Royal Journal of Business Management
2022, Vol. 1, No. 1, pp. 18-34
Determinants of Electronic banking Usage in Northern
Ethiopia of East Gojam Zone, Evidence from
Commercial Banks in Ethiopia
Zewdu Eskezia Gelaye (MSc)1, Birhanu Daba Chali2 and Eshetu Beyene
Kefenu2
1. Department of Accounting & Finance, Dembi Dollo University, Dembi Dollo, Ethiopia
2. Department of Business management & Entrepreneurship, Dembi Dollo University, Dembi Dollo, Ethiopia
Abstract:
The main objective of this study was to determine the factors that affect the use of
electronic banking system in East Gojam Zone. To achieve this objective, the necessary
data was collected from electronic banking system users and non-users by using
questionnaires. Convenience nonrandom sampling technique was used to select
number of samples from the target population of the study. The researcher used binary
logistic regression analysis method to analyze the raw data which was obtained from
the respondents. The findings of the study was identified as perceived risk of the
customers about the new technologies, age of the customers, perceived cost to use
electronic banking system, education level of the customers and compatibility of the
system affects the use of electronic banking system in East Gojam Zone. The
researcher suggests that the bankers that are existed in East Gojam Zone should give
awareness about the system and they should make confident the customers about the
new technology by increasing the promotion through medias and in person too. And at
the same time they should minimize the cost of using electronic banking system.
Keywords; Electronic banking, perceived risk, perceived cost, system compatibility
INTRODUCTION
Background of the Study
Introduction of new technologies allowed banking institutions to offer new channels of service
outlets like ATM facility, Internet Banking, Telephone Banking, SMS banking and Mobile Banking.
Ethiopian customers have lately gained access to a slew of new ways to communicate with their
banks. Banks compete with one another to deliver the most cutting-edge technologies to their
clients and themselves. However, few studies have been undertaken to determine whether the
"Internet Banking" channel is adequately employed by Ethiopian consumers, and factors
influencing customer acceptance of the Internet banking channel, if any exist, have also not been
examined in an Ethiopian context.
The rapid growth of information technology, provides commercial banks to reach their customers
everywhere at any time simply. IT facilitates a user-friendly banking service and customers have
different alternatives of payment methods. It helps to provide services such as checking accounts,
transferring funds, and buying financial products or services online (Paul, 2013)
E-banking is defined as a variety of self-service platforms such as internet banking, mobile
banking, ATM dispensers, agent banking, point of sale where by customers access these services
using electronic devices like personal computer, Automated teller machine (ATM), Point of sale
terminals and mobile phones without their physical presence in the bank (business dictionary).
Royal Journal of Business Management (RJBM)
The pressure of globalization, consolidation, Banks must re-examine their service delivery
systems in light of deregulation and fast changing technology in order to position themselves
appropriately within the dynamism of information technology and users' flexibility. (paefe, 2016)
For more than 200 years, banks were using branch based operations but the advent of multiple
technologies and applications changed the nature of financial services delivered to customers
(Milanzi, 2013) The fastest growth of internet in the world accelerates the modernization of banks
by facilitating the accessibility, delivery time, self-service and ease of marketing.
The Ethiopian banking industry is not an exception of it, though it comes late compared to the
rest of the world. Currently, banks are faced with competitive environment and in order to
succeed in such market places, they must provide different user friendly products with latest
technology. As such, many banks and financial institutions are actively providing new electronic
banking products for their customers throughout the world. The financial sector in Ethiopia is
composed of the banking industry, insurance companies, microfinance institutions, saving and
credit cooperatives and the informal financial sector.
In Ethiopian there are 16 private and 1 state owned commercial banks; Out of these 17 banks, the
state owned commercial Bank of Ethiopia (CBE) is the largest and leading bank in financial
operations(NBE, document). Commercial Banks as such provide all the banking services including
ATM facility, internet Banking, mobile Banking and agent Banking beside the conventional
banking activities. In the industrialized world, factors influencing customers' adoption of Ebanking service channels have been investigated (Salim 2013, Alice 2012 & John, 2015). In
comparison, there are few published research that look at the elements that influence the use of
E-banking from the perspective of customers in Ethiopia. The relatively recent introduction of
electronic banking in Ethiopia is one of the reasons for limited empirical study in this area. The
study conducted (Sira, 2013) are remarkable exceptions. However, if users are unmotivated to use
that type of technology, the adoption of an e-banking system is unlikely to be successful, and thus
the company and customers will not reap the full benefits. As a result, in order to encourage
customers to utilize electronic banking, banks must offer significant enhancements that address
their concerns. Although electronic banking has many advantages for both banks and users, it
also has some drawbacks.; customers still fear from the risk of electronic banking service(Alsmadi, 2012) Therefore to get the potential benefits of e-banking, bank users may adopt the
attributes of ebanking i.e. ATM machines, POS, internet banking, mobile banking and agent
banking. Hence there is limited understanding of the benefits of adopting e-banking, the factors
influencing the CBE customers to adopt e-banking and the role played by e-banking to the
performance of banking institution are the current concern of the bank. In this way they don‟t
benefit from lower transaction costs, 24 hours trading, more extended business destination,
higher customer satisfaction and also increased efficiency in daily banking processes in addition
to the simultaneous importance to the customers. Keeping in view studying and examining
factors affecting for the use of e-banking was conducted to provide academic recommendation
for the maximum significance of e-banking service channels for both CBE and the customer.
Statement of the Problem
E-banking was a new technology in Ethiopia which needs a lot of academic contribution to service
providers regarding the factors affecting e-banking users. Hence, the ground motivating and
inhibiting factors of e-using banking, of customer‟s usage have been examined. The serving of
customers at the branch level forces customers for, long waiting line, high transaction error and
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Gelaye, et al., 2022
lower reliability, etc. then it encourages users to see other banks or to use informal financial
institutions.
Therefore, giving due attention on e-banking and user‟s adoption has been the current focus of
all banks to get the remedy for lower acceptance rate of users. Most of the study on e-banking
has been reported from western countries and other Asian countries. Unlike those countries most
of the researchers in Ethiopia, studied about e-banking adoption don‟t incorporate non users in
their study(Bultum, 2014) In addition most of the study focused only on single channel of
ebanking like ATM service not widely on e-banking adoption(Asrat, 2017) Moreover(Paul, 2013)
the study was incorporating on the demographic variables and internal factors unlike external
factors which have influencing factors are not covered. Because Commercial bank of Ethiopia
possesses more than 60% of the country‟s banking market,(CBE, 2016) then examining the
factors for the use of e-banking in case of Ethiopian banking industry, East Gojam Zone, may lead
to solve the big share of e-banking challenges in East Gojam Zone.
There are longest waiting lines in commercial bank of Ethiopia because of the traditional banking
practice and little academicals contribution in this area.
Despite the growth of e-banking worldwide, commercial banks in Ethiopia continue to conduct
most of their banking transactions using traditional teller based methods. Banking operation is
still under developed due to low level of awareness creation about the comparative advantage
(perceived benefit) and disadvantage (perceived risk) of using e-banking system. In addition
infrastructural development, legal and regulatory framework, literacy level, power, ICT and for
security issues are the main influencing factors of users e-banking adoption(Belay & Mengesha,
2016) Therefore, the delivery of service mainly at the branch level lead customers to commit
longest transaction time, repetitive transaction errors, service inconvenience, lower supervision
of their bank accounts and less financial inclusion in the society. Then the result of the thesis
functions; to examine the factors on e-banking adoption like internet banking, mobile banking,
ATM, POS and agent banking. Besides, there is very little information available on this issue by
previous attempts and mainly any one is done by using a logit model. Hence, this research is
undertaken to fill the knowledge gap, Considering the above concepts studying factors that affect
using of e-banking services in Ethiopia, Amhara, East Gojam Zone is the motivation to conduct
this study.
Objectives
General Objective:
The General objective of this study was to identify the factors influencing the use of electronic
banking system In East Gojam Zone, Amhara, Ethiopia
Specific Objectives:
1. To identify bank internal factors that influence customers to use electronic banking system.
2. To identify bank external factors that influence customers to use electronic banking system
Hypotheses of the Study
1. Ho: there is no a significant relationship between promotion and the use of E- banking
2. Ho: there is no a significant relationship between accessibility of the network and use of Ebanking
3. Ho: there is no a significant relationship between flexibility of the system with the use of Ebanking
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Royal Journal of Business Management (RJBM)
4. Ho: there is no a significant relationship between number of branches that a bank has with
the use of E- banking by the customers
5. Ho: there is no a significant relationship between knowledge of the consumer with the use of
E- banking
6. Ho: there is no a significant relationship between education level of the consumer with the use
of E-banking
7. Ho: there is no a significant relationship between age of the consumer with the use of Ebanking
8. Ho: There is no a significant relationship between system compatibility with the use of
electronic banking system
9. Ho: there is no a significant relationship between customers perceived risk with the use of
electronic banking
10. Ho: There is no a significant relationship between customer perceived benefit with the use of
electronic banking
11. Ho: There is no a significant relationship between customers perceived cost and the use of
electronic banking system
12. Ho: there is no a significant relationship between system complexity with the use of electronic
banking system
13. Ho: there is no a significant relationship between gender of the customers and the use of
electronic banking system.
Significance of the Study
The results of this study will be expected to have advantages for the financial institutions, mainly
banks, for customers and other researchers to study further as a projecting point.
Scope of the Study
The study was been limited to East Gojam Zone. The reasons for this were: Ethiopia is too large
for the researcher to travel all over the country. And East Gojam Zone is one of the largest zones
in Ethiopia and has a heterogeneous population which ensures a wide spread of potential
respondents to the study. The cost and time required to conduct the study all over the country is
too large and at the same time the researcher’s regular work time would be affected.
Bank external factor
.perceived cost
.Perceived risk
.Perceived benefit
.Education level
.Age of the customer
.Knowledge of the
customer
. Gender
The use of E. banking
system
Conceptual Frame Work of the Study
Bank internal factor
.Compatibility
.flexibility
.promotion
.Network
accessibility
.Number of branches
.Complexity
Figure 1: Conceptual framework, developed by the researcher
21
Gelaye, et al., 2022
(Al-Smadi,
2012)Moha
med o.alsmadi (2012)
Shubhra
Vohra(unp)
Sig
Si
g
si
g
Si
g
Si
g
si
g
CofS
KofC
NA
FofS
NofB
PB
PC
Promm
EL
AC
SC
Si
g
Desc Si
riptiv g
e
OLS
GofC
Empirical results
PRR
Methodology
Type of the data
used
Cross
section
Cross section
OLS
Cross
section
(Aklog,
2018)
AklogTegin
Alellegn
(unpub)
2018
(Atnkut,
2018)
Atenkut ayal
(2018)
Cross
section
Name of the
author &
publication year
Table 1: Summary of some empirical literature reviews and research gap
Si
g
si
g
si
g
si
g
Si
g
RESEARCH METHODOLOGY
Research Design
This study employs explanatory research design, because the researcher is intended to get the
relationship between independent and dependent variable of the effect of explanatory variables
over the dependent variable.
Definition of the Target Population
The sampling population was defined as customers of Ethiopian retail banks both users and
nonusers of internet banking who have bank accounts; non-users are included in the sample to
know their perceptions towards internet banking.
Sample Size
Due to the covid19 the sample were picked conveniently from customers of each commercial
bank branch customers that exist in East Gojam Zone. The sample size is 351. Without formula by
using convenience non random sampling method the researcher took 50 customers from
commercial bank of Ethiopia, 31 from Awash international bank, 33 from Dashen bank, 29 from
bank of Abyssinia, 42 from Abay bank, 23 from nib bank, 21 from Lion international bank, 34 from
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Royal Journal of Business Management (RJBM)
Buna International bank, 19 from Addis International bank, 15 from Hibret bank, 13 from Oromia
International bank, 16 from Oromia Cooperative bank, and 5 from Wogagen bank, total 351
Data Collection
The data were collected by using questionnaires with the support of unstructured interview.
Method of Data Analysis
The raw data obtained from the respondents was analyzed and interpreted by running STATA
version 12. binary logistic regression analysis methods were used as data analysis Techniques.
Multicollinearity
When the predictor variables are highly correlated with each other, there will be a problem of
multicollinearity. This is an issue, as the regression model will not be able to accurately associate
variance in the dependent variable with the correct predictor variable, leading to jumbled results
and incorrect inferences (Statistics, 2018). So that to avoid this problem the researcher tests the
problem of multicollinearity between the independent variables by using pair wise correlation
between independent variables
Measurement of the Dependent Variable
The dependent variable in binary logistic model cannot be measured in terms of interval scales;
rather it must be measured in terms of two labels. I.e. by using ‘1’ if yes or use or positive finding
and ‘0’ if no or negative finding (Statistics). So, here in this study the dependent variable is the use
of electronic banking system in East Gojam Zone. And its coded as if the customers use electronic
banking system ‘1’ and ‘0’ if they didn’t use. So it fulfills the dependent variable measurement
assumption
Test of Model Specification
When we construct a probit or logit regression version, we anticipate that we have got blanketed
all of the relevant variables and those we have no longer included any variables that ought to not
be with in the the model. That is constantly authentic for any statistical model obtainable right
specification of the model is essentially important; parameters might also trade value and even
direction when variables are added to or removed from the version.
The Stata command linktest can be used to locate a specification mistakes, and it is issued after
the logit command. The idea in the back of the link take a look at is that if the version is nicely
distinctive, one should no longer be able to find any extra predictors that are statistically
significant except by using chance after the regression command.
Link test take a look at makes use of the linear anticipated value (_hat) and linear predicted value
squared (_hatsq) because the predictors to rebuild the model. The variable _hat should be a
statistically significant predictor, considering it’s the predicted value from the model. This will be
the case unless the model is absolutely misspecified. On the other hand, if our model is well
particular, variable _hatsq should not have a good deal predictive power except via chance.
Therefore, if _hatsq is significant, then the link test is significant. This generally means that we
have neglected applicable variable(s)
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Gelaye, et al., 2022
The form of the link test applied right here is based totally on an idea of (Tukey, 1949), which
turned in to similarly defined by (Pregibon, 1980) elaborating on his unpublished thesis (Pregibon,
1980) whilst we run link check after logit, the end result is every other logit specification:
Model Fit Test
Use the tests of goodness to check whether the projected probabilities depart the observed
probabilities differ from the observed probabilities in a way that the binomial distribution does
not predict. If the value of P for the goodness of –of-fit test is less than your chosen level of
significance, the predicted probabilities differ from the observed probabilities in a way that the
binomial distribution does not predict, and the reason is an incorrect link function, omitted term
higher-order for variables in the model, omitted predictor variables not included in the model,
and spill over (Minitab, 2019). (Minitab, 2019).
Ethical Consideration
Ethical considerations were followed to collect data from each of the clients participating in the
study. Each of the participants took part in the study voluntarily and each of the respondents was
informed of the purpose of the study and of their right to withdraw from the study without giving
a reason. They have been informed that the responses received from each participant will be kept
confidential and that respondents are not at risk in the study.
Test of Reliability and Validity of Instruments
Study score of 0.7 and above implies an acceptable level of internal reliability ((Bryman & Bell,
2003) . So; The internal consistency coefficient alpha was calculated to determine whether the
items on a scale all measure the same underlying construct, and the researchers found the result
for alpha is 0.792. To assure validity, the researchers designed questionnaires on the basis of
previous studies’ questionnaires and review of related literature.
VARIABLE DEFINITIONS
Adoption Of Internet Banking
Adoption refers to a product's, services, or idea's acceptance and continuing use. Consumers go
through "a process of knowing, convincing, deciding, and verifying" before they are ready to
accept a product or service, according to (Rogers & Shoemaker, 1971).
Attitude and Perception of Consumers
Lamb, Hair, and McDaniel (Lamb, Hair, & McDaniel, 2000) Confirming — the process by which a
person chooses, organizes, and turns stimuli into a meaningful, integrated whole. Perception
includes all of these senses (sight, touch, taste, smell, and hearing), and sensory stimuli have a
part in eliciting certain experiences that impact customers' purchase decisions, as well as being
utilized to protect consumers from harmful stimuli from the environment. Different consumers
will interpret a product offer product differently depending on their needs, according to (Reekie
& Brits, 1997). Consumer impressions of a product or service might have an impact on their
purchasing decisions.
Innovation
(Rogers, 1983) defines innovation as having three characteristics: relative advantage,
compatibility, and complexity. Adaptors view these features differently from non-adopters, as
has been demonstrated numerous times. The features of an innovation, according to (Kotler,
2000), determine its acceptance rate. Some items gain traction quickly, while others take a
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Royal Journal of Business Management (RJBM)
lengthy time to gain traction. It is more likely that a favorable attitude toward the innovation will
be formed if it is better than the existing system (a measure of relative advantage), is compatible
with the needs of the potential adopter (a measure of compatibility), and is simple to understand
and use (a measure of complexity) (Ching & Ellis, 2004)
Compatibility
The degree to which an invention is viewed as being consistent with current values, prior
experiences, and the needs of potential users is referred to as compatibility. An innovation may
or may not be compatible with socio-cultural values and beliefs, previously presented ideas, or
client requests for innovations. (Rogers, p. 213, 1983) The rate of adoption of an innovation is
positively related to its compatibility as viewed by members of a social system (Rogers, 1983)
Complexity
The degree to which an innovation is considered as simple to understand and user-friendly is
referred to as complexity. When an innovation is seen as complex or difficult to utilize, adoption
is less likely (Rogers, 1983, p. 230) Adoption of the Internet (Leaderer, Maupin, Sena, & Zhuang,
2000)
Perceived Cost
Costs as they are perceived Adoption is influenced by the perceived costs and advantages of the
innovation, according to (Ching & Ellis, 2004). The cost of an innovation consists of many
components: initial investment costs, operating costs, and usage costs. (1984, Rothwell &
Gardiner) State that there are two basic groups of factors affecting user needs, namely price
factors and non-price factors. In respect (Gupta, 1988) identifies price as an important factor in
brand switching. If consumers are to adopt new technologies, the technologies must be
inexpensive compared to alternatives Otherwise, acceptance of the new technology may not be
viable from a consumer perspective
Perceived Risk
The degree to which consumers are unsure about the repercussions of purchasing, using, or
discarding an offer is measured by perceived risk. It's critical to remember that risk is a personal
experience. That is, a customer's perception of risk when making a purchase decision may not be
accurate (Hoyer & MacInnis, 2001) , A important determinant determining the overall amount of
information acquired by consumers will be risk or ambiguity regarding the most appropriate
buying decision or the decision's results (Loudon & Bitta, 1993)
Age of the Respondents
At different periods of their life, people purchase different commodities and services. The type of
food that appeals to teenagers, for example, is unlikely to appeal to elders. Furthermore, people's
interests in dress, furniture, and amusement are influenced by their age (Kotler, 2000, p. 180)
People of various ages have a wide range of values, meanings, and behaviours. In any case, when
it comes to segmenting customers based on their actual age, marketers must exercise caution.
Many adults in the United States believe they are ten to fifteen years younger than they are. Their
psychological age is more directly tied to their behaviour and intellect than their chronological
age (Peter, Olson, & Irwin, 1994)
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Gelaye, et al., 2022
Level of Education
A person's educational level is regarded as a means of gaining admission to a specific occupation
(Kotler & Amstrong, 2000). There is a substantial link between educational attainment and
income. Consumers with a higher level of education have more money to spend, which has an
impact on their lifestyle. Higher education has an impact on the types of things individuals buy,
the places they buy them from, and the prices they are willing to pay (Wilkie, 1990).
Income
The amount of money spent on goods by consumers is determined by their income. The impact
of income on expenses can be quantified in three ways: Personal income, disposable income, and
discretionary income are all examples of d. H. personal income (McCarthy & Perreault, 1993) In
cases where income levels effect customer needs and define their purchasing power, income is a
popular demographic variable for segmenting markets (Lamb, Hair, & McDaniel., 2000)
Occupation
Person’s occupation also influences their consumption behaviour. For example, a rworker is
unlikely to buy the same types of clothing, join the same types of clubs, or enjoy the same types
of pastimes as a company president would. Marketers try to identify the professional groups that
have an above-average interest in their products and services. A company can even specialize its
products in certain occupational groups (Kotler P. , 2000) Demographic variables are often used
as a basis to describe different types of consumers (Wilkie, 1990)
Social Influences
Face-to-face communication is employed frequently, which has a social influence. Social factors
include the opinions of friends and neighbors, peer criticism, and family pressure (DuPlessis &
Rousseau, 1999)
RESULTS AND DISCUSSION
Logistic Regression Results
Binary logit model was employed to analyze the effect of constraints like perceived cost,
Perceived risk, Perceived benefit, Education level, Age of the customer, Knowledge of the
customer, Gender, Compatibility, flexibility, promotion, Network accessibility, Number of
branches and Complexity of the system on theuse of electronic banking system by customers. To
measure the perception the dummy variable use of electronic banking system (UEBS)is
constructed as dummy one if operators use E-banking and zero otherwise. This shows the
probability that the customers will experience the use of electronic banking system while
controlling other factors.
Testing the Hypothesis and Discussion of Findings
Each hypothesis was tested and interpreted from the above model as follows. The pseudo R
Square is 17.05%which shows that 17.05% of the increase or decrease in the use of electronic
banking system was explained by the independent (or predictor) variables in this model. The
Pearson model fit test yielded a chi-square value of 272.49 with p-value of 0.3627, suggesting
the logistic model fits the data well.
Perceived Risk (PRR):
The perception of the risks regarding e-banking is expected to influence the adoption of electronic
banking system and the use of it by the customers too. As noticed or displayed on the above logit
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Royal Journal of Business Management (RJBM)
regression result, the customers fear related with, trusting the technology of e- banking and
Customers fear of risk of new technology innovation negatively affects the use of electronic
banking system by customers (B of odds ratio = -0.81929, and P value =0.094). This means the
customers that believe using electronic banking is a risky, use electronic banking system -0.81929
(81.929%) times less than the customers that believe using electronic banking system is not risky
at all.
Gender of the Customers (GofC):
The odds ratio for this variable is 0.66 and the ‘P value is 0.204. This showsthat sex of the
customers do not have a significant relationship with the use of electronic banking system in East
Gojam Zone.
Figure 2: Source: from own computation
System Compatibility (SC):
As clearly shown on the above regression result, the odds ratio for the variable system
compatibility is B = 0.958 and the ‘P’ value is P = 0.079, which means that customers that perceive
the system is consistent or in line with socio cultural believes or ideas use electronic banking
system more than customers that do not believe that the system is compatible. So, the variable
system compatibility positively and significantly affects the use of electronic banking system in
East Gojam Zone.
Age of the Customers (AC):
The odds ratio of the variable AC is B = -1.5619 and ‘P’ value = 0.0.001. This means the customers
with old ages use electronic banking system-1.5619times less than young age customers. This
shows that age ofthe customers significantly affects the use of electronic banking system in East
Gojam Zone.
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Gelaye, et al., 2022
Education Level of the Customers (EL):
As shown on the above regression result the beta coefficient foreducation level is 2.922, and the
‘P’ value is 0.0960.071 which means that the customers with education level of above grade12
uses electronic banking system 2.922 times more than the customers that are below grade
twelve. This shows that education is a significantcontributor for theuse of electronic banking
system in East Gojam Zone customers.
Promotion of the System by the Banks (Promm):
From the above regression result the odds ratio for promotion is B = -0.8395 and the ‘P’ value is P
= 0.119. This shows that promotion of the system do not have a significant relationship with the
use of electronic banking system by customers in East Gojam Zone.
Perceived Cost (PC):
From the logit estimation the above the odds ratio for the variable perceived cost is B = -1.067 and
the ‘P’ value is 0.06. This means the customers that perceive using electronic banking system is
costly, uses electronic banking system -1.067 times less than the customers that do not thought
that using electronic banking system is costly. So, the variable ‘perceived cost’ is significantly
affects the use of electronic banking system by customers In East Gojam Zone.
Perceived Benefit (PB):
From the regression result the variable of perceived benefit have a value of ‘B’ = 1.362 and ‘P’ value
= 0.121 which means that the the variable ‘perceived benefit’ do not have asignificant relationship
with the use of electronic banking system in East Gojam Zone.
Number of Branches (NofB):
As shown on the above regression result the variable number of branches have a B value of =
0.348 and P value = 0.65. Which means that number of branches do not have a significant
relationship with the use of electronic banking system in East Gojam Zone.
Flexibility of the System (FofS):
Flexibility of services or the system in the use of electronic banking system has a B value of = 0.50
and P value of = 0.525. It shows that the variable ‘system flexibility’ has no a significant
relationship with the use of electronic banking system in East Gojam Zone.
Accessibility of Networks (NA):
The variable ‘accessibility of networks’ have a value of B = 0.101 and P value = 0.876. Which means
that accessibility of networks do not have a significant relationship with the use of electronic
banking system in East Gojam Zone.
Knowledge of Customers (KofC):
The odds ratio of the variable knowledge of customers is B = -0.944 and P =0.140. This indicates
that the variable ‘knowledge of customers do not have a significant relationship with the use of
electronic banking system in Ethiopia, East Gojam Zone.
System Complexity (CofS):
The variable system complexity has B value of B = 0.134 and the ‘P’ value of 0.583. Which means
it does not have a significant relationship with the use of electronic banking system in East Gojam
Zone.
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Royal Journal of Business Management (RJBM)
Table 1:Summary of Results and Hypotheses Confirmation
Variable
‘P’ value Decision
Perceived risk (PRR):
0.094
Reject Ho @ 10%
Gender of the customers (GofC):
0.204
Fail to reject Ho
System compatibility (SC):
0.079
Reject Ho @ 10%
Age of the customers (AC):
0.001
Reject Ho @ 5%
Education level of the customers (EL):
0.071
Reject Ho @ 10%
Promotion of the system by the banks (Promm):
0.119
Fail to reject Ho
Perceived cost (PC):
0.036
Reject Ho @ 5%
Perceived benefit (PB):
0.121
Fail to reject Ho
Number of branches (NofB):
0.650
Fail to reject Ho
Flexibility of the system (FofS):
0.525
Fail to reject Ho
Accessibility of networks (NA):
0.876
Fail to reject Ho
Knowledge of customers (KofC):
0.140
Fail to reject Ho
System complexity (CofS):
0.582
Fail to reject Ho
CONCLUSIONS AND RECOMMENDATIONS
Conclusions
The general objective of the study was to determine factors that affect the use of electronic
banking system in East Gojam Zone, Amhara Ethiopia. In order to achieve the major objective,
there were two specific objectives.The first specific objective of the study was to determine the
effect of bank internal factors that influence customers to use internet banking and the second
specific objective of the study was identifying bank external factors that influence customers to
use internet banking system.
Based on the findings of the study from bank internal factors, System compatibility (SC) positively
and significantly affects the use of electronic banking system in East Gojam Zone. The other bank
internal factors like, Promotion of the system by the banks (Promm), Number of branches (NofB),
Flexibility of the system (FofS),Accessibility of networks (NA) and System complexity (CofS) have
been found that do not have a significant relationship with the use of electronic banking system
in East Gojam Zone according to this studies result. System compatibility is positively and
significantly related with the use of electronic banking system in East Gojam Zone. And the
reason for that is Compatibility is the degree to which an innovation is perceived as being
consistent with the existing values, past experiences and the needs of potential adopters. An
innovation canbe compatible or incompatible with socio-cultural values and beliefs; with
previously introduced ideas; or with client needs for innovations (Rogers, 1983) The compatibility
of an innovation, as perceived by members of a social system, is positively related to its rate o
fadoption (Rogers, 1983)
From bank external factors that affect the use of electronic banking system in East Gojam Zone
Perceived risk (PRR), Education level of the customers (EL) and Perceived cost (PC) found as
significant factors and Gender of the customers (GofC), Perceived benefit (PB) and Knowledge of
customers (KofC) have been found as insignificant factor to affect the use of electronic banking
system in East Gojam Zone
Perceived risk (PRR), negatively and significantly affects the use of electronic banking system in
the sense of that Perceived risk reflects the extent to which consumers are uncertain about the
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Gelaye, et al., 2022
consequences of buying, using or disposing of an offering. It is important to recognize that risk is
subjective. That is, the risk that a customer perceives in making a purchase decision may not really
exist (Hoyer & MacInnis, 2001) Risk or uncertainty regarding the most appropriate purchase
decision or the consequences of the decision is a significant variable influencing the total amount
of information gathered by consumers (Loudon & Bitta, 1993) Education level of the customers
(EL) it has a positive and significant relationship with the use of electronic banking system in East
Gojam Zone and the reason is that, There is a strong relationship between income and education
level. More educated consumers have more money available to spend, due to better education,
and this affects their life-styles. As people attain higher education, it affects which type of
products they buy, what kind of services they will use, what kind of stores to buy them in, and
what prices they are willing to pay(Wilkie, 1990) and finally, Perceived cost (PC) have been found
that it has a negative significant relationship with the use of electronic banking system and the
reason will be that according to(Rothwell & Gardiner, 1984) observaction, that there are two
fundamental sets of factors affecting user needs, namely price factors and non-price factors. To
this extent (Gupta, 1988) identifies price as a major factor in brand switching. If consumers are to
use new technologies, the technologies must be reason ably priced relative to alternatives.
Otherwise, the acceptance of the new technology may not be viable from the standpoint of the
consumer.
Recommendations
The main objective of the study was to identify the factors that affect the use of electronic
banking system in East Gojam Zone. based on the findings of the study, the following
recommendations are suggested to the concerned bodies. Perceived risk, level of education and
perceived cost have been found as negatively and significantly determining factors for the use of
electronic banking system in Ethiopia, Amhara, East Gojam Zone.
The problems can be simply managed and handled if they are attentively followed. Perceived risk
is simply a thought that using a technology will be risky but the bankers can handle this by giving
a brief explanation about the electronic banking system and machines and at the same time they
should deliver a high quality technology to get the confidence of customers over it.
Level of education may be difficult to handle fully but, if the bankers become strong enough they
can change the attitude of customers by using promotions, by preparing short training programs
and the like they can change the attitude and thought of customers about using electronic
banking systems. Only illiterates might find it hard to use but anyone who is keen to learn and
change will come to use the system if they get the chance of enough trainings.
Perceived cost can be eliminated or reduced by reducing the cost of transactions by using
electronic banking systems. Most of the time except ATM machines the others are free to transact
just like mobile banking CBE birr, M birr, internet banking etc. The bankers can solve this problem
by reducing the cost of transaction by ATM machines.
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Appendix I: Logit estimate results
Appendix II: Goodness of fit test
Appendix III: Test of multicollinearity
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Appendix IV: Test of model specification
Appendix V
Table 2: Operating Definition of Dependent and Independent Variables
Variable n
Variable definition
Measurement scale
UEBS
Use of electronic banking Dichotomous (1=use and (0= not)
system
PRR
315 Perceived risk
Ordinal(1=high,2= moderate, 3=low)
GofC
315 Gender of the customers
Dummy(1=male, 0=female)
SC
315 System compatibility
Ordinal(1=high, 2=moderate, 3=low)
AC
315 Age of the customers
Ordinal(1=20-30, 2=31-40, 3=>40
EL
315 Education level of the
Ordinal(1=below grade 12, 2=diploma,
customers
3=degree & above)
Promm 315 Promotion of the system
Ordinal (1=high,2=moderate, 3=low)
by the banks
PC
315 Perceived cost
Ordinal (1=high,2=moderate, 3=low)
PB
315 Perceived benefit
Ordinal (1=high, 2=moderate, 3=low)
NofB
315 Number of branches
Continuous
FofS
315 Flexibility of the system
Dummy(1=flexible, 0=not)
NA
315 Accessibility of networks
Ordinal (1=excellent, 2=good, 3=fair)
KofC
315 Knowledge of customers
Dummy (1=have knowledge, 0=no)
CofS
315 System complexity
Dummy (1=complex, 0=not)
Mean
34