Investigation of Effective Factors on e-Banking using the Technology - sersc
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International Journal of Advanced Science and Technology
Vol. 29, No. 9s, (2020), pp. 2932-2944
Investigation of Effective Factors on e-Banking using the Technology
Acceptance Model
Dr. R. Navaneetha Krishnan Ph.D, Dr. R. Venkateswaran Ph.D.
Faculty, Business Studies, Salalah College of Technology, Salalah.
bba_rnk@yahoo.co.in, venka.r@sct.edu.om
V.Sathish MBA.
Faculty, Business Studies, Sona College of Technology, Salem.
sathishv@sonamgmt.org
Abstract
In the changing and challenging COVID world, E-banking and E-commerce have become certain. Here
the question of acceptance and use of technology raises. The adoption of new technologies has e vital
importance in all businesses, and the banking industry is not excluded. The implementation of emerging
technology has been under deliberation since the year 1970. Over many decades, many theories and
models have proposed to address the consumer adoption issues; one of them is the Technology
Acceptance Model (TAM). Perfect usage of information and communication technology by banks not only
decreases the operational costs but also increases customer satisfaction. This paper aims to determine
whether the motivation for using banking technology in the banking sector, can be explained by perceived
ease of use and perceived usefulness as the main elements of the technology acceptance model. This
paper also empirically investigates the correlation between using different types of e-banking services.
Besides, the paper studies the effect of several parameters like customer’s age, gender, annual revenue,
education, and level of information technology skill on the utilization of e-banking services. To derive the
results, Chi-square and Friedman’s non-parametric ranking tests were used. It also provides the banks
with appropriate approaches to present effective training to clients and efficacious customer notification
of e-banking advantages. The results confirmed that both elements of the technology acceptance model
significantly influence the acceptance of Internet banking. It is concluded that demographic and economic
characteristics and perceptions of individuals affect the acceptance and use of Internet banking. The
results showed that both elements of the technology acceptance model influence the acceptance of
Internet banking.
Keywords: Technology Acceptance Model, Factors of e-Banking Acceptance, TAM development and
limitations, Internet and Mobile banking.
Introduction
With the spread of Coronavirus continuing across the globe, all the countries have officially been placed
on notice to prepare for a pandemic. What does this mean in terms of finances? Sometimes just the act of
making a plan helps to ease the stress of facing the unknown. Take a proactive approach (and a few deep
breaths), with these strategies for financial preparedness. Using e-banking is one of the most considerable
steps in this situation. The paper also aims to give some valuable suggestions in the mentioned area.
Electronic cash which is the reserved value on cards and financial networks (Heffernan, 2005) caused
fundamental alterations in banking services. Superior security, easy application, and variation of banking
services that can be defined by e-cash are among the central motives that increase the usage of this type of
money (Freedman, 2000; Heffernan, 2005). Furthermore, employing e-cash and appropriate exploitation
of its related tools not only reduces the operational cost of banks but also boosts customer satisfaction.
Significant developments in Information and Communication Technology (ICT), related technologies,
and e-cash have caused major alterations in the banking industry all over the world. Currently, clients do
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Copyright ⓒ 2020 SERSCInternational Journal of Advanced Science and Technology
Vol. 29, No. 9s, (2020), pp. 2932-2944
not need to go out of their houses to receive banking services. But they can use computers to receive their
desired and required banking services anytime and anywhere. Therefore, it is natural that banks choose to
make use of e-cash and disseminate related equipment like a long term strategy for increasing their
benefits and attracting more clients (Kuisma et al., 2007). These concepts have initiated a new term
“banking technology”. Although banking is not a new industry and roots in the economy, trading, and all
financial affairs, banking technology is relatively a new concept (Ravi, 2008).
It is necessary to mention that there are numerous researches in the field of banking technology,
especially the first aspects; but these researches are just about investigating some limited factors and
effects of them on internet banking. However, ATMs, credit cards, internet banking, and telephone
banking are very novel services in India and in many developing countries. In such countries, studying the
characteristics and behavior of customers, when deciding to use or not to use one of the offered services is
very valuable for banks. This paper consists of all of the mentioned services in the first aspect of banking
technology and their effect on each other which helps banks in compiling comprehensive plans to
increase the usage of all of the services existing in the first aspects. In addition, this paper investigates
many effective factors on the application of e-banking services by clients that helps banks to formulate an
integrated expansion plan. Furthermore, in this paper, we use statistical tests to do various rankings on
effective factors of e-banking usage such as different training models and persuasive role of intensive
leverages. The applied model in this paper is the Technology Acceptance Model (TAM).
Literature Review
Liao et al (1999) used the Theory of Planned Behavior (TPB) for recognizing the attitude and reaction
of people about provided internet banking services. It is concluded in this research that TPB cannot
predict the client's behavior properly (Liao et al., 1999). Research by Aladwani (2001) shows that
financial institutes, their managers and client have a positive attitude about e-banking services (Aladwani,
2001). Lai and Li (2005) used TAM to recognize the effect of age, gender, and level of IT skills of a
typical customer at internet banking acceptance (Lai and Li, 2005). The results of this research show that
the application of internet banking services is independent of the mentioned three factors. On the
contrary, Bauer and Hein (2006) conclude that elder people intend not much on internet banking (Bauer
and Hein, 2006). This contradiction and also mentioned issues in the introduction section demonstrates
the need for further research in recognizing the effect of mentioned factors on e-banking service
acceptance. Cheng et al. (2006) used TAM to predict internet banking acceptance in Hong Kong (Cheng
et al., 2006). Their model includes another parameter: "perceived web security". Cheng et al. concluded
that TAM is a very potent tool for predicting the acceptance of new technology. The role of internet
banking in the banking industry as a whole is investigated by DeYoung et al. (2007). This research
compares the performance of 424 community banks that offered internet banking in the USA in the late
1990s with the performance of 5175 American community banks that did not offer internet banking
services at the same time. This research concludes that the financial performance of the first category is
better than the financial performance of the second studied class (DeYoung et al., 2007). Kuisma et al.
(2007) scrutinized the causes of resistance against internet banking in developed countries (Kuisma et al.,
2007). According to the results of this research, internet banking is a profitable innovation. However,
banks were not successful in reaching predetermined targets in this field. This research concludes that the
reasons are both the functionality of internet banking and psychological obstacles between clients. The
mutual benefits of clients and financial institutes when using Self-Servicing Technologies (SST), has
been studied by Durkin et al. Durkin et al. believe that e-banking services are SSTs. The results of this
research show that a bank can successfully attract clients if the face-to-face relationship with clients is
preserved. And at the same time clients are encouraged to use internet banking services (Durkin et al.,
ARTICLE IN PRESS).
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Copyright ⓒ 2020 SERSCInternational Journal of Advanced Science and Technology
Vol. 29, No. 9s, (2020), pp. 2932-2944
Citation Perspective Outcomes
Companies can adjust their business strategies
and improve the consumers’ willingness to
Propose a research model to
online banking usage. Hence, in the business
explore the key factors
of internet banking, the companies must
Hung Y-M, 2020 affecting consumers’
strengthen areas such as liquidity monitoring,
willingness to use online
information security, and compliance with
banking.
financial regulations, in order to reduce risks
and gain customers’ trust.
Effect of the Application of
Technology Acceptance
Perceived ease of use has a positive and
Model and Trust in
Yasa, 2019 significant effect on perceived usefulness in
Explaining Customer
internet banking.
Intention to Use internet
banking
Demographic and economic characteristics and
perceptions of individuals affect the acceptance
Determine whether the and use of Internet banking. The results showed
Marija, 2019 motivation for using that both elements of the technology acceptance
Internet banking model influence the acceptance of Internet
banking.
The framework of internet The research has a practical implication for a
Sahar Afshan, 2018 banking with extended financial institution to formulate its strategies
TAM model enhancing the adoption of internet banking.
All the variables contribute to and support the
proposed model. The adoption of internet
Integrated constructs into
banking usage variation among variables found
Marakarkandy, 2017 TAM model to discover
26.5% and variation in the TAM model was
internet-banking adoption
29.9% described by predictors variables in this
research.
The outcome highlight variables like website
quality and consumer trust were found the best
predictors of consumer acceptance of internet
Alwan and Al-Zu’bi, Examined the determinants banking. Although, the consumer adoption rate
2016 of internet banking adoption is very low in the study area. Consumers with
high educational backgrounds and high ability to
use computer applications are the actual users of
this useful technology.
Perceived ease of use found significantly
Examined the latent factors affecting users’ attitudes. On the contrary,
Lin, 2015
of internet banking adoption perceived credibility has not found any direct
linkage with consumer’s attitudes.
Salient determinant that Easiness of use, usefulness and credibility found
Santouridis and Kyritsi,
affects the adoption of a significant impact on consumer’s perception
2014
internet banking using internet banking. Moreover, satisfaction
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Vol. 29, No. 9s, (2020), pp. 2932-2944
and innovativeness also found strong predictor
of users' intentions
Perceived usefulness implies the most
Consumer’s adoption of
Safeena, 2013 significant predictors of consumer’s intention to
internet banking
accept internet-banking adoption.
Perceived risk negatively affects user’s
Security and privacy threat
behavioral intention to adopt internet banking.
Singh Bisht, 2012 in relation to the adoption
While trust and perceived risk factors also have
of internet banking
a negative relationship.
The low perceived value of internet banking,
Barriers influencing the lack of knowledge and information found the
Tanveer, 2011
adoption of internet banking most critical barriers to internet banking
adoption
Perceived usefulness and perceived behavioral
factors that affect online
Yaghoubi, 2010 control positively linked with the intention to
banking adoption
use online banking.
Factors affecting internet- Financial risk affected positively to perceived
Lee, 2009
banking adoption. usefulness, perceived benefit and attitude.
The above literature review illustrates that:
1. The results of some researches contradict each other.
2. The mutual relationship between using internet banking and other e-banking services is assumed
negligible.
3. Few factors such as age, gender, and level of IT knowledge are studied as effective factors.
4. In this paper, we aim to resolve the above issues. The next section is a brief introduction to TAM.
Technology Acceptance Model (TAM)
This paper aims to study the first aspect of banking technology. The discussed aspect is mostly
covered by ICT developments. On the other hand, an Information System (IS) is an organized
composition of individuals, hardware, software, telecommunication networks, and data resources that
gather, transfer, and distribute data at an organization (O'Brien, 2005). According to the above definition,
it can be inferred that the first aspect of banking technology is an IS. TAM is one of the best-developed
models for studying an IS (Davis, 2003). Regard that usage, in fact, determines the success of an IS which
has possibly cost a lot to be developed (Mathieson, 1991). TAM describes a rational relationship among
ease of use and usefulness of an IS and users’ attitudes, purposes, acceptance, and actual usage of an IS
(Hartwick and Barki, 1994). Acceptance is one of the main and vital factors in predicting the success of
an IS (Borthick, 1988), and TAM attempt to clarify why an IS is accepted or not accepted (Davis, 2003).
Usefulness and ease of use are defined as bellow (Davis, 1989; Davis et al., 1989)
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Usefulness: “the degree to which a person believes that using a particular system would enhance his or
her job performance.”
Ease of use: “the degree to which a person believes that using a particular system would be free of
effort.” TAM is illustrated in figure 3. The Interested reader is referred to (Davis, 2003) for further
studying of TAM. Section 4 investigates the effective factors of e-banking acceptance in India. These
factors will be classified under mediating variables: perceived usefulness and perceived ease of use while
the dependent variable is system usage.
Research Method
In this paper, survey studies are used to collect proper data. This is done by means of open and closed
questionnaires which are discussed in detail. After collecting proper data, statistical data analysis is done
and results will be provided in detail. To use TAM, all effective factors in accepting provided e-banking
services should be classified under the mediating variables, usefulness and ease of use. Then, research
results will be achieved by means of proper statistical tests. Figure 3 depicts the research method.
Open Questionnaire and Stratified Sampling
TAM predicts IS acceptance based on usefulness and ease of use. However, usefulness and ease of use
are two very general concepts and their forming components must be recognized. In this paper, we have
used an open questionnaire to recognize the mentioned components. We have also exploited stratified
sampling in collecting data with the designated open questionnaire. We place managers of Indian banks
and e-banking research groups in the desired stratum since we believe that they have comprehensive
information about effective factors that we are interested in.
Content Analysis
Content analysis is a standard methodology to analyze and study the contents of recorded
communications such as interviews (Weber, 1990). Content analysis is used for studying recorded human
communications and discovering its characteristics through a systematic method (Brown et al., 1999). In
the research, content analysis is applied to the recorded data, collected from the statistical population of
the stratum, to discover effective factors of e-banking acceptance.
Effective Factors of e-Banking Acceptance in India
Using content analysis the following factors are recognized:
1. Cultural factors: Cultural issues are one of the most effective factors of acceptance or rejection of new
technology in any society, especially in India. These factors should be covered and classified under the
variable ease to use. Culture-making has several aspects and in this paper, we intend to investigate the
aspects that have an influence on e-banking acceptance. Different aspects of culture-making are as below:
a) Using mass media for informing people about new technologies.
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b) Using exclusive programs to inform new and experienced users about new technology.
c) Presentation of experienced users to new users as successful models.
d) Recommendations to new users by skilled users who have successful experiences with respect to a
technology application.
2. Public training: According to the fact that a few percentages of bank customers do not have sufficient
knowledge about using the Internet and other intermediates of using e-banking services, public training
increases knowledge of customers and removes resistance against change. This factor must be categorized
under the variable ease of use.
3. Obligation: Sometimes obligation leads in using a new technology by potential users. However,
obligation increases the resistance against change. Obviously, the obligation is classified under the
variable ease of use.
4. Financial added values: Financial added values are classified under the usefulness variable. This
subject includes issues such as bonuses and interests for depositors. Financial added values are incentive
factors for using new technology and contain the followings:
a) Considering bonus for technology users.
b) Considering higher interest rates for users.
c) Designating profitable payment terms, provided that clients use e-banking services.
5. Development of infrastructures: It facilitates user’s technology utilization and thus is classified as a
component of the variable ease of use. This factor has the following components in the e-banking context:
a. Bandwidth and availability of the internet.
b. Availability of PCs in a variety of locations.
c. Availability and proper function of ATMs.
d. Availability and proper function of Point of Sale (POS) devices.
e. Reliability of telecommunication devices especially in the case of mobile banking.
6. Easy application of technology: This means that a typical user does not need tiresome and boring
effort to use technology. Obviously, it is a component of the variable ease of use.
7. Technical support: It ensures users about easy and rapid troubleshooting. This factor is also one of the
components of the variable ease of use.
8. Security: Is one of the components of the variable usefulness. Security has two sub-components:
a. Individual security when using e-banking services for financial issues.
b. Infrastructure security.
9. Supportive legal routines: It is one of the components of the variable usefulness.
10. Other notable superiorities: This is a major incentive in using new technology. And must be
classified as a component of the variable usefulness. The subject contains the following:
a. Time-saving.
b. Cost reduction.
c. Access to a bank account, anytime and anywhere.
d. Gaining respect in society.
e. Possibility of purchasing goods and services via the internet.
Defining independent and dependent variables is one of the requirements of TAM. In this paper,
the acceptance of e-banking services by bank clients is considered as a dependent variable while the
above factors are considered as independent variables. Thus, usefulness and ease of use are considered as
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mediating variables. The next stage includes data gathering and conducting appropriate statistical tests to
determine the effect of independent variables on the dependent variable.
Close Questionnaire
People generally have little tendency to reveal their financial information and a close questionnaire is
very suitable for confidential sampling. Moreover, responses of respondents to the questions of a close
questionnaire can simply be prepared for statistical tests. This has made the authors of this paper use a
close questionnaire for data gathering. In addition, all respondents answered the questions in the presence
of an interviewer to increase the accuracy of the research results. Therefore, all respondents have the
chance of asking help from a trained interviewer in case of a blur question. The close questionnaires were
completed by 200 Indian users of e-banking services. However, only 150 questionnaires distinguished to
be reliable and used for the statistical tests.
Internal consistency and reliability of the designed close questionnaire were measured by
Cronbach’s Alpha coefficient. Cronbach’s Alpha factor is one of the most popular reliability assessment
methods of close questionnaires. Cronbach’s alpha coefficient is a number between 0 and 1 (Cronbach,
1951). Higher Cronbach’s coefficient indicates more reliability of measurement tool while the lower
Cronbach’s factor emphasizes unreliability (Cronbach, 1951). Cronbach’s Alpha coefficient of the
designed close questionnaire is equal to 0.8302 which is a sublime figure and points out the internal
consistency and reliability of the questionnaire. This number also guarantees the trustworthy results of
this paper.
Statistical Tests and Ranking of Effective Factors
In this section, we perform a statistical test on resulted data from the questionnaire. As it is mentioned
before, the role of many factors on acceptance and usage of e-banking services is studied in this paper.
Also in this paper, many effective factors will be ranked which facilitates the adoption of successful
policies to increase the usage of e-banking services. Statistical tests used in this research include:
Chi-square statistical tests
Friedman non-parametric ranking tests
Chi-square statistical tests reveal the relationship between independent and mediating variables
(usefulness and ease of use) and hence dependent variable (usage of e-banking services). To perform chi-
square independence tests, one needs to utilize contingency tables. A contingency table is used to
determine the impact of a discrete (nominal or ordinal) variable on another discrete (nominal or ordinal)
variable (Yates, 1934). In a contingency table, the independent variable is called the row variable and the
dependent variable is called the column variable. When the row and column variables have no
relationship, they are called independent and thus uncorrelated. To test the independence hypothesis, a
chi-square independence test is used.
In the equation, the number of rows, and is the number of columns of the contingency table. It is
the observed value in the cell and is the expected value of this cell when the alternative hypothesis is true.
The test statistic of the equation has a chi-square distribution with degree of freedom. As mentioned
before, in this paper, Friedman’s non-parametric statistical test is used for ranking the effective factors.
Friedman test, unlike analysis of variance, uses observed rankings to perform the test.
Results of Independency Tests
In this section, results of independent tests are provided. In table 1, independent and dependent variables
are shown in the first column and first row of the table respectively. The result of independency tests is
shown in other columns and rows of the table.
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Table 1– Correlation between general characteristics of clients and e-banking services
Demographic Using internet Using POS Using a Using a
Factors banking services terminals telephone bank mobile bank
Age × ×
Education ×
Average annual
× × ×
income
Having computer at
× × × ×
home
Table 2 shows the relationship between independent variables and e-banking components. The first
column of Table 2 indicates the independent variables. Columns 2 to 5 of table 2 illustrate whether a
meaningful correlation between independent variables and e-banking components exists.
Table 2- The correlation between independent variables and e-banking components
Independent Variables Dependent Variables
Factors Using Internet Using POS Using a Using a
banking terminals telephone mobile
services bank bank
Easy access to PC × ×
Easy access to the internet × ×
Simplicity of interface ×
Feeling comfortable when using the × × ×
service
Bandwidth of internet port × × × ×
Accessibility of POS terminals × × ×
Trust on the correct function of POS × × ×
terminals
Trust on the correct function of × × ×
mobile banking
Performance of technical support × × ×
department
Performance of legal schemes and × ×
liable organizations on meeting the
complaint of users
Security × ×
Results of Ranking Tests
The result of the Freidman ranking tests is shown in Table 3. The first column of Table 3 shows the test
number. The second column of this table specifies the head factor of the ranking. In the third column of
table 3, sub-factors of the head factor are ranked. This ranking is based on the mean observed ranking
value, shown in the fourth column. Columns 5 and 6 give information about test statistics. The last
column of Table 3 demonstrates whether the null hypothesis is rejected.
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Vol. 29, No. 9s, (2020), pp. 2932-2944
Table 3 - Results of the Friedman tests
Test Head Mean observed Test Reject null
Sub-factors
No. factor ranking value statistic hypothesis
Number of
Supermarkets 2.97 148
observations
Business in
Chi-square
which e- Home appliance vendors 3.11 25.251
statistic
banking
Degree of
1 services Cloth vendors 3.43 5 Yes
freedom
should be
Significance
spread the Restaurants 3.61 0.000
level
most.
Electronics vendors 3,79
Hotels 4.08
Number of
Which one Mass media 2.05 149
observations
does
Chi-square
encourage Benchmarking from users 2.44 29.756
statistic
2 the usage of Yes
Degree of
e-banking Recommendation of users 2.48 3
freedom
services the
Instructive handbooks, Significance
most? 3.03 0.000
brochures, etc level
Number of
150
observations
Verbal instructions by bank staff 1.42
Chi-square
What is 2.560
statistic
3 more No
Degree of
instructive? 1
freedom
Banks’ instructive documents 1.58
Significance
0.110
level
Which one Considering higher interest rates Number of
1.46 148
does for users observations
encourage Designating profitable payment Chi-square
1.88 72.230
the usage of terms statistic
e-banking Degree of
services the 2.000
freedom
most?
4 Yes
Considering bonus for
2.66
technology users Significance
0.000
level
Which one Number of
5 Time saving and cost reduction 2.17 150
does observations Yes
Security
encourage 2.48 Chi-square 102.563
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Analyses of Statistical Tests
Results from the open and close questionnaire and statistical tests in this study have revealed facts which
their clear analysis significantly helps the development and growth of e-banking. These analyses are
discussed below. Table 1 shows a meaningful relationship between gender and using telephone banking
which means that banks must have specially adapted plans for attracting males and females and
increasing the usage of telephone banking. Obviously, the plans must distinct in instruction and
notification areas. A meaningful relationship between age, and using internet bank as well as POS
terminals is another interesting result of Table 1. This leads the planners to particularly strive for
attracting students and juveniles (mostly because they accept more risk (Bauer and Hein, 2006)). If the
banks are successful in attracting the mentioned group, there will be a high possibility that other members
of the family get involved since they may benchmark the young users in the family. Also, there is a
meaningful relationship between the average annual income and using POS terminals. This means that
banks must classify their clients into defiles and provide a separate expansion plan for each class to
absorb all the classes in using POS terminals. Table 1 also shows that there is a correlation between the
level of education and all of the e-banking components except mobile banking. According to this fact,
banks can thrive in attracting a group of clients without higher education in using e-banking services
through mobile banking. Table 2 shows that having a PC at home has no relationship with using e-
banking services. This means that clients can easily access hardware facilities in places other than home,
at work for instance. Therefore, banks must focus to simplify the interface of e-banking (based on the
results from table 2) Table 2 indicates that there is a correlation between easy access to PC and internet,
and using internet banking and POS terminals. It should be noted that the mentioned facts have no
conflict with the results obtained from table 1. The results of table 1 indicate that there is no relationship
between having a PC at home and using e-banking services while table 2 signifies that there is a
relationship between using POS terminals and internet banking, and easy access to PC and internet. As a
result, banks should increase the internet penetration rate in order to increase the usage of e-banking
services. This target needs inter-organizational cooperation and indirect advertisement. It should be noted
from Table 2 that there is not a meaningful relationship between the bandwidth of internet ports and using
e-banking services. Therefore, users of e-banking services do not require high-speed internet to use the
services available. As a result, increasing the internet penetration rate (opposite to the internet bandwidth)
should be noticed.
Conclusion and direction for further research
The significant role of the banking industry in the economy of a country is inevitable. An advanced
banking system may lead the economy of a country to boom. Besides, banks as economic agents try to:
1. Increase the number of their clients
2. Increase customer satisfaction
3. Increase income, and
4. Reduce costs
E-banking services are potent tools for increasing profitability and customer satisfaction. In this
paper, effective factors of e-banking acceptance in India are recognized and classified as sub-components
of the ease of use and usefulness variables. Then, survey studies are used to determine the effect of the
sub-components on acceptance of e-banking services in India. In this paper, statistical independency tests
have been used to verify the correlation between independent and dependent variables. Friedman’s
ranking test is also used to compare the effect of independent variables against each other. These rankings
significantly facilitate the burdensome strategic planning process. Finally, the results of the mentioned
tests are analyzed. In this paper, we have investigated the effect of many factors on the acceptance of e-
banking services. And unlike other papers, we have involved the whole e-banking services in our studies.
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1. Obtaining a regression model that can lead to enormous investments and increase the e-banking
acceptance.
2. Providing a strategic plan that makes synergy between the investments of different banks in order
to increase the usage of e-banking services. Undoubtedly, this approach leads to economic
growth.
3. Developing a model that enables Indian banks to compete with their global competitors,
especially in the field of e-banking services.
4. Developing a model to increase the creative relationship between banks and clients. This model
leads to developing new e-banking services and diminishing current weaknesses.
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