But the deposits and

advances of all the banks under study increase with the development of advanced

technology.

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4.16 Conclusion

The main findings of the chapter reveal that majority of the responding banks find their

customers satisfied with internet banking services. They trust their banks for providing

all the relevant information about all products and services online. The banks have

adopted internet banking facilities a decade and few years back and ICICI Bank is the

first bank to adopt internet banking in its operations. But now a days, almost all the

banks have realised the need to maintain their customer’s data base and their resources

better in order to provide wide array of products and services to their customers. In

general, there is a positive attitude of almost all the bank managers. Moreover, the

overall mean values awarded by J&K Bank, SBI, PNB, ICICI Bank, HDFC Bank, UBI

and Canara Bank reveal that in the case of public sector banks, SBI leads in terms of

amount of profitability, customer satisfaction and commitment, as it is the largest and

oldest bank in the country. Whereas PNB leads in terms of online effectiveness and has

higher proportionate average increase in profits as compared to SBI. Similarly, in case

of private sector bank, HDFC Bank, followed by ICICI Bank, has a better impact on

customer satisfaction and business performance as reflected by more than above

average mean scores obtained by various dimensions viz. Perceived Usefulness, Trust,

Customer Satisfaction, Commitment, Service Quality and Perceived Ease of Use as

well as by percentage of growth in their profits. The above analysis also reveals that

PNB and HDFC Bank offer better customer oriented services to suit the needs of

various customers online. But the level of commitment is highest in JKB, as private

sector bank and in SBI, as public sector bank. Also the quality of online services

offered by ICICI Bank is much better than services offered by other banks and they

tried their best to make their customers committed to deal online.

130

Table 4.1: Demographic Profile of Bank Managers

Respondents Profile Number Percentage

Gender

Male 98 68%

Female 46 32%

Age

Above average 85 59%

Average 4 2.8%

Below Average 55 38.2%

Qualification

Graduate 62 43%

Post Graduate 42 30%

Professionals 40 27%

Length of service

0-5 years 22 15.27%

5-10 years 11 7.64%

10-15 years 14 9.73%

15 and above 97 67.36%

Table 4.2: Process of Data Reduction

Rounds Variance

Explained

Items

Emerged

No of

Factors

Extracted

Iterations No of

Items

Deleted

KMO Bartlett

1 77.692 100 23 75 36 0.776 12338.45

2 74.452 64 16 56 8 0.838 6466.14

3 75.461 56 15 19 6 0.8333 5562.88

4 76.538 50 14 38 2 0.837 4909.55

5 75.793 48 13 10 2 0.838 4698.92

6 74.934 46 12 13 1 0.838 4518.71

7 75.194 45 12 10 1 0.838 4381.14

8 75.486 44 12 8 1 0.836 4225.67

9 74.475 43 11 8 1 0.840 4185.40

10 74.879 42 11 8 1 0.836 4054.86

11 75.255 41 11 8 1 0.837 3904.23

12 74.277 40 10 8 10 0.842 3871.95

13 76.202 30 8 8 - 0.846 2922.38

131

Table 4.3: Factorial Profile of Data from Bank Managers

Variables Mean Standard

deviation

Factor

Loadings

Eigen

Values

% of

Variance

Explained

Factor 1 Perceived Usefulness 10.207 16.381

Helps to accomplish tasks quickly 4.40 .83 .797

Improves job performance 4.44 .87 .762

Enhances effectiveness of job 4.50 .70 .771

Easier to do job 4.53 .70 .773

WWW useful 4.39 .85 .712

Transaction is advantageous 4.36 .86 .667

Various information are easily

available

4.34 .80 .600

Enhance effectiveness in banking

career

4.45 .80 .657

Factor 2 Trust 3.609 12.565

Bank has strongly commitment to

security measures

4.56 .59 .801

Bank ensures that transaction

information is protected during a

connection

4.51 .61 .801

Banks web page offers all the

relevant information about all

products & services.

4.44 .70 .769

Bank does not allow any third

person to access customers

personal information

4.54 .74 .828

Bank’s login process is secure 4.48 .83 .658

Factor 3 Customer Satisfaction 2.048 11.373

Website provides clear transaction

and price information

4.31 .86 .772

Website provides accurate and

upto date information to its

customers

4.40 .78 .697

Website provides privacy and

security to customer transaction

4.48 .70 .723

Website deals with customer order

fast enough

4.32 .76 .655

Customers are satisfied with

online payment system

4.33 .83 .734

Factor 4 Commitment 1.754 10.333

It pays of economically to be a

customer of your bank

4.09 1.08 .758

132

Customers are committed to buy

from your bank

3.97 1.20 .898

Commitment is due to reasonable

price of bank

4.05 1.04 .759

Customers are committed because

of banks performance

4.12 .97 .799

Factor 5 Better Facilities 1.507 6.983

Bank’s deposits have been

increased by using online system

4.02 1.08 .862

Banks profits have been increased

by providing facilities to

customers

4.01 1.09 .846

Factor 6 Service Quality 1.400 6.294

Bank has upto date equipment and

technology

4.40 .71 .886

Bank provides online services to

its customers.

4.53 .61 .864

Factor 7 Perceived Ease of Use 1.268 6.166

Find interaction with web pages

clear & understandable

4.31 .70 .866

Find easy to become skilful at

navigating the web pages

4.34 .70 .852

Factor 8 Profitability 1.067 6.106

Administrators can quickly

determine the profitability of

major customers

4.31 .76 .792

Administrators can quickly

determine the profitability of

various schemes

4.33 .78 .717

133

Table 4.4: Demographic Profile-wise ANOVA results

Factors

Age wise Qualification wise Length of Service

wise

F Sig. F Sig. F Sig.

Perceived Usefulness .001 .980 .079 .924 1.125 .341

Trust .408 .524 3.445 .035 .541 .655

Customer Satisfaction 1.232 .269 .112 .894 .354 .786

Commitment .232 .631 .362 .697 .504 .680

Better Facilities .758 .386 1.482 .231 2.594 .055

Service Quality .203 .653 .802 .450 .125 .945

Perceived Ease of Use .340 .561 .605 .547 .845 .471

Profitability 4.548 .035 1.115 .331 .732 .534

Table 4.5: Demographic Group Wise Mean Values

FACTOR AGE QUALIFICATION LENGTH OF SERVICE

Below

Average

Average Above

Average

G PG PF 0-5

years

5-10

years

10-15

years

15

years

and

above

Perceived

Usefulness

4.43 4.58 4.43 4.43 4.45 4.39 4.27 4.51 4.65 4.42

Trust 4.55 4.40

4.48 4.37 4.57 4.66 4.62 4.54 4.38 4.50

Customer

Satisfaction

4.29 4.33 4.42 4.39 4.34 4.34 4.27 4.25 4.44 4.38

Commitment 4.09 3.83 4.01 3.99 4.01 4.15 3.94 4.34 3.91 4.05

Better

Facilities

3.93 4.50 4.08 4.15 4.03 3.80 3.79 3.36 4.32 4.10

Service

Quality

4.44 4.00 4.49 4.40 4.47 4.56 4.52 4.45 4.39 4.46

Perceived

Ease of Use

4.37 4.66 4.30 4.32 4.26 4.42 4.22 4.22 4.57 4.33

Profitability 4.48 4.66 4.22 4.28 4.26 4.47 4.45 4.50 4.42 4.26

134

Table 4.6: Bank wise ANOVA Results

Factors Bank Wise

F Sig

Perceived Usefulness .652 .688

Trust .589 .739

Customer satisfaction 2.124 .054

Commitment 2.604 .020

Better facilities 3.825 .001

Service quality 3.630 .002

Perceived ease of use 1.278 .271

Profitability 1.042 .401

Table 4.7: Bank wise cum Factor wise Mean

Factors J&K SBI PNB ICICI HDFC UBI Canara

Perceived

Usefulness

4.41 4.51 4.50 4.19 4.55 4.12 4.53

Trust 4.46 4.57 4.44 4.65 4.80 4.51 4.35

Customer

Satisfaction

4.29 4.64 4.33 4.40 4.68 3.85 4.10

Commitment 4.19 4.02 3.76 4.38 4.10 2.86 4.12

Better

Facilities

4.10 4.51 3.70 4.05 3.14 3.07 3.87

Service

Quality

4.36 4.71 4.50 4.83 4.78 4.07 3.75

Perceived

Ease of Use

4.24 4.46 4.42 4.44 4.71 3.92 4.25

Profitability 4.29 4.50 4.27 4.27 4.71 3.92 4.12

135

Table 4.8: Summary of regression analysis showing impact of different dimensions

and factors on Customer Satisfaction , Customer Commitment and Business

Performance

Dependent Independent R R2 Adj.

R2

B T F Sig. S.E.

Customer

Commitment

HO1:

Customer

Satisfaction

.414 .171 .165 .414 5.415 29.324 .000 .112

Profitability H02:

Service

Quality

.283 .080 .073 .283 3.510 12.319 .001 .094

Customer

Satisfaction

HO3: Trust .434 .188 .182 .434 5.736 32.902 .000 .086.

Customer

Satisfaction

HO4:

Service

Quality

.348 .121 .115 .348 4.423 19.559 .000 .084

Profitability HO5:

Perceived

Ease of Use

.340 .116 .109 .340 4.307 18.550 .000 .085

Profitability HO6:

Perceived

Usefulness

.470 .221 .215 .470 6.342 40.224 .000 .085

Table 4.9: Results of Various CFA Fit Indices

Constructs CMIN/DF GFI AGFI RMR RMSEA CFI TLI

PU 1.581 .962 .909 .019 .064 .988 .977

Trust 0.472 .996 .981 .006 .012 1.000 1.013

CS 1.329 .989 .947 .010 .048 .997 .991

Commitment 1.057 .993 .964 .017 .020 1.000 .999

Profitability 1.021 .997 .985 .016 .023 1.000 1.000

136

Table 4.10: Reliability and Validity of Latent Constructs

Constructs Convergent Validity/AVE Construct reliability

PU .510 .937

Trust .610 .938

CS .600 .900

Commitment .653 .818

Profitability .464 .839

SQ .536 .823

PEOU .895 .854

Table 4.11: Split Half Reliability

Before Factor Analysis After Factor Analysis

Group 1 4.34 4.35

Group 11 4.31 4.33

Cronbach’s Alpha 0.965 0.919

Diagonal axis show average variance extracted. Values within parenthesis are

squared correlation between the dimensions and values without parenthesis are

actual correlation values, **sig. at 0.01 level, * sig. at 0.05 level

Table 4.12: Discriminant Validity of Latent constructs

PU Trust CS CMT BF SQ PEOU

PU 0.51

Trust .252**

(0.063)

.61

CS .552**

(0.304)

.434**

(0.188)

.60

CMT .341**

(0.116)

.454**

(0.206)

.414**

(0.171)

.653

BF .370**

(0.136)

.199*

(.039)

.389**

(.151)

.185*

(.034)

.464

SQ .250**

(0.062)

.383**

(.146)

.348**

(.121)

.256**

(.065)

.234**

(.054)

.536

PEOU .534**

(0.285)

.212*

(.045)

.450**

(.202)

.260*

.0.06

.218*

(.047)

.137*

(.018)

.895

137

Table 4.14: Results Of Hypothesis Testing Through SEM

Variables P.value SRW Results

Commit<-CS .000 .404 Accepted

CS<-Trust .000 .363 Accepted

CS<-SQ .004 .219 Accepted

PEOU<-EP .000 .546 Accepted

PU<-EP .000 .978 Accepted

BP<- CS .000 .440 Accepted

Table 4.13: Various Stages of Structural Modelling

Stages CMIN/DF GFI AGFI RMR RMSEA CFI TLI DEL Addition

1 6.97 .886 .710 .085 .204 .776 .572 -

2 5.14 .915 .761 .061 .170 .859 .703 - PEU-CS

3 3.48 .942 .821 .050 .132 .924 .822 - PU-CS

4 1.80 .973 .905 .037 .084 .943 .978 - T-CMT

5 1.83 .976 .903 .036 .076 .980 .940 - SQ-BF

Table 4.15: Profitability Measures of Jammu and Kashmir Bank

Parameters 1990-95 1996-2000 2001-05 2006-12

Net Profit (In Lakh)

(Mean Values)

% Increase

Rs.1695

Rs.5987

253%

Rs. 25730

329%

Rs.45050

75%

ROA

(Mean Values)

% Increase

1.004%

1.15%

14.54%

1.498%

30.26%

1.145%

-23%

ROE

(Mean Values)

% Increase

13.78%

20.14%

46%

25.15%

24.8%

16.69%

-33.6%

Advance (In Crore)

(ean Values)

% Increase

Rs. 107786

Rs.233708

116%

Rs.799996

242%

Rs. 2195776

174%

Deposits(In Crore)

(Mean Values)

% Increase

Rs.221564

Rs.526038

137%

Rs.1581209

200%

Rs.3507661

122%

138

Table 4.16: Profitability Measures of HDFC Bank

Parameters 1996-2000 2001-05 2006-12


(Mean Values)

% Increase

Rs.6628

Rs. 41396

524%

Rs.255565

517%

ROA

(Mean Values)

% Increase

1.69%

1.508

-10%

1.455%

-3%

ROE

(Mean Values)

% Increase

19.98%

20.26%

1.40%

17.69%

-12%

Advance (In Crore)

(Mean Values)

% Increase

Rs.130973

Rs.870127

564%

Rs. 2307852

165%

Deposits(In Crore)

(Mean Values)

% Increase

Rs.309986

Rs.2501283

706%

Rs.6171952

146%

Table 4.17: Profitability Measures of ICICI Bank

Parameters 1996-2000 2001-05 2006-12


(Mean Values)

% Increase

Rs.5510

Rs. 105357

1812%

Rs.417254

296%

ROA

(Mean Values)

% Increase

0.84%

1.104

31.42%

1.21%

9.60%

ROE

(Mean Values)

% Increase

16.95%

17.35%

2.35%

10.82%

-37%

Advance (In Crore)

(Mean Values)

% Increase

Rs.16687

Rs.521692

3026%

Rs. 2053221

293%

Deposits(In Crore)

(Mean Values)

% Increase

Rs.41286

Rs.529119

1181%

Rs.2202129

316%

139

Table 4.18: Profitability Measures of State Bank of India

Parameters 1990-95 1996-2000 2001-05 2006-12


(Mean Values)

% Increase

Rs.55836

Rs.142428

155%

Rs. 302527

112%

Rs.770511

154%

ROA

(Mean Values)

% Increase

0.418%

0.712%

70%

0.798%

12%

0.892%

12%

ROE

(Mean Values)

% Increase

12.24%

16.67%

36%

17.54%

5.21%

15.62%

-10%

Advance (In Crore)

(Mean Values)

% Increase

Rs. 40820

Rs. 75351

84%

Rs. 146492

74%

Rs. 544922

271%

Deposits(In Crore)

(Mean Values)

% Increase

Rs. 71298

Rs.140809

97%

Rs. 299035

112%

Rs.562534

88%

Table 4.19: Profitability Measures of Punjab National Bank

Parameters 1990-95 1996-2000 2001-05 2006-12


(Mean Values)

% Increase

Rs.17960

Rs.27988

56%

Rs. 87740

213%

Rs.304880

247%

ROA

(Mean Values)

% Increase

0.646%

0.74%

15%

0.946%

28%

1.23%

30%

ROE

(Mean Values)

% Increase

14.14%

19.50%

38%

21.28%

9%

19.91%

-6%

Advance (In Crore)

(Mean Values)

% Increase

Rs. 10867

Rs.16881

55%

Rs.42052

149%

Rs. 166844

296%

Deposits(In Crore)

(Mean Values)

% Increase

Rs.21412

Rs.36272

69%

Rs.77430

113%

Rs.225368

191%

140

Table 4.20: Profitability Measures of Union Bank of India

Parameters 1990-95 1996-2000 2001-05 2006-12


(Mean Values)

% Increase

Rs.9458

Rs.16154

70.79%

Rs. 49068

203%

Rs.151115

207%

ROA

(Mean Values)

% Increase

0.524%

0.45%

-14%

0.918%

104%

1.05%

14%

ROE

(Mean Values)

% Increase

13.57%

12.07%

-11%

18.96%

57%

18.58%

-2%

Advance (In Crore)

(Mean Values)

% Increase

Rs. 62891

Rs.108094

71%

Rs.267868

147%

Rs. 1049644

291%

Deposits(In Crore)

(Mean Values)

% Increase

Rs.134032

Rs.240386

79%

Rs.463639

92%

Rs.1424579

207%

Table 4.21: Profitability Measures of Canara Bank

Parameters 1990-95 1996-2000 2001-05 2006-12


(Mean Values)

% Increase

Rs.15460

Rs.21281

37%

Rs. 89858

322%

Rs.239021

165%

ROA

(Mean Values)

% Increase

0.61%

0.546%

-11%

1.01%

84%

1.09%

8%

ROE

(Mean Values)

% Increase

8.58%

8.77%

2%

21.77%

148%

18.69%

-14%

Advance (In Crore)

(Mean Values)

% Increase

Rs. 94894

Rs.174820

84%

Rs.418980

139%

Rs. 1480687

253%

Deposits(In Crore)

(Mean Values)

% Increase

Rs.207216

Rs.371386

79%

Rs.758094

104%

Rs.2078987

174%

141

Table 4.22: Bank wise objectively and subjectively comparison of performance

Dimensions

/ banks

JKB HDFC ICICI SBI PNB UBI CB

SQ BM 4.35 4.78 4.75 3.75 4.50 4.07 3.70

CR 3.69 4.22 4.37 3.69 3.93 3.21 3.67

Trust BM 4.42 4.79 4.60 4.57 4.44 4.50 4.35

CR 3.89 4.57 4.50 3.94 4.08 3.92 3.98

CS BM 4.26 4.68 4.56 4.50 4.36 3.83 4.10

CR 4.04 3.66 4.11 4.28 3.94 3.92 3.65

CC BM 4.18 4.08 4.35 3.90 3.77 2.99 4.12

CR 3.91 2.96 3.51 4.16 4.06 3.26 3.54

PEOU BM 4.24 4.71 4.44 4.46 4.42 3.92 4.25

CR 4.23 3.87 4.12 4.14 4.13 4.40 4.25

PU BM 4.41 4.55 4.19 4.51 4.45 4.12 4.53

CR 4.21 4.19 4.33 4.36 4.49 4.40 4.56

Average Net Profit of three development stages (In Lakhs)

1996-2000 Rs.5987 Rs.6628 Rs.5510 Rs.142428 Rs.27988 Rs.16154 Rs.21281

2001-2005

Rs.25730

330%

Rs.41396

524%

Rs.105357

1812%

Rs.302527

112%

Rs.87740

213%

Rs.49068

203%

Rs.89858

322%

2006-2012 Rs.45050

75%

Rs.255565

517%

Rs.417254

296%

Rs.770511

154%

Rs.304880

247%

Rs.151115

207%

Rs.239021

165%

142

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Chapter 5



Chapter 5

Impact of Internet Banking on Customer Satisfaction

Contents Page No

5.1 Introduction 146

5.2 Data Collection 146

5.3 Scale Generation 146

5.4 Profile of Respondents 147

5.5 General Information 147

5.6 Data Purification 147

5.7 Factor Wise Analysis 148

5.8 Demographic Profile Wise Analysis 152

5.8.1 Age Wise Analysis 152

5.8.2 Qualification Wise Analysis 154

5.8.3 Occupation Wise Analysis 155

5.8.4 Income Wise Analysis 155

5.8.5 Length of Association Wise Analysis 157

5.9 Bank Wise Analysis 158

5.10 Confirmatory Factor Analysis 161

5.11 Validity and Reliability 165

5.12 Structural Equation Model 167

5.13 Testing of Hypothesis 169

5.14 Conclusion 170

References 181

146

CHAPTER-5

IMPACT OF INTERNET BANKING ON CUSTOMER

SATISFACTION

5.1 Introduction

The fast changing dynamics of global market place, duly further strengthened by

increasingly intense competition, forces the bank to shift from traditional banking to

online banking services (Cheung and Lee, 2005), resulting into emergence of customer

satisfaction as the key to long term success of any banking business. Therefore, specific

understanding on customers perceived requirements and meeting their demands and

expectations is becoming an intricate challenge for banks to provide customer oriented

services. In this context, the present chapter studies the impact of internet banking

facilities on customer satisfaction in both public and private sector banks operating in

Jammu city and also presents a bank wise comparative status of the same.

5.2 Data Collection

The data for the present study have been obtained from secondary and primary sources.

The secondary data were obtained from various available journals such as International

Journal of Bank Marketing, Journal of Internet Research, Journal of Services

Marketing, International Journal of Electronic Commerce, Journal of Internet Banking

and Commerce etc. The primary data were collected from 410 internet banking users

residing in Channi Himmat Colony of Jammu through systematic sampling.

5.3 Scale Generation

The primary data were collected through specifically developed schedule (Annexure -2)

on the basis of the available literature (Wakefield et al., 2004; Cry et al., 2005; Pavlou,

2003; Khan and Mahapatra, 2009; Zeng et al., 2009 etc) and discussion with experts in

the related fields of the study. It comprised of 10 items of general information, 13 items

of peripheral services that banks provide to them and 99 items based on 5 point Likert

scale (5 ---1) ranging from strongly agree (5) to strongly disagree (1) (Malhotra,

2007, p.274) covering the entire domain of the study.

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5.4 Profile of Respondents

Brief profile of a sample of online bank customers in Jammu city summarised in table

5.1 reveals that out of 410 customers personally contacted in Channi Himmat Colony of

Jammu, 77.5% were male, 36% belonged to the age group of 20-30 years, followed by

26% of respondents between the age group of 30-40 years, 20% between 40-50 years

and 18% belonging to above 50 years of age. About 45% were graduate, 58.5% belong

to service sector, 54% were married and 63% of customers had annual income above

than Rs. 2,00,000.

5.5 General Information

The study finds majority of the respondents having JKB (Jammu and Kashmir Bank) as

their prime bank followed by SBI (24%), PNB (20%), ICICI Bank (8%), HDFC Bank

(7%), UBI (8%), Canara Bank (7%). The study reveals JKB as the most preferred bank

among private sector banks and SBI (24%) as the most preferred one among public

sector banks in Jammu. About 39% of sampled respondents were found to be dealing

online with their prime banks for the last 5 years, 32.6% dealing for last 5-10 years,

21.4% for 10-15 years and 7% for the last more than 15 years. In fact, majority of

respondents start dealing online with their banks in the beginning itself because of

awareness about latest techniques in doing banking transactions at their work place.

However, the most important reason for dealing online is time and cost saving,

followed by 24 hour facility, easy transfer of money within and outside the country.

Approximately, 60% of respondents have Saving Bank Account followed by Current

Account (37%), Recurring Account (1.8%) and FDs (1.2%). Thus, it is evident that

saving bank account is the most common account held by the salaried class with their

prime bank. Almost all the respondents of various banks are availing ATM facilities,

credit cards (60%) and debit card. Also 67.5% of respondents preferred online banking

for electronic transfer of payments.

5.6 Data Purification

Principal Component Analysis (PCA) was run in order to condense the information

from the original large number of variables into a smaller and meaningful set of

variables (Factors), incurring a minimal loss of information. EFA has been used to

analyse the interrelationships among larger number of variables and to explain them in

terms of their common underlying dimensions. It was run overall on a schedule

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consisting of 99 items. During the process, factor loadings and communalities greater

than 0.5 were considered good and factors with eigen values equal to or greater than

one were retained. The indicators related to internet banking are trust, commitment,

service quality, perceived ease of use, perceived usefulness, behavioural intentions and

customer satisfaction. The twenty items to measure trust in internet banking were factor

analysed, resulting into only seven items converged into two factors viz. ‘trust’ and

‘security’. The four items of commitment were eliminated for further analysis as these

items had very low loadings. The service quality consists of 25 items and after running

EFA only 12 items got grouped into four factors namely ‘website quality’,

‘responsiveness’, ‘better services’ and ‘courtesy’. Six items of both perceived ease of

use and perceived usefulness have been eliminated and remaining items were grouped

into three factors viz. ‘perceived ease of use’, ‘perceived usefulness’ and ‘interactivity’.

The four items of behavioural intention have also been eliminated and remaining items

resulted into one factor as behavioural intention. Lastly, twenty items of customer

satisfaction, when factor analysed, resulted in the elimination of 14 items and

remaining got converged in two factors viz. ‘customer oriented services’ and ‘after

sales services’.

5.7 Factor Wise Analysis

Following factors have emerged after factor analysis when all the statements were put

together:-

Factor 1: Website Quality

This factor consists of four items viz. ‘website appealing’, ‘valuable information’, ‘easy

to use and navigate’, ‘information about new deposit schemes’. About 79% of

respondents found their bank’s website very easy to use and navigate (MS: 4.01),

enabling them to access valuable information about the banking transaction online.

About 70% of respondents find information about new deposit schemes etc easily

available in their bank’s website which helps them in channelising their money in

various sources. Thus, website easiness to use and navigate is the most influential

factor that induce customers to use internet banking facilities and remain active in using

new technology (Ganguli and Roy, 2010; Khurana, 2009). The present findings appear

to be in line with Jayawardhena and Foley (2000) who also found website features as

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speed, website content and design, navigation, interactivity and security as the factors

influencing user satisfaction in internet banking.

Factor 2: Customer Oriented Services

This factor consists of four variables viz. ‘pleased with bank for providing online

services’, ‘website provides innovative deposit schemes’, ‘website allows easy transfer

of money’, and ‘website provides customer oriented services’. Of these variables,

‘website allows easy transfer of money’ is found to be significant contributor towards

customer oriented services (Gbadeyan and Gbonda, 2011 and Tulani et al., 2009)

followed by innovative deposit schemes (MS: 4.05). This implies that respondents are

happy to use online banking because of various facilities such as remittance of funds

from one account to another immediately with very less cost and time which is in line

with Auta (2007) who found customers satisfied with e-banking systems due to flexible

advantages such as easy transfers, speedy transactions and cost and time saving

benefits.

Factor 3: Trust

Trust comprises of four variables viz., ‘trust for not using personal information

inappropriately’, ‘doesn’t allow any person to access anyone’s personal information’,

‘relevant information about all schemes’, ‘website keeps its commitments’. About 83%

of respondents trust their prime banks for not using personal information

inappropriately and for not allowing any third person to access their personal

information (MS: 4.16). Singal and Padhmanabhan (2008), Qureshi et al., (2008) and

Manzano et al., (2008) also find customers shifting from traditional banking to online

banking because of security and privacy provided by their respective banks. Thus,

website security and privacy, usability and reputation of the banks create customer

satisfaction and make them committed to use online banking channel (Casolo et al.,

2007; Bander and Charles, 2006).

Factor 4: Commitment

Commitment comprises of three variables viz. ‘visit website if when you need banking

service’, ‘links are problem free, accurate and easy page download ’, ‘banks take care

of problems properly’. Out of these three variables, majority of the respondents (89%)

visit their bank’s website as it is available in the understandable language. Shifting

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from traditional banking to online banking saves time and cost and facilitates

transactions by sitting anywhere at home or office. Further, respondents are committed

to their banks for online services because the links are problem free and the pages of

the website are downloaded easily. These findings also commensurate with the findings

of Siu and Mou (2005) in which they found credibility, security, and problem handling

attitude of the bankers making the customers satisfied and committed to use internet

banking services.

Factor 5: Courtesy

Factor five consists of two variables viz., ‘administrators are willing to help’ and

‘administrators show confidence in customers’. About 80% of respondents found their

administrators always helpful in conducting banking transactions online and informing

customers immediately about the status of their respective accounts. This implies

responsiveness of bankers towards their customer as the most important factor in

generating customer satisfaction (Singh and Kour, 2011; Kumbhar, 2011 and

Mohammad and Alhamadani, 2011).

Factor 6: After Sales Service

Factor six comprises of two variables viz. ‘experience with online banking is good’,

‘satisfied with after sales services’. About 82% of respondents found their experience

with online banking very good, thus enabling them to do banking conveniently at any

place.

Factor 7: Responsiveness

Responsiveness consists of four variables viz. ‘administrators are never busy to respond

enquiries’, ‘administrators are courteous’, ‘administrators have all knowledge’,

‘problem solving approach in delivering services’. About 75% of respondents found

their bank staff and administrators having all knowledge regarding various services

provided by the bank which assist them in doing transactions online (MS: 3.86). Thus,

the findings are very much in line with many other studies conducted by Ravichandran

et al., (2010); Nupur (2010); Sohail and Shaikh (2007) in which they also found

responsiveness of the bankers in customer problems, assisting customers in doing

transactions online and creating customer satisfaction. Singh and Kour (2011) found

employee responsiveness as the significant factor for generating customer satisfaction.

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Factor 8: Security

Security comprises of three variables viz. ‘feel confident using online banking

services’, ‘bank is capable and proficient’, ‘login process is secure’. About 83% of

respondents were satisfied with their bank’s login process and they feel confident and

secured while having transactions online with their banks. These findings are consistent

with the studies of Abdullah et al., (2011); Yousafzai et al.,(2005); Casolo et al.,(2007)

in which they found trust in online banking being created by website security and

safety to customer’s transactions, reducing security risks and thus improving customer

trust. Further, the banks should also tighten security of online banking and reduce the

associated risk by employing various technologies such as firewalls, authentication,

intrusion detection etc (Zakaria, 2011).

Factor 9: Perceived Usefulness

Factor nine comprises of three variables viz. ‘effectiveness in banking transaction’,

‘doing online banking useful’, ‘useful for utilisation of banking services’. About 98%

of respondents found online banking very useful for utilising various banking services

(MS: 4.43) (Suki and Suki, 2011; Muhammad et al., 2011; Jalal et al., 2011).

Factor 10: Interactivity

Interactivity consists of two variables viz. ‘enhances effectiveness in information

seeking’, ‘site does not make lose time interactivity’. About 95% of respondents find

online banking enhancing their effectiveness in information seeking. Yang et al., (2004)

also find information systems enabling the customers to function independently and to

conduct numerous transactions on their own on the bank’s website.

Factor 11: Perceived Ease of Use

It consists of four variables viz. ‘simple to do banking’, ‘website looks professionally

designed’, ‘user menus are clearly categorised and laid out in the screen’,

‘demonstrations or guidelines help in doing banking’. Out of these four variables,

respondents find online banking easy to use because the user menus are clearly

categorised and laid out in the screen (MS: 4.32). Hanzaee and Sadeghi (2010) also

found convenience, website design, accuracy and accessibility as the factors that

influence internet banking adoption.

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Factor 12: Behavioural Intentions

It consists of two variables viz. ‘use online banking for banking needs’, ‘strongly

recommend other’. About 90% of respondents find online banking useful as it is

convenient and saves cost of both customers and banks.

Factor 13: Better Services

Better services consist of two variables viz. ‘call centres have operating hours

convenient to customers’ and ‘call centres give personalised attention to customers’.

About 75% of respondents feel satisfied with the personalised attention of the call

centres in any problem while conducting transaction online. Hawari et al., (2005) also

concludes that call centres of banks provide accurate information about the product and

services and give personalised attention to the customers for conducting online

transactions. Ombati (2010) established direct relationship between technology and

service quality and found customers as quite satisfied with online banking services

because of user friendliness, ease of use and 24 hours operation.

5.8 Demographic Profile Based Analysis

In order to measure the impact of different demographic background of customers on

their satisfaction, respondents were segregated into five groups on the basis of age,

qualification, occupation, income and length of association with banks. (Table: 5.4).

The analysis done through ANOVA is as under:-

5.8.1 Age- wise analysis

The respondents have been classified into four groups on the basis of age viz. 20-30,

30-40, 40-50 and 50 years and above. Each group has significant number of

respondents, thus findings were drawn for each of them. The first group comprised of

highest number of respondents i.e 36% followed by second group (26%), third group

(20%) and the last group consists of 18% of sampled respondents. The results of

ANOVA (Table: 5.5) indicates significant difference existing in the mean satisfaction

of respondents belonging to these four groups (F=11.414, sig<.05). It is discussed as

under:-

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20-30 years

This group accorded above average mean scores to six factors viz. after sales services

(4.05), security (4.00), perceived usefulness (4.38), interactivity (4.25), perceived ease

of use (4.12) and behavioural intentions (4.02). However, the factors such as courtesy

(3.68) and responsiveness (3.76) have just obtained slightly above average mean scores.

The respondents of this group are more satisfied with perceived usefulness of the

system, perceived ease of use and interactivity and are moderately satisfied with the

attitude of bank administrators in conducting banking transactions online.

30-40 years

This group accorded above average mean scores towards eight factors viz, customer

oriented services (4.32), trust (4.24), after sales services (4.25), security (4.12),

perceived usefulness (4.37), interactivity (4.30), perceived ease of use (4.25) and better

services (4.10). Thus, respondents of this group are more satisfied with perceived

usefulness, customer oriented services, interactivity and perceived ease of use and are

moderately satisfied with commitment (3.96), responsiveness (3.95) and behavioural

intentions (3.72).

40-50 years

This group accorded above average mean scores to seven factors viz. website quality

(4.06), customer oriented services (4.01), trust (4.03), security (4.17), perceived

usefulness (4.36), interactivity (4.25) and perceived ease of use (4.31). Thus, it can be

apprehended that respondents of this group are more satisfied with perceived usefulness

and perceived ease of use and are moderately satisfied with better services (3.51) and

commitment (3.73).

Above 50 years

The respondents of this group accorded above average mean scores towards two factors

only viz. perceived usefulness (4.35) and interactivity (4.16). However, almost average

scores were accorded to the remaining factors viz. website quality (3.50), customer

oriented services (3.93), trust (3.82), commitment (3.95), courtesy (3.27), after sales

services (3.71), responsiveness (3.23), security (3.97), perceived ease of use (3.93),

behavioural intentions (3.39) and better services (3.60). Thus to conclude, persons

senior in age feel comfortable in doing banking online (Odumeru, 2012).

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5.8.2 Qualification Wise Analysis

The impact of qualification of respondents has been studied under four groups viz. 12th

standard, graduate, post graduate and professional. Majority of the respondents are

graduate followed by post graduate and holding professional qualification. Due to

negligible number of sampled customers (32) in the first group, it was dropped from

further analysis. The results of ANOVA indicates significant mean difference in the

perceptions of respondents belonging to these four groups (F =4.462, sig<.05). On

further analysis, by applying post- hoc test, there exists maximum mean difference

between graduate and post graduate respondents, which is consistent with the studies of

Karjaluoto et al., (2002); Mattila et al., (2003); Stavins (2001) and Sathye (1999) in

which they found that higher educational respondents adopt internet banking because

they have a higher knowledge of new information technology and skills as compared to

respondents of low education.

Graduate Respondents

This group accorded above average mean scores to seven factors viz. customer oriented

services (4.01), commitment (4.05), after sales services (4.02), security (4.00),

perceived usefulness (4.37), interactivity (4.23) and perceived ease of use (4.07) and

are moderately satisfied with website quality (3.76), trust (3.97), courtesy (3.68),

responsiveness (3.58), behavioural intentions and better services (3.63).

Post Graduate Respondents

This group of respondents accorded above average mean scores towards ten factors viz.

website quality (4.10), customer oriented services (4.25), trust (4.17), commitment

(4.03), after sales services (4.01), security (4.04), perceived usefulness (4.47),

interactivity (4.43), perceived ease of use (4.33) and better services (4.04). Higher

qualified respondents are more satisfied with online banking services due to their

knowledge and experience with the new innovative technologies which save their time

and costs. Wong et al., (2009) also found post graduate respondents having higher

willingness to use e-banking as compared to trade qualified or secondary degree

holders.

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Professionals

This group accorded above average mean scores to only five factors viz. after sales

services (4.01), security (4.10), perceived usefulness (4.30), interactivity (4.10) and

perceived ease of use (4.16). Thus, it is apprehended that people having professional

qualification find it useful to do banking online.

5.8.3 Occupation -wise Analysis

The impact of occupation of respondents has been examined under two groups viz

service and business. Majority of respondents are from service class. The ANOVA

results indicate significant mean difference existing among the respondents belonging

to these two groups (F=5.40, sig < .05). Further, significant mean difference exists

between nine factors viz. website quality (F=7.320, sig< .05), customer oriented

services (F=4.164, sig < .05), trust (F=5.8, sig < .05), after sales services (F=3.941, sig

< .05), responsiveness (F=7.255, sig < .05), security (F=17.303, sig < .05), perceived

usefulness (F=14.626, sig < .05), interactivity (F=6.899, sig < .05) and perceived ease

of use (F=5.295, sig < .05). On the whole, business class people found internet banking

more useable as compared to service class people (Table 5.6).

5.8.4 Income wise Analysis

Income has been classified into four groups viz. below Rs 50000, 50000-100000,

100000-200000 and above Rs 200000 per annum. The first group contains 9.7% of the

sampled customers. The second group consists of 12.7% and the third group contains

14.6% of the sampled respondents and the fourth group consists of majority of sampled

respondents i.e (63%). ANOVA gives significant difference in the mean satisfaction of

respondents belonging to these four groups (F=17.564, sig < .000). Moreover,

significant difference exists between respondents with regard to twelve factors viz.

website quality (sig .000), customer oriented services (.030), trust (.000), commitment

(.000), courtesy (.001), after sales services (.000), responsiveness (.000), security

(.001), interactivity (.037), perceived ease of use (.000), behavioural intentions (.001)

and better services (.000). Only one factor i.e perceived usefulness is insignificant

between various groups (Table: 5.6). Thus, each of four groups of respondents has been

analysed separately.

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Income below Rs 50,000

This group accorded above average mean scores to two factors viz. perceived

usefulness (4.23) and interactivity (4.08). However, other factors obtained just average

level of mean scores viz. website quality (3.73), customer oriented services (3.83), trust

(3.85), commitment (3.05), courtesy (3.65), after sales services (3.19), security (3.79),

perceived ease of use (3.91), behavioural intention (3.60) and better services (3.84).

The factor responsiveness (2.97) obtained below average mean scores. Thus,

respondents of this category are satisfied with perceived usefulness and interactivity

and is least satisfied with responsiveness of bank administrators.

Income between Rs 50,000-Rs 1,00,000

This group awarded high mean scores towards twelve factors viz. website quality

(4.40), customer oriented services (4.15), trust (4.29), courtesy (4.20), after sales

services (4.33), responsiveness (4.37), security (4.47), perceived usefulness (4.42),

interactivity (4.12), perceived ease of use (4.51), behavioural intentions (4.11) and

better services (4.31). The factor commitment has obtained just average score (3.64).

Thus, respondents of this group are highly satisfied with security, website quality,

perceived ease of use and perceived usefulness of internet banking system but are

averagely committed to deal online.

Income between Rs 1,00,000-Rs 2,00,000

This group attributed above average mean scores to seven factors viz. commitment

(4.40), after sales services (4.13), perceived usefulness (4.48), interactivity (4.14),

perceived ease of use (4.19) and behavioural intentions (4.04). They accorded average

mean scores to website quality (3.69), customer oriented services (3.94), trust (3.82),

courtesy (3.65), responsiveness (3.88) and better services (3.27). Thus, it becomes

evident that this group is satisfied with its prime banks for providing internet banking

services but expects more innovative services to be provided online.

Income above Rs 2,00,000

This group attains above average mean scores to seven factors viz. customer oriented

services (4.08), trust (4.00), after sales services (4.06), security (4) perceived usefulness

(4.35), interactivity (4.32) and perceived ease of use (4.11). However, they accorded

average mean scores to remaining factors viz. website quality (3.87), commitment

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(3.83), courtesy (3.65), responsiveness (3.68), behavioural intentions (3.67) and better

services (3.86). Thus to conclude, respondents are quite satisfied with perceived

usefulness, interactivity and perceived ease of use of the system to deal online with

their prime banks and are moderately satisfied with the attitude of bank administrators.

5.8.5 Length of Association- wise Analysis

The length of association of customers with their prime bank has been divided into four

groups viz. upto 5 years, 5-10 years, 10-15 and 15 years and above. Majority of the

respondents are from first group (39%), followed by second (32.6%) and third group

(21.4%). The fourth group has very few respondents (7%), not sufficient for further

analysis. ANOVA results indicate significant mean difference existing between

respondents belonging to these three groups (F= 4.848, sig < .003). Thus, each of three

groups of respondents has been analysed separately:-

Less than 5 years of Association

This group of respondents accorded above average mean scores to four factors viz.

security (4.06), perceived usefulness (4.38), interactivity (4.12) and perceived ease of

use (4.04). The remaining factors have just obtained slightly above average mean

scores viz. website quality (3.81), customer oriented services (3.87), trust (3.82),

commitment (3.92), courtesy (3.61), after sales services (3.90), responsiveness (3.78),

behavioural intentions (3.87) and better services (3.78). Thus, respondents of this

category found very easy and useful to do banking online, as it saves their time, cost

and efforts.

5-10 years of Association

This group of respondents obtained above average mean scores towards six factors viz.

customer oriented services (4.17), trust (4.05), after sales services (4.06), perceived

usefulness (4.42), interactivity (4.43) and perceived ease of use (4.21). Thus to

conclude, respondents of this group are highly satisfied with perceived usefulness,

perceived ease of use and interactivity of internet banking system.

10-15 years of Association

This group of respondents awarded above average mean scores to eleven factors viz.

website quality (4.21), customer oriented services (4.18), trust (4.17), commitment

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(4.12), after sales services (4.13), security (4.25), perceived usefulness (4.28),

interactivity (4.20), perceived ease of use (4.34), behavioural intention (4.06) and better

services (4.05). The factors courtesy (3.87) and responsiveness (3.76) have obtained

just average mean scores. On the whole respondents of this category are quite satisfied

with internet banking system because of their maximum experience of using the latest

technology. Gbadeyan and Gbonda (2011) also found respondents with long term

relationships satisfied with their banks because of prompt and effective delivery of

services, good customer relationship, conducive environment, good public image and

financial capability of the bank.

5.9 Bank Wise Analysis

The Jammu and Kashmir Bank (JKB) figured as most popular bank in terms of number

of respondents followed by SBI, PNB, ICICI Bank, HDFC Bank, UBI, and Canara

Bank in the area of study. ANOVA was used to know significant difference existing in

the mean satisfaction of respondents of different banks and it was found to be

significant (F=14.144, sig <.05). Moreover, significant difference also exists with

regard to all the thirteen factors extracted in the study. Thus, the data gathered from

each group of respondents belonging to different banks have been analysed separately

to understand separate features figuring in the study.

JKB

The JKB obtains above average mean scores in four factors viz. security (MS: 4.22),

perceived usefulness (MS: 4.45), interactivity (MS: 4.38) and behavioural intentions

(MS: 4.15). However, the remaining factors have obtained just average mean scores.

Thus, it can be apprehended that respondents of this bank using internet banking

facilities are highly satisfied with their bank for innovative services, being secured and

useful in their banking transactions. Ganguli and Roy (2010) found customer service,

technology security and information quality, technology convenience and technology

usage easiness and reliability affecting customer satisfaction. The respondents of JKB

have also positive attitude towards these services in future due to ‘time-cost-effort’

effectiveness.

159

SBI

SBI also attains above average mean scores towards five factors viz. customer oriented

services (MS: 4.23), trust (MS: 4.01), perceived usefulness (MS: 4.09), interactivity

(MS: 4.14) and perceived ease of use (MS: 4.25). The other factors have obtained just

average mean scores. The respondents of SBI are highly satisfied with their bank for

providing customer oriented services such as internet banking being easy to use and

effective in online transactions. Also, they find bank website interactivity very easy and

useful for online banking services. Moreover, respondents are moderately satisfied with

responsiveness and courtesy of bank administrators, in contrast to the findings of Singh

and Arora (2011), in which they found customers of nationalised banks not satisfied

with employee behaviour.

PNB

The respondents of PNB give above average mean scores on seven factors viz.

customer oriented services (MS: 4.24), trust (MS: 4.17), after sales services (MS: 4.07),

perceived usefulness (MS: 4.47), interactivity (MS: 4.28), perceived ease of use (MS:

4.24) and better services (MS: 4.14). The remaining factors have obtained slightly

above average mean scores viz website quality (MS: 3.99), commitment (MS: 3.82),

courtesy (MS: 3.93), responsiveness (MS: 3.76), security (MS: 3.93) and behavioural

intentions (MS: 3.66). Thus, the respondents are highly satisfied with perceived

usefulness, interactivity and perceived ease of use, being consistent with the findings of

Wu et al., (2012) in which they found that perceived usefulness, perceived ease of use

and relative advantage are the factors having significant effect on customer’s

behavioural intentions to adopt internet banking facilities. Moreover, respondents are

also satisfied with after sales services, inducing them to remain committed to use such

interactive online banking services. Yang and Peterson (2004) also found customer

commitment and loyalty generated through improving customer satisfaction and

offering high product/service value to customers.

Canara Bank

This bank receives above average mean scores in six factors viz. customer oriented

services (MS: 4.15), commitment (MS: 4.08), security (MS: 4.04), perceived usefulness

(MS: 4.54), interactivity (MS: 4.00), behavioural intention (MS: 4.06) and better

services (MS: 4.25), indicating thereby the respondents being highly satisfied with

160

perceived usefulness and feel effectiveness in doing transactions online. Chang and

Hamid (2010) also found perceived usefulness and perceived ease of use influencing

customer behaviour in favour of internet banking services. However, respondents are

not much satisfied with the responsiveness of bank administrators towards their

expectations in online transactions being consistent with the findings of Loonam and

Loughlin (2008), wherein it is depicted that customers expect high e-service

responsiveness in contrast to traditional banking responsiveness and found e-service

responsiveness being increased with e-service experience.

HDFC Bank

This bank got above average mean scores in twelve factors viz. website quality (MS:

4.00), customer oriented services (MS: 4.16), trust (MS: 4.02), commitment (MS:

4.10), courtesy (MS: 4.16), after sales services (MS: 4.50), responsiveness (MS: 4.33),

security (MS: 4.50), perceived usefulness (MS: 4.60), interactivity (MS: 4.41),

perceived ease of use (MS: 4.52) and better services (MS: 4.51). Only one factor viz.

behavioural intention (MS: 3.25) has obtained just average mean score. Thus, on the

whole respondents are highly satisfied with internet banking services of HDFC Bank.

ICICI Bank

This bank also obtains above average mean scores towards twelve factors viz. website

quality (MS: 4.42), customer oriented services (MS: 4.25), trust (MS: 4.44),

commitment (MS: 4.22), courtesy (MS: 4.35), after sales services (MS: 4.37),

responsiveness (MS: 4.38), security (MS: 4.61), perceived usefulness (MS: 4.67)

interactivity (MS: 4.48), perceived ease of use (MS: 4.48) and better services (MS:

4.32), indicating thereby the respondents being highly satisfied with perceived

usefulness and security in online transactions. All this enhances customer trust and

makes them committed to deal online.

UBI

This group of respondents receives above average mean scores in five factors viz. after

sales services (MS: 4.09), responsiveness (MS: 4.13), security (MS: 4.28), perceived

usefulness (MS: 4.22) and perceived ease of use (MS: 4.02). The factors such as

website quality (MS: 2.92) and courtesy (MS: 2.76) have obtained below average mean

scores. Thus, on the whole respondents of this bank are highly satisfied with security of

161

their business but are least satisfied with the attitude of their bank administrators

towards online transactions.

5.10 Confirmatory Factor Analysis (CFA)

CFA has been used to provide a confirmatory test to the measurement theory as a

method of testing how well measured variables represent a smaller number of

constructs. In the present study, CFA was performed to assesss fitness, reliability and

validity of measurement models for different constructs of online banking. In CFA, no

distinction is made between exogeneous and endogeneous constructs, hence it is an

interdependence technique like exploratory factor analysis (EFA). CFA distinguishes

from EFA, as in EFA all measured variables are related to every factor by a factor

loading estimates, whereas in CFA researcher has to assign variables to each factor on

the basis of preconceived theory. Thus, the various resulting measurement models are

as follows:

Service Quality

EFA resulted into four factors viz. website quality, responsiveness, courtesy and better

services. These four factors resulted into twelve measured indicators. One statement of

factor responsiveness and two statements of factor website quality got deleted due to

low regression weights. The measurement model analysis was carried on remaining set

of observed indicators. The model has been found to be appropriate as the values are fit

under the threshold criteria (Chi-square/df=3.804, RMR= 0.05, GFI= 0.955, AGFI=

0.908, TLI= 0.906, CFI= 0.943 and RMSEA= 0.084). The model has been proved to be

valid as indicated through Average Variance Extracted (AVE), which came to be 0.53,

higher values of standardised regression weights and higher construct reliability (0.845)

was assessed from the construct loadings and error variances (Hair et al., 2009)

162

Fig 5.1: Measurement Model of Service Quality

Trust

This construct consisted of two factors viz. trust and security comprising of four and

three items respectively. Application of CFA resulted in deletion of two items of factor

trust and one item of security because of low regression weights (<.05). The model was

found to be as fit under the threshold criteria (Chi-square/df=3.220, RMR= 0.039, GFI=

0.992, AGFI= 0.960, TLI= 0.961, CFI= 0.987 and RMSEA= 0.075). The model was

also proved to be valid as AVE came to be 0.606 and construct reliability came to be

0.836.

.19

wq

.35

sq14 e1 .59

.86

sq16 e2 .93

.70

ct

.26

sq2 e5 .51

.16

sq8 e6 .41

.69

res

.97

sq1 e7 .98

.63

sq3 e8 .79

.27

sq7 e9 .52

.11

bs

.33

sq9 e11 .57

.96

sq10 e12 .98

sq

e13

e14

e15

e16

.44

.84

.83

.33

.18

.18

.26

.16

163

Fig 5.2: Measurement Model of Trust

Commitment

CFA is also run on the construct commitment and all the indicators are confirmed due

to higher regression weights (>.05) but model fitness is not assessed due to lesser

number of items under this construct. This construct was also found to be valid as

assessed by AVE (.534) and construct reliability (.727).


This construct consisted of two factors viz. perceived usefulness and interactivity

consisting of three and two items respectively. The model showed strong fit as all the

.36

tr

.94

t5 e1 .97

.26

t10 e3

.51

.36

se

.60

t3 e5 .77

.63

t15 e7

.79

e8

e9

trst

.60

.60

164

fitness measures were found to be acceptable with chi-square/df=3.194, GFI= 0.990,

AGFI= 0.952, CFI= 0.988, TLI= 0.959, RMR= 0.011 and RMSEA= 0.074. Further, the

model has been found to be valid as revealed through AVE (0.538) and construct

reliability (0.925).

Fig 5.3: Measurement Model of Perceived Usefulness


This construct consisted of four items which were reduced to two due to low regression

weights (<.05). The model fitness is not assessed due to less number of items retained

after CFA, but the validity could be assessed through AVE (.614) and construct

reliability (.867).


This construct originally consisted of twenty items, which were reduced to six items

after EFA under two factors with four for customer oriented services and two for after

sales services. Two of the items of customer oriented services have got deleted due to

.84

pu

.70

pu1 e1 .84 .25

pu3 e2 .50

.14

pu11 e3

.38

.46

int

.95

pu2 e4 .97

.36

pu6 e5 .60

peuse

.91

.67

e6

e7

.27

.36

165

low regression weights (<.05), finally resulted in four statements two for each factor for

final analysis. The model has been found to have a good fit (Chi-square/df=2.766,

RMR= 0.020, GFI= 0.993, AGFI= 0.966, TLI= 0.955, CFI= 0.985 and RMSEA=

0.067). Further the model has been proved to be valid as indicated through AVE which

came to be 0.50, higher values of standardised regression weights of each indicators,

higher construct reliability (0.79), which was assessed from the construct loadings and

error variance.

Fig 5.4: Measurement model of Customer Satisfaction

5.11 CFA and Construct Validity

CFA was performed to assess the construct validity of each latent construct. Construct

validity directly affects the substantive models being tested (Bagozzi and Edwards

1998). Thus, one of the major benefits of using SEM technique is that it allows for

concurrent assessment of both reliability and validity (Landis, Beal, and Tesluk 2000).

Construct reliability is the extent to which a set of measured items actually reflect the

theoretical latent construct that is designed to measure. Thus, it deals with the accuracy

of measurement. Basically, it is made up of three important components:-

5.11.1 Convergent validity

The items that are the indicators of a specific construct should converge or share a high

proportion of variance in common, which is known as convergent validity. The various

.63

cos

.39 cs17 e2 .62

.54 cs19 e4

.73

.17

ass

.83

cs3 e5 .91 .31

cs6 e6 .56

cs

.80

.42

e7

e8

166

ways to estimate the relative amount of convergent validity among item measures are

as under;

5.11.1(a) Factor Loadings: High factor loading, i.e., above 0.50 or ideally 0.7 or

higher indicates higher level of convergence. Convergent validity gets established in

the present study as majority of standard loadings came out to be above 0.50.

5.11.1(b) Variance Extracted: In CFA, the average percentage of variance extracted

(VE) among a set of construct items is a summary indicator of convergence. VE is

computed as the total of all squared standardised factor loading divided by number of

items. VE should be 0.50 or greater to suggest adequate convergent validity and in our

case VE for all the constructs came to be above .70 (Table 5.8).

5.11.2 Reliability

Reliability is also an indicator of convergent validity. The rule of thumb for reliability

estimate is 0.70 or higher and reliability in the present case is established as it is above

0.70 in all the cases (Table 5.8). High construct reliability indicates that internal

consistency exists, meaning thereby that all measures consistently represent the same

latent construct.

CR= (Sum of standardised loadings) 2/ (Sum of standardised loadings)

2 + Sum of error

variance terms

5.11.3 Dicriminant Validity: Dicriminant validity is the extent to which a construct is

truly distinct from other constructs. High discriminant validity provides evidence that a

construct is unique and captures some phenomena, which other measures do not (Ahire

et al., 1996). It has been proved by two ways. First, the diagonal elements of the

correlation matrix (Table: 5.9) show the average variance extracted. Each diagonal

element of the matrix should be greater than all other elements in the corresponding

row and column of which the diagonal element is a part if discriminant validity is

sufficient. The results meet this requirement. Second, for good discriminant validity, no

item should load more highly on other constructs than on the construct to which it is

supposed to belong (Fey et al., 2009). Since, the data fulfil both of these requirements,

it is proved that the disciminant validity of the construct used is more than adequate.

167

5.12 Structural Equation Model

A structural theory is a conceptual representation of the relationship between latent

constructs. It can be expressed in terms of a structural model that represents the theory

with a set of structural equations and is usually depicted through a visual diagram. A

good measurement theory is a necessary condition to obtain useful results from SEM.

Once theory is expressed in terms of relationships among measured variables and latent

constructs, SEM will assesss how well the theory fits reality as represented by data.

Initially a model was proposed with seven constructs viz. Service quality, trust,

behavioural intentions, perceived ease of use, perceived usefulness, customer

satisfaction and customer commitment. It was proposed that service quality and trust

affects customer satisfaction and commitment. Further, perceived ease of use and

perceived usefulness affects behavioural intentions of customers to use internet banking

and hence customer satisfaction. Thus on the whole, customer satisfaction is not only

predicted through service quality and trust but also through perceived ease of use and

perceived usefulness. However, this model was not found to have good fit as chi-square

statistic came to be 32.00, RMR= 0.077, GFI= 0.768, AGFI= 0.593, TLI= 0.247, CFI=

0.050 and RMSEA= 0.279, hence revealing a poor fit.

Certain paths were added as suggested by modification index. But these additions in the

model have not been done on the basis of modification index but also on the basis of a

strong theoretical support (Hair et al., 2009) for each path. In the first phase of

modification indices, relationship between perceived ease of use and customer

satisfaction were established which reduces the CMIN/df= 20.166, RMR= 0.067, GFI=

0.848, AGFI= 0.716, TLI= 0.229, CFI= 0.450 and RMSEA= 0.219. Jalal et al.,(2011)

proved that perceived ease of use is the source of satisfaction in context of e-banking.

Chang and Hamid (2010), Tandrayen et al.,(2010), Alam and Soni (2012) also support

the relationship between perceived ease of use and behavioural intention and also

between perceived ease of use and customer satisfaction.

In the second phase, relationship between service quality and trust is established which

further reduced the chi-square statistic to 9.718. This relationship of service quality

with trust is added after revisiting the literature such as Yap et al., (2009) found that

service quality and website feature gives customers confidence and hence builds trust in

e-banking. Lee and Lin (2005); Hassan (2012) also state that website design, reliability,

responsiveness and trust affect overall service quality and hence customer satisfaction.

Further Casalo et al., (2007) found website security and privacy, usability and

168

reputation have a direct and significant effect on customer trust in a financial services

website, thus giving a theoretical support for service quality and trust relationship.

In the third phase, relationship between perceived ease of use and perceived usefulness

were established which further reduced the chi-square statistic to 7.806. (Muhammad

and Rana, 2012; Suki and Suki, 2011; Chang and Hamid, 2010). Further relationship

between behavioural intention and commitment is established which reduced the

CMIN/df= 6.396. Ayo et al., (2010) found that perceived ease of use and perceived

usefulness are not only antecedents to e-banking acceptance, they also influence

customer’s behavioural intention and hence are the factors to retain the customers.

In the next phase, relationship between service quality and perceived ease of use was

established, which further reduced the chi-square statistic to 4.793 (Cao, Zhang and

Seydel, 2005). Lastly relationship between perceived usefulness with customer

satisfaction and commitment was established, thus, giving a proper model fit as

CMIN/df= 3.834, RMR= 0.023, GFI= 0.979, AGFI= 0.926, TLI= 0.886, CFI= 0.957,

NFI= 0.944 and RMSEA= 0.084.

169

Fig 5.5: Structural Equation Model of Customer Satisfaction in Online Banking

5.13 Testing of Hypotheses

HO1: Customer satisfaction influences commitment in online banking.

It becomes evident from SEM results that customer satisfaction positively affects

customer commitment (0.27), thus, accepting first hypothesis.

HO2: Trust in online banking positively affects customer satisfaction.

The direct effect of trust on customer satisfaction is significant (.08) and is positive,

thus, accepting of the hypothesis.

HO3: Service quality of online banking affects customer satisfaction.

This hypothesis also stands accepted as indicated by SEM results (.09).

HO4: Perceived ease of use will have a positive effect on behavioural intention to use

online banking.

This hypothesis also stands accepted as the effect of perceived ease of use on

behavioural intention is .11 and on customer satisfaction, it is very high (.65).

servqual

trust

perease

peruse

cussat

.09

.08

e1 1

e4 1

e5 1

e6 1

e7 1

behaint

commit

.11

.06

.27

e8 1

e9 1

.65

.60

.27

.22

.18

-.29

.31

.10

170

HO5: Perceived usefulness will have a positive effect on behavioural intention to use

online banking.

This hypothesis also stands accepted as effect of perceived usefulness on behavioural

intention is .06, 0.12 on customer satisfaction and 0.31 on customer commitment.

5.14 Conclusion

Customer satisfaction has long been found as playing an essential role for success and

survival in today’s competitive environment. Overall, results show that highly educated

persons who are employees, businessmen and belong to higher income groups and

younger are major users of internet banking. The findings of the study reveal that

customers are satisfied with their respective bank for internet banking facilities which

save their time and cost and enable them to know their account balances and remit

funds from one place to another anywhere and any time. Respondents of private sector

banks viz. ICICI Bank and HDFC Bank are more satisfied with all aspects of internet

banking under study as compared to respondents of other banks, thus indicating the

need for improvement in their infrastructure and facilities to compete with private

banks. The results of SEM show that customer satisfaction is not only influenced by

better service quality and trust but also through other factors such as perceived ease of

use and perceived usefulness, which are not only antecedents of behavioural intention

but also the source of generating customer satisfaction and commitment. Further, trust

which is generated through security and privacy of customer’s personal information is

the least important dimension for predicting customer satisfaction, thus suggesting the

managers of online banking services to ensure their respective customers that their site

is free from a torrent of spam and that customers personal information (especially credit

and debit card details) is not exposed to any fraudulent use. Keeping in view limited

impact of online service quality on customer satisfaction, bank managers must adopt

strategies with regard to optimising perceived service quality. Moreover, it is also

found that customers attach more importance to employee behaviour, their friendliness

attitude, politeness, cooperation, promptness in answering enquires online. Hence

banks must train their employees to effectively handle customer problems, so that they

develop trust in the minds of customers about bank personnel and service package

available online. Thus, offering of internet banking service is essential for bank’s

survival and thus mandatory to compete effectively.

171

Table 5.1: Demographic Profile of Bank Customers

Respondents

Profile

Number Percentage Respondents

Profile

Number Percentage

Gender Marital Status

Male 318 77.5% Single 190 46%

Female 92 22.5% Married 220 54%

Age Income

20-30 148 36% Below 50,000 40 9.7%

30-40 106 26% 50,000-

1,00,000

52 12.7%

40-50 82 20% 1,00,000-

2,00,000

60 14.6%

50 &Above 74 18% Above

2,00,000

258 63%

Qualification Length of

Association

12th

32 7.8% Up to 5 years 160 39%

Graduates 184 45% 5-10 years 134 32.6%

Post

Graduates

98 24% 10-15 years 88 21.4%

Professionals 96 23.2% Above 15 years 28 7%

Occupation

Service 240 58.5%

Business 170 41.5%

Table 5.2: Process of Data Reduction

Rounds Variance

Explained

Items

Emerged

Number

Of

Factors

Extracted

Iterations No.of

Items

Deleted

KMO Bartlett

1 84.866 99 28 40 34 .693 3263.828

2 81.015 65 21 22 7 .603 3864.922

3 80.503 58 19 16 3 .667 2976.262

4 80.123 55 18 26 2 .633 2117.139

5 79.089 53 17 14 2 .625 2112.236

6 77.323 51 15 17 1 .740 1242.685

7 76.146 49 14 14 4 .842 6452.14

8 75.238 45 13 15 3 .837 3604.23

9 73.717 42 13 22 3 .856 4054.86

172

Table 5.3: Factorial Profile of Data from Bank Customers

Variables Mean Standard

Deviation

Factor

Loadings

Communalities % of

Variance

Explained

Eigen

Values

Cronbach

Alpha

Factor 1Website

Quality

7.291 19.413 .369

Website

Appealing

3.92 .913 .731 .771

Website Provides

Valuable

Information

3.96 .953 .730 .753

Website is easy to

use and Navigate

4.01 .991 .810 .827

Information about

new deposit

schemes

3.69 1.31 .625 .780

Factor 2

Customer

Oriented

Services

7.197 7.819 .487

Pleased with

bank for

providing online

services

3.92 .838 .746 .784

Website provides

innovative

deposit schemes

4.05 1.00 .676 .710

Website allows

easy transfer of

money

4.22 .982 .785 .724

Website provides

customer oriented

services

4.00 1.16 .762 .721

Factor 3 Trust 6.420 6.586 .478

Trust for not

using personal

information

inappropriately

4.07 .899 .766 .718

Does not allow

any one to access

personal

information

4.16 .983 .713 .805

173

Website offers

relevant

information about

all schemes

3.91 1.02 .741 .738

Website keep its

commitments

3.84 1.15 .776 .805

Factor 4

Commitment

6.329 6.024 .746

Visit website if

need banking

services

4.20 1.02 .870 .837

Committed

because links are

problem free,

accurate and

pages download

easily

4.02 .902 .720 .743

Committed

because banks

takes care of

problems

properly and

compensate for

the problems they

create

3.35 1.33 .627 .725

Factor 5

Courtesy

5.952 5.815 .280

Administrators

are willing to

help

3.92 .798 .681 .711

Administrators

show confidence

in customers

3.52 1.52 .643 .837

Factor 6 After

Sales Services

5.844 4.906 .674

Experience with

online banking is

good

4.07 .772 .643 .785

Satisfied with

after sales

services

3.97 .825 .655 .750

Factor 7

Responsiveness

5.499 4.418 .769

174

Administrators

are never busy to

respond enquires

3.82 1.28 .759 .853

Administrators

are courteous

3.64 1.28 .802 .776

Administrators

have all

knowledge

3.86 1.15 .716 .736

Problem solving

approach in

delivering

services

3.60 1.19 .722 .849

Factor 8

Security

5.455 4.214 .666

Feel confident

using online

banking services

4.24 1.13 .814 .829

Bank is capable

and proficient

3.90 1.13 .703 .793

Login process is

secure

4.04 1.13 .637 .673

Factor 9

Perceived

Usefulness

4.993 3.709 .695

Online banking

effectiveness in

banking

transactions

4.31 .653 .556 .761

Find doing online

banking useful

4.37 .681 .688 .693

Useful for

utilisation of

banking services

4.43 .549 .705 .676

Factor 10

Interactivity

4.844 3.057 .740

Enhances

effectiveness in

information

seeking

4.28 .778 .779 .819

Site does not

make lose time

interactivity

4.21 .762 .754 .707

175

Factor 11

Perceived Ease

of Use

4.762 2.862 .334

Simple to do

banking

4.09 .984 .729 .853

Website looks

professionally

designed

4.17 1.05 .712 .678

User menus are

clearly

categorised and

laid out in the

screen

4.32 .627 .757 .775

Demonstrations

or guidelines

helps in doing

banking

4.06 .949 .729 .716

Factor 12

Behavioural

Intentions

3.99 2.761 .383

Use online

banking for

banking needs

4.36 .763 .728 .718

Strongly

recommend

others

3.20 1.49 .600 .714

Factor 13 Better

Services

3.881 2.327 .720

Call centres have

operating hours

convenient to

customers

3.79 1.13 .837 .811

Call centres gives

personalised

attention in doing

banking

3.87 1.10 .739 .687

176

Table 5.4: Demographic Profile–wise ANOVA Results

Age wise Qualification

wise

Occupation

wise

Income wise Length of

Association

wise

F Sig. F Sig. F Sig. F Sig. F Sig.

Website

Quality

14.059 .000 6.784 .000 7.320 .001 16.805 .000 15.051 .000

Customer

Oriented

Services

9.212 .000 4.766 .003 4.164 .016 3.008 .030 7.437 .000

Trust 8.677 .000 9.232 .000 5.876 .003 6.094 .000 7.956 .000

Commitment 1.405 .241 14.12 .000 1.643 .195 20.948 .000 6.405 .000

Courtesy 10.490 .000 1.008 .389 1.617 .200 5.576 .001 3.985 .008

After sales

services

9.357 .000 .130 .942 3.941 .020 27.431 .000 2.945 .033

Responsiveness 9.827 .000 3.233 .022 7.255 .001 19.288 .000 2.914 .034

Security .979 .403 1.247 .292 17.303 .000 5.719 .001 3.411 .018

Perceived

Usefulness

.081 .970 2.234 .084 14.626 .000 2.159 .092 1.655 .176

Interactivity .655 .580 3.647 .013 6.899 .001 2.860 .037 5.195 .002

Perceived ease

of use

8.757 .000 5.243 .001 5.295 .005 12.425 .000 7.929 .000

Behavioural

intentions

8.146 .000 3.734 .011 2.044 .131 5.449 .001 8.393 .000

Better services 7.376 .000 6.148 .000 .490 .613 11.788 .000 6.206 .000

177

Table 5.5: Age and Qualification Wise Analysis of Internet Banking Customers

20-30

yrs

N=148

30-40

yrs

N=106

40-50

yrs

N=82

Above

50 yrs

N=74

Under

Graduate

N=32

Graduate

N=184

Post

Graduate

N=98

Professional

N=96

M M M M M M M M

Website

Quality

3.94 3.99 4.06 3.50 3.88 3.76 4.11 3.94

Customer

oriented

services

3.93 4.32 4.01 3.93 4.00 4.01 4.25 3.93

Trust 3.89 4.24 4.03 3.82 4.29 3.97 4.17 3.77

Commitment 3.81 3.96 3.73 3.95 3.60 4.05 4.03 3.40

Courtesy 3.68 3.99 3.87 3.27 3.81 3.68 3.84 3.63

After sales

services

4.05 4.25 3.95 3.71 4.09 4.02 4.01 4.01

Responsiveness 3.76 3.95 3.85 3.23 3.91 3.58 3.75 3.93

Security 4.00 4.12 4.17 3.97 4.32 4.00 4.04 4.10

Perceived

Usefulness

4.38 4.37 4.36 4.35 4.27 4.37 4.47 4.30

Interactivity 4.25 4.30 4.25 4.16 4.23 4.23 4.43 4.10

Perceived ease

of use

4.12 4.25 4.31 3.93 4.14 4.07 4.33 4.16

Behavioural

intention

4.02 3.72 3.77 3.39 3.87 3.61 3.87 3.97

Better services 3.93 4.10 3.51 3.60 3.96 3.61 4.09 3.95

178

Table 5.6: Occupation, Income and Length of Association wise Analysis of Internet Banking

Customers

Service

N=240

Business

N=170

Below

Rs

50000

N=40

Rs

50000-

100000

N=52

Rs

100000-

200000

N=60

Rs Above

200000

N=258

Upto 5

yrs

N=160

5-10

yrs

N=134

10-15

yrs

N=88

M M M M M M M M M

Website Quality 3.81 4.01 3.73 4.40 3.69 3.87 3.81 3.88 4.21

Customer

oriented

services

4.06 4.03 3.83 4.15 3.94 4.08 3.87 4.17 4.18

Trust 4.07 3.89 3.85 4.29 3.82 4.00 3.82 4.05 4.17

Commitment 3.83 3.89 3.05 3.64 4.40 3.83 3.92 3.60 4.12

Courtesy 3.66 3.80 3.65 4.20 3.65 3.65 3.61 3.83 3.87

After sales

services

4.02 4.02 3.19 4.33 4.13 4.06 3.90 4.06 4.13

Responsiveness 3.64 3.86 2.97 4.37 3.88 3.68 3.78 3.57 3.76

Security 3.92 4.25 3.79 4.47 4.13 4.00 4.06 3.89 4.25

Perceived

usefulness

4.26 4.52 4.23 4.42 4.48 4.35 4.38 4.42 4.28

Interactivity 4.32 4.15 4.08 4.12 4.14 4.32 4.12 4.43 4.20

Perceived ease

of use

4.15 4.17 3.91 4.51 4.19 4.11 4.04 4.21 4.34

Behavioural

intention

3.85 3.67 3.60 4.11 4.04 3.67 3.87 3.57 4.06

Better services 3.87 3.77 3.84 4.31 3.27 3.86 3.78 3.62 4.05

179

Table 5.7: Results of various CFA Fit Indices

Constructs CMIN/DF GFI AGFI RMR RMSEA CFI TLI

Service Quality 3.804 0.955 0.908 0.050 0.084 0.943 0.906

Trust 3.220 0.992 0.960 0.039 0.075 0.987 0.961

Perceived

Usefulness

3.194 0.990 0.952 0.011 0.074 0.988 0.959

Customer

Satisfaction

2.766 0.993 0.966 0.020 0.067 0.985 0.955

Table 5.8: Reliability and Validity of Latent Constructs

Constructs Convergent

Validity/AVE

Construct Reliability

Service Quality 0.53 0.85

Trust 0.61 0.84

Commitment 0.54 0.73

Perceived Usefulness 0.54 0.93

Perceived Ease of Use 0.62 0.87

Customer Satisfaction 0.51 0.80

Table 5.9: Discriminant Validity of Latent Constructs

Trust CMT SQ PEOU PU BI CS

Trust .606

CMT -.131**

(0.017)

.534

SQ .584**

(0.341)

-.099*

(.0098)

.53

PEOU .013

(.00169)

.168**

(0.028)

.206**

(0.042)

.614

PU .049

(.0024)

.226**

(.051)

-.063

(.0039)

.288**

(.082)

.538

BI -.092

(.0084)

.244**

(.059)

.079

(.0062)

.070

(.0049)

.05

(.0025)

.41

CS .131

(.017)

.213**

(.045)

.001

(.00001)

.635**

.403

.267**

(.071)

.019

(.00037)

.50

Diagonal axis show average variance extracted. Values within parenthesis are

squared correlation between the dimensions and values without parenthesis are

actual correlation values, **sig. at 0.01 level, * sig. at 0.05 level

180

Table 5.10: Various Stages of Structural Modelling

Stages Chi-

Square

GFI AGFI RMR RMSEA CFI TLI Deletion Addition

1 32.00 0.768 0.593 0.247 0.279 0.050 0.247 - PEOU-

CS

11 20.166 0.848 0.716 0.067 0.219 0.450 0.229 - SQ-Trust

111 9.718 0.912 0.824 0.055 0.148 0.766 0.649 - PEOU-

PU

1V 7.806 0.935 0.860 0.050 0.131 0.831 0.726 - BI-CMT

V 6.396 0.950 0.884 0.033 0.116 0.876 0.783 - SQ-

PEOU

V1 4.793 0.968 0.911 0.028 0.097 0.927 0.847 - PU-

CS&Cmt

V11 3.834 0.979 0.926 0.023 0.084 0.957 0.886 - -

Table 5.11: Results of Hypothesis Testing

Variables P.value C.R. Results

Commit<-CS .000 3.367 Accepted

CS<-Trust .001 3.239 Accepted

CS<-SQ .03 2.135 Accepted

Behaint<-PEOU .020 2.170 Accepted

Behaint<-PU .002 3.120 Accepted

181

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Chapter 6

Strategy for Online Customer

Satisfaction and Business

Performance

Chapter 6

Strategy For Online Customer Satisfaction and Business Performance

Contents Page No

6.1 Background 185

6.2 Major Findings 186

6.3 Perceptual Gap Between Private and Public

Sector Bank Managers 189

6.4 Perceptual Gap Between Private and Public

Sector Bank Customers 189

6.5 Perceptual Gap Between Customers and Managers 190

6.6 Managerial Implications 191

6.7 Theoretical Implications 194

6.8 Customer Awareness 195

6.9 Future Research 195

References 199

185

CHAPTER-6

STRATEGY FOR ONLINE CUSTOMER SATISFACTION AND

BUSINESS PERFORMANCE

6.1 Background

In the present highly competitive environment, online customers are very expensive to

be attracted and difficult to retain because it is relatively easy for customers to switch

their online providers. Customer satisfaction is the key to long term success of the

business and is the main reasons for and the driving force behind bank’s functioning.

Therefore, it is extremely important for online providers to know how to keep their

online customers satisfied and committed because committed customers are known to

visit the site more, deal more and gives more business to the banks in the form of

higher deposits and profits. In this respect, it is essential for all the banks to switch from

managing means to managing customers in order to satisfy them with the whole

bouquet of services they offer. Further, all the banks taken into consideration in the

study are offering complete e-bouquet of banking and financial services which include

ATM, credit card, debit card, electronic transfer, tele-banking, e-banking etc. In this

way, providing quality of online services by banks is increasingly becoming a ‘need to

have’ than a ‘nice to have’ service (Ganesan R. and Vivekanandan, K., 2009). Bank

Managers believe that with the improvement of information technology and literacy

level of customers, more than 20% of Indian population is aware to use internet

banking, which enables them to use more and more services. Thus, the challenge to all

banks is to expand internet banking user base and slowly increase the range of services

that customers use. In this context, the first chapter discusses the dimensions that lead

to customer satisfaction within the framework of detailed reviewed literature in second

chapter. The third chapter covers the research design and methodology used in the

present study. The fourth and fifth chapters focussed on the various components of

internet banking from the perspective of bank managers and online banking customers.

The findings from these chapters indicate a strong and positive relationship between all

the dimensions of internet banking and customer satisfaction. It further strengthens this

premise with many people adopting internet banking because of lot many benefits

associated with it (Katri, 2003; Musiime and Ramadhan, 2011) and thus leads to

increased profits. The results also show that in spite of better service quality and trust,

other factors such as perceived ease of use and perceived usefulness also affect

186

customer’s and manager’s intention to adopt the technology which further enhanced

their performance in the career perspective. Further, the perceptual gap between the

private bank managers and public bank managers, private bank customers and public

bank customers has also been examined. The business performance of these banks has

been studied after consulting their independent annual reports from year 1995 onwards.

Although the findings of the study revealed positive responses which were slightly

above average on five point scale, the banks should not be complacement, instead it

should be creative and proactive in creating innovative products and services with the

adoption of latest technologies to meet the needs of diversified internet users. It is in

this context that strategic action plan focussing on how to improve quality of online

services to keep and maintain high level of customer satisfaction as well as good

business performance has also been presented in this chapter. This chapter provides

suggestions to the bankers and policy makers to make online banking experiences more

useful and productive.

6.2 Major Findings

Major findings of the study are summarised as under:-

Perception of Bank Managers

Bank managers are satisfied with online services they create and maintain as the

same reduces work load of managers and enables them to carry out their

respective tasks more efficiently and effectively with less of time and efforts.

Managers having higher length of service are more satisfied with internet

banking as compared to their counterparts having lesser length of service.

Managers have strong commitment to security measures (MS: 4.56) and they do

not allow any third person to access customer’s personal information (MS:

4.54).

Bank managers are able to provide relevant information about all products and

services on their bank’s website (MS: 4.44).

Bank’s login process is secured (MS: 4.48) and transaction information is

protected during a connection (MS: 4.51).

Bank managers find their customers committed to deal online because of bank’s

performance (MS: 4.12), higher customer satisfaction and reasonable price

(MS: 4.05).

187

Bank managers are not much happy with regards to rapid delivery of online

services (MS: 3.47).

Bank has up to date equipment and technology (MS: 4.40) and about 97% of

respondents are satisfied for online services they get.

About 92% of respondents feel skilled at navigating the web pages (MS: 4.34)

followed by easy interaction on web pages, which is clear and understandable

(MS: 4.31).

They are also satisfied because it becomes easier to do their job (MS: 4.53),

helps them to accomplish their tasks quickly (MS: 4.40), enhances their

effectiveness on the job (MS: 4.50) and in their banking career (MS: 4.45).

Bank managers provide clear information about the transaction and

price/interest to their clients (MS: 4.40) and accurate and up to date information

(MS: 4.48).

Online payment system (MS: 4.61) has figured to be fast enough and effective

(MS: 4.32).

Bank managers also feel that implementation of information technology also

enables them to determine quickly the profitability of bank (MS: 4.47) as well

as of schemes (MS: 4.33) and customers (MS: 4.31).

Online services have proved to be productive, cost effective and time saving.

Business performance of all the banks under study has been improving after the

implementation of internet banking services.

In case of public sector bank, SBI leads in terms of amount of profitability,

customer satisfaction and commitment, as it is the largest and oldest bank in the

country. Whereas PNB leads in terms of online effectiveness and have higher

proportionate average increase in profits as compared to SBI.

In case of private sector banks, HDFC bank, followed by ICICI bank, has a

better impact on customer satisfaction and business performance as reflected by

more than above average mean scores obtained by various dimensions. Further,

the level of commitment is highest in JKB, as it is the leading bank in J&K

state, providing latest technology and changed the way to carry on their

financial transactions, thereby generating trust in the minds of customers.

The highest returns among public sector banks are provided by PNB followed

by Canara Bank and Union Bank of India. Whereas in case of private sector

banks, highest return on equity is provided by J&K Bank followed by HDFC

188

Bank and ICICI Bank and highest return on assets is provided by HDFC Bank

followed by J&K Bank and ICICI Bank.

Customer Perceptions

Highly educated persons who are employees, businessmen and belong to higher

income groups are the major users of internet banking.

Majority of the customers are in the age group of 20-30 years followed by 30-

40, 40-50 and 50 above age group of customers. Almost all age groups of

respondents are satisfied with perceived usefulness, perceived ease of use,

customer oriented services and interactivity provided by various banks

operating online. Customers young in age are not satisfied with the

responsiveness of bank administrators whereas customers old in age are not

committed to deal online.

Customers having longer length of association are more satisfied with internet

banking system as compared to their counterparts.

Majority of respondents have saving account with their respective bank with

ATM and credit card facility.

Majority of customers are satisfied with online services because it saves their

time and efforts. Besides, the system, being cost effective, enables them to

accomplish their banking transactions by sitting anywhere and anytime.

Respondents are also satisfied with login process and feel confident and secured

while conducting transactions online.

The respondents also trust their bank for not using personal information

inappropriately (MS: 4.07) and for not allowing any third person to access the

same (MS: 4.16).

90% of respondents committed to use online banking only if it is available in

the understandable language.

Respondents also find convenient to transfer money from one account to

another as well as from one place to another (MS: 4.22).

Respondents are also satisfied with online information system for getting

familiar with different services of various banks (MS: 4.05).

About 80% of respondents are satisfied with the attitude of bank administrators

in conducting banking transactions.

189

Respondents find their online bank administrators focussing customers in mind

(MS: 3.48), understand their specific needs (MS: 3.37), and showing confidence

in customers while dealing online (MS: 3.52).

Respondents found their bank’s website easy to use and navigate (MS: 4.22),

professionally designed (MS: 4.17) and user menus are clearly categorised and

well laid out in the screen (MS: 4.32).

98% of respondents found online banking very useful for utilising various

banking services (MS: 4.43) and thus enhances their effectiveness in

information seeking (MS: 4.28).

In spite of all these findings, respondents are not committed to deal online (MS:

3.50). Moreover, the level of trust in conducting online transaction is also less

because of security issues.

6.3 Perceptual Gap Between Private and Public Sector Bank Managers

Perceptual gap has been obtained from the differences in the responses of private bank

managers and public sector bank managers towards eight factors viz. perceived

usefulness, trust, customer satisfaction, commitment, better facilities, service quality,

perceived ease of use and profitability. The results of independent sample ‘t-test’ has

been used to know whether there exists significant difference between the mean scores

of the respondents or not (Table: 6.1). The study found no significant difference in the

opinion of respondents towards all the factors except commitment. Managers view that

customers of private sector bank are more committed to deal online (MS: 4.20) as

compared to their counterparts (MS: 3.80). Thus, from the above analysis, it becomes

evident that quality of online delivered services is more in case of private sector banks

which makes customers committed to deal online.

6.4 Perceptual Gap Between Private and Public Sector Bank Customers

Perceptual gap has been obtained from the differences of private and public sector bank

customer’s responses towards thirteen factors of online banking viz., website quality,

customer oriented services, trust, commitment, courtesy, after sales services,

responsiveness, security, perceived usefulness, interactivity, perceived ease of use,

behavioural intention and better services (Table: 6.2). Further, independent sample ‘t’-

test has been used to know whether there exists significant difference in the mean

scores of two sets of respondents or not. Study found no significant difference in the

190

opinion of respondents towards website quality, customer oriented services, trust,

courtesy, after sales services, responsiveness, security, perceived ease of use and

behavioural intention. However, significant difference exists between private and

public sector bank customers towards remaining four factors and these are

commitment, perceived usefulness, interactivity and better services. Both the groups

have exhibited almost average level of commitment towards their bank but respondents

of public sector bank (3.99) are more committed to deal online as compared to private

sector banks (3.72). This may be attributed to various reasons such as financial security,

government control etc. Moreover, respondents of public sector banks are also satisfied

with perceived usefulness and interactivity with their bank’s website as compared to

their private sector counterparts whereas respondents of private sector banks are more

satisfied with the services provided by their banks online (4.01) as compared to public

sector banks (3.66). This may be due to the reason that private sector banks are more

specialised in providing online services to their customers.

6.5 Perceptual Gap Between Online Banking Customers and Bank Managers

The perceptual gap has been measured to examine the discrepancy in the opinion of

customers and bank managers towards operation of online banking services. To test the

significant mean differences, independent t-test has been used. The results of t-test

exhibit significant mean differences between customers and managers about online

banking services. Bank managers accorded highest mean scores to most of the items

and thus believe that they provide better quality online services to their customers

(Table 6.3). Customers claim some deficiencies in online services, they find problem

in remitting funds to others due to network problem and sometimes due to slow down

of bank’s website, they are unable to access their accounts etc. Further, bank managers

claim that they adopt problem solving approach to take care of their customers and are

truly sincere to their clients whereas customers find difficulty in gathering the requisite

information from bank administrators while dealing online. This is also consistent with

the findings of Chaudry et al., 2013 and Lee et al., 2009 in which they found significant

mean difference in the perceptions of customers and managers regarding online service

quality of banks. Also, customers find bank employees too busy in their work and thus

unable to help in any matter regarding online banking services. Thus, bank managers

are required to provide customer oriented services with no delay of time.

191

6.6 Managerial Implications

Makes customers committed to deal online

Customer commitment can be considered as the key construct in bank financial

performance. But it is found in the present study that customer commitment is less

(MS: 3.50). Thus, it is required that banks which want customers to be committed to

deal online must implement personalised aspect of the services i.e. getting to

understand what customers need and act as per demand.

Problem solving approach

Customers are averagely satisfied (MS: 3.60) with problem solving approach of banks.

Thus, banks are required to provide problem solving approach to customers in dealing

online i.e by providing them a toll free number which could handle customer

complaints and general feedback about the electronic banking services. This would not

only provide a service to a customer that is free, but also provide the bank with

valuable information for future developments on e-banking.

Creation of trust in customers

It is found from the path diagram that level of customer trust (SRW=.08) in generating

online customer satisfaction is less. So, bank managers must try to earn customer’s trust

by incorporating effective technology tools and motivational messages that reflect full

guarantee to protect their personal information. Also the banks must provide balance

enquiries through SMS/emails and also provide statements for every transaction

conducted electronically. This will enable the customers to know the accounts status,

verify accuracy of all transactions online including confirmation of the same. It is also

worth noting that online banking is less verifiable and controllable, customers usually

have difficulty in claiming compensation when any transaction error occurs. Thus,

online bank administrators must provide customers with digital receipts or a guarantee

for every transaction in order to increase confidence of customers.

Training to employees/Internal Marketing

It is also found in the present study that customers attach more importance to employee

behaviour, their friendliness attitude, politeness, cooperation, promptness in answering

enquiries online, helping attitude etc. Thus, banks must pay special attention on hiring

competent and friendly personnel, train them to effectively handle customer problems

192

and trust their employees in dealing online. Also, banks can enhance their competitive

advantage if employees are supported effectively to satisfy customer needs because it is

only service oriented staff that plays a vital role in enhancing organizational capabilities

for delivering high quality and pleasant services to customers which enhance customer

satisfaction, their loyalty to their bank and make them committed to deal online and

hence result in better organizational performance in terms of higher deposits and

profits.

Enhances contents of websites

It is obviously said phrase that ‘content is king’. Without content and clear information,

a website will lack an essential element of online marketing regardless of how nice or

elegant the design of the site is. These days, majority of bank customers are

increasingly utilizing online content to make financial decisions, it is advise able to

website content developers that they should display only relevant bank products and

services with relevant details.

Security for transactions

It has also been seen in the present study that customers are conscious about security of

usage of credit card, debit card and electronic transfers (MS: 3.28). Thus, security of

online transactions can be enhanced by continuously strengthening the security control

of the information systems and by implementing the most advanced and latest security

technologies.

Incentives

Bank do not provide any incentives for continuous dealing (MS: 3.48). Infact they are

required to introduce certain types of incentives to their online banking customers for

continuous dealing with their bank’s website and not switching to any other banks. The

incentives may be in the form of less charges for conducting transactions online after a

certain time period and so on. For instance, ICICI bank had launched a pure online

banking savings account in July 2008 called ‘b2b-Branch-free-Banking’, the

advantages of which includes ‘Zero minimum balance’, ‘Zero charges for fund

transfer’, ‘online bill payments’, ‘mobile top-ups’ etc. (Business Line, 2008).

193

Makes e-banking error free

Almost average mean scores are awarded by customers to transaction that e-banking is

error free (MS: 3.57), which may be due to the fact that like manual banking system, e-

banking also has its own weaknesses and risks. Thus, to make e-banking error-free,

developers are required to make sites easy to use and navigate with sufficient security

measures (Maureen et al., 2013).

Delivery of better service quality

In banking industry, delivery of better service quality is a way to achieve higher

customer satisfaction. In an online environment, banks interact with customers through

their call centres. It implies that quality customer service staff is a key ingredient in a

successful bank-customer relationship. Back office employees are also required to be

well equipped with enough knowledge to respond to problems of their customers.

Understand specific needs

It is found that customers are averagely satisfied with call centre administrators for

understanding their specific needs (MS: 3.37). In this way, bank employees need to

serve customers politely, striving to get information first hand, where they are expected

to stimulate customers trust for creating good relationship between bank employees and

customers. In addition to this, employees are required to listen to customer complaint

by giving them special attention and help them in solving their problems by giving

advice on new products with their advantages compared to similar products of

competitors (Rahman, 2004).

Technical Problems

There are lot of technical problems which are faced by both bankers and customers

such as slow down of network, hardware problems, electricity etc. To overcome these

problems banks must properly check their internet connectivity with sustained power

supply to make internet banking successful. Further, all relevant information should be

saved so that the attempt of fraud can be traced, which means that hard drive should not

be formatted immediately. In addition to this, the backed up data should be periodically

tested to ensure recovery without loss of transaction

194

6.7 Theoretical Implications

Awareness to customers

Banks are also required to make the non users aware through print media followed by

internet, SMS on mobile, outdoor advertisement and television. They should resort to

video presentations at bank branches to project the user- friendliness of their banking

services in general and e-banking in particular (Sharma, 2011). Also, they should

organise seminars/workshops/talks on the healthy usage of e-banking. Moreover,

bankers need to provide sufficient guidance to customers for using e-banking services.

Customer feedback

It is an established concept of strategic planning. The performance of online banking

be monitored on a regular basis by sending any feedback questions to be filled by

customers through their websites (Joseph et al., 1999).

Installation of separate counters

Banks must help customers to do online banking. A separate counters should be opened

by banks at their various branches and the persons to be selected to assist online

customers must be expert in information technology and have wide knowledge and

patience to assist the customers.

Government regulation

Government or central bank can also play major role in the development of internet

banking by reducing service charges on the transactions and by assuring the customers

adequate regulatory framework that will ensure customer protection and security of

transactions (Abdullah et al., 2011).

Maintenance of record

All applications, including those received online, have proper record keeping facilities

for legal purposes. It is necessary to keep all received and sent messages both in

encrypted and decrypted form for future reference.

Good working conditions

Good working conditions are also generally considered as a pre-requisite for good

service quality, as employees perform better when organisation creates a climate of

195

concern and care (Kinicki et al., 1992). Since back office employees also play

important role in online environment as compared to front line employees, so they must

be provided better working conditions as an important reward to make them deliver

quality service to their customers, because employee satisfaction can be the major

factor influencing customer satisfaction (Snipes et al., 2005).

6.8 Customer Awareness

Customers are required to be made aware and knowledgeable about the proper

use of e-banking services such as making strong passwords, logging out and

closing browsers after completing online banking (Patil, 2012).

They are also required to be enlightened to update antivirus systems. Further

customers must be advised that they do not respond to suspicious e-mails and

SMS and also do not save their personal information (passwords, PINs, credit

card or debit card numbers) on hard drive if their PC is not used by the customer

alone because this could enable third parties to view the information.

6.9 Future Research

Although this research reveals certain aspects of customer satisfaction and customer

commitment in context of internet banking in Indian context, there is lot of room for

future research in order to ascertain and enrich online banking service in India:

Instead of focussing on banking sector, the broader concept of online services

should be taken into account such as online shopping, online ticketing etc.

Future research ought to apply more comprehensive approach by making a

comparative analysis of branch and online banking services, thereby taking into

consideration the same aspects of study.

Moreover, in future, perception of bank employees should also be taken into

consideration to make study more meaningful and interesting.

Further, comparison between existing users and persons intending to use

internet banking should also be made in future study.

196

Table 6.1: Perceptual Gap between Private and Public Sector Bank Managers

Factors Private Bank

Managers

Public Bank

Managers

Mean

Difference

T. Value Sig

Perceived

Usefulness

4.40 4.46 0.06 .560 .576

Trust 4.51 4.50 0.01 .075 .940

Customer

Satisfaction

4.33 4.40 0.07 .623 .534

Commitment 4.20 3.80 0.40 2.461 .015

Better

facilities

4.01 4.02 0.01 .045 .964

Service

Quality

4.44 4.50 0.06 .502 .616

Perceived

ease of use

4.30 4.37 0.07 .583 .561

Profitability 4.32 4.33 0.01 .009 .993

197

Table 6.2: Perceptual Gap Between Private and Public Sector Bank Customers

Factors Private

Bank

Customers

Public Bank

Customers

Mean

Difference

T. Value Sig

Website

Quality

3.86 3.93 0.07 1.07 .282

Customer

Oriented

Services

3.99 4.10 0.11 1.72 .086

Trust 4.03 3.96 0.07 1.04 .298

Commitment 3.72 3.99 0.27 3.05 .002

Courtesy 3.65 3.78 0.13 1.37 .171

After Sales

Services

3.96 4.08 0.12 1.72 .086

Responsiveness 3.76 3.70 0.06 .656 .512

Security 4.09 4.03 0.06 .667 .505

Perceived

Usefulness

4.30 4.49 0.19 2.851 .005

Interactivity 4.08 4.41 0.33 4.94 .000

Perceived Ease

of Use

4.14 4.18 0.04 .757 .450

Behavioural

Intention

3.83 3.72 0.11 1.160 .247

Better Services 4.01 3.66 0.35 3.57 .000

198

Table 6.3: Perceptual Gap of Customers and Bank Managers

Items C BM MD T. Value Sig.

Doesn’t allow third person to access

personal information

4.16 4.54 .381 4.812 .000

Login process is secure 4.04 4.48 .440 4.240 .000

Truly sincere in its promises to users 3.75 4.38 .633 6.353 .000

Trust bank 4.09 4.47 .382 4.575 .000

Feel confident in doing e-banking 4.24 4.34 .095 .892 .373

Believe in information presented on

bank’s website

4.45 4.15 .290 2.575 .011

Continue to use the services 3.73 3.98 .253 -1.909 .057

Up to date equipment & technology 4.39 4.40 .010 -.047 .963

Online services free from deficiencies 3.54 4.16 .626 4.909 .000

Problem solving approach 3.60 4.55 .953 3.221 .002

Simple to do banking 4.09 4.43 .342 4.50 .000

Website easily navigated 4.22 4.34 .122 1.78 .074

Increases productivity 4.06 4.45 .386 4.24 .000

Enhances effectiveness 4.31 4.53 .219 3.25 .001

Happy with online services 4.27 4.35 .084 1.23 .220

Satisfied with transaction procedure 4.01 4.42 .107 1.255 .217

Clear transaction and price

information

4.20 4.31 .110 2.448 .126

Satisfied with payment system 4.21 4.32 .116 1.53 .124

Overall satisfied with online services 4.38 4.61 .235 -3.82 .000

199

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ANNEXURES

222

ANNEXURE 1

Impact of Internet Banking on Customer Satisfaction and Business Performance

Questionnaire to be filled by Bank Managers

Dear Sir/Madam

I am Ph D scholar of Department of Commerce, University of Jammu doing research

on topic entitled ‘Impact of Internet Banking on Customer Satisfaction and Business

Performance’. Please oblige and help in filling up the questionnaire with fair and frank

responses. I assure that the information supplied will be kept strictly confidential and

used for research purpose only.

A. General Information

1. Gender: M……….. F……..

2. Age in years: …………………………………………………....………

3. Qualification:…………………………………………………....……….

4. Name of the Bank:…………………………………………….…...…….

5. Name of the Branch:……………………………………...…………....…

6. Position Held:…………………………………………………………......

7. Department:………………………………………………………….........

8. Length of service:………………………………………………….........…

B. Tick the peripheral services that bank provides

1. ATM facility …………………………………………………………........

2. Credit card facility ……………………………………………………....….

3. Debit card facility …………………………………………………….....…..

4. Electronic transfer facility ………………….....................................................

5. Home banking facility ………………………………………………….....….

6. Tele banking facility ……………………………………………………...……

7. Internet banking …………………………….....................................................

8. 24 Hours banking …………………………………………………………....…

9. Any where banking ………………………………………………………....….

10. Travellers cheque facility ………………………………………………...........

11. Foreign exchange ………………………………………………………..……..

12. Facility for payment of household services (eg. Bills etc) ……………….…….

13. Depository facilities for stocks/shares …………………………………….......

Note: Please tick any no. from 5 to 1 on the basis of your experience with your prime

bank. Here 5 means strongly agree, 4 means agree, 3 means neutral, 2 means disagree

1 means strongly disagree, N.K. means not known. Here prime bank means the bank

you served for maximum period.

223

S.NO TRUST 5 4 3 2 1 NK

1. Your bank has strong commitment to

security measures.

5 4 3 2 1 NK

2. Your bank ensures that an information

transaction is protected during a connection.

5 4 3 2 1 NK

3. Your bank’s web page offers all the relevant

information about all products and services.

5 4 3 2 1 NK

4. Your bank does not allow any third person

to access to customer’s personal

information.

5 4 3 2 1 NK

5. Your bank keeps promises it makes to

customers.

5 4 3 2 1 NK

6. Your bank provides detailed online terms

and conditions.

5 4 3 2 1 NK

7. Your bank’s login process is secure. 5 4 3 2 1 NK

8. Your bank works very openly online. 5 4 3 2 1 NK

9. Your bank considers customer welfare when

making important decisions.

5 4 3 2 1 NK

10. Customers have full confidence in your

bank’s reliability.

5 4 3 2 1 NK

11. Bank practices that harm customers’ self

esteem or destroy trust are restricted in your

bank.

5 4 3 2 1 NK

12. There are clear explanations of security on

your bank’s website.

5 4 3 2 1 NK

13. Your bank uses appropriate safeguards

(privacy protection measures) to ensure

customers of a successful transaction.

5 4 3 2 1 NK

14. Your bank site is properly secure for credit

or debit card information.

5 4 3 2 1 NK

15. Customers believe in the online information

that your bank provides to them.

5 4 3 2 1 NK

16. Your bank administrators respond very

quickly online.

5 4 3 2 1 NK

17. Your customers feel confident when using

e-banking services with your bank.

5 4 3 2 1 NK

18. Your bank administrators help the customer

in any query online.

5 4 3 2 1 NK

19 Your bank gives customers a feeling of

trust.

5 4 3 2 1 NK

Commitment

20 Your bank has customer’s best interest in

mind.

5 4 3 2 1 NK

21. Customers are committed to deal online

with your bank because of your best online

services.

5 4 3 2 1 NK

22. Your bank’s image determines customer’s

commitment online.

5 4 3 2 1 NK

23. Customer’s commitment is influenced by 5 4 3 2 1 NK

224

the positive attitude of your bank’s online

administrators.

24. Customers continue to deal online with your

bank because they feel a strong attachment

to your bank.

5 4 3 2 1 NK

25. Customers’ commitment to your bank is

determined by their continuous satisfaction.

5 4 3 2 1 NK

26. Customers want to remain with your bank

because they feel a strong sense of

belonging with the bank.

5 4 3 2 1 NK

27. Customers are willing ‘to go the extra mile’

to continue with your bank.

5 4 3 2 1 NK

28. Customers take pleasure in being a customer

of your bank.

5 4 3 2 1 NK

29. It pays of economically to be a customer of

your bank.

5 4 3 2 1 NK

30. Customers are committed to buy from your

bank.

5 4 3 2 1 NK

31. Commitment is due to reasonable price of

your bank.

5 4 3 2 1 NK

32. Customers are committed to deal online

with your bank because of your

performance.

5 4 3 2 1 NK

33. Customers speak high about your services

that your bank provides to them.

5 4 3 2 1 NK

34. Customer focus and service quality are

driving forces behind day-to-day operations

of your bank.

5 4 3 2 1 NK

35. Customers are committed to your bank

because of all time availability of services.

5 4 3 2 1 NK

36. Your customers are committed because of

rapid delivery of online services.

5 4 3 2 1 NK

37. Your bank provides facility of fund transfer

to third party easily.

5 4 3 2 1 NK

38. Customers are committed because your

bank allows easy access to transaction data

both recent and historical.

5 4 3 2 1 NK

39. Your bank provides customers convenient

way of interaction with bank administrators

online.

5 4 3 2 1 NK

Service Quality

40. Your bank has up to date equipment and

technology.

5 4 3 2 1 NK

41. Your bank provides online services to its

customers.

5 4 3 2 1 NK

42. Your bank services are customised to meet

the heterogeneous customer needs online.

5 4 3 2 1 NK

43. There is a high reliability in the delivery of

bank services online.

5 4 3 2 1 NK

225

44. Your bank gives accurate presentation of

what its services will do for customers.

5 4 3 2 1 NK

45. Online services delivered by your bank are

free from deficiencies.

5 4 3 2 1 NK

46. Your bank takes a problem solving

approach in delivering online services to its

customers.

5 4 3 2 1 NK

47. Your bank charges a reasonable price for

online services.

5 4 3 2 1 NK

48. Your bank administrators respond very

promptly to any customer service needs

online.

5 4 3 2 1 NK

49. Overall, your bank provides best quality

services to its customers online.

5 4 3 2 1 NK

50. Services delivered by your bank are

standardised.

5 4 3 2 1 NK

51. Your bank’s online services is more

competent than other banks.

5 4 3 2 1 NK

52. Your bank has a better overall online

performance.

5 4 3 2 1 NK

53. Your bank keeps customer informed of any

new scheme online.

5 4 3 2 1 NK

54. It is very easy for your customers to do

banking transactions online.

5 4 3 2 1 NK

55. Your bank tries to help customers to fulfill

their online banking need.

5 4 3 2 1 NK

56. Your bank provides best value for money as

compared to other banks.

5 4 3 2 1 NK

57. Your bank pays special attention on online

service failures.

5 4 3 2 1 NK

58. Customers have full confident in your

bank’s reliability.

5 4 3 2 1 NK

59. Your bank effectively uses customer

feedback to improve service standard

online.

5 4 3 2 1 NK


60. I would find interaction through web pages

clear and understandable.

5 4 3 2 1 NK

61. I would find it easy to become skilful at

navigating the web pages.

5 4 3 2 1 NK

62. My interaction with online banking does not

require a lot of effort.

5 4 3 2 1 NK

63. It was easy to find information about

various clients online.

5 4 3 2 1 NK

64. I think online banking is easy to use. 5 4 3 2 1 NK

65. It is quick to do transactions online. 5 4 3 2 1 NK


66. Using online banking on my job enables me

to accomplish tasks more quickly.

5 4 3 2 1 NK

226

67. Online banking improves my job

performance.

5 4 3 2 1 NK

68. Online banking would enhance my

effectiveness on the job.

5 4 3 2 1 NK

69. Online banking would make it easier to do

my job.

5 4 3 2 1 NK

70. I would find the world wide web useful. 5 4 3 2 1 NK

71. Web based transaction is advantageous. 5 4 3 2 1 NK

72. Information regarding various deposit

schemes, loan structure are easily available

by retrieving our bank’s website.

5 4 3 2 1 NK

73. Using online banking would enhance my

effectiveness in banking career.

5 4 3 2 1 NK


74. Customers are satisfied with online services

of your bank.

5 4 3 2 1 NK

75. Your bank objectives are driven by

customer satisfaction.

5 4 3 2 1 NK

76. Your bank provides incentives to customer

for continuous dealing online.

5 4 3 2 1 NK

77. Your bank has a system of monitoring,

analyzing and solving customer problems

online.

5 4 3 2 1 NK

78. Customer focus and better online service

quality are driving forces behind day to day

operations of your bank.

5 4 3 2 1 NK

79. Customers of your bank believe that their

online transactions completed timely.

5 4 3 2 1 NK

80. Your bank’s online infrastructure is good. 5 4 3 2 1 NK

81. Your bank administrators understand what

online service attributes customers value

most.

5 4 3 2 1 NK

82. Your bank’s strategy for online competitive

advantage is based on its understanding of

online customer needs.

5 4 3 2 1 NK

83. Your bank completely meets online

customer satisfaction.

5 4 3 2 1 NK

84. Your bank administrators help customers in

doing banking transactions online.

5 4 3 2 1 NK

85. Administrators of your bank maintain good

relations with your customers online.

5 4 3 2 1 NK

86. Your customers are satisfied with the online

transaction procedures.

5 4 3 2 1 NK

87. Your bank’s website provides clear

transaction and price information.

5 4 3 2 1 NK

88. Your bank’s website provides accurate and

up to date information to its customers.

5 4 3 2 1 NK

89. Your bank’s website provides privacy and

security to customer transaction.

5 4 3 2 1 NK

227

90. Your bank’s website deals with customers

order fast enough.

5 4 3 2 1 NK

91. Your customers are satisfied with the online

payment system of your bank.

5 4 3 2 1 NK

92. On the whole, customer satisfaction is the

motto of your bank.

5 4 3 2 1 NK

Profit Emphasis

93. Your bank’s deposits have been increased

by using online system.

5 4 3 2 1 NK

94. Your bank’s profits have been increased by

providing online payment facilities to

customers.

5 4 3 2 1 NK

95. Administrators of your bank can quickly

determine the profitability of major

customers.

5 4 3 2 1 NK


determine the profitability of various

schemes.

5 4 3 2 1 NK


determine the profitability of your branch.

5 4 3 2 1 NK

98. Your bank believes that all your services

must be profitable.

5 4 3 2 1 NK

99. Your bank administrators can quickly

determine the profitability of your bank.

5 4 3 2 1 NK

100. On the whole, doing online transaction is

very profitable.

5 4 3 2 1 NK

ANY SUGGESTION

………………………………………………………………………………………......

THANK YOU FOR YOUR COOPERATION

228

ANNEXURE 2 Impact of Internet Banking on Customer Satisfaction and

Business Performance

Questionnaire to be filled by Bank Customers

Dear Sir/Madam

I am Ph D scholar of Dept of Commerce, University of Jammu doing research on topic

entitled ‘Impact of Internet Banking on Customer Satisfaction and Business

Performance’. Please oblige and help in filling up the questionnaire with fair and frank

responses. I assure that the information supplied will be kept strictly confidential and

used for research purpose only.

A. General Information

1. Gender: M……………...….F………………...……..........

2. Age (in years): ………………………….....…………...........…..

3. Qualification: …………………………………………...................

4. Occupation: …………………………………………….................

5. Marital status: a) Single…...…..b) Married…….………...........….

6. Income in Rupees (per annum): ………………………….................

A) up to 50,000 b) 50,000-1,00,000 c) 1,00,000-2,00,000 d)Above 2,00,000

7. Name of the Prime Bank: …………………………………...............

8. Length of association with the Prime Bank:………………..............

9. Name and reason for association with other Banks:

A. ……………………………………………………………................

B. …………………………………………………………….................

C. ……………………………………………………………................

10. Existing Deposit Accounts: ……………………………..............

a) Current b)Saving c) Recurring d)F D R e)other

B. Tick the peripheral services that your bank provides:

1. ATM Facility

2. Credit Card Facility

3. Debit Card Facility

4. Electronic Transfer Facility

5. Home Banking Facility

6. Tele Banking Facility

7. Internet Banking

8. 24 Hour Banking

9. Anywhere Banking

10. Traveller’s cheque Facility

11. Foreign Exchange

12. Facility for payment of household services (eg. Bills etc)

13. Depository facilities for Stocks/Shares

Note: Please tick any no. from 5 to 1 on the basis of your experience with your

prime bank. Here 5 means strongly agree, 4 means agree , 3 means neutral,2 means

disagree, 1 means strongly disagree and NK means not known. Here prime bank

means the bank you have maximum transactions.

229

S.NO. Trust 5 4 3 2 1 NK

1. You feel secure in doing transaction

online with your bank.

5 4 3 2 1 NK

2. You believe the information presented

on your bank’s website.

5 4 3 2 1 NK

3. You feel confident while using e-

banking method to access money.

5 4 3 2 1 NK

4. The practices that harm customer’s self

esteem or destroy trust are not given on

your bank’s website

5 4 3 2 1 NK

5. You trust the site of your bank for not

using your personal information

inappropriately.

5 4 3 2 1 NK

6. Your privacy is protected on your

bank’s website.

5 4 3 2 1 NK

7. You trust the security of your bank’s

website information quality.

5 4 3 2 1 NK

8. Your bank website doesn’t allow any

third party to access your personal

information.

5 4 3 2 1 NK

9. Your bank’s website ensures that an

information transaction is protected

during a connection.

5 4 3 2 1 NK

10. Your bank’s website offers all the

relevant information about all schemes.

5 4 3 2 1 NK

11. Your bank’s website works in your best

interest.

5 4 3 2 1 NK

12. Your bank’s website would keep your

commitments.

5 4 3 2 1 NK

13. Your online bank is truly sincere in its

promises to users.

5 4 3 2 1 NK

14. Your online bank is capable and

proficient in its business.

5 4 3 2 1 NK

15. The login process of your online bank is

secure.

5 4 3 2 1 NK

16. Your online bank performs its business

role very well.

5 4 3 2 1 NK

17. It is likely that you will use the e-bank

in the near future.

5 4 3 2 1 NK

18. Using an online bank is financially

secure.

5 4 3 2 1 NK

19. Your bank’s site is secure for your

credit card information.

5 4 3 2 1 NK

20. Overall you trust your bank while doing

online services.

5 4 3 2 1 NK

Commitment

21. You will not stop using your bank

website in the future.

5 4 3 2 1 NK

22. You will continue to use the services of 5 4 3 2 1 NK

230

your bank’s website.

23. You will visit your bank’s website if

you need banking services.

5 4 3 2 1 NK

24. You feel emotionally attached to your

online bank.

5 4 3 2 1 NK

25. You are committed to your online bank

because the links are problem free,

accurate and the pages download easily.

5 4 3 2 1 NK

26. You are committed because your bank’s

website is available in the language you

can understand.

5 4 3 2 1 NK

27. You are committed because your online

bank takes care of problems properly

and compensate for the problems they

create.

5 4 3 2 1 NK

Service Quality

28. Administrators of your online bank

providing online services are never too

busy to respond to your enquiries.

5 4 3 2 1 NK

29. Administrators of your online bank are

always willing to help you

5 4 3 2 1 NK

30. Administrators of your online bank are

always courteous to you.

5 4 3 2 1 NK


inform you promptly for the completion

of transactions.

5 4 3 2 1 NK

32. Your online bank gives you individual

attention in doing transaction online.

5 4 3 2 1 NK

33. You have full confidence in dealing

with your bank online.

5 4 3 2 1 NK

34. Administrators of your online bank have

all knowledge to answer your queries

online.

5 4 3 2 1 NK


show confidence in customers while

dealing online.

5 4 3 2 1 NK

36. Call centres of your online bank have

operating hours convenient to its

customers.

5 4 3 2 1 NK

37. Call centres or help desks of your online

bank give you personal attention in

doing transaction online.

5 4 3 2 1 NK

38. Administrators or call centres of your

online bank understand your specific

needs.

5 4 3 2 1 NK

39. Administrators or call centres of your

online bank have best interest of

customers in mind.

5 4 3 2 1 NK

40. Your online bank has up to date 5 4 3 2 1 NK

231

equipment and technology.

41. The website of your online bank is

appealing.

5 4 3 2 1 NK

42. You find information easily on your

bank’s website.

5 4 3 2 1 NK

43. The website of your online bank

provides you with valuable information.

5 4 3 2 1 NK

44. The advertised messages on your bank’s

website are attractive.

5 4 3 2 1 NK

45. The website of your online bank is easy

to use and navigate.

5 4 3 2 1 NK

46. Your online bank performs the online

services very quickly.

5 4 3 2 1 NK

47. Online services delivered by your bank

are standardised.

5 4 3 2 1 NK

48. Prompt response is given for all

enquiries online.

5 4 3 2 1 NK

49. Your bank takes a problem solving

approach in delivering online services.

5 4 3 2 1 NK

50. Online services delivered by your bank

are free from deficiencies.

5 4 3 2 1 NK

51. Information about new deposit schemes

are provided by your bank online.

5 4 3 2 1 NK

52. Your online bank performs the service

right first time.

5 4 3 2 1 NK


53. It was very simple to do banking on

computer system.

5 4 3 2 1 NK

54. It was easy to find information you

needed regarding your banking

transactions.

5 4 3 2 1 NK

55. The information presented on your

online bank’s website is clear and

understandable.

5 4 3 2 1 NK

56. The website of your online bank can be

easily navigated.

5 4 3 2 1 NK

57. The website of your online bank looks

professionally designed.

5 4 3 2 1 NK

58. The user menus are clearly categorised

and are well laid out in the screen.

5 4 3 2 1 NK

59. Your online bank is error free. 5 4 3 2 1 NK

60. The demonstrations or guidelines

provided by your online bank can help

you how to do banking online.

5 4 3 2 1 NK

61. You find an online bank to be flexible to

interact with.

5 4 3 2 1 NK

62. Overall, online banking is easy to use. 5 4 3 2 1 NK


63. Online banking enhances your 5 4 3 2 1 NK

232

effectiveness in doing banking

transactions.

64. Online banking enhances your

effectiveness in information seeking

regarding various schemes.

5 4 3 2 1 NK

65. You find doing online banking useful. 5 4 3 2 1 NK

66. Online banking saves your time. 5 4 3 2 1 NK

67. It is quick to make transactions on your

bank’s website.

5 4 3 2 1 NK

68. The site of your bank does not make you

lose your time interactivity.

5 4 3 2 1 NK

69. Using the world wide web would enable

you to accomplish banking transactions

more quickly than going to bank

branches.

5 4 3 2 1 NK

70. Online bank increases your productivity. 5 4 3 2 1 NK

71. Using an online bank makes it easier for

me to utilise banking services.

5 4 3 2 1 NK

72. Online banking is advantageous for me. 5 4 3 2 1 NK

73. Overall, an online bank is useful for me

to utilise banking services.

5 4 3 2 1 NK

Behavioural Intention

74. You use the online banking for your

banking needs.

5 4 3 2 1 NK

75. You intend to continue doing online

banking with your bank.

5 4 3 2 1 NK

76. You will strongly recommend others to

use online banking.

5 4 3 2 1 NK

77. You would see yourself using the online

banking for handling your banking

transactions.

5 4 3 2 1 NK

78. Using the internet banking for handling

your banking transactions is something

you would do.

79. Your favourable intention would be to

use online banking rather than

traditional banking for your banking

transactions.

5 4 3 2 1 NK


80. You are completely happy with your

bank providing online services.

5 4 3 2 1 NK

81. You are very pleased with your bank

providing online services.

5 4 3 2 1 NK

82. Your experience with the online bank

has always been good.

5 4 3 2 1 NK

83. You use online banking for checking

balances and doing other banking

transactions.

5 4 3 2 1 NK

84. You are satisfied with the customer 5 4 3 2 1 NK

233

support provided on your bank’s

website.

85. You are satisfied with the after sales

service provided on your bank’s

website.

5 4 3 2 1 NK

86. You are satisfied with the various

deposit schemes and loan procedures

provided on your bank’s website.

5 4 3 2 1 NK

87. Your bank’s website is easy to use. 5 4 3 2 1 NK

88. The various deposit schemes provided

on your bank’s website meet your

specific needs.

5 4 3 2 1 NK

89. You are satisfied with the payment

system provided on the bank’s website.

5 4 3 2 1 NK

90. You are satisfied with the transaction

procedures.

5 4 3 2 1 NK

91. Your bank’s website provides

information that exactly meets your

needs.

5 4 3 2 1 NK


information that you trust.

5 4 3 2 1 NK

93. Your bank’s website is user friendly. 5 4 3 2 1 NK

94. Your bank’s output format is easy to

read.

5 4 3 2 1 NK

95. Your bank’s website provides clear

transaction and price information.

5 4 3 2 1 NK


innovative deposit schemes.

5 4 3 2 1 NK

97. Your bank’s website allows easy

transfer of money.

5 4 3 2 1 NK

98. Your bank’s website provides customer

oriented services.

5 4 3 2 1 NK

99. You are very satisfied with your bank

providing online services.

5 4 3 2 1 NK

ANY SUGGESTION

………………………………………………………………………………………......

THANK YOU FOR YOUR COOPERATION

impact of internet banking on customer satisfaction … · 2017-11-30 · impact of internet...

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