EXTENSION OF TECHNOLOGY ACCEPTANCE MODEL (TAM): A STUDY ON INDIAN INTERNET BANKING CONTEXT

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Anoop K.K. and Prof. Dr. K. Sreeranganadhan.” Extension of Technology Acceptance Model

(TAM): A Study on Indian Internet Banking Context”- (ICAM 2016)

International Journal of Management (IJM)

EXTENSION OF TECHNOLOGY ACCEPTANCE MODEL (TAM): A STUDY

ON INDIAN INTERNET BANKING CONTEXT

Anoop K.K.

Research Scholar, School of Management and Business Studies, Mahatma Gandhi University

Kottayam

Prof. Dr. K. Sreeranganadhan

Director, School of Management and Business Studies

Mahatma Gandhi University, Kottayam

ABSTRACT

Internet banking plays significant role in the development of banking business in our

country. An application of electronic service brings predominant changes in the way of doing

banking transactions. In simpler terms, internet banking refers to banking through bank’s

website with the help of internet connection. Internet banking provides lot of benefits to the

customers as well as the banks. Internet banking provides different kinds of services to the

customers in the form checking balances, account statement, pay utility bills etc...

The purpose of present study is to identify the reason for adoption of internet banking in

Kerala. The proposed study will be in empirical nature. The required data for the study will

be collected from various pockets from Kerala. The prime objective of the study is to examine

the factors associated with net banking adoption.

Key word: Internet banking, Adoption, TAM model, PEOU, PU

Cite this Article: Anoop K.K. and Prof. Dr. K. Sreeranganadhan. Extension of Technology

Acceptance Model (TAM): A Study on Indian Internet Banking Context. International

Journal of Management, 7(2), 2016, pp. 802-814.

http://www.iaeme.com/ijm/index.asp

1. INTRODUCTION

It is evident from the literature service sector have contribute a large share of profit in the last decade

with the help of superior technology which create new business opportunities. The progress of any

economy largely depends on the financial system of that country. Banking system is considered to be

the engine for economic as well as financial growth. Technology plays significant role in the overall

performance of banking industry. The evolutions of internet banking has basically changed the

traditional ways that banks use in conducting their business and the way customers execute their

banking transactions (Eriksson et al., 2008).It facilitates the customers to do most of the banking

transactions through online without visiting physical branch. Internet banking provides bundle of

benefits to the customers as well as the banks. From the perspective of customer, it is highly cost

effective, convenient way of doing banking etc or banks; it helps to save the cost of building,

appointing new staffs etc…Internet banking is useful tool in banking system that offers less waiting

time and is more convenient than traditional branch banking (Pikkarainen et al., 2004). Analysis of the

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existing materials revealed that, there were only few studies happened in the area of internet banking in

Kerala context, particularly on the matter of adoption.

Hence the problem of this study is to identify the factors affecting internet banking adoption

among the customers of the bank. This article presents an extended technology acceptance model

developed with an idea to examine the factors which influence the choice to use internet banking. In

this study, the researcher tests whether TAM is a clear indicator of acceptance of technology in internet

banking context.

2. RESEARCH QUESTION

What are the factors affecting internet banking adoption among the customers?

Is Technological Acceptance Model (TAM) shows clear indicator of acceptance of

technology in the context of internet banking?

3. OBJECTIVES OF THE STUDY

The proposed study mainly concentrated on the following objectives;

To examine the factors influencing the adoption of internet banking among the customers.

To develop a new model for internet banking by applying extended TAM model.

4. HYPOTHESES OF THE STUDY

H1: Perceived usefulness has a positive effect on internet banking adoption

H2: Perceived ease of use has a positive effect on internet banking adoption

H3 Relative advantage has a positive effect on internet banking adoption

H4: Compatibility has a positive effect on internet banking adoption

H5: Self-efficacy has a positive effect on internet banking adoption

5. LITERATURE REVIEW

It is very important to discuss relevant previous works in the related areas of the subject to find out and

to fill up the research gap, if any. In this section, the researcher presents relevant literature in internet

banking scenario in both national and global level.

5.1. Technology Acceptance Model

The theory Technology Acceptance Model (TAM) was firstly introduced by Davis (1989) for job

contexts are considered to be the famous model theoretical framework of information technology

acceptance. This is assumed to be the best ever model in technology acceptance for the following

reasons. First, this theory can be applicable to all information technologies contexts (David, Bagozzi &

Warshaw, (1989), Pikkarainen et al., (2004). The second reason is, TAM always explains about 40%

variance both in usage intentions and behavior (Pikkarainen et al., (2004) Davis and Venkatesh ( 2000).

Besides, Yousafzai et al., (2010) made a comparison between other technology acceptance theories

such as Theory of reasoned Action (TRA), Theory of Planned behaviour (TPB) and ended with a

conclusion that TAM is the better predictor of behavioural intention and superior to other models.

Fourth, according to Ericksson, Kerem and Nilsson (2005) this model is suitable to study the behaviour

of online shopping customers and also appropriate in the case of online banking scenario. Lastly, it is

clear from the literatures this model is heavily applied in developing countries (Reid & Yair, 2008) and

India is not an exception to this.

Technology Acceptance Model has its roots in Theory of Reasoned Action which Davis (1989) as

well as Davis et al., modified to elucidate the adoption of information technology. The TAM describes

that an individual’s beliefs with regard to his/her intention to use particular technology. TAM focus on

two theoretical constructs namely, perceived usefulness (PU) and perceived ease of use (PEOU). Both

variables having influence on intention to use the system, it may be positive or negative that’s depends

on the context.



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5.2. Perceived usefulness (PU)

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

performance (Davis et al., 1989)

Shih (2004) defined perceived usefulness of e-shopping as the degree to which an individual

believes that trading on the internet would enhance the effectiveness of his or her shopping.

5.3. Perceived ease of use (PEOU)

Degree to which a person believes that using a particular system would be free from effort (Davis et al.,

1989).

In relation to e-commerce perceived ease of use is generally related to the navigational facilities of

the websites. Hence as the navigation around the site is getting better, the use of the site is getting

easier (Van der Heijden et al., 2000).

Finally, in TAM, an individual’s intention to use a system is proposed to be a precursor of actual

usage (Venkatesh & Davis 2000; Vijayasarathy, 2004). The informational and purchasing related

nature of the online transaction process, makes the description of the consumers’ behaviour by the

‘intention to use’ construct, rather incomplete and unclear. TAM postulated that user acceptance of a

new technology is determined by their behavioural intention to use the systems which can be jointly

explained by user’s perception about the technologies usefulness and attitude towards use (figure 1).

Attitude is jointly influenced by two behavioural beliefs; perceived usefulness and perceived ease of

use. External variables such as tasks, user features and organizational factors are expected to influence

technology acceptance behaviour indirectly by affecting perceived usefulness and perceived ease of use

(Szajna, 1996).

TAM model, Davis, Bagozzi & Warshaw (1989).

Figure 1. Technology Acceptance Model (TAM)

6. EXTENDED MODEL

TAM has emerged as powerful and reliable model for predicting customer intention to use a particular

system and it also robust for explaining the user behavioural intention. Many researchers have studied

TAM with additional variables. Among these Venkatesh and Davis made second version of TAM

which incorporates new variables like subjective norm, Voluntariness and cognitive instrument process

(Yu et al., 2005; Cao & Mokhtarian, 2005).

Perceived

usefulness

(PU)

Perceived ease

of use (PEOU)

External

variables Actual

system use

Behavioral

Intention to

use

Attitude

toward using



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Table. Research based on Extended TAM approach

Research

Additional variables added to

TAM New Findings

Moon & Kim (2001) Perceived playfulness

The study found that Perceived

ease of use is much related to

perceived playfulness.

Furthermore, perceived

playfulness has a strong

influence on attitude and

behavioural intention.

Mathieson et al. (2001) Perceived user resources

It is clear that, perceived

resources influence users’

intention to use an information

system. This is considered to be

the powerful predictor of TAM.

Chen et al. (2002)

Compatibility

The results of the study indicate

that

Compatibility is the significant

predictor of consumer attitude

towards using virtual stores. The

outcome of the study also

revealed compatibility has

positive influences on virtual

stores.

Gefen et al. (2003)

Familiarity, Disposition, and

Trust

The study recommend that

Familiarity and trust are the

solitary predictor of purchasing

intentions for potential

customers, while repeat

customers are influenced by

both trust and useful.

Klopping & McKinney (2004) Task-technology fit (TTF)

In this research, TTF positively

affects perceived usefulness,

ease of use and behavioural

intention to use the system,

Vijayasarathy (2004)

Compatibility, Privacy,

Security, Normative beliefs, and

Self-efficacy

The outcome of the study state

that, compatibility and security

are the important predictors of

attitude toward online shopping,

but privacy is not. Moreover,

normative beliefs and self-

efficacy powerfully influence

intention to use online shopping.



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Research

Additional variables added to

TAM New Findings

Porter & Donthu (2006)

Demographic variables (age,

education, income, and race)

and Perceived access barriers.

The researchers conclude that,

age, education, income and race

are found to be associated

differentially with certain

beliefs about the internet and

that these beliefs mediate

consumer attitudes toward use

of the internet. Perceived access

barriers also have a significantly

negative effect on attitude.

Schepers & Wetzels (2007) Subjective norm

The researcher found that,

subjective norm has a

significant influence on

perceived usefulness and

behavioural intention to use.

Wu et al. (2007)

Individual factors (computer

self-efficacy, computer

enjoyment), internal factors

(subjective norm, management

support, internal computing

support and training), External

factors (external computing,

support and training, network

externality), and System factors

(task-technology fit).

The work done by Wu et al.,

found that Perceived usefulness,

ease of use, and computer

enjoyment all directly influence

actual usage.

7. ADOPTION STUDIES

Sathye (1999) conducted a research work in Australia with the purpose of knowing the

internet banking adoption among them. The major findings of his study were unawareness and

lack of security concern is the reason for non-adoption internet banking.

Polatoglu and Ekin (2001) in their study found factors affecting internet banking adoption.

These factors includes, relative advantage, complexity, perceived risk, type of group, type of

decision, observability, trial ability and marketing effort.

Karjaluoto et al. (2002) they found prior experience to handle the technology and attitudes

towards computer are the most powerful factor influencing internet banking adoption. Hence

the major outcome of the study is to educate the customers on the usage of both computer and

internet.

Erickson et al., (2005) found that, perceived usefulness is the main reason to the customer

adoption of internet banking. The study was formed with the help of TAM theory.

8. RESEARCH GAP

After having an extensive review of literature, it was observed that though there was many studies were

conducted in abroad regarding the factors influencing the adoption of internet banking using

Technology Acceptance model ( TAM) but there exist only very few studies happened in the Kerala

scenario . Another reason for carried out this study is there were very few studies have made with a

frame work of TAM model even though it is a powerful predictor of behavioural intention to use

particular system. Additionally, this model (TAM) widely applied in other areas like online shopping



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and e-commerce but in online banking context there were only few studies exist so far. All these reason

led me to adopt TAM model in this research work.

Conceptual Research Model

Source: Based on literature review

9. RESEARCH VARIABLES

Perceived ease of use

Perceived usefulness

Relative advantage

Compatibility

Self-efficacy

Table Operational definition of the variables selected for the study

Variable Author Definition

Perceived ease

of use

Davis et al., 1989

“Degree to which a person believes that using a particular

system would enhance his or her job performance”

Perceived

usefulness

Davis et al., 1989

“Degree to which a person believes that using a particular

system would be free from effort “

Compatibility Rogers, 1983;

Tornatzky

Compatibility with personal characteristics is positively

related to innovation adoption since the more compatible the

less the uncertainty to the potential adopter

Relative

advantage

Rogers, 1983 The degree to which innovation is perceived to be better than

idea it supersedes

Self-efficacy Bandura, 1977,

1986, 1997

Self-efficacy refers to an individual's belief in his or her

capacity to execute behaviors necessary to produce specific

performance attainments

10. METHODOLOGY

In accordance with Hussey and Hussey (1997) the term methodology is concerned with the reasons for

collecting data, kinds of data, sources of data, time of collecting data, processes and tools for collecting

Self-efficacy

Perceived ease of use

(PEOU)

Perceived usefulness

(PU)

Compatibility

Adoption of Internet Banking



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data and the analysis of data. The present study is an empirical in nature based on survey method. Both

primary and secondary data are used in this research. Primary data were collected from the customers

from the selected public sector and private sector banks in Kerala, India. Secondary data are gathered

from the journals, magazine, records and annual reports.

11. RESEARCH DESIGN

Kerlinger (1986) defines research design as a plan, structure and strategy of investigation so conceived

as to obtain answers to research questions or problems. The proposed employed three types of research

designs namely, exploratory, descriptive and explanatory design (Cooper & Schindler, 2001). Initial

stage researcher used exploratory design in order to discover exhaustive literature available in the study

area. In the second level, researcher adopted descriptive research design for the reason of describing the

sample profile of the respondents. Finally, explanatory design was undertaken for establishing

meaningful relationship with the selected variables for the study.

12. QUESTIONNAIRE

In order to collect primary data, the researcher designed a well-developed questionnaire with different

sub-sections. The first section deals with the demographic profile of the sample respondents such as

age, sex, educational qualification and occupation etc... The next section talks about the banking habit

of the customers followed by questions relating to internet banking and its usage level. The last section

of the questionnaire talks about reasons for internet banking adoption among the customers using TAM

approach. The questionnaire was pre-tested among 30customers drawn from different background. The

reliability and validity of the questionnaire also checked and it was above 0.70 (Cronbach’s alpha).

13. SAMPLING AND COLLECTION OF DATA

Crimp et al., (1995)113 observed that sample size anything larger than 30 and below 500 is appropriate

for the research methods. The researcher has adopted convenience sampling technique for collecting

the primary data. Total 80 questionnaires were distributed and each of the responses was screened for

error and missing responses. After the filtering process was carried out 22 found to be as unusable.

Hence the total sample size for the study is 60.

14. RELIABILITY AND VALIDITY

The measurement accuracy of a multi item scale mainly depends on its reliability and validity (V.G

Sabu, 2014). Naresh K. Malhotra et al. (2011) explains reliability as the extent to which a scale

produces consistent results if repeated measures are made on the characteristic. In this study, cronbach

alpha is used to assess the reliability of the item scale which is considered to be the common measure

of scale reliability. The value above 0.7 indicates that the acceptable level of reliability of the

measuring scale is good. The face validity and content validity of the questionnaire is also checked

with the experts in this domain and made necessary modifications according to their suggestions.

15. STATISTICAL TECHNIQUE USED

Appropriate statistical tests were used to analyse the data. Descriptive statistics is used to discuss about

the profile of the internet banking users. Independent t test also performed in order to analyse the

significance of difference in group mean.

Frequency descriptive analysis

Pearson's chi-square test (χ2)

Factor analysis

Contingency table / Cross tabulation

Levene’s test

Correlation analysis



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16. DATA ANALYSIS & DISCUSSION

This section deals with the statistical analysis of collected data in order to satisfy the objectives

formulated. The Statistical Package for Social Sciences (SPSS 21.0) was used for the primary data

analysis.

17. PROFILE OF THE SAMPLE RESPONDENTS

The internet banking customers of Kerala are the universe considered for this particular study. In the

first stage, the entire population is divided in to three strata, namely urban, semi-urban and rural. The

distribution of sample respondents on the basis of age is given in the below table.

Table Age of the Respondents

Frequency Percent

Below 20 year 81 40.5

20-30 years 94 47.0

30-40 years 17 8.5

Above 40 years 8 4.0

Total 200 100.0

Source: Primary data

From the above table majority of the respondents belonging to the age group of 20-30 followed by,

below 20 years. Both these indicate that younger generations are the most targeted customers of

internet banking.

Table Gender of the Respondents

Frequency Percent

Male 111 55.5

Female 89 44.5

Total 200 100.0


The table 10.2, it is clear that, male sample respondents are more (55.5 %) and female respondents

are (44.5). It says that, males are most familiar with the use of internet banking.

Table Locality of the Respondents

Frequency Percent

Urban 87 43.5

Semi-urban 73 36.5

Rural 40 20.0

Total 200 100.0




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The above table discussed about the locality of the sample respondents. The result shows that, the

customers from urban area are 87%, Semi-urban (73 %) and Rural is 20 %.

Table Zone-Wise Distribution of the Respondents

Frequency Percent

North 70 100

Central 70 100

South 70 100

Total 200 100.0


It is very much clear that, the samples taken from above zones are equal. That is 70 sample

respondents were taken from each zone.

Table Educational qualification of the Respondents

Frequency Percent

Primary School 6 3.0

Secondary School 4 2.0

Graduate 85 42.5

Post Graduate/ Professional 105 52.5

Total 200 100.0


It can be seen that 100% of sample respondents belonging to high educational profile, possessing the

qualification level of graduation and above.

Table Occupation of the Respondents

Frequency Percent

Job in private sector 121 60.5

Student 49 24.5

Self employed 6 3.0

Business 2 1.0

Job in public sector 22 11.0

Total 200 100.0

Source: Primary Data



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In the above table, employment status is categorized in six segments namely job in private sector ,

Business, Self Employed, Student, job in public sector. The table indicates that, majority of the sample

respondents are working in private organizations (60.5 %) followed by students (24.5 %).

Table Monthly Income of the Respondents

Frequency Percent

Below Rs. 25,000 86 43.0

Rs. 25,000-35,000 73 36.5

Rs. 35,000-45,000 21 10.5

Rs. 45,000-55,000 7 3.5

Above Rs. 55,000 13 6.5

Total 200 100.0


From this table, it is clear that majority (86%) of the customers belonging to the income level of

below rupees 25000.

Table Respondents Experience in the use of Computer/Laptop

Frequency Percent

Yes 170 85.0

No 30 15.0

Total 200 100.0


The above table indicates that, most of the customers are experienced in the usage of computer

/laptop. It shows that, many of the sample respondents were skilled in handle the technologies.

18. INDEPENDENT TEST

Independent t test was performed in order to know whether there is any significant difference in mean

score of two groups.

19. FACTOR ANALYSIS

Table. Kaiser-Meyer- Olkin Measure of Sampling Adequacy.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .620

Bartlett's Test of Sphericity

Approx. Chi-Square 327.221

df 66

Sig. .000




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To find out the primary structure, the correlation matrix was initially examined to determine how

suitable it was for factor analysis. Factor analysis was performed with 12 statements related to adoption

of internet banking. The KMO value of the data was 0.620 which was greater than recommended

minimum of 0.6( Kaiser, 1974), indicating that the sample size was appropriate for doing factor

analysis, and significant Bartlett’s test of sphericity supported the use of factor analysis to filter

independent variables relating to internet banking adoption.

Table Communalities

Communalities

Initial Extraction

IBADPN very easy to conduct banking transactions PEUSE 1.000 .799

IBADPN manage account effectively PEUSE 1.000 .791

IBADTN easy for skillful at IBPEEASY 1.000 .842

IBADTN easy to use PEEASY 1.000 .682

IBADTN accomplish banking task quickly PEUSE 1.000 .781

IBADTN internet banking useful PEUSE 1.000 .769

IBADTN complicated to use PEEASY 1.000 .667

IBADTN use IB with help function SELF 1.000 .770

IBADTN use IB even changed bank SELF 1.000 .597

IBADTN more compatible with my lifestyle COMPATIBILITY 1.000 .579

IBADTN fits well with way I manage f und COMPATIBILITY 1.000 .777

IBADT fits with my working style COMPATIBILITY 1.000 .590

Extraction Method: Principal Component Analysis.

Source: primary data

From the above table, it is clear that, all the variables have the communalities of more than 0.5.

This means that all the variables have significant portion of the variance that contributes to the

common factors. As the communality is the sum of squares of the loadings of the variable is

contributing significantly, all are included for the analysis of the final data.

Varimax rotation (Table) was used to identify the underlying factors for adoption of internet

banking. Items with eigen values more than one were extracted and all the factor loadings greater than

0.5 were retained. 12 items yielded three factors explaining 72.033 % of variance shown in Table

(10.12)

All the variables extracted under group 1 are related to the usefulness of the system. Therefore,

factor 1 is termed as “perceived usefulness”. The factor perceived usefulness can be measured with

four statements such as easy to conduct banking transactions, managing account effectively etc…

The variables extracted under factor 2 are related to benefits of the system, so factor two is named

as “Relative advantage”. This item measured by two variables such as more convenient than physical

branch and more accessible than visiting a physical branch. The three variables extracted under factor 3

are related to the easy of using the system. This item named as “perceived ease of use” and this factor

is measured with the help of three statements. Fourth factor is loaded with two variables and this factor



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is named as “Self-efficacy” The next is factor 5 which talks about compatibility to handle the system

and this can be measured with the help of three variables.

Total Variance Explained

Component Initial Eigen values Extraction Sums of Squared

Loadings

Rotation Sums of Squared

Loadings

Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative

%

1 4.168 34.734 34.734 4.168 34.734 34.734 3.369 28.075 28.075

2 1.772 14.766 49.500 1.772 14.766 49.500 1.912 15.932 44.007

3 1.477 12.310 61.810 1.477 12.310 61.810 1.715 14.290 58.297

4 1.227 10.223 72.033 1.227 10.223 72.033 1.648 13.736 72.033

Extraction Method: Principal Component Analysis.


From the table it is very much clear that, observed significant value .673(Risk), .204 (PEOU),

Website (.225), convenience (.565), and perceived usefulness (.433). In the case of Risk, significant

level is .673 which is greater than the required significance level of .05. Hence we accept the null

hypothesis. That means there is no significant difference between Risk in both public and private

banks.

In the case of other variables like, PEOU, Perceived usefulness, Convenience, and website the

value is .204, .433, .565. .225 Respectively which is more than the required level of .05. Hence there is

no significant difference between mean score of the variables in both public and private banks.

20. RESULT OF MULTIPLE REGRESSION ANALYSIS

The multiple regression analysis was used to test the hypotheses. The estimated coefficients indicates β

(constant) is 2.477, βPEOU is -.231, βPU is 0.038, βRA is -.096, βSE is 0.336, βCom is 0.109. The

result shows that all five variables are not significant at 0.05 significance level (< 0.05) except self-

efficacy. This indicates that the independent variables (perceived ease of use, perceived usefulness,

perceived relative advantage, and compatibility) have a no influence on Internet banking adoption. The

variable self-efficacy shows significant relationship towards internet banking adoption.

21. FINDINGS AND CONCLUSION

It is evident from the survey and literature internet banking plays predominant role in the development

of banking system in our country. The major findings of the study were there is no significant

difference between different dimension of internet banking in both public and private commercial

banks. The study was based on the TAM model of technology acceptance which contributes two

variables for internet banking adoption among the customers. These variables includes, Perceived

usefulness and perceived ease of use. In order to strengthen the theoretical model new variables are

added to the existing TAM model (Website, Convenience, and Risk).

The study also proven that, TAM is the most widely used theory in technology acceptance

especially in the case of net banking. TAM describes the clearest indicator of acceptance of technology

in the context of internet banking.

The study also proposed a new theoretical model for measuring internet banking adoption among

the customers. The additional variables are drawn from the existing literatures.

The result of multiple regression analysis shows that self-efficacy is the most important predictor

of internet banking.



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So it can be concluded that, internet banking enables banking business more easy and it provides

convenient way of doing banking transactions. The major outcome of this study is there is no big

difference in the adoption of internet banking among the customers of both public and private banks.

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EXTENSION OF TECHNOLOGY ACCEPTANCE MODEL (TAM): A STUDY ON INDIAN INTERNET BANKING CONTEXT

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