technology assesment model

7/28/2019 Technology Assesment Model

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CHAPTER I

INTRODUCTION


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INTRODUCTION

During the past decade, the online service industry has witnessed tremendous growth,

much of it spurred by the Internet revolution (Keaveney and Parthasarathy, 2001). Especially, the

potential of the Web as a commercial medium is widely recognized and the growth in online

service industries such as online banking has increased rapidly. In addition to Internet

companies, traditional organizations are investing a huge amount of money and effort in

information systems to provide online services through the Web. The underlying assumption of

their investment is that, because online services provide their customers with convenience,

interactivity, relatively low cost, and a high degree of customization/personalization, they will

enhance customer satisfaction and retention more effectively than offline-based services (Khalifa

& Liu, 2001). Since the mid-1990s, there has been a fundamental shift in banking delivery

channels toward using self-service channels such as online banking services. Although in recent

years the number of online banking users has grown rapidly, there is some evidence supporting

the opposite fact that online banking acceptance is faced with problems. Robinson (2000) for

instance found that half of the people that have tried online banking services will not become

active users.

Online Banking

Internet has emerged as a key competitive arena for the future of financial services

(Cronin, 1998) in that online banking offers customers more features with lower cost than

traditional banking activities. Since the Security First Network Bank (SFNB) first started its

Internet bank on the web site (www.SFNB.com), more than 1,500 financial institutions have

made plans to offer certain forms of Internet banking in 3 years. Advanced technologies enable

banks to utilize new banking products, such as a smart card and electronic money, through the

Internet. Internet banking is easier, more convenient and offers more features with lower cost

than home banking in the 80s. Customers responses to the Internet banking system have been

so much different from the home banking due to its easy accessibility. Customers can access


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their account from anywhere in the world and at any time. To secure loyal customers, many

banks try to provide customers with unique online experiences that customers cannot access

through the offline channels. Considering that enormous capital investment is needed for

developing these online banking services, it is very critical for them to measure the service

quality produced by online banking systems.

Online banking in this study is defined as an Internet portal, through which customers can

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

Therefore banks Web sites that offer only information on their pages without possibility to do

any transactions are not qualified as online banking services. The goal of this study is to increase

our current understanding of the factors that influence online banking acceptance in the light of

the technology acceptance model (TAM) (Davis et al., 1989; Mathieson, 1991; Davis and

Venkatesh, 1996). More precisely, online banking acceptance will be studied from the

information systems acceptance point of view referring to the idea that consumers are using

banks information system (online banking service) directly and hence more knowledge on the

factors that affect information systems adoption is needed in order to better understand and

facilitate the acceptance.

This article is divided into four parts: the first part contains a literature review on online banking

and information systems acceptance. The second part presents the research methodology used in

this work. The third part comprises of the results and analysis. In this part the data is analysed

using regression and correlation analyses. The final part consists of the conclusions and practical

implications of the research.

.


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CHAPTER II

REVIEW OF LITERATURE


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REVIEW OF LITERATURE

Online banking acceptance has gained special attention in academic studies during the

past five years as, for instance, banking journals have devoted special issues on the topic (e.g.

Karjaluotoet al., 2002; Waite and Harrison, 2002; Bradleyand Stewart, 2003; Gerrard and

Cunningham,2003; Mukherjee and Nath, 2003). We can find two fundamental reasons

underlying online banking development and diffusion. First, banks get notable cost savings by

offering online banking services. It has been proved that online banking channel is the cheapest

delivery channel for banking products once established (Sathye, 1999; Robinson, 2000; Giglio,

2002). Second, banks have reduced their branch networks and downsized the number of service

staff, which have paved the way to self-service channels as quite many customers felt that branch

banking took too much time and effort (Karjaluoto et al., 2003). Therefore, time and cost savings

and freedom from place have been found the main reasons online banking acceptance (Polatoglu

and Ekin, 2001; Black et al., 2002; Howcroft et al. 2002).Several studies indicate that online

bankers are the most profitable and wealthiest segment to banks (Mols, 1998; Robinson, 2000;

Sheshunoff, 2000). On this basis, no bank today can underestimate the power of the online

channel. Luxman (1999) for instance estimates that in the near future the online channel

reinforces its importance especially in the countryside, where banks have closed many branches.

However, there is no supporting evidence on this regional issue. Without the possibility of

managing banking affairs directly from home or office, customers easily perceive troubles in

managing their financial affairs such as paying bills. As noted, online banking offers many

benefits to banks as well as to customers. However, in global terms the majority of private

bankers are still not using online banking channel. There exist multiple reasons for this. To start

with, customers need to have an access to the Internet in order to utilize the service. Furthermore,

new online users need first to learn how to use the service (Mols et al., 1999). Second, nonusers

often complain that online banking has no social dimension, i.e. you are not served in the way

you are in a face-to-face situation at branch (Mattila et al., 2003). Third, customers have been

afraid of security issues (Sathye, 1999; Hamlet and Strube, 2000; Howcroft et al., 2002).


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However, this situation is changing as the online banking channel has proven to be safe to

use and no misuse has been reported by the media. Traditional banks have been the vanguard of

online banking channel development and control lions share of the total market. However, the

online banking channel works without having an extensive branch network, at least in theory. In

recent years we have witnessed the rise of pure online banks, but their impact on the whole

banking sector has been remote. Pure online banks often use other channels as well, such as

contact centers (both outbound and inbound), and some have even established physical presences

by establishing branch services. Quite many pure online players have suffered from achieving

sufficient customer base and thus have had to close their business down (Orr, 2001; Schneider,

2001). In this regard, Sievewright (2002) forecasts that in USA many pure online banks will

close down their business in the next five years.

Technology Acceptance Model

The technology acceptance model is an influential extension of Ajzen and Fishbeins

theory of reasoned action (TRA). It was introduced and developed by Fred Davis in 1986 (Davis

et al., 1989). TAM is a model derived from a theory that addresses the issue of how users come

to accept and use a technology. The model suggests that when users are presented with, for

instance, a new software package, a number of variables influence their decisions about how and

when they will use it. There are two specific variables, perceived usefulness and perceived ease

of use, which are hypothesized to be fundamental determinants of user acceptance. (Davis and

Arbor, 1989). TAM uses TRA as a theoretical basis for specifying the causal linkages between

the two key features: perceived usefulness and perceived ease of use, and users attitudes,

intentions and actual computer adoption behaviour. TAM is designed to apply to any type of

technology.

Perceived usefulness:

Perceived usefulness is defined as the degree to which a person believes that using a

particular technology will enhance his or her job performance. People tend to use or not to use an


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application to the extent they believe it will help them perform their job better - (Davis et

al.,1989). Phillips and colleagues defined perceived usefulness as the prospective adopters

subjective probability that applying the new technology from foreign sources will be

beneficial to his personal and/or the adopting companys well-being. (Phillips et al., 1994,

p. 18). Perceived usefulness explains the user's perception to the extent that the technology will

improve the user's workplace performance (Davis et al. 1989). This means the user has a

perception of how useful the technology is in performing his job tasks. This includes decreasing

the time for doing the job, more efficiency and accuracy.

Perceived ease of use:

This refers to the degree to which a person believes that using a particular technology

will be free of effort. Users believe that a given application is useful, but they may, at the same

time, believe that the technology is too hard to use and that the performance benefits of usage are

outweighed by the effort of using the application (Davis and Arbor, 1989). Phillips and his

colleagues defined perceived ease of use as the degree to which the prospective adopter

expects the new technology adopted from a foreign company to be free of effort regarding

its transfer and utilization. (Phillips et al., 1994, p. 18,). Perceived ease of use explains the

user's perception of the amount of effort required to utilize the system or the extent to which a

user believes that using a particular technology will be effortless. (Davis et al., 1989).

The theoretical importance of perceived usefulness and perceived ease of use as

determinants of user behaviour is indicated by several diverse lines of research. The impact of

perceived usefulness on technology utilization was suggested by the work of Schultz and Slevin

(1975) and Robey (1979), cited by (Davis and Arbor, 1989). Davis (1989) conducted numerous

experiments to validate TAM by using perceived ease of use (PEOU) and perceived usefulness

(PU) as two independent variables and system usage as the dependent variable. He found that PU

was significantly correlated with both self-reported current usage and self-predicted future usage.

PEOU was also significantly correlated with current usage and future usage. Overall, he found

the PU had a significantly greater correlation with system usage than did PEOU. Further


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regression analysis suggested that PEOU might be an antecedent of PU rather than a direct

determinant of system usage. That is, PEOU affects technology acceptance indirectly through

PU. (Ma and Liu, 2004). The technology acceptance model proposes that perceived ease of use

and perceived usefulness predict the acceptance of information technology (Ma and Liu, 2004).

The technology acceptance model (TAM) is specifically tailored for modelling user

acceptance of information technology. The goal of the model is to provide an explanation of the

determinants of computer acceptance by tracing the impact of external factors on internal beliefs,

attitudes and intentions (Davis et al. 1989) cited by (Phillips et al., 1994, p. 16). TAM is a

valuable tool for predicting attitudes, satisfaction, and usage from beliefs and external variables

cited by (Algahtani & King, 1999, p. 277).

Organizations invest in information systems for many reasons, for example cutting costs,

producing more without increasing costs, improving the quality of services or products (Lederer

et al., 1998). It has been noted that users attitudes towards and acceptance of a new information

system have a critical impact on successful information system adoption (Davis, 1989;

Venkatesh and Davis, 1996; Succi and Walter, 1999). If users are not willing to accept the

information system,

it will not bring full benefits to the organisation (Davis, 1993; Davis and Venkatesh, 1996). The

more accepting of a new information system the users are, the more willing they are to make

changes in their practices and use their time and effort to actually start using the new information

system (Succi and Walter, 1999). A system that satisfies users needs reinforces satisfaction with

the system and is a perceptual or subjective measure of system success. Similarly, usage of a

system can be an indicator of information system success and computer acceptance in some

cases. Success is not necessarily dependent of the technical quality of the system (Ives et al.,

1983). Using the system is connected with the effectiveness of the system systems that users

regard as useless cannot be effective. Therefore it is important to find out the reasons why peopledecide to use or not to use information system (IS). This knowledge will help both systems

designers and developers in their work (Mathieson, 1991). One of the most utilized model in

studying information system acceptance is the technology acceptance model (TAM) (Davis et


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al., 1989; Mathieson, 1991; Davis and Venkatesh, 1996; Gefen and Straub, 2000; Al-Gahtani,

2001) in which system use (actual behaviour) is determined by perceived usefulness (PU) and

perceived ease of use (PEOU) relating to the attitude toward use that relates to intention and

finally to behaviour. According to DeLone and McLean (1992) system use as the dependent

variable is acceptable, if system usage is not compulsory.

Although the TAM has been tested widely with different samples in different situations

and proved to be valid and reliable model explaining information system acceptance and use

(Mathieson, 1991; Davis and Venkatesh, 1996,), many extensions to the original TAM have been

proposed (e.g. Venkatesh and Speier, 1999; Venkatesh and Davis, 2000; Venkatesh et al., 2002;

Henderson and Divett, 2003; Lu et al., 2003). Venkatesh and Davis (2000) extended the original

TAM by introducing the second generation of the model labelled TAM2 to explain how

subjective norms and cognitive instrumental processes affect perceived usefulness and

intentions. TAM is based on the theory of reasoned action (TRA) (Fishbein and Ajzen, 1975;

Ajzen and Fishbein, 1980), which is concerned with the determinants of consciously intended

behaviours (Ajzen and Fishbein, 1980; Davis et al., 1989). Although the TAM and the TRA

share many issues they have some considerable differences. The first difference is that according

to TRA beliefs are bound to context and hence they can not be generalised. Contrary to that,

TAM states that PEOU and PU are issues that have an effect on acceptance of all information

systems. The other significant difference is that in TRA all beliefs are summed together, but in

the TAM both beliefs are seen as distinct constructs. Modelling each belief separately allows

researchers to better trace influences of all of the affecting factors on information systems

acceptance (Davis et al., 1989).

TAM has been tested in many studies (see, for example, Davis, 1989; Davis et al., 1989;

Mathieson, 1991; Adams et al., 1992; Davis, 1993; Segars and Grover, 1993; Taylor and Todd,

1995), and it has been found that TAMs ability to explain attitude toward using an information

system is better than other models (TRA and TPB) (Mathieson, 1991). These studies have found

that TAM consistently explains a significant amount of the variance (typically around 40

percent) in usage intentions and behaviour. The use of an information system has been

understood in many studies as the user acceptance of the information system in question (Davis


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et al., 1989; Davis, 1993; Al-Gahtani, 2001). In other words the use of information system acts

as an indicator for information systems acceptance.

The research model

Based on the literature review, a model indicating the acceptance of online banking was

developed. The model consists of six factors that are assumed to have an effect on acceptance of

online banking. TAM posits that Perceived Usefulness(PU) is a significant factor affecting

acceptance of an information system (Davis et al., 1989). Davis defined PU as the degree to

which a person believes that using a particular system would enhance his or her job

performance (Davis, 1989).

According to TAM Perceived Ease of Use (PEOU) is a major factor that effects

acceptance of information system (Davis et al., 1989). PEOU is defined as the degree to which

a person believes that using a particular system would be free of effort (Davis, 1989). Hence an

application perceived to be easier to use than another is more likely to be accepted by users.

Enjoyment refers to the extent to which the activity of using a computer is perceived to

be enjoyable in its own right (Davis et al., 1992). PU can be seen as an extrinsic motivation

whereas Perceived Enjoyment (PE) as an intrinsic motivation to use information systems.

The amount of information consumers have about online banking has been identified

as a major factor impacting the adoption. According to Sathye (1999) while the use of online

banking services is fairly new experience to many people, low awareness of online banking is a

major factor in causing people not to adopt online banking.

The importance ofsecurity and privacy to the acceptance of online banking has been

noted in many banking studies (Roboff and Charles, 1998; Sathye, 1999; Hamlet and Strube,

2000; Tan and Teo, 2000; Polatoglu and Ekin, 2001; Black et al., 2002; Giglio, 2002; Howcroft

et al., 2002). Roboff andCharles (1998) found that people have a weak understanding of online

banking security risks although they are aware of the risks. Furthermore, they found that

consumers often rely that their bank is more concerned about privacy issues and protect them.

Finally they argue that although consumers confidence in their bank was strong, their


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confidence in technology was weak (see also Howcroft et al., 2002). As the amount of products

and services offered via the Internet grows rapidly, consumers are more and more concerned

about security and privacy issues.

The importance of a decent Internet connection and its quality was raised focus group

interview. Also Sathye (1999) used Internet access as one of the factors affecting the adoption of

online banking in her research. Without a proper Internet connection the use of online banking is

not possible.

Perceived usefulness

Perceived ease of use

Perceived enjoyment

Information on Online

banking

Security and Privacy

Quality of internet

connection

Online

banking

Use


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CHAPTER III

RESEARCH METHODOLOGY


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RESEARCH METHODOLOGY

Definition of variables

INDEPENDENT VARIABLES

Perceived usefulness: It is defined as the degree to which a person believes that using a

particular system would enhance his or her job performance. According to Technology

acceptance model(TAM) it is a significant factor affecting acceptance of an information system.

Perceived Ease of Use: It is defined as the degree to which a person believes that using a

particular system would be free of effort, which is another major factor that affects acceptance of

information system. An application perceived to be easier to use than other is more likely to beaccepted by users.

Perceived Enjoyment: It refers to the extent to which the activity of using a computer to be

enjoyable in its own right. It is an intrinsic motivation to use information systems. It correlates

positively with time.

Information about online banking: The information the consumers have about online banking

has been identified as a major factor impacting the adoption. Low awareness of online banking is

a major factor in causing people not to adopt online banking.

Security and Privacy:privacy and security were found to be significant obstacles to the

adoption of online banking. The reason is that people are having a weak understanding of online

banking security risks although they are aware of these risks. Consumers confidence in their

bank was strong, but their confidence in technology was weak.

Quality of Internet connection: internet access is also one of the important factors affecting

adoption on online banking.


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General Objective

To determine the effect and its extend, of factors affecting consumer acceptance of

online banking.Specific Objectives

To determine the effect of perceived usefulness on online banking use

To determine the effect of perceived ease of use on online banking use

To determine the effect of perceived enjoyment on online banking use

To determine the effect of information on online banking on online banking use

To determine the effect of security and privacy on online banking use

To determine the effect of quality of internet connection on online banking use

HYPOTHESES

Based on the literature given earlier, the following hypotheses have been formulated on the

anticipated relationship among the variables in the study.

1. H11: Perceived usefulness has a positive effect on consumer acceptance of online banking

2. H12: Perceived ease of use has a positive effect on consumer acceptance of online

banking

3. H13: Perceived enjoyment has a positive effect on consumer acceptance of online banking

4. H14: The amount of information a consumer has about online banking has a positive effect

on consumer acceptance of online banking

5. H15: Security and privacy has a positive effect on consumer acceptance of online banking

6. H16: The quality of internet connection has a positive effect on consumer acceptance of

online banking.

POPULATION

The population for the study was the customers who are using online banking services. The

population was vast, hence the sampling technique can be used instead of census due to time and

cost constraints.


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SOFTWARE USED:

The software statistical tool for social sciences (SPSS 17.0) has been used for the analysis

of the data. Functions like Regression, Correlation analysis of the data were used. These

functions have a specific value which helps in the interpretation of the results.

These specific values are given below:

In Regression function, the significant value or p value has been used as the parameter to analyze

the influence of independent variable on the dependent variable. The values should be below

0.05. This value is used for the accepting or rejection of the null hypothesis. If the p-values are

below 0.05, then the null hypothesis is to be rejected and the alternate hypothesis accepted. In

Correlation function, the main focus is on the values of the correlation coefficient. If the values

are more than 0.5, it is considered as highly correlated and if the values are lower than 0.5, it

indicates low correlation between the variables. If the values are 0.00, then it is considered that

there is no correlation between the variables.

Sample Size and sampling

It was decided to administer the questionnaire to only those consumers who have been

using online banking services. Sample size was decided was 210, and the sampling design used

is Non Probabilistic Sampling design rather than the Probabilistic sampling design

.


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CHAPTER IV

DATA ANALYSIS

AND

INTERPRETATION


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DATA ANALYSIS

The researcher distributed 235 questionnaires to the customers who agreed to participate

and 224 filled questionnaires were collected back from the customers of online banking.

Detailed examination of the data resulted in deletion of 14 samples, which were found invalid.

Thus, the final data set had 210 usable records from customers. The questionnaire consisted of

questions that were related to the background, possible factors affecting acceptance of use of

online banking services. Likerts five point scales ranging from strongly agree to strongly

disagree were used as a basis of questions. The questionnaire was developed and tested with a

focus group of banking professionals from the banking sector in previous TAM related research.

The focus group finally verified that the hypotheses developed might be the affective factors

explaining online banking acceptance. The use of online banking has been chosen as the

dependent variable in the model.

Hypothesis Testing

In this section researcher tries to test different hypothesis which are formulated on the bases

of the review of the literature. The testing of hypothesis is done by using different testing

methods these are Correlation and Regression. In this section researcher also tries to make out a

conceptual model on the bases of the results of the hypotheses which are under consideration and

the review of literature. This section presents the output of the hypothesis testing. The result of

the testing of each hypothesis is given under each hypothesis.


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Testing hypothesis 1

H1: Perceived usefulness has a positive effect on consumer acceptance of online

banking

For testing this hypothesis we are using regression as a method in which perceived usefulness is

considered as an independent variable and online banking use is considered as a dependent

variable.

TABLE: - showing the regression results between perceived usefulness and online banking

use

Inference:

The value of coefficient of determinant is obtained as 0.15. This explains that we can

explain the variation of the dependent variable with respect to the independent variable up to

15% using the regression equation. Since R=0.393 there exist a positive relationship between the

two variables.

Model Summary

Model R R Square Adjusted R Square

Std. Error of the

Estimate

1 .393a

.154 .150 1.21258

a. Predictors: (Constant), PERCEIVED USEFULNESS


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Inference:

The value of significance 0.000 states that, the change in the dependent variable due to the

independent variable is significant and not merely by chance.

The regression line that explains variation in the dependent variable customer satisfaction is

Y= 0.339+0.622X

Where, Y= Online banking use and X=Perceived usefulness

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) .339 .401 .845 .399

PERCEIVED

USEFULNESS

.622 .101 .393 6.156 .000

a. Dependent Variable: ONLINE BANKING USE


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H12: Perceived ease of use has a positive effect on consumer acceptance of online

banking

For testing this hypothesis we are using regression as a method in which perceived ease of use

is considered as an independent variable and online banking use is considered as a dependent

variable.

TABLE: - showing the regression results between perceived ease of use and online banking

use

Inference:

The value of coefficient of determinant is obtained as 0.052. This explains that we can explain

the variation of the dependent variable with respect to the independent variable up to 5.2% using

the regression equation. Since R=0.237 there exist a positive relationship between the two

variables.

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .237a

.056 .052 1.28091

a. Predictors: (Constant), PERCEIVED EASE OF USE


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Inference:



The regression line that explains variation in the dependent variable online banking use is

Y= 0.869+0.477X

Where, Y= Online banking use and X=Perceived ease of use

Coefficientsa

Model


Standardized

Coefficients


1 (Constant) .869 .542 1.602 .111

PERCEIVED EASE OF

USE

.477 .136 .237 3.516 .001



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H3: Perceived enjoyment has a positive effect on consumer acceptance of online

banking

The testing of this hypothesis is done with the help of regression which also helps to find

out the strength of the relationship between the variables. The results are shown in the table

shown below

TABLE: - showing the regression results between Online banking use and Perceived

enjoyment

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .432a

.186 .182 1.18924

a. Predictors: (Constant), PERCEIVED ENJ OYMENT

Inference:


the variation of the dependent variable with respect to the independent variable up to 18.2%

using the regression equation. Since R=0.432 there exist a positive relationship between the two

variables.


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Inference:

The value of significance 0.000 states that , the change in the dependent variable due to the



Y= 0.065+0.732X

Where, Y= Online banking use and X= Perceived Enjoyment

Coefficientsa

Model

UnstandardizedCoefficients

StandardizedCoefficients


1 (Constant) .065 .398 .165 .869

PERCEIVED

ENJOYMENT

.732 .106 .432 6.902 .000



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H4: The amount of information a consumer has about online banking has a positive

effect on consumer acceptance of online banking

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .145

a

.021 .016 1.30454

a. Predictors: (Constant), AMOUNT OF INFORMATION

Inference:




variables.


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Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) 1.959 .386 5.078 .000

AMOUNT OF

INFORMATION

.248 .118 .145 2.110 .036


The value of significance 0.036 shows that the change in the dependent variable due to the

independent variable is significant at 0.05 level

The regression line that explains variation in the dependent variable customer satisfaction is

Y= 1.959+0.248X

Where, Y= Online banking Use and X=Amount of information


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H5: Security and privacy has a positive effect on consumer acceptance of online

banking

Inference:




variables.

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .219a

.048 .043 1.28650

a. Predictors: (Constant), SECURITY AND PRIVACY


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Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 1.321 .451 2.930 .004

SECURITY AND

PRIVACY

.398 .123 .219 3.233 .001




The regression line that explains variation in the dependent variable online banking source is

Y= 1.312+0.398X

Where, Y= Online Banking Use and X=Security and Privacy


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H6: The quality of internet connection has a positive effect on consumer acceptance of

online banking

This hypothesis is tested with the help of Regression test to find out the strength of the

relationship also. The results are displayed in the table given below.

TABLE: - showing the regression results between quality of internet connection and online

banking use

Inference:




variables.

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .236a

.056 .051 1.28111

a. Predictors: (Constant), QUALITY OF INTERNET CONNECTION


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Coefficientsa

Model


Standardized

Coefficients


1 (Constant) 1.514 .364 4.162 .000

QUALITY OF

INTERNET

CONNECTION

.338 .096 .236 3.506 .001


The value of significance 0.001 states that the change in the dependent variable due to the



Y= 1.514+0.338X

Where, Y= Online banking use and X=Quality of internet connection


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TABLE showing the multiple regression results

Inference:


the variation of the dependent variable with respect to the independent variables up to 26.6%

using the regression equation. Since R=0.535 there exist a high positive relationship between the

dependent variables and the independent variables taken into consideration in this study.

Model Summary

Model R R Square Adjusted R Square

Std. Error of the

Estimate

1 .535 .287 .266 1.12721

Predictors: (Constant), PERCEIVED USEFULNESS, PERCEIVED EASE OF USE,

PERCEIVED ENJ OYMENT, AMOUNT OF INFORMATION, QUALITY OF

INTERNET CONNECTION, SECURITY AND PRIVACY


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ANOVAh

Model

Sum of

Squares df Mean Square F Sig.

6 Regression 103.622 6 17.270 13.592 .000f

Residual 257.931 203 1.271

Total 361.553 209

Predictors: (Constant), PERCEIVED USEFULNESS, PERCEIVED EASE OF USE,

PERCEIVED ENJ OYMENT, AMOUNT OF INFORMATION, QUALITY OF INTERNET

CONNECTION, SECURITY AND PRIVACY

Inference:

The value of significance is obtained as 0.000. This explains that the model

in this study is significant.

Coefficients a

Model


Standardized

Coefficients


(Constant) -.249 .530 -.469 .640

PERCEIVED

USEFULNESS

.814 .184 .514

4.399

.000

PERCEIVED EASE OF

USE

.195 .196 .097 .993 .322

PERCEIVED

ENJOYMENT

.582 .148 .343 3.923 .000

AMOUNT OF

INFORMATION

-.324 .145 -.189 -2.235 .026

QUALITY OF INTERNET

CONNECTION

.212 .096 .148 2.204 .029

SECURITY AND

PRIVACY

-.782 .248 -.429 -3.149 .002


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Perceived usefulness (t=4.4, p


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CHAPTER V

FINDINGS AND CONCLUSION


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Conclusion of the Research Outcomes

This research is conducted with an aim to find out any relationship between the Online

banking use and factors such as quality of internet connection, amount of information, perceived

usefulness, perceived ease of use, perceived enjoyment, security and privacy and gender. The

primary objective was to study the consumer acceptance of online banking in the light of

technology acceptance model, added with new variables derived from online banking acceptance

literature on one hand and from a focus group interview with bank managers on the other. The

model developed proposed that online banking acceptance can be modelled with the variables

derived from the TAM (PU and PEOU) and four other variables referring to perceived enjoyment

(PE), information on online banking, security and privacy, and the quality of the Internet

connection. In the results section the model was tested with 210 consumers and revised.

The results of the regression analysis conducted on the five factors indicate that PU, PE

and the quality of internet connection were found to be the most influential factors explaining the

use of online banking services. This finding refers to the fact that consumers use online banking

for the benefits it provides in comparison to other banking delivery channels. This finding is in

line with other TAM studies (e.g. Davis, 1989; Davis et al., 1989), which found that PEOU has

less impact on technology acceptance than PU. The second influential factor PE is similar to the

concept of perceived playfulness which consists of three parts: concentration, curiosity and

enjoyment (Moon and Kim, 2001). It was discovered that perceived playfulness had a significant

impact on the intention to use information system, hence perceived enjoyment which is an

intrinsic factor unlike other independent variables in the study, influence the use of online

banking. Third influential factor namely quality of internet connection supports the fact that

without proper internet connection the use of online banking is not possible.


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Contributions

The study makes a contribution to electronic banking literature by providing insights on the

factors that seem to affect online banking acceptance. The results hint that quality of internet

connection is a critical factor influencing the acceptance. Secondly, the article contributes to

the technology acceptance literature by suggesting that perceived usefulness (PU) as well as

perceived enjoyment (PE) were found to have significant effect on technology acceptance

(cf. Davis, 1989; Davis et al., 1989; Teo et al., 1999). Furthermore, we found that PU was

more influential than PEOU in explaining technology acceptance.

The results of the study provide managers information about the planning of online banking

Web sites and service selection. In the planning and development of online banking services,

software developers should pay attention to informative content that is above all perceived

useful and with relevant information and services. In the marketing process of online banking

services marketing experts should accentuate the benefits its adoption provides. Banks should

now concentrate in their advertising more to informative issues rather than in building only

brands with less informative advertisements.

Limitations and further research

Although the results can be considered statistically significant in most parts, the study has several

limitations that affect the reliability and validity of the findings.

The regression model developed had relatively low coefficient.

Although the sample size was quite large compared to sample sizes of other TAM studies,

and representative, it consisted of Indian consumers only. This has an effect on the

generalization of the findings.

TAM studies have found that PU and PEOU are not the only predictors of technology

acceptance. Legris et al. (2003) found that many TAM studies are not consistent or clear

and lack many significant factors that influence adoption. On this basis, our model might


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also suffer from the fact that for example subjective norms and other possible factors

influencing the acceptance of online banking were not included in the model.

These limitations pave the way to future studies. Furthermore, another interesting avenue for

further research could be a detailed study on online banking usage in firms. We should also

measure online banking acceptance with other possible factors derived from different sources of

literature.


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REFERENCES


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REFERENCES

1. Davis, F.D. (1993), User acceptance of information technology: system characteristics,

user perceptions and behavioral impacts, International Journal of Man-Machine Studies,

Vol. 38, pp. 475-87.

2. Tero Pikkarainen, Kari Pikkarainen Heikki Karjaluoto and Seppo Pahnila (2004).

Consumer acceptance of online banking: an extension of the technology acceptance

model, Internet Research, Volume 14 Number 3 2004 pp. 224235

3. Sathye, M. (1999), Adoption of Internet banking by Australian consumers: an empirical

investigation, International Journal of Bank Marketing, Vol. 17 No. 7, pp. 324-34

4. Howcroft, B., Hamilton, R. and Hewer, P. (2002), Consumer attitude and the usage and

adoption of home-based banking in the United Kingdom, The International Journal of

Bank Marketing, Vol. 20 No. 3, pp. 111-21.

5. Bradley, L. and Stewart, K. (2003), A Delphi study of the drivers and inhibitors of

Internet banking, The International Journal of Bank Marketing, Vol. 20 No. 6, pp. 250-

60.


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ANNEXURE


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Questionnaire

(The questionnaire is designed on the basis of the review of literature and taken from standard

questionnaire and measured on the scale of 5 likert scale)

Instructions: Please choose the option that you feel describes the statement most closely.

A) USE

1. I use online banking mainly

a) At home

b) At work

c) In a bank

2. On an average I use online banking -------- times a month

3. On an average I do -------- transactions at a time

4 .How often do you use the following online banking services?

1. Primary current accounts

a) Almost never

b) Rarely

c) Sometimes

d) Frequently

e) Almost always.

2. Credit based accounts

a) Almost never

b) Rarely

c) Sometimes

d) Frequently

e) Almost always.

3. Investment based accountsa) Almost never

b) Rarely

c) Sometimes

d) Frequently

e) Almost always


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4 .Insurance based accounts

a) Almost never

b) Rarely

c) Sometimesd) Frequently

e) Almost always

B) Internet connection

1. My internet connection is fast

a) Totally disagree

b) Disagree

c) Neutral

d) Agreee) Strongly Agree

2. My internet connection is reliable

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

C) AMOUNT OF INFORMATION

1. I have generally received enough information about online banking

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

2. I have generally received enough information about the benefits of using online banking.

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree


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3. I have generally received information about online banking from

a) a bank

b) a friend

c) Internetd) Another source

D) PERCEIVED USEFULNESS

1. Using online banking enables me to utilize banking services more quickly.

a) Totally disagree

b) Disagree

c) Neutral

d) Agreee) Strongly Agree

2. Using online banking improves my performance of utilizing banking services

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

3. Using online banking for my banking services increases my productivity

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

4. Using online banking enhances my effectiveness of utilizing banking services

a) Totally disagree

b) Disagreec) Neutral

d) Agree

e) Strongly Agree


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5. Using online banking makes it easier for me to utilize banking services

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

6. Overall, Using online banking is useful for me to utilize banking services

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

E) PERCEIVED EASE OF USE

1. Learning to use online banking is easy for me

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

2. I find it easy to do what I want to do in online banking

a) Totally disagreeb) Disagree

c) Neutral

d) Agree

e) Strongly Agree

3. My interaction with online banking is clear and understandable

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree


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4. I find online banking flexible to interact with

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

5. It is easy for me to be skilful at using online banking

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

6. Overall, I find online banking easy to usea) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

F) PERCEIVED ENJOYMENT

1. Using online banking is fun


c) Neutral

d) Agree

e) Strongly Agree

2. Using online banking is pleasant

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree


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3. Using online banking is positive

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

4. Using online banking is exciting

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

5. Using online banking is wisea) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

G) SECURITY AND PRIVACY

1. Using online banking is financially secure


c) Neutral

d) Agree

e) Strongly Agree

2. I trust in the ability of online banking in protecting my privacy

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree


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3. I trust in the technology online banking is using

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

4. I trust in online bank as a bank

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

5. I am not worried about the security in online banking

a) Totally disagree

b) Disagree

c) Neutral

d) Agree

e) Strongly Agree

6. Matters of security have no influence on using online banking

a) Totally disagree

b) Disagreec) Neutral

d) Agree

e) Strongly Agree

Gender

a) Female

b) Male

*THANK YOU*

technology assesment model

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