The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
TECHNOLOGY ACCEPTANCE MODEL:
IS IT APPLICABLE TO USERS AND NON USERS OF INTERNET BANKING
T. Ramayah
Chairman, Operations Management
School of Management, Universiti Sains Malaysia
Tel: 04-6577888 Ext: 3889, Fax: 04-6577448
E-mail: ramayah@usm.my
Jasman J. Ma’ruf
Faculty of Economics, Universitas Syiah Kuala
Tel: 0651-54321, Fax: 0651-51014
E-mail: jasmanjm@yahoo.com
Muhamad Jantan
Deputy Dean, Postgraduate Research & Development
School of Management, Universiti Sains Malaysia
Tel: 04-6577888 Ext: 3343, Fax: 04-6577448
E-mail: mjantan@usm.my
Osman Mohamad
Chairman, Marketing Management
School of Management, Universiti Sains Malaysia
Tel: 04-6577888 Ext: 2317, Fax: 04-6577448
E-mail: osman@usm.my
ABSTRACT
Technology Acceptance Model (TAM) has been used extensively in research
that looks at the acceptance of new technology (Davis, 1989; Venkatesh,
1996). This paper looks at the applicability of TAM in predicting intention to
use internet banking among current users and future users. We begin with the
argument that the TAM model is more applicable in predicting intention to use
(adoption) and usage for users than non users of a particular technological
innovation. A survey of 180 bank customers (Users=136 and Non users=44)
showed that when both the groups were used in the analysis, about 24.1% of
the variation in the intention to use can be explained by perceived usefulness
and perceived ease of use. When the sample was split and analyzed separately,
39% of the variation in intentions among users can be explained whereas only
5.2% of the variation in intentions among non-users can be explained by
perceived ease of use and perceived usefulness. This lends support for our
argument that the TAM model is more useful in predicting intention to use
among users than non users. The research also confirmed the importance of
perceived usefulness which has been found to be a significant predictor in
most technology acceptance research with perceived ease of use showing no
significant effect on intention to use. Implications are further discussed.
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
INTRODUCTION
While it is difficult to directly measure IT contribution because of its hidden and intangible
benefits (En Mao & Palvia, 2001), researchers have developed other measures, such as
technology acceptance, which directly relates to IT usage. It is therefore important for the
implementers to fully understand the determinants of IT acceptance as they need to plan
effectively for it.
Technology Acceptance Model (TAM) (Davis, 1989; Davis, Bagozzi & Warshaw, 1989)
derived from the Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975) offers a
powerful explanation for user acceptance and usage bahaviour of information technology.
TAM is one of the most influential models widely used in the studies of the determinant of
IS/IT acceptance. Many previous studies have adopted and expanded this model which was
empirically proven to have high validity (Chau, 1996; Davis, 1989; Mathieson, 1991; Adams,
Nelson & Todd, 1992; Segars & Grover, 1993; Igbaria, 1992, 1995; Igbaria, Zinatelli, Cragg
& Cavaye, 1997; Jantan, Ramayah & Chin, 2001; Koay, 2002, Ramayah, Siron, Dahlan &
Mohamad, 2002).
Perceived
Usefulness
External
Variables
Attitudes
Towards Use
Intention
To Use
Actual
System
Usage
Perceived
Ease of Use
Figure 1: Technology Acceptance Model
TAM theorizes that an individual’s behavioral intention to adopt a system is determined by
two beliefs, perceived usefulness and perceived ease of use. Perceived usefulness is defined
as “the degree to which an individual believes that using a particular system would enhance
his or her productivity” while perceived ease of use is defined as “ the degree an individual
believes that using a particular system would be free of effort” (Davis, 1989). Between these
two, perceived ease of use has a direct effect on both perceived usefulness and technology
usage (Adams et al., 1992; Davis, 1989).
Davis (1989) has also found that there is a relationship between users’ beliefs about a
technology’s usefulness and the attitude and the intention to use the technology. However,
perceived usefulness exhibits stronger and more consistent relationship with usage than did
other variables reported in the literature. In addition, an individual may adopt a technology if
he or she perceives it as convenient, useful and socially desirable even though they do not
enjoy using the technology (Saga & Zmud, 1994). Thus, there might be a possibility of a
direct relationship between beliefs and intentions.
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
Subsequent research by Venkatesh (1996) refined the TAM suggesting that the mediating
effect of attitude could be excluded as empirical evidence found that the attitude element did
not fully mediate the effect of perceived usefulness on intention to use.
Perceived
Usefulness
External
Variables
Intention
To Use
Actual
System
Usage
Perceived
Ease of Use
Figure 2: Refined Technology Acceptance Model (Refined TAM)
In Malaysia, the refined TAM model was used by Jantan, Ramayah & Chin (2001) to study
the various factors influencing personal computer acceptance by small and medium sized
companies. Basyir (2000) replicated TAM model to study the various factors associated with
acceptance of Internet shopping behavior. Fok (2001) adopted TAM that explicitly
incorporates self-efficacy and its determinants as factors that affect perceived ease of use,
perceived usefulness and the use of the Internet. Wong (2001) extended the refined TAM into
examining the impact of extrinsic and intrinsic motivational factors in influencing
individual’s acceptance of Internet job search. On the other hand Koay (2002) used the TAM
model to measure receptiveness of E-banking by Malaysian consumers. Ramayah et al. used
the basic TAM model to predict technology usage amongst SME owners/managers by
including three demographic variables such as age, education level and gender as predictors.
While there are some convergent results from the IT acceptance research, the effects of some
determinants remain debatable. While most researchers have found perceived usefulness to
be a key determinant in IT acceptance, there has been mixed results for the perceived ease of
use construct. This is particularly evidenced in the researches of Adams et al. (1992), Hu et
al. (1999), Igbaria et al. (1995) and Ndubisi et al. (2001).
Although the TAM literature reveals that certain inconsistencies exist but they are rarely dealt
with clearly (En Mao & Palvia, 2001). So this research delves into one of the many
inconsistencies which may be explored to enrich the literature in the TAM research.
Therefore this study aims to test the applicability of TAM in predicting intention to use
internet banking among current users and future users. We begin with the argument that the
TAM model is more applicable in predicting intention to use (adoption) and usage for users
than non users of a particular technological innovation. This study attempts to answer the
following questions: (1) What is the impact of perceived ease of use on intention to use
internet banking? (2) What is the impact of perceived usefulness on intention to use internet
banking. (3) Is TAM more applicable in predicting the intention to use among users or non
users of internet banking.
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
RESEARCH MODEL
For the purpose of our research we have used the TAM model (Davis, 1989) minus the
external variables. The research model is as shown in Figure 3. The reason why we stopped at
intention to use and exclude the actual usage is because the Internet banking is a new
phenomenon in Malaysia which has not caught on with the bank customers. Warshaw and
Davis (1985) defined intention as the degree to which a person has formulated conscious plan
to perform or not to perform some specified future behavior.
Perceived
Usefulness
Intention
to Use
Perceived
Ease of Use
Figure 3: Research Model
METHODOLOGY
A questionnaire was used to gather the information required for the study. The questionnaire
elicited information about demographic, perceived usefulness, perceived ease of use and
intention to use.
The questionnaire was developed based on researches conducted by Davis, Bagozzi and
Warshaw (1989), Basyir (2000), Ndubisi et al. (2001) and Polatoglu et al. (2001). The
Cronbach alpha obtained for the two measures were 0.70 for perceived usefulness and 0.69
for perceived ease of use. The intention to use measure was adopted from Davis et al. (1989).
Respondents were asked to rate their opinion using a 5-point Likert scale ranging from
1=Strongly disagree, 2=Disagree, 3=Neither disagree nor disagree, 4=Agree and 5=Strongly
agree, for perceived ease of use and perceived usefulness. Questions measuring intention to
use Internet banking used a 5-point Likert scale ranging from 1=Very Unlikely, 2=Unlikely,
3=Neither unlikely nor likely, 4=Likely and 5=Very Likely.
A factor analysis with varimax rotation was performed to validate whether the respondents
perceived the two constructs of perceived ease of use and perceived usefulness to be distinct
from each other. The results showed a two factor solution with eigenvalues greater than 1.0
and the total variance explained of 60.92%. KMO measure of sampling adequacy was 0.721
indicating sufficient intercorrelations while the Bartlett’s Test of Sphericity was significant
(Chi square=207.827, p< 0.01). The criteria used by Igbaria et al., 1995 (as cited by Teo,
2001) to identify and interpret factors were: each item should load 0.50 or greater on one
factor and 0.35 or lower on the other factor. Table 1 shows that result of the factor analysis.
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
These results confirm that each of these constructs is unidimensional and factorially distinct
and that all items used to measure a particular construct loaded on a single factor.
Table 1: Result of Factor Analysis
Items
PEU1
PEU2
PEU3
PEU4
PU1
PU2
Factor 1
Factor 2
0.801
0.663
0.594
0.728
0.187
0.095
0.012
0.315
0.309
0.070
0.845
0.857
Eigenvalue
2.524
1.131
Percentage variance
33.43
27.49
Cronbach Alpha
0.69
0.70
Mean
3.51
3.84
Standard deviation
0.52
0.64
* 2 items from Perceived Usefulness were dropped due to low anti image correlation
Sampling and Profile
A convenience sampling method was used, since it is against the Banking And Financial
Institution Act (BAFIA) to obtain a list of bank customers and contact numbers and addresses
from financial institutions, telephone interviews cannot be implemented. In order to ensure a
better response rate and co-operation from potential respondents, mail drop survey might not
be suitable as the response rate might be low. The questionnaire was distributed to selected
respondents of different banks, and the researcher collected the questionnaires directly from
the respondents. A total of 194 questionnaires were collected out of the total 230
questionnaires distributed. There were 14 incomplete questionnaires that were discarded.
Therefore, only 180 questionnaires were used for data analysis, thereby giving a response rate
of 78.26%.
Table 2 presents the demographic profile of the respondents who participated in this survey.
Whereas Table 1 shows the descriptives of the main variable of the study.
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
Table 2: Profile of respondents
Demographic
Gender
Male
Female
Frequency
85
95
Percentage
47.2
52.8
Age
< 20 years
21-30 years
31-40 years
41-50 years
> 50 years
5
96
57
17
5
2.8
53.3
31.7
9.4
2.8
Education level
Master Degree
Bachelor Degree
Diploma
High School or lower
24
90
30
36
13.3
50.0
16.7
20.0
Total Personal
Income Per Annum
Student/ Unemployed
< RM 10,000
RM 10,000-RM 24,999
RM 25,000-RM 49,999
RM 50,000-RM 74,999
RM 75,000-RM 99,999
RM 100,000-RM 149,999
> RM 150,000
7
9
47
70
25
14
6
2
3.9
5.0
26.1
38.9
13.9
7.8
3.3
1.1
Total Family
Income Per Annum
< RM 10,000
RM 10,000-RM 24,999
RM 25,000-RM 49,999
RM 50,000-RM 74,999
RM 75,000-RM 99,999
RM 100,000-RM 124,999
RM 125,000-RM 149,999
RM 150,000-RM 199,999
> RM 200,000
8
7
46
50
27
23
7
6
5
4.5
3.9
25.6
27.9
15.1
12.8
3.9
3.4
2.8
Position
Executive/ Top Management
Middle Management
Supervisory
Administrative/ Clerical
Technical
Others
39
56
21
22
21
21
21.7
31.1
11.7
12.2
11.7
11.7
Marital Status
Single
Married
Divorced
95
83
2
52.8
46.1
1.1
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
Table 3: Frequency of Internet Usage
Variable
Internet or
Computer Access
Yes
No
Frequency
177
3
Percentage
98.3
1.7
Internet Experience
Yes
No
174
6
96.7
3.3
Duration use
Internet or
Computer
< 6 months
0.5- 1 year
1-2 years
> 2 years
8
7
17
147
4.5
3.9
9.5
82.1
Frequency of use
Only once before
Few time before
Few time a month
Once a month
Once a week
Few times a week
Everyday
2
6
12
0
4
50
105
1.1
3.4
6.7
0
2.2
27.9
58.7
Table 4: Frequency of Internet Banking Usage
Variable
Know Internet
Banking websites
Yes
No
Frequency
139
40
Percentage
77.7
22.3
Internet Banking
Experience
Yes
No
44
136
24.4
75.6
Frequency of use
Only once before
Few time before
Once a month
Few times a month
Once a week
Few times a week
5
13
6
13
4
3
11.4
29.5
13.6
29.5
9.1
6.8
Hierarchical regression was used to test the hypotheses. We used a two step hierarchical
regression where perceived ease of use was entered in the first step. Perceived usefulness was
entered in the second step to see the additional variance explained in addition to that
explained by perceived ease of use. We performed three separate hierarchical regression, first
on both the users and non users combined (aggregate) , second only for the current users
(users) and third for current non-users (non-users). The adjusted R2 will be used to see if
there are differences in the variation explained between the three models.
Table 5 presents the result of the hierarchical regression. As can be seen from Table 5, the
adjusted R2 for both the groups combined (aggregate) shows a value of 0.24, whereas for the
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
current users, the adjusted R2 is 0.357 whereas for the non users, the adjusted R2 is 0.052.
The comparison shows that the TAM model is able to explain higher variation in intention to
use among currents users as compared to non users or when both the groups are combined.
This provides strong support for our earlier contention that the TAM model will be more
applicable to predict intention to use of current users than future users or non users.
Table 5: Results of regression analysis
Aggregate
Variable
Step 1
Step 2
Perceived ease of
use
0.314**
0.173*
Perceived
0.413**
usefulness
F value
19.372** 29.205**
2
Adjusted R
0.094
0.241
*
**
p<0.05, p < 0.01
Step 1
Users
Step 2
Non Users
Step 1
Step 2
0.331*
0.177
0.551**
0.170*
0.120
0.160*
4.690**
0.086
11.836**
0.357
3.823*
0.029
3.491*
0.052
In the aggregate model both the peceived ease of use and perceived usefulness are significant,
perceived usefulness is a partial mediator. For the users, perceived usefulness is significant
and perceived ease of use is not significant in the second step, which provides support for
perceived usefulness as a full mediator. In the third model for the non users, perceived
usefulness is significant and perceived ease of use is not significant in the second step, which
provides support for perceived usefulness as a full mediator.
DISCUSSION
Although the findings confirms the validity of the TAM model in explaining intention to use
Internet banking, there remains the issue of applicability of the model to both users and non
users. We have shown evidence that the TAM model is more applicable for predicting the
intention to use among current users.
This findings might be attributed to the nature of the technological innovation in question. As
Internet banking is still new, there are not many users at the present moment, this might be a
potential explanation for the anomally. It cannot be argued that the respondents do not know
the existence of Internet banking as 77.7% of the respondents have indicated that they were
aware of Internet banking websites.
The findings that perceived usefulness is more influential in determining technology use
confirms previous research such as Adams et al. (1992), Hu et al. (1999), Igbaria et al. (1995)
and Ndubisi et al. (2001), which have highlighted that perceived usefulness is more
significant in explaining computer usage. Thus it is important for designers to develop a
system that is perceived to be useful more than easy to use.
LIMITATIONS
There are however several limitations to this research. First, this research only looks at the
basic TAM model and not the extended TAM. Second, the sample was drawn from the
The proceedings of The International Seminar, Indonesia-Malaysia, “The Role of Harmonization of Economics
and Business Discipline in Global Competitiveness, Banda Aceh, Indonesia 14-15th October 2002
northern region of Malayisa only and may not represent the whole population. The third
limitation is that although the variables that we have forwarded may explain the variation in
intention to use, there are other variables that may also influence intention to use that have
been left out such as self efficacy (Bandura, 1977, 1982, 1986; Gist, 1987; Gist & Mitchell,
1992) and external variables such as computer skills, organizational support and social
pressure (Chang & Cheung, 2001)
CONCLUSION
While TAM is one of the most influential models used widely in the studies of the
determinant of IS/IT acceptance and which has empirically been proven to have high validity,
it must be used to a certain extent with caution as we have shown in this research. While
many previous researches have used technological innovation which have been widely
accepted, there is scarce research which delves into the acceptance in newer technologies and
innovations. Let alone separating the users and non users to study if there are differences. For
future researches we would suggest that they look at this new angle with more zest and see if
our notion is supported, for other types of technological acceptance and innovations.
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