ASSOCIATION BETWEEN STRATEGIC VALUES AND EBANKING ADOPTION IN IRANIAN BANKS
Dr. Mohammad Aghdassi, Dr. Lennart Persson, Roja Ghasemi
ABSTRACT
This paper attempts to understand strategic value of e-banking for Iranian banks and examine the causal
effect of perceiving e-banking as a value and its adoption.
We propose an e-banking adoption model that is identifying five factors that have been found to be
influential in the perception of strategic value of IT: performance support, operational support, managerial
productivity, and strategic decision aids. We also identified eight factors that influence electronic banking
adoption: organizational readiness, Infrastructural readiness, external dependency, Intangible pressure,
persuasive pressure, perceived ease of use, and perceived usefulness. Data are collected via a questionnairebased survey from Decision maker unit of Iranian Banks.
We can express the result of this study such that bank managers' perception through e-commerce is very
positive and effective in their adoption trend. This perception will help them accelerate the adoption
process.
Keywords: Perception, Adoption, Strategic value, Banking industry, DMU
Dr. Mohammad Aghdassi: Associate professor of Tarbiat Modarres University (Iran), aghdasim@modares.ac.ir
Dr. Lennart Persson: Assistant Professor of Luleå University of technology (Sweden), Lennart.Persson@ltu.se,
Roja Ghasemi: Master student of marketing and e-commerce: Luleå University of technology (Sweden) and Tarbiat
Modarres University (Iran), roja.gh@gmail.com
1. INTRODUCTION
“Among the myriad of computer- and telecommunication-based applications in the modern era, the advent
of e-commerce is having the biggest impact on organizations. E-commerce is changing the way
organizations perform their tasks, interact with customers and, in general, do their business. E-commerce
enables firms to reduce telecommunication costs, minimize warehousing expenses, and cut down the
distribution chain (Quaddus & Achjari 2005)”. “Technological developments particularly in the area of
information technology are revolutionizing banking industries (Sohail & Shanmugham 2003) ”.
E-commerce adoption in a bank means using all electronic means of data transmission and financial
transaction bank to bank, bank to customer and customer to customer. It is not always the matter of
monetary transaction sometimes banks grant a credit for someone or for some companies that is very
valuable in a business network. On the other hand E-banking means to provide facilities for staff to enhance
their efficiencies in offering bank services in a branch and also among branches and other banks all over the
world. Along with providing hardware and software facilities for customers such that they can work with
bank and use any services safety, without being there 24h a day. By adopting e-commerce, banks can work
as facilitators and accelerators for different industries and firms in several scales, small and large, so the
business world will find a new definition and the global market will become realistic. By the adoption of ecommerce their traditional ways of doing business has changed to a highly dynamic communication that
not only is cost-effective but also is revenue generating. In this regard many banks and financial institutions
are actively developing new way of transaction for themselves and their customers throughout the world
but still it is a very new market to enter and to work in. In spite of the many potential advantages of ebanking, its adoption by Iranian Banks remains limited or none. It is very limited in service channels and
very incomplete in offering e-banking services to customers. Because of this shortcomes, e-banking in Iran
causes many duplications in work processes and causes customer dissatisfaction. Does this mean that top
managers/ owners of Banks do not realize the strategic value of e-banking to their organization?
This study may identify main factors which facilitate the adoption process by managers and experts. This
study would be one of the first studies that examine the Iranian managers’ attitudes towards e-commerce
adoption in Iranian banks. The aim of this study is to examine the determinant factors of strategic value and
adoption of electronic commerce as perceived by managers and experts in Iranian banking industry using
the model which is proposed by Grandon and Pearson (2004) for e-commerce adoption. By using this
model of e-commerce adoption, we examined the causal relationship between determinant factors of
strategic value and adoption of electronic commerce as perceived by decision maker unit of Iranian Banks.
The observed research model consists of two main concepts: perception and adoption. Three factors have
been found to be influential in the perception of strategic value of information technologies in previous
researches: operational support, managerial productivity, and strategic decision aids, along with five factors
that influence electronic commerce adoption according to literature: organizational readiness, compatibility,
external pressure, perceived ease of use, and perceived usefulness. We hypothesized a causal link between
the perceived strategic value of electronic commerce and electronic commerce adoption. To validate the
research model, we collected data from decision maker unit of Iranian Banks, both governmental and
private, that contains Top managers, assistant, managers and co-assistants by using a survey.
2. LITERATURE
To reach e-commerce objectives, many studies were done to find the problem of e-commerce adoption in
different industries. In this regard, numbers of influencing factors were developed among them for example
in the study of (Quaddus & Achjari, 2005) Key factors impacting e-commerce are differentiated according
to their contribution to the success of e-commerce and to the locus of impact. Or in the study of (Hong &
Zhu 2005), which was for better positioning of firms when adopting e-commerce for revenue generation, a
conceptual model is developed upon technology diffusion theory, TOE framework, for assessing ecommerce adoption and migration, incorporating six factors in the technology-context (technology
integration, web spending, and web functionalities, electronic data interchange (EDI) use, outsourcing
partner usage, and perceived obstacles). It was also attempted to identify those factors which affect the
adoption of e-commerce among SMEs in the study of (Ching & Ellis 2004). These factors were described
within 3 in dependent variables:
1- Decision maker characteristics (Age, Education, and Cosmopolitanism)
2- Innovation characteristics (Relative advantage, Compatibility, Complexity, Cost effectiveness)
3- Environmental characteristics (Supplier incentives, Customer pressure, and Competitive intensity).
In the study of (Grandon & Pearson 2004) a research model was developed that suggested three factors that
had been found to be influential in the perception of strategic value of other information technologies:
operational support, managerial productivity, and strategic decision aids. They also identified four factors
that influence electronic commerce adoption: organizational readiness, external pressure, perceived ease of
use, and perceived usefulness. A causal link between the perceived strategic value of electronic commerce
and electronic commerce adoption is hypothesized. The model that they proposed then was completed by
adding compatibility to adoption factors as follows in figure 1:
Figure 1: Grandon and Pearson model of adoption
The factors influencing e-commerce adoption in this study have been extracted from several studies in IT
adoption. In addition the main structure of (Grandon & Pearson)'s model corresponds to the structure of
models, theories and frameworks such as TAM (technology acceptance model, TPB (theory of planned
behavior), Diffusion theory and TOE (Technology-organization-environment) framework. Consequently, it
was interesting to investigate (Grandon & Pearson)'s model as the research model of this study.
Therefore, this study is an investigation of causal effect of perception on e-banking adoption in banking
industry in Iran by using (Grandon et. al)'s adoption model which has been tested before in SMEs in US.
This study is a combination of two different studies that have been represented in an adoption model. The
former has been studied by Subramanian and Nosek (2001) and others (Barua et. Al 1995, Chan 2000)
while the latter has been investigated by Davis (1989) and others (e.g. Adams et. al 1992, Igbaria et. al
1997, Lederer et. al 2000 and Venkatesh et. al 1996) primarily through the technology acceptance model
(TAM).
3. METHODOLOGY
3.1 Sample
We targeted top managers, assistant, managers, co-assistants and experts of private and Governmental
banks in Iran. Co-assistants are those people who have high responsibility after managers in a certain
department in a bank. In this study Experts are those people who have more than 10 years work experience
and works sometime as managers' arm in implementing their decision but they have lower position than
managers and higher than other typical experts. Qualified persons were introduced to us by research and
development department in each bank. In this study 4 private banks and 2 Governmental banks were
chosen. Banks were chosen according to their accessibility and willingness of corporation.
3.2 Data Collection
We used a self-administered questionnaire method for collecting primary data. More importantly we were
replicating a study that had been done in United state with (Grandon et al. 2004)'s questionnaire. Hence in
this research we also replicated the same questionnaire. First, we deduced the questionnaire from the tables
that were presented in (Grandon et al. 2004) paper. The questionnaire then was translated into Farsi. A
covering letter was also provided for the first page. Two hundred questionnaires were distributed to
respondents and One hundred and sixty individuals completed the survey for a response rate of 80%. To
make such high response rate we were delivering questionnaires individually by making an appointment.
3.3 Questionnaire design
The questionnaire is designed to poll the opinion of bankers with respect to:
1- Their perception of e-commerce adoption in their banks as a strategic value.
2- Their attitude towards factors affecting e-commerce adoption in their banks.
Respondents were required to complete the survey that had the following major sections (see Appendix A).
 Eight demographic questions (respondent’s gender, age, education, years of work in present
position, years of work in present firm, department, position in the department, and department
responsibility ).
 Two questions about the technology in the organization (presence of web site, and utilization of ecommerce).
 Sixteen questions asking the extent to which e-commerce is perceived as contributing to strategic
value.
 Twenty-nine questions to measure the factors involved in e-commerce adoption.
A seven-point Likert scale (from strongly disagree to strongly agree) was utilized to measure the questions
about perceived strategic value and adoption of e-commerce.
3.4 Pilot testing
As this questionnaire was verified and used before, a pilot was not required.
However as it was translated into Farsi, we sent it out to 25 people, all experts and specialized in IT, EC
and Banking to make certain that no problem was raised during the translation process. Having the pilot
testing completed and feed back received, some changes were made through the questionnaire. We also
added seven questions according to the responders’ feedback:
i. E-banking should support linkage with other network suppliers
ii. Having skillful human resource is an important factor in our decision to adopt e-banking
iii. Having require under structure is an important factor in our decision to adopt e-banking
iv. Adopting e-banking is depends on infrastructure of organizational process
v. Having legal infrastructure readiness is an important factor in our decision to adopt e-banking
vi. Having telecommunication infrastructure readiness is an important factor in our decision to adopt
e-banking
vii. Having technical infrastructure readiness is an important factor in our decision to adapt e-banking
3.5 Reliability and validity
As we dispensed the questionnaires directly or indirectly to the qualified persons and had a chance to be
with them while they were filling out the questionnaires or a contact number to call them after distribution
we really did not face the subject error. For reducing the subject bias we tried to make sure that their
answers were considered confidential. Since the questionnaire was designed in a survey format we did not
face with observer error or the observer bias. Table 1 shows that alpha values range from 0.73 to 0.75 for
the perceived strategic value and 0.7 to 0.90 for the adoption of e-banking factors. “The scale reliabilities
are unusually good compared to the acceptable 0.7 level for field research (Nunnally, 1978)”.
Table 1 reliability analysis, alpha test
Variables
Organizational Support (OS)
Managerial Productivity (MP)
Decision Aid (DA)
Organizational readiness (OR)
Compatibility (CC)
External Pressure (EP)
Ease of Use (EU)
Perceived Usefulness (PU)
Reliability
0.75
0.73
0.74
0.74
0.81
0.70
0.84
0.90
4. RESULTS
4.1. Demographics and descriptive statistics
The 160 surveys were returned over an 8-week period. Results indicated that the DMU's of banks were well
educated, with over 50% holding a bachelor degree or a master's degree. The majority were male and
between 20 and 40 years of age. Table 2 shows other demographics.
Table 2: demographics graphics of responders
Variable
Governmental
Private
Classification of
Variable
Frequency
Percentage
Frequency
Percentag
e
Female
15
26.8%
35
34%
Male
38
67.9%
68
66%
Missing
3
5.3%
0
0
Diploma
11
19.6%
4
3.9%
Higher Diploma
4
7.1%
3
2.9%
Bachelor
30
53.6%
66
64.1%
Master
8
14.3%
26
25.2%
PhD
3
5.4%
2
1.9%
Missing
0
0
2
2%
20-30
16
28.6%
52
50.5%
31-40
23
41.1%
20
19.4%
41-50
6
10.7%
14
13.6%
51-60
1
1.8%
16
15.5%
Missing
10
17.8%
1
1%
Gender
Educational
Level
Age
4.2. Statistical analysis
The instrument used in this study was adopted from Grandon et al's (2004) study. In order to test the model,
a statistical analysis was conducted in two stages. The first step employed factor analysis to measure
whether the number of factors and loadings of items involved in the two main constructs (perceived
strategic value and adoption) conform to the proposed model. Since we were also interested in exploring
how the perceptions of strategic value influence the decision to adopt e-commerce, canonical analysis was
utilized in the second step. This technique involves developing a linear combination of independent
variables (strategic value variables) and dependent variables (adoption variables) to maximize the
correlation between the two sets (J.F. Hair, et al. 1998). This method was also conducted in the (Grandon et
al.)'s study to investigate the causal relationship between variables.
4.3. Factor analysis
4.3.1. Perceived strategic value construct
A factor analysis was run using SPSS 13. The factor analysis used principal components in order to extract
the maximum variance from the items. To minimize the number of items that have high loading on any
given factor, a varimax rotation was utilized. All items measuring the perception of strategic value of ecommerce were considered during the first run and by using the Kaiser Eigenvalues criterion over 1 (see
table 3); we extracted three factors that collectively explained 66.13% of the variance in all items in one
factor, organizational support. Hence, Organizational Support was broke up into three main factors,
Performance support, Operational Support and Relationship Support respectively, that each of them can be
considered to be a value of e-banking. Table 4 shows rotated component matrix of these three factors:
and Bartlett's
Test test
TableKMO
3: KMO
and Bartlett's
Kais er-Meyer-Olkin Measure of Sampling
Adequacy.
Bartlett's Tes t of
Sphericity
Approx. Chi-Square
df
Sig.
.687
315.895
28
.000
Table 4: components' loadings
(Organizational Support)
component
Factor 1
Factor 2
Factor 3
.114
.081
0.861
.151
.104
0.823
.128
.154
0.554
0.209
-.038
0.805
0.049
.146
0.771
0.295
.427
0.600
0.128
.228
0.849
0.145
-.002
0.849
OS2
OS3
OS1
OS8
OS4
OS5
OS6
OS7
Managerial productivity and Strategic Decision aids' item were both covering marginally 60% of the
cumulative variance of all items and remained the same as before. Therefore the model of the Perceived
Strategic Value factors of e-banking would be as shown in figure 2, in this figure also each factors loading
has been shown:
Performance
Support
Operational
Support
0.722
Relationship
Support
Managerial
Productivity
0.663
0.662
Perceived
Strategic Value
0.831
Strategic
Dec. Aids
0.764
Figure 2: PSV revised model after factor analysis
4.3.2. Adoption construct
As well as Perception variables, Adoption variables were also analyzed using principal component factor
analysis. By using the Kaiser Eigenvalues criterion, we extracted two factors that collectively explained
63.73% of the variance in all items in Organizational Readiness factor. Hence, Organizational Readiness
was broke up into two main factors, Organizational readiness and Infrastructural Readiness respectively,
that each of them can be considered to be influencing in e-banking adoption (Table 5).
Table 5: components' loadings
(Organizational Readiness)
component
Factor 1
Factor 2
-.040
OR4
.884
.069
OR2
.844
.140
OR3
.744
.202
OR1
.620
.112
OR6
.871
.145
OR5
.870
.043
OR7
.644
Using the Kaiser Eigenvalues criterion External Pressure was also broke up into three main factors,
Intangible Pressure, External Dependency and Persuasive Pressure that correspondingly explained 71% of
the cumulative variance of all items (Table 6).
Table 6: components' loadings
(External Pressure)
component
Factor 1
Factor 2
Factor 3
0.221
-0.053
EP5
0.837
-0.056
0.102
EP6
0.834
0.001
-0.055
EP1
0.893
0.170
0.424
EP4
0.633
-0.035
0.088
EP2
0.846
0.565
0.008
EP3
0.568
Other factors in adoption construct, Compatibility, Perceived Ease of Use and Perceived Usefulness, were
marginally covering 60%, 62 and 68% of the cumulative variance of all items in each factor respectively.
Therefore the model of factors affecting e-banking in Iran with related loading would be as shown in figure
3:
Organizational
readiness
0.709
Intangible
Pressure
Persuasive
Pressure
0.543
Adoption
0.723
Compatibility
0.626
Perceived
Usefulness
0.590
0.549
Ease of Use
External
Dependency
0.569
0.409
Infrastructural
Readiness
Figure 3: Adoption revised model after factor analysis
4.4. Canonical analysis
Considering the fact that perception was independent variable in the Grandon and Pearson's model and
adoption was the dependent one, we had to consider the impact of perception factors on adoption factors
and among several statistical tools and techniques the canonical analysis was the most suitable ones. The
“Canonical analysis is a multivariate statistical model that studies the interrelationships among sets of
multiple dependent variables and multiple independent variables. By simultaneously considering both, it is
possible to control for moderator or suppressor effects that may exists among various dependent variables
(Mahmood et al. 1993)”. In canonical analysis there are criterion variables (dependent variables) and
predictor variables (independent variables). “The maximum number of canonical correlations (functions)
between these two sets of variables is the number of variables in the smaller set (Green et al. 1966)”. In our
case, the number of variables for the perception of strategic value construct is five while the number of
variables in the adoption construct is eight (figure 4). Thus, the number of canonical functions extracted
from the analysis is five; i.e., the smallest set. Canonical correlation is a measure to interpret the canonical
functions. Canonical correlation size also gives the measures of overall model fit given.
PS
0.709
OS
0.543
IP
0.569
E
D
0.663
OR
0.722
0.409
R
S
MP
0.662
PSV
Adoption
0.590
0.831
0.723
DA
IR
C
PP
0.549
EU
0.764
0.626
PU
Figure 4: the revised model after factor analysis
In order to answer research question (Is there any association between factors of perceived strategic value
and adoption?) and to investigate the causal relationship between two set of variables and factors in the
model, we uses canonical correlation running STATISTICA 5.5A.
In order to test the significance of the canonical functions we followed the same path in Grandon and
Pearson's canonical analysis section that was also followed the guidelines given by Hair et al. They suggest
three different measures to interpret the canonical functions:
(a) The significance of the F-value given by Roy’s gcr (see table 7)
(b) The measures of overall model fit given by the size of the canonical correlations (see table 8); and
(c) The redundancy measure of shared variance (see table 9).
Table 7: multivariate test of significance
Note that the strength of the relationship between the canonical covariates is given by the canonical
correlation (Grandon et al. 2004). Even though the multivariate test of significance shows that the canonical
functions, taken collectively, are statistically significant at the 0.01 level, from the overall model fit (Table
8) it can be concluded that only the first canonical function is significant (P < 0.01). This conclusion is
consistent with the canonical R² values showed in Table 8.
Table 8: Measures of overall model fit
For these data, in the first canonical function the independent variables explain approximately 42% of the
variance in the dependent variables; the second canonical function explains approximately 19%, the third
one explains 17%, the forth function (MP) explains 10% and the fifth one explains only 11%. This is not
unusual since typically the first canonical function, "Performance Support", is far more important than the
others. Even though the first canonical function was deemed to be significant, it has been recommended
that redundancy analysis be utilized to determine which functions to use in the interpretation. Redundancy
is the ability of a set of independent variables, to explain the variation in the dependent variables taken one
at a time.
Table 9: canonical redundancy analysis
Table 9 summarizes the redundancy analysis for the dependent and independent variables for the five
canonical functions. The results indicate that the first canonical function accounts for the highest proportion
of total redundancy (81.7% including both dependent and independent variables), the second one accounts
for 60.2%, the third one accounts for 35.1%, the forth and the fifth ones accounts for 30.5 and 24.73%
respectively. In addition, the redundancy indexes are higher for the first canonical function than for the
second. Therefore, only the first canonical function is considered for interpretation.
5. DISCUSSION
In this model adoption of e-commerce is considered as a dependent variable which is also conceptually
consist of several factors and is caused by the perception of the adopters. It means that the perception of the
adopter of e-commerce in any industry through e-commerce as a strategic value caused an organization to
adopt it. And those banks who perceived e-banking as adding strategic value to the firm have a positive
attitude toward its adoption.
With this definition of the model, e-commerce perception has overwhelmed its adoption. But according to
the findings of this study it appears that, in a developing country like Iran and a big industry like banking,
although the items of this model are applied, the story is a bit different. In this country the e-commerce
adoption specifically e-banking adoption is in its beginning stages. And still there are lots of gaps. These
gaps could be technological, economical, socio-cultural, geopolitical and other gaps.
Iranian Bankers are informed about the strategic values that are brought by e-banking.
Although they are not grown with e-banking step by step but they want to reach these values. They try to
change some of the bank's processes and services by providing them electronically, yet they still have so
many problems. These new services are inefficient and not integrated.
Another issue related to e-banking in Iran is returning to the factors of adoption.
Although the factors in the (Grandon et al, 2004)'s model were examined, yet there are other factors that
can be put in the model. However six other factors were replaced with two factors (Organizational Support)
and (External Pressure) in the model as a result of factor analysis, three to the PSV (Performance Support,
Operational Support and Relationship Support) and three to the Adoption (Infrastructural Readiness,
Intangible pressure, Persuasive pressure, External dependency).
6. CONCLUSION, IMPLICATIONS, LIMITATIONS AND SUGGESTIONS
We can express the result of this study such that bank managers' perception through e-commerce is very
positive and effective in their adoption trend. It can defiantly make their steps towards such an important
issue faster and help them to remove impediments more rapidly. Thus, interventions toward changing
managers’ perceptions about the strategic value of e-banking can be devised in order to increase the
adoption/utilization of electronic banking by banks. As a final point, the confirm model of e-banking
adoption in this study has been shown in figure 5:
Figure 5: the improved model of e-banking adoption in Iran
6.1. Implications
In order to adopt e-banking, managers should know about the internal attitude toward e-banking
adoption. This study will help them:
1- To understanding that how their organization thinks and perceive e-banking.
2- Which factors are important than others.
3- This study is also giving a very valuable trend e-banking adoption of Governmental and Private
Banks for the Government. Which factors are important from the viewpoint of each bank? And
how they perceive e-banking adoption as a value added strategic issue for their organization.
4- The result of this study is also useful for the Central bank of Iran. Having understood each bank
drivers and perception through e-banking, they can better decide about e-banking adoption
strategies and instructions for other banks.
Having understood this fact:
1) Managers can move easier toward adoption.
2) They can reduce the reluctant to change and make important drivers more controlling
than before.
Many bank's experts and managers believed that there must be several infrastructural readiness before
adopting e-banking; consequently, Top-managers will try to solve the mentioned impediment so that they
can adopt e-banking easier than before.
6.2. Limitations
This research has a number of limitations. We use particular model of e-commerce adoption that may not
be sufficiently inclusive. The finding reported here are snapshots in time. The e-commerce adoption in Iran
demands several infrastructural readinesses that may effect the perception toward its adoption and change
the adoption model.
6.3. Suggestions
According to the above findings, it is interesting to know that Iranian banks have several drivers and
impediments, internally and externally to adopt e-banking. In addition to the model factors of e-commerce
and added items to this study after pilot test, there are some other items that are mentioned in the free
question section of the questionnaire. This would be very interesting to consider them in the future study of
e-banking in Iran.
7. REFERENCES
Adams, D.A., Nelson, R.R., Todd, P.A. (June 1992) Perceived usefulness, ease of use, and usage of
information technology: a replication, MIS Quarterly, pp. 227–247.
Barua, A., Kriebel, C.H., Mukhopadhyay, T. (1995) Information technology and business value: an analysis
and empirical investigation, Information Systems Research, pp. 3–23.
Ching, H.L., Ellis P. (2004) Marketing in Cyberspace: What Factors Drive Ecommerce Adoption?, Journal
of Marketing Management, pp. 409-429.
Chan, Y.E. (2000) IT value: the great divide between qualitative and quantitative and individual and
organizational measures, Journal of Management Information Systems, pp. 225–261.
Davis, F.D., (1989) Perceived usefulness, perceived ease of use, and user acceptance of information
technology, MIS Quarterly, pp. 319–340.
Grandon, E.E., Pearson, J.M. (2004) Electronic commerce adoption: an empirical study of small and
medium US businesses.
Green, P.E., Halbert, M.H., Robinson, P.J. (1966) Canonical analysis: an exposition and illustrative
application, Journal and Marketing Research pp. 32–39.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C. (1998) Multivariate Data Analysis, Prentice-Hall,
New Jersey.
Hong, W., Zhu K., (2005) Migrating to internet-based e-commerce: Factors affecting e-commerce adoption
and migration at the firm level, Information & Management.
Igbaria, M., Zinatelli, N., Cragg, P., Cavaye, (1997) A. Personal computing acceptance factors in small
firms: a structural equation model, MIS Quarterly, pp. 279– 302.
Lederer, A.L., Maupin, D.J., Sena, M.P., Zhuang, Y. (2000) The technology acceptance model and the
World Wide Web, Decision Support Systems , pp. 269–282.
Mahmood, M.A., Mann, G.J. (1993) Measuring the organizational impact of information technology
investment: an exploratory study, Journal of Management Information Systems, pp. 97–122.
Nunnally, J.C., (1978) Psychometric Theory, McGraw-Hill, New York.
Quaddus, M., Achjari, D. (2005) A model for electronic commerce success, Telecommunications Policy
pp. 127–152.
Subramanian, G.H., Nosek, J.T. (2001) An empirical study of the measurement and instrument validation
of perceived strategy value of information systems, Journal of Computer Information Systems, pp. 64–69.
Sadiq Sohail, M., Shanmugham, B. (2003) E-banking and customer preferences in Malaysia:
An empirical investigation
Venkatesh, V., Davis, F.D. (1996) A model of the antecedents of perceived ease of use: development and
test, Decision Sciences, pp. 451–481.Wall Street Journal.
Appendix
- Questionnaire
In The Name of God
E-BANKING ADOPTION: A COMPARISON BETWEEN PRIVATE AND
GOVERNMENTAL BANKS
Among the myriad of computer- and telecommunication-based
applications in the modern era, the advent of e-commerce is having the
biggest impact on organizations. E-commerce enables firms to reduce
telecommunication costs, minimize warehousing expenses, and cut down the
distribution chain.
E-commerce adoption in a bank means using all electronic means of data
transmission and financial transaction among different banks, among
different customers and among customers and bank.
Thank you for your time and attention to this research, please fill
out the forms bellow:
Section 1: General information
Gender
Male
Female
Age
20-30
31-40
41-50
<50
Education
High school
2-year college
4-year college Master/MBA
Doctorate
Other
Years in present position
Years with present Bank
What is your department responsibility?
What is your responsibility in your bank or relevant department?
Does your firm have an Internet service provider?
Yes
No
Does your firm have a web site?
Yes
No
URL
Does your firm utilize electronic commerce?
Yes
No
Section 2: The following questions ask you about your perceptions of strategic value of
electronic commerce. Please indicate your agreement with the next set of statements
using the following rating scale.
In order to provide strategic value to our bank, electronic commerce should help:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Reduce costs of
business operations
Improve customer
services
Improve distribution
channels
Reap operational
benefits
Provide effective
support role to
operations
Support linkages with
suppliers
Support linkage with
other network partners
Increase ability to
compete
Provide managers
better access to
information
Provide managers
access to methods and
models in making
functional area
decisions
Improve
communication in the
bank
Improve productivity
of managers
Support strategic
decisions of managers
Help make decisions
for managers
Support cooperative
partnerships in the
industry
Strongly Disagree Somewhat
disagree
disagree
1
2
3
Neutral Somewhat Agree
agree
4
5
6
Strongly agree
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
16 Provide information
for strategic decision
1
2
3
4
5
6
7
Section 3: The following questions ask you about your perceptions of adopting
electronic commerce. Please indicate your agreement with the next set of statements
using the same rating scale above.
1
Having financial
resources is critical in
decision to adopt ebanking
2 Having technological
resources is important
to adopt e-banking
3 Having skillful human
resources is important
to adopt e-banking
4 Having Infrastructural
readiness is important
to adopt e-banking
5 Having
telecommunication
Infrastructure is
important to adopt ebanking
6 Having regulation
Infrastructure is
important to adopt ebanking
7 Having technical
Infrastructure is
important to adopt ebanking
8 Our bank perceives
that electronic
commerce is
consistent with culture
9 Our bank perceives
that electronic
commerce is
consistent with values
10 Our bank perceives
Strongly Disagree Somewhat
disagree
disagree
1
2
3
Neutral Somewhat Agree
agree
4
5
6
Strongly agree
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
11
12
13
14
15
16
17
18
19
20
21
that electronic
commerce is
consistent with
preferred work
practices
Electronic commerce
would be consistent
with our existing
technology
infrastructure
Top management is
enthusiastic about the
adoption of electronic
commerce
Competition is a factor
in our decision to
adopt electronic
commerce
Social factors are
important in our
decision to adopt
electronic commerce
Banks' nature of
process and
procedures is
important to adopt ecommerce
We depend on other
Banks and firms that
are already using
electronic commerce
Our industry is
pressuring us to adopt
electronic commerce
Our bank is pressured
by the government to
adopt electronic
commerce
Learning to operate
electronic commerce
would be easy for me
I would find electronic
commerce to be
flexible to interact
with
My interaction with
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
22
23
24
25
26
27
28
29
electronic commerce
would be clear and
understandable
It would be easy for
me to become skillful
at using electronic
commerce
I would find electronic
commerce easy to use
Using electronic
commerce would
enable my bank to
accomplish specific
tasks more quickly
Using electronic
commerce would
improve my job
performance
Using electronic
commerce in my job
would increase my
productivity
Using electronic
commerce would
enhance my
effectiveness on the
job
Using electronic
commerce would
make it easier to do
my job
I would find electronic
commerce useful in
my job
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
1
2
3
4
5
6
7
I would like to receive the aggregated results of this survey
I am interested in participating further in this study
Yes
Yes
No
No
Thank you for completing this survey. We recognize that your time is limited and we
value your participation. Please complete the following section if you answered YES
to either question 24 or 25 and you would prefer to be contacted at a different address
than that shown on the cover sheet or if the person who completed this survey is not
the same as the person to whom it was originally sent.
Name:
Telephone:
Fax:
E-mail:
Address:
URL Address:
We will appreciate your suggestions:
………………………………………………………………………………
………………………………………………………………………………
………………………………………………………………………………
………………………………………………………………………………
………………………………………………………………………………
………………………………………………………………………………
………………………………………………………………………………
………………………………………………………………………………
………………………………