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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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 -
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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

807
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

808
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.

814
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