The Impact of Virtual Banking Services Cost on Profitability:
Applied Study on Jordanian Commercial Banks
LUBNA AL-AMAWI, ASMA’A AL-AMARNEH, JAMILEH MUSTAFA, SALEH DAHBOUR
Financial and Accounting Sciences Department, Faculty of Business,
Middle East University,
Airport Rd., Amman,
JORDAN
Abstract: - This research aimed to investigate the virtual services effective provided by the Jordanian
commercial on banks' profitability; particularly banks listed at Amman Stock Exchange (ASE). This study
adopted an explanatory research design depending on the secondary method of data collection via financial
report analysis, panel, and quantitative approach was used. The data were analyzed using descriptive and
multiple linear regression used to provide an answer to the research questions. All commercial banks listed at
Amman Stock Exchange were included in the research sample and the study time period covers the years from
2010-2019. Specifically, the study used Net Profit Margin (NPM) and Tobin’s Q to measure profitability,
ATMs, Smart Cards, and Mobile & Internet Banking Services to measure virtual bank services. Moreover,
control variables were considered including liquidity and financial leverage. The study findings supported a
statistically positive relationship between the two variables, indicating that using virtual banking tools leads to
an increase in bank profitability. The study recommends that banks need focus on the disclosure of transparent
and clear information concerning the cost of virtual banking services and promote such services among the
main sector’s actors. This research contributes to the body's knowledge in two methods. First, the profitability
of banks was examined using virtual banking activities, and second, it was found that ATMs, Smart Cards, and
Mobile & Internet Banking Services affect banks' profitability measured by NPM and Tobin’s Q. Thus,
financial technology innovation could encourage the profitability of the Jordanian Commercial Banks.
Key-Words: - Virtual Banking Services, profitability, ATMs, Smart Cards, Mobile Banking, Internet Banking.
Received: January 3, 2023. Revised: May 23, 2023. Accepted: June 3, 2023. Published: June 13, 2023.
1 Introduction
The banking sector has a notable contribution
towards the facilitation of transactions, which
particularly aligns with the commercial banks'
attempt toward profitability achievement and
enhancement.
In relation to the above, banking services have
come to depend on digital transformation in the
face of dynamic technological environmental
forces, urging them to adopt and use digital forms
of virtual banking to meet the demands of financial
services users, [18].
Among the studies dedicated to this line of
knowledge is the study, [9], that investigated how
Internet banking intensity affects the profitability of
banks, their study includes both private and public
banks operating in India. They collect data from 67
commercial banks during the period from 2011-
2020. The intensity of online banking is presented
by the online banking transaction value and
volume, while the bank profitability is presented by
Return on Assets (ROA) and Return on Equity
(ROE) ratios. The results show that the intensity of
Internet banking (value and volume) increase the
bank’s profitability measured by ROA and ROE.
This positive impact is higher in public sector
banks as a result of economies of scale of
operation.
Generally speaking, a virtual bank refers to a
bank that offers retail banking services online or
through various types of E-Channels as opposed to
through physical entities. In other words, this type
of banking service encompasses online transactions
using the web, e-mail, and ATMs, which takes the
banking services to another level using financial
technology and developments to enhance the
experience of users and banking customers, [6].
Moreover, in the banking sector, new delivery
methods for depositor services have been
introduced throughout the years, including ATMs,
online banking, and phone centers and these have
contributed to greater scale economies than their
conventional equivalents, [19].
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Lubna Al-Amawi, Asma’a Al-Amarneh,
Jamileh Mustafa, Saleh Dahbour
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The study thus aims to examine and determine the
effect of virtual banking services cost on Jordanian
commercial banks' profitability using data gathered
from 2010 to 2019. Specifically, the study aims to
develop and propose a theoretical framework for
the cost of virtual banking services and Jordanian
commercial banks' profitability and to assess the
relative significance of virtual banks in terms of
importance among the banks.
2 Literature Review
2.1 Digital Transformation and Banks
Digitalization
The virtual bank concept can be traced back to the
virtual corporation analogy, where banks devoid of
branches and offices have legal addresses. In other
words, the website of the bank is the primary and
only department it has, through which data is
received concerning its services/products, their
uses, account status confirmation, and online
specialists’ advice, [28].
Moreover, the shift from traditional to
digitalized banking was made by banks to bring
about the offering of multiple services through the
Internet, as customers’ demands for electronic
services have grown throughout the years.
Transformation into digitalization began in
financial institutions through call centers and online
branches that mimic the services of physical
branches. More importantly, virtual banks offer
applications through smartphones referred to as
mobile banking to facilitate customers’
management of accounts through such phones at
their convenience. They can also conduct their day-
to-day financial transactions and avail of various
features, which is the main reason that prompted
banks to adopt digitalized processes. Generally
speaking; virtual banking has improved the
efficiency level of services provided by banks to
their customers.
The increase in the use of virtual services in
banks requires the determination of the needs of
customers and the reasons behind their inclination
towards adoption of virtual banking and services
offered and as such, banks continuously seek to
search for suitable channels through which services
can be offered for maximized profitability and
shareholders’ equity – in other words, virtual
banking services has a key role in lowering banks
costs and in reaching their objectives in
profitability, [2].
Furthermore, digital banking services offer
several advantages including but not limited to
reasonable cost and price as the services are offered
through digital channels at reasonable prices. Costs
are decreased through the internet’s ability to lower
service prices. Also, new services can be availed
from the customers’ convenience through ease of
use. Banks can also direct customers to third-party
services like e-commerce, invoice payments, and
tax payments via digital banking, while effortlessly
collecting and processing customer information. In
other words, digital banking greatly contributes to
the achievement of customer satisfaction, loyalty
confirmation, and profitability enhancement, [1].
2.2 Digital Transformation and Banks
Profitability
Banks' profitability can be classified based on two-
factor groups, namely internal and external factors,
with the former being those that management can
control through quality decision-making
concerning the banks' size, capital adequacy, credit
risk, effective administration, and revenue sources
of banks, [4].
[20], found that using tools of financial
technology in banking services significantly and
positively affects the bank performance measure by
Return on Equity (ROE) and the Nominal Interest
Rate Margin, while an insignificant but positive
impact was founded on Return on Assets.
On the other hand, [5], examining the financial
technology tools impact (Mobile banking, Virtual
teller machine (VTM), and Automated teller
machines (ATM),) on banks' performance for non-
financial using data from China, the findings
indicate that financial technology products have a
significant positive effect on banks' non-financial
performance. These products improve the bank’s
service quality, and employee performance
efficiency and increase customer satisfaction, at the
same time, these products help reduce the
perception of defects related to the difficulty of
use.
More importantly, the development of banks
went hand in hand with the revolution and
development of information communication
technologies (ICTs), which brought about the
transformation of procedures and processes among
banks. The method by that customers access
financial products and services is changing as a
result of digital development, [25]. New scenarios
and horizons for the financial service industry have
been opened through internet penetration.
Financial organizations are now providing their
services majorly via electronic mediums. Having a
substantial effect on financial performance is
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Lubna Al-Amawi, Asma’a Al-Amarneh,
Jamileh Mustafa, Saleh Dahbour
E-ISSN: 2224-2899
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considered due to the adoption of the Internet by
financial organizations, [16].
Suffice it to say, potential and current
customers’ satisfaction and the bank's performance
were the focus of the banking system’s
digitalization. Consequently, e-banking was
introduced as an e-payment system enabling banks
or financial institutions’ customers to carry out
various financial transactions through electronic
channels and means as opposed to conventional
brick-and-mortar visits. online banking system
connects to the core banking system that the bank
operates, unlike the traditional banking physical
provision of banking services, [23].
Literature has focused on the impact of banking
transactions' effect on profitability using different
banks' data plus they have generally supported a
positive and statistically significant correlation
between ATMs of old and new-generation banks
and their performance. It is evident that through the
adoption of new technologies, banks can respond
efficiently to customer demands for their
satisfaction. In this regard, online or e-banking
provides easy access, security of transactions, and
24/7 banking transactions, which ensure daily
operations, [14].
In relation to the above, automated routine bill
payments have minimized the physical presence of
clients in the banks' premises, and on top of this,
they can easily transact at a lower cost incurred by
banks. Notably, banking digitalization is not
confined to banking or mobile banking, yet it also
covers new technologies used in order to introduce
innovative business modules to the business model
of the banks.
3 Research Methodology
3.1 Population and Sampling
The research population includes all commercial
banks listed on Jordan's Amman Stock Exchange
(ASE). The banking sector was found to be suitable
owing to its economic development role of the
country and the easy access to reliable financial
statements, from which data was gathered to
examine Net Profit Margin and Tobin’s Q
(dependent variables) and financial leverage and
liquidity (control variables). The sample comprised
banks that have been active in the market and listed
in the ASE from 2010-2019. Data was gathered
from the banks’ annual reports as well as from the
annual bulletins in ASE accessible through the
database of ASE, [32].
3.2 Variables Definition
The study’s dependent variable is commercial
banks' profitability, which has several
measurements; but in this paper, two measurement
proxies were used, Tobin’s Q in market-based
performance plus Net Profit Margin (NPM) in
accounting-based performance, following prior
studies, [31], [15], [30], the calculation of which
involves the use of the following formulae;
NPMit = NI it /IC it
In the above formula, NPM it denotes the Net Profit
Margin ratio for bank i for the year t, NIit denotes
Net Income for bank i for year t, whereas ICit
denotes interest, commissions, and other bank
income for bank i for year t.
The market-based performance proxy; Tobin’s Q
was determined using the below formula;
Tobin's Q it = (MV it + TD it)/ TA it
In the above formula, Tobin's Q it denotes the
second profitability measurement, MV it denotes
the Equity of Market Value (JD) for bank i and
year t, while TDit denotes total debt for bank i in
year t. Lastly, TAit denotes bank i total assets for
year t.
Moving on to the control variables – such variables
were included to overcome the bias of bank size –
they included financial leverage and liquidity, and
they were included in the regression model owing
to their use in extensively applied measurement of
virtual banking services cost, serving as a proxy for
the ability of the bank towards profit generation,
[7], [22]. The formula used is as follows;
FLEVit = TD it /TAit
In the above formula, FLEVit denotes the debt to
total assets ratio of bank i, in year t, while TD it
denotes the total debt of bank i in year t. TAit
denotes the total assets of bank i in year t and it
goes to show that liquidity is a representation of
current assets, fewer inventories, to current
liabilities of bank i, in year t.
3.3 Regression Model and Hypotheses
The research used two empirical models to test the
main and sub-hypotheses and to determine the
effect of the cost of virtual bank services including
its three components, namely, Mobile & Internet
Banking, Smart Cards, and ATM (MBI Cost), on
profitability(NPM and Tobin’s Q). The models are
represented in the following formulae;
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𝑵𝑷𝑴it = 𝜷0 + 𝜷1 𝑴𝑩𝑰 𝑪𝒐𝒔𝒕𝒔 it +
𝜷2 𝑨𝑻𝑴𝒔 𝑪𝒐𝒔𝒕 it + 𝜷3 𝑪𝒂𝒓𝒅𝒔 𝑪𝒐𝒔𝒕𝒔it + 𝜷4
𝑸𝒖𝒊𝒄𝒌it + 𝜷5 𝑭𝑳𝑬𝑽 it + 𝜺 it
model (1)
𝑻𝒐𝒃𝒊𝒏𝒔𝑸it = 𝜷0 + 𝜷1 𝑴𝑩𝑰 𝑪𝒐𝒔𝒕𝒔 it +
𝜷2 𝑨𝑻𝑴𝒔 𝑪𝒐𝒔𝒕 it + 𝜷3 𝑪𝒂𝒓𝒅𝒔 𝑪𝒐𝒔𝒕𝒔it + 𝜷4
𝑸𝒖𝒊𝒄𝒌it + 𝜷5 𝑭𝑳𝑬𝑽 it + 𝜺 it
model (2)
Following a thorough literature review, the study
contends that the cost of virtual banking services
significantly affects Jordanian commercial banks'
profitability and accordingly, the objectives are
achieved by testing the following hypotheses;
H0a: The cost of virtual banking services does not
have a significant impact on profitability measured
by Net Profit Margin as a proxy.
H0a-1: The cost of mobile & internet
banking does not have a significant impact
on profitability, measured by Net Profit
Margin as a proxy.
H0a-2: The cost of ATMs does not have a
significant impact on profitability,
measured by Net Profit Margin as a proxy.
H0a-3: The cost of cards does not have a
significant impact on profitability,
measured by Net Profit Margin as a proxy.
H0b: The cost of virtual banking services does not
have a significant impact on profitability, with
Tobin’s Q as the proxy.
H0b-1: The cost of mobile & internet
banking does not have a significant impact
on profitability, with Tobin’s Q as the
proxy.
H0b-2: The cost of ATMs does not have a
significant impact on profitability, with
Tobin’s Q as the proxy.
H0b-3: The cost of cards does not have a
significant impact on profitability, with
Tobin’s Q as the proxy.
4 Results and Discussion
4.1 Descriptive Statistics
The descriptive statistics analysis of the findings of
the research variables concerning 130 firm-year
observations culled from 13 Jordanian ASE-listed
commercial banks are tabulated in Table 1, dating
from 2010-2019. Based on the figures in Table 1;
Tobin’s Q has a maximum value of 1.198, while
the minimum value is 0.904, averaging at 1.006,
and with a standard deviation of 0.060. This is
indicative of the variation among the commercial
banks in Jordan in light of their investment
opportunities based on their sizes. On the other
hand; the ratio of Net Profit Margin, has a
maximum value of 46.8% while the minimum
value is 1.3%, averaging at 28.3%, and with a
standard deviation value of 9.3%. Indicating that;
the sample banks average a positive ratio of net
income to the income of commissions and net
interest.
Table 1. Descriptive statistics of Jordanian
commercial banks' variables, 2010-2019, with 130
firm-year observations
Min
Max
Std. Dev.
Mobile &
Internet
Banking
(000) JOD
487.6
21,141.0
5,215.0
Mobile &
Internet
Banking to
total
assets.
0.03%
0.78%
0.21%
ATMs
Costs
(000)
JOD
323.3
40,197.0
8,690.4
ATMs
Costs
to
total Costs
1.37%
36.22%
9.08%
Cards Cost
(000)
JOD
64.1
34,045.6
9,270.0
Cards
Costs
To
total Costs
0.21%
12.47%
2.69%
NPM
1.39%
46.83%
9.34%
Tobin's Q
90.43%
119.84%
6.04%
Financial
Leverage
80.91%
93.50%
2.58%
Quick
ratio
11.88%
51.71%
8.50%
4.2 Multi-collinearity
Multicollinearity is an issue that happens when the
explanatory variables show a strong correlation
with one another, which means they are measuring
a distinct single thing, [10], and thus, t through the
correlations between the independent and control
variables, tests are run to ascertain the existence
of multicollinearity.
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The independent-control variables correlation
matrix is presented in Table 2, and in this regard,
[8], stated that multicollinearity becomes an issue
when high correlation exists between the
independent variables (r=0.9 and above). On the
other hand, [10], claimed that the issue of
collinearity arises with correlation constant of 0.80
or 0.90. Based on the values on the table, the
independent and control variables correlation
remained below 0.80 and thus, multicollinearity is
not an issue.
Table 2. The Correlations Matrix
Mobile &
Internet
Banking
to
Total assets
ATMs
Cost
to
total
Costs
Cards
Costs
to
Total
Costs
Financial
Leverage
Quick
Ratio
Mobile
&
Internet
Banking
1
ATMs
Costs
0.366**
1
Cards
Costs
0.451**
0.305**
1
Financial
Leverage
0.025
0.079
0.016
1
Quick
ratio
0.108
0.119
0.025
-0.202*
1
Notes:
** Correlation is significant at the 0.01 level (2-tailed).
*Correlation is significant at the 0.05 level (2-tailed).
4.2.2 Variance in Inflation Factor Test
Given that a lack of high correlation does not
always imply the absence of multicollinearity, the
matrix is also helpful in identifying potential
multicollinearity problems between explanatory
variables, [10].
The problem is dealt with by using the variance
inflation factor test and obtaining the values of the
independent variable. The criterion is such that
indicative of multicollinearity presence is tolerance
factor value which is near zero and variance
inflation factor higher than 10, [10].
Table 3. The independent and control variables
using Collinearity Statistics
Tolerance
VIF
Mobile &
Internet
Banking
0.672
1.487
ATMs Costs
0.415
2.412
Cards Costs
0.492
2.031
Financial
Leverage
0.943
1.060
Quick ratio
0.929
1.077
Based on Table 3, the variance inflation factor
values ranged between 1.060 till 2.412 while
tolerance factors ranged between 0.415 till 0.943,
indicating the absence of multicollinearity between
independent variables and their control
counterparts.
4.2.3 Outliers
Predictive analytics is used in data collection to
explain the form of normal data and to observe
unusual forms that deviate from the normal pattern
– such unusual forms are referred to as outliers. In
this study, Cook’s distance was used to detect
outliers, whereby the study obtained the regression
coefficient's difference between the one obtained
from the data, and another obtained from the
sample, with the exclusion of a case from the
process of estimation, [3]. In addition, if a case has
more than 1.0 Cook’s distance value, it is deemed
as an outlier as suggested by [26]. The Cook’s
distance calculated values are tabulated in Table 4.
Table 4. Cook’s Distance Test for Outliers’
Detection
Min
Max
Mean
Std.
Dev.
Cook’s
Distance
Model (1)
0.000
0.315
0.012
0.037
Cook’s
Distance
Model (2)
0.000
0.079
0.006
0.011
4.2.4 Normality
Normal distribution of data is also referred to as
rectangular distribution and it has equally
distributed values ranging between the smallest and
the largest one. In this regard, [13], stated that
normal distribution does not necessarily take a
symmetrical shape, as it can be bell-shaped
(suggesting the bell-profile). More specifically, the
Melville-Bell-shaped data represents that the mean
is the point at which most of the continuous
variable values are clustered. The Melville-Bell-
shaped data normal distribution reduces the chance
that extremely large or small values will occur,
despite the fact that the normal distribution can run
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4.2.1 Independent and Control Variables
Correlation
from negative infinity to positive infinity The
Melville-Bell shaped data normal distribution
reduces the chance that extremely large or small
values will occur, despite the fact that the normal
distribution can run from negative infinity to
positive infinity, [3]. Large-scale sample data from
this research was examined – a condition that may
not lead to the distortion of the outcome as a
considerable deviation from non-N may be ignored
owing to the sample size (over 100 observations),
[29], [11], [12], [3].
4.2.5 Testing the Autocorrelation
If the residuals are reliant on one another or if there
is a correlation between adjacent residues,
autocorrelation occurs in the model. Due to the
correlation, this ultimately affects the validity of
the linear regression analysis by increasing the
influence of the independent variables on their
dependent counterpart. This problem is verified
using the Durbin-Watson test in this study – this is
one of the most commonly utilized methods among
statisticians, with values ranging between 0 and 4.
According to [10], values closer to 0 are indicative
of a significant positive correlation between the
contiguous residues, whereas those closer to 4 are
indicative of a significant negative correlation. The
same author added that the optimal result, which
shows the absence of autocorrelation among
contiguous variables, ranges between 1.5 and 2.5.
Also, values calculated (D-W) closer to 2 show no
autocorrelation problem.
Table 5. The Durbin-Watson tests for
autocorrelation
Model
D-W
Model (1)
1.933
Model (2)
1.818
In Table 5, (D-W) statistics for the two models
were near 2, which indicates the absence of
autocorrelation.
4.3 Hypotheses Testing and Results
Discussion
4.3.1 Hypotheses Testing
The regression analysis conducted between
profitability and the independent variables, using
control variables yielded the findings tabulated in
Table 6. The model's strength was demonstrated by
its 35.0% R-square and 32.4% Adjusted R-square
values, which indicate that all independent
variables together explained 32.4% of the variation
in profitability across the control variables for the
complete sample of Jordanian commercial banks.
The results also show the F-statistic value to be
13.375, with 0.000 as the Sign. F. Therefore, the
model is significant at the level of 1%, and the null
hypothesis is rejected, while the alternative
hypothesis, stated as profitability measured by net
profit margin is affected positively via the cost of
virtual banking services, is accepted. This result is
aligned with that reported by past studies (e.g.,
[27], [21], [17]).
Table 6. Multi Regression Results for the first main
hypothesis (Model #1)
Variable
Coefficient
p-Value
Mobile & Internet
Banking
747.360
0.009
ATMs Costs
14.136
0.024
Cards Costs
8.178
0.000
Financial Leverage
-0.417
0.002
Quick Ratio
14.750
0.000
Model (1)
R Square
Adjusted
R Square
0.350
0.324
F-statistic
Sign.F
13.375
0.000
Dependent Variable: Net Profit Margin
Based on the research results, the investigated
dimensions of banking service costs have a positive
and significant impact on the profitability
(approximately net profit margin) of commercial
banks in Jordan.
In the same way, to assess the second hypothesis,
Panel Multi Regression was used, the findings in
Table 7; showed that the model's strong
explanatory power was demonstrated by its 64.3%
R-square and 62.8% adjusted R-square, which
show that all independent variables together were
explained 62.8% of the variation in profitability.
throughout the control variables for the total
commercial banks sample in Jordan.
In Table 7, the f-statistics value is 44.629, with
0.000 as Sign. F, confirming the significance of the
model at the level of 1%.
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Banking
ATMs Costs
0.237
0.003
Cards Costs
0.063
0.002
Financial Leverage
-8.760
0.916
Quick Ratio
0.136
0.000
Model (2)
R Square
Adjusted
R
Square
0.643
0.628
F-statistic
Sign.F
44.629
0.000
Dependent Variable: Tobin's Q
Based on Tobin’s Q results show that profitability
measured by Tobin's Q is significantly impacted
via virtual banking services cost, which is accepted.
In other words, the results supported the significant
impact of virtual banking services cost, through all
its dimensions, on profitability (Tobin’s Q) in the
context of commercial banks in Jordan.
5 Conclusion
The research sought to assess the effect of virtual
banking services cost on the profitability of the
ASE-listed Jordanian commercial banks from 2010
till 2019. The results showed that virtual banking
services costs, through its three components
(mobile & internet banking, ATMs, and cards), do
have a positive and significant impact on the bank’s
profitability, peroxide by net profit margin and
Tobin’s Q. The obtained findings have
implications to bank management, policymakers,
shareholders, and bank regulators in Jordan, as well
as, other relevant parties and entities.
Discussion: The effects on net profit margin may
signal that; investment in virtual banking services
will improve the standard that banks offer, plus the
efficiency of daily work which leads to operating
cost savings and increasing the net profit. Savings
in operating costs can be explained by the great
completion between the financial technology
providers who were forced to decrease their
commission to satisfy the customer (banks)
preferences and increase their market share, this
result is consistent with that of [24], Innovative
Financial Technology Solutions Significantly
Impair Current Performance of Indonesian Banks.
The positive impact on Tobin’s Q indicates that the
firm value improved by increasing the investment
in information technology to enhance the standard
of services offered to clients.
Limitations: One of the limitations of this study is
the refusal of the banks to disclose clear data
regarding their virtual services costs, thereby
urging the researcher to depend on financial
reports' explanations as an additional information
source and on the discussions with financial
managers of the banks.
Recommendations: This study recommends that
the banking sector focus on information disclosure
when it comes to the virtual banking services cost
and on promoting the sector actors’ investment in
them for positive developments and outcomes.
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Jamileh Mustafa, Saleh Dahbour
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DOI: 10.37394/23207.2023.20.115
Lubna Al-Amawi, Asma’a Al-Amarneh,
Jamileh Mustafa, Saleh Dahbour
E-ISSN: 2224-2899
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
-Lubna Al-Amawi: Conceptualization,
methodology, Writing - original draft, and
Validation
-Asma’a Al-Amarneh: Supervision,
Conceptualization, methodology, Writing - review
& editing and Validation
-Jamileh Mustafa: Validation
-Saleh Dahbour: Validation
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
The Middle East University, Amman, Jordan, has
provided financial assistance to cover the cost of
publishing this article, for which the author(s) are
grateful.
Conflicts of Interest
The authors have no conflicts of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.115
Lubna Al-Amawi, Asma’a Al-Amarneh,
Jamileh Mustafa, Saleh Dahbour
E-ISSN: 2224-2899
1297
Volume 20, 2023