Universal Journal of Accounting and Finance 10(1): 62-71, 2022
DOI: 10.13189/ujaf.2022.100107
http://www.hrpub.org
The Effect of Perceived Risk on Intention to Use
Online Banking
Reepu1,*, Rakhi Arora2
1
Research Scholar, Department of Management, Chandigarh University, Punjab, India
Assistant Professor, Department of Management, Chandigarh University, Punjab, India
2
Received September 21, 2021; Revised November 13, 2021; Accepted December 23, 2021
Cite This Paper in the following Citation Styles
(a): [1] Reepu, Rakhi Arora , "The Effect of Perceived Risk on Intention to Use Online Banking," Universal Journal of
Accounting and Finance, Vol. 10, No. 1, pp. 62-71, 2022. DOI: 10.13189/ujaf.2022.100107.
(b): Reepu, Rakhi Arora (2022). The Effect of Perceived Risk on Intention to Use Online Banking. Universal Journal of
Accounting and Finance, 10(1), 62-71. DOI: 10.13189/ujaf.2022.100107.
Copyright©2022 by authors, all rights reserved. Authors agree that this article remains permanently open access under the
terms of the Creative Commons Attribution License 4.0 International License
Abstract Online banking is a major service for the
contemporary banking sector's expansion plan. Numerous
researchers have contributed to the research paradigm the
positive aspects of online banking. Consumers sense the
interconnectivity due to its presence online. Nonetheless,
this service was not extensively utilized due to consumers’
remaining afraid of the danger of online transactions. Users
fear to use such services online due to the prevalence of
different kinds of risks. Thus, the detailed and distinctive
risk job in risk awareness for the banking industry is an
important and useful task. The influence of perceived risk
in online banking use is investigated in this research. As it
has been regarded for the majority of times, perceived risk
serves as one of the major barriers towards usage of such
kind of services. The paper has set out the varied
categorical risks like privacy, social risk etc. which
influences the usage or intention towards usage of such
online banking services. The research model is envisaged
on the basis of different theories of information technology
acceptance. Questionnaire method was employed to obtain
responses specifically from female users of online banking.
Data collected were analyzed through Structural Equation
Modelling (SEM). Results have been analyzed well. The
findings of SEM show risk elements “privacy risk, security
risk, social risk, time risk, and financial-performance risk”
in perceived risk, which has a negative impact on desire to
utilize online banking. Research findings may assist in
suggesting ways to improve safety and mitigate online
banking risks prevalent among users.
Keywords Perceived Risk, Online Banking, Users
1. Introduction
The term internet banking is the supply of information
and services provided by the bank with the use of a
computer to its customers. More sophisticated services
provide customers the chance to check their accounts, carry
out transactions and even purchase online products via the
net. Internet banking provides banks with more facilities
and customers may obtain services. This means that
Internet banking users are interconnected via the Internet,
while mobile banking users are interconnected by wireless
devices.
Many of the characteristics for practices and the non-use
of Internet banking services may be mentioned in
underdeveloped nations. Ezeoha A.E. [17] is arguing in
Nigeria that internet services are so lenient than those of
industrialized nations and part of the continent of Africa.
Nigeria is classified as a new invention for online banking
services. Therefore, a sensitive subject in the Nigeria
banking industry may be enhanced for future purposes for
quality and quantity. Although online banking has several
advantages, such as faster transactions, speed, and
subordinate oversight duties, significant numbers of
customers still do not embrace Internet banking.
Featherman & Pavlou [18] has indicated that perceived
danger is proposed as a barrier to online banking adoption
by customers. When setting up Internet banking, danger
may either be observed through assaults of the system and
exchange of information or by untruthful and poor
verification via unlawful access to the account. Thus, many
problems from economic loss to secrecy may be addressed
through perceived risk.
Universal Journal of Accounting and Finance 10(1): 62-71, 2022
Like online purchases, internet banking adoption is
traditionally more complex since it ensures that users and
internet banking services have a long-term relationship.
According to Byrne B. M [9], a significant measure for
customers, as they contemplate entering a commercial
connection with reserved, unknown Internet banking
services, has been taken into account in many studies'
views on the dangers of embracing Internet banking.
Perceived risk changeable a single idea has previously
been shown to mimic the real characteristics of perceived
risk and explain why clients struggle against financial
services. Numerous research projects, however, have
previously taken into account the factors which affect IT
adoption or the internet in the past period of Heijden; the
partly experiential work by Taylor et al. [45] captures
elements or positive characteristics of Internet banking in
others to assist shape a tactical agenda.
Several studies have previously shown that the use of
internet services was hampered by issues of secrecy such as
Westin [49]; Ackerman, M et al. [1] etc. Users would want
to determine what kind of information is being gathered
and for what reasons, how long, and what purpose the file
is being processed. The research emphasized two ideas of a
reasonable act technology acceptance model to offer a
sound theoretical basis for checking the adoption of
internet banking services (Technology Acceptance Model).
The planned behavior hypothesis Davis, F. et al [13] Azjen,
I. [2] posits five risks: risk of safety, financial risk, social
risk, risk of time or convenience and risk of performance.
All of these dangers are linked to online banking. The
Internet banking issue as mentioned Haque et al. [24],
Durkin et al [16] have claimed that the acceptance and use
by majority of the banking customers of Online banking
services remains ineffective, notwithstanding of significant
internet banking savings by many monetary institutions
worldwide. The outcome is because of the perceived
danger associated with the use of online banking services.
1.1. Perceived Risk
Since the 1960s, perceived risk was employed to explain
client behavior (Forsythe S.M. and Shi B) [20]. The
perceived risk is a feeling of loss in Bauer, R.A. [8],
Dowling G.R. [15] defined risks as "a scenario in which
both alternative outcomes and their chance of occurrence
are a previous knowledge of the decision-maker."
The risk perception, in conjunction with risk inclination,
“is one of the drivers of risk behavior, according to Sitkin
S.B. and Pablo A.L. [43]”. In the context of internet buying,
Forsythe S.M. and Shi B [20] defined perceived risk in the
context of a "on-line shopping member's subjectively
decided anticipation of loss."
In the online transaction environment, some kinds of
hazards are significant. “Online-based transactions,
product performance hazards, financial risks, time and
mental health risks and other risk kinds, both for internet
and internet buyers, predominate (Forsythe S.M. and Shi B)
[20]. The scientists also discovered that the browsers saw
63
much greater financial, time and psychological hazards
than those of heavy and moderate consumers. Featherman
& Pavlou [18] showed that when participants perceive less
behavioral and contextual uncertainty”, they may see
greater control over the usage of online transaction.
Therefore, when the perceived risk is minimal (as opposed
to large), consumers may contemplate transacting using
online platforms. Uncertainties about the prospective or
current connection that needs website confidence are a
consequence of perceived risk, as reported by
Hampton-Sosa W and Koufaris M [23].
Yousafzai S.Y. et al. [51] has researched several models
aimed at showing that Internet banking consumers embrace
technology. The planned conduct theory (Ajzen, I., [3]),
“which extends the reasoned action theory (Fishbein, M.,
& Ajzen, I., [19]), include perceived behavioral control as
part of the models. The perceived behavioral control,
according to Ajzen, I., [3], comes from control beliefs that
deal either with accessible or unavailable resources and
opportunities and the expectation of barriers to targeting”,
for example, the adoption of Internet banking. The
technology acceptance model proposed by Davis, F et al.
[14] was another paradigm that was considered, “This
model shows the perceived utility and usability of
buildings. Both are closely linked to the results and the
technology's operationalization”.
Theory of planned behavior as well as the model of
technological acceptance is implicated in the risk
perception, particularly in terms of the trust that a
technology is beneficial to the work of a user.
Overall, the perceived risk affects adoption of internet
banking, Tan, M., & Teo, T. S., [44], Maditinos et al [30],
have had significant and bad effects on consumers’
acceptance by online banking of two different dimensions
of perceived risk: performance risk (e.g. problems of
connection, loss of data, etc.) and safety risk (e.g. data
transaction attacks). Barros L., et al., [7] connected the
perceived danger of debt and shown that the higher the
perceived risk of debt, the lower the risk of debt.
1.2. Performance Risk
The customer's evaluation of risk performance takes
their knowledge and rationale in a certain subject field into
consideration.
In the absence of individual contacts, the customer
cannot adequately evaluate the item's characteristics and
reduce safety in the form of asymmetry in Internet banking
data, the likelihood of failure and not execution, as
anticipated and advertised, and thus the desired benefit
deteriorated. A method of delivering advantages to
consumers may also be called a fear of loss if a variety,
product or dealer does not achieve the same thing as
planned. The risk of performance involves losses from
online banking platforms' deficiencies or shortcomings.
Sometimes customers are worried about system server
failure or website closure since circumstances may lead to
64
The Effect of Perceived Risk on Intention to Use Online Banking
unexpected fatalities.
1.3. Social Risk
Social risk is the concern about the probability that a
particular thing may lead to negative consideration and
response. The social well-being of the customer who uses
online banking services may be affected by the good or bad
perception of individuals, family or companions in Internet
banking management. People who perceive social
connections are more unwilling to create an elevating
attitude or positive approach to Internet banking consider
the numerous methods utilized to get their features. The
absence of human collaboration may prevent the utilization
of innovation-oriented infrastructures.
Social risk refers also to an imminent loss of rank in the
community gathering, as an effect of adopting items and
administrative systems that seem unfashionable. The
choice of using online banking may result in condemning a
family or group. It is conceivable that the social stand-up in
the field of online banking may be enhanced or diminished.
These people may have a disadvantageous or favorable
view of online banking. In other words, the views of its
adopters that Internet banking does not embrace may have
bad or good consequences.
primarily cultivated. It is also known as the possibility of
financial loss due to transaction errors or theft of bank
account. For example, reliable merchants carry inadequate
goods or even fail to provide goods to customers. People
sometimes pay money to revise difficult things. Again,
while dealing with the Internet, Master Card information
may be deleted.
1.6. Security Risk
Different studies have shown that security risks are
fascinating to customers with regard to security issues via
the highest Internet banking tests. This danger creates
security risks when consumers are ready to transfer money
from their own accounts or reliable economic information
to others who are deprived of their permission. The key
impediment to using online banking is security risk.
Improved safety in the defense of private information may
increase the degree to which online banking is made
available as has been suggested. Risk to security and
privacy is classified as a potential default owing to fraud or
a hacker that negotiates security for a user of an online
bank. Phishing is a different original misbehavior, where
Phishers try to trickle get sensitive information, such as
user names, passwords and subtle items from MasterCard,
in an automated message as a reliable object.
1.4. Time Risk
There is a combination of wasted time and effort in the
purchase of all items and services. When more time is
necessary to research how to get to a particular
administration, there is an increase in risk perception.
Customers are told that they are at risk when currency
transfers are not understandable in due course and mistakes
occur within the transaction period that reverts to period
loss. Discomfort and time may be a result of losses due to a
delay in payment or directing effort (discovery suitable
services and hyperlinks). It could not be feasible to
download two main reasons of discomforts to online
banking experience which could be seen as a time risk
involving a confusing website and pages that are so
sluggish. The time involved in the information about
perfuming online banking websites may be linked, and
time is wasted when consumers make a poor decision by
spending time exploring and completing their purchases,
learning to use the product only to replace it if the
expectations are not met.
1.5. Financial Risk
Risk also includes monetary risk, which in the processes
of online buying or purchasing is the probability of
economic loss. According to Ajzen, I., [2]; Aladwani A.M.,
[4] the loss of money as a result of the acquisition of goods
and facilities is in another manner around FR. In the risk
assessment of Internet banking customers, IT gaps and the
consequent losses in misleading client accounts are
1.7. Effect of Perceived Risk on Internet Banking
Intention
Studies have shown that the risk is regarded as a key
element and its link to online banking. Past research has
shown that the danger associated with deaths is more
noticeable than in usual circumstances in the Internet
banking exchange.
The concept of perceived risk first came from Bauer,
R.A. [8]. He identified the risks as regards instability and
results related to the actions of a customer. Consumer
researchers, for example, describe risk as a customer's
perception of hesitation and the unfavorable results of
buying an item (or facility). Risk perceived with the
associated negative effect increased vulnerability and size.
Risks were seen as multidimensional theory in a number
of research. Prior effort has been shown to include different
types of risk, including risk of performance, social risk,
time risk, monetary risk and security risk, which include
perceived danger. Zimund confirmed the importance of the
risk associated with the opportunity cost of a purchasing
option. It became known that customers needed more facts
to decide on a riskier alternative.
2. Literature Review
Halvadia, Nirav & Patel, Vipul [22] analyzed how the
attitude to Internet banking use of online trust and
perceived risk affects. This research examined the role of
Universal Journal of Accounting and Finance 10(1): 62-71, 2022
online trust in the context of Internet banking and the
perceived risk. Psychometric characteristics had been
evaluated using Cronbach alpha and the first order
confirmatory factor analysis for each perceived risk of
online banking (CFA). The second order CFA was then
conducted to assess each risk facet's relative significance.
Additional structural equation modeling using AMOS
software was conducted to investigate the effect on the
attitude to internet banking of perceived danger and online
trust. The sample included 200 adopters and no adopters of
online banking. The following aspects were identified:
security risk, financial risk, privacy risk, time-loss risk and
performance risk, and it was also discovered in the online
banking adoption that respondents did not see any social
danger. The findings indicated that the perceived risk
negatively affects the attitude to Internet banking adoption
whereas online confidence has a favorable influence.
Practical implementation: Indian banking sector requires a
publicity campaign to build online confidence and
minimize risk associated with internet banking. For bank
managers, it is essential to grasp how to build internet
banking online trust. Financial risk and time loss risk are
the main influencing factors for online bank adoption.
Bank managers should convey that Internet banking is
financially secure and saves your time with their target
audience. Structure Equation Modeling: Internet Banking,
online trust, perceived risk, internet banking behavior, first
orders CFA, second orders CFA.
In order to identify those variables affecting the desire to
use mobile bank services in Saudi Arabia, the study
conducted by Al-Jabri, I. M. [6] aimed to build and
evaluate a research model. The research used the Partial
Least Squares (PLS) to experimentally evaluate the model
using a paper-based survey of 253 respondents. With 66.7
percent of the variation in mobile banking intention, the
findings provide significant support for the validity of the
suggested model. The findings also showed that
compatibility was the most intentional factor, whereas
perceived danger was a barrier to mobile banking. The
connection between trust and perceived risk was
significantly bad and suggested that trust may reduce the
risk barrier that could affect mobile banking intention.
Unlike prior study, there was no substantial impact on
mobile banking's aim on perceived utility and perceived
ease of use. The consequences of the results were
examined and recommendations were given for further
study. Kassim N.M. et al. [25] identified risk variables
influencing the intention of continued use of Internet
banking in Malaysia. Personal Internet banking customers
in Peninsular Malaysia were the main participants. Data
have been gathered via a self-administered questionnaire
using the DOPU technology. Through this approach, the
questionnaires are disseminated to the various bank
managers who are ready to distribute. As requested, a total
of 413 interrogators were completed. For data analysis and
hypothesis testing, the SPSS statistical analysis software
and partial minimum squares have been employed. The
65
findings indicated that social risk, danger of time loss, cost
of opportunity and perceived utility are important variables
that affect your willingness to continue to utilize Internet
banking. Having the Internet banking system in Malaysia
will be influenced by a major aspect. Other postulated
connections are not important. A total of 413 interviewees
could not reflect the population as a whole. In addition,
interlocutor profiles were private and the management of
the institutions was not revealed. Therefore, for each bank,
it was not known the entire number of internet banking
clients. The results of this research should be very useful
for Internet banking service providers. A knowledge of the
variables indicated in the research enables internet banking
providers to improve services in the most efficient and
effective manner to possibly grow bank business in the
long term.
Namahoot, K.S. et al. [32] examined the relationships
between five dimensions of the quality of services with
overall compartmental intent to use Internet banking in
Thailand and the indirect effect between service quality
and compartmental intentions to use Internet banking as
mediation variables using perceived risk and trust. The 505
respondents for this research were selected using a
multi-stage sampling method. The participants were
chosen on the basis of their experiences in Thailand with
Internet banking. The data from participants were
examined using a modeling method using structural
equations. The findings demonstrate that the quality of
service, risk perception and confidence affect the behavior
of online banking. The main objective of the research is to
determine if perceived risks and trust were mediator
variables or the usage of online banking between service
quality and behaviors. When building a system in line with
prospective user requirements and lifestyles, and CEOs
establish strategies and appropriate policies in order to gain
the competitive advantage, the research should be helpful
to developers in internet banking.
3. Research Conceptual Framework
The factors of this research include perceived risk, risk
to performance, the social risk, time risk, financial risk and
security risks. The following framework describes the
connection between the perceived dangers of using the web
banking and the intention to utilize the web banking. This
study believes that the increase in risk that prospective
consumers perceive reduces the intention to use the
services of Internet banking. Thus, the link between
perceived risk and desire to utilize Internet Banking
Services is predicted to be positive.
3.1. Research Model and Hypotheses
“This study is based on theories of the IT adopted by
Chen C.S. [10], Littler & Melanthiou [29], Aldás-Manzano
et al., [5], Martins et al. [31], Khan et al. [26], Pikkarainen
et al. [39], TPB, UTAUT and other theories of IT adoption,
perceived risk theory, such Bauer, R.A. [8], Featherman &
66
The Effect of Perceived Risk on Intention to Use Online Banking
Pavlou [18], Park et al [36].” This research provides an
assessment of significant perceived risk effects on India's
desire to utilize internet banking, the corresponding
literature and the following assumptions.
(1) Perceived Risk
According to Littler & Melanthiou [29] Risk
perceived in decision-making about acquiring new
technology/services (RIS) is important. Many writers
demonstrate the kind of danger. “Some kinds of
hazards - privacy risk, safety risk, social risk, financial
risk, time risk and performance risk, are said to exist”.
The perceived risk is therefore a second order,
represented and deconstructed in its first order as a
composite variable.
Privacy Risk (PRR) is linked to the possibility of
exposure for direct marketers to personal information
from customers, whether inside or outside the
business. In the context of internet banking, when the
service is used by hackers or by banks to exchange
client documents with outsiders for another reason,
customers may screen for their identity. Chen C.S. [10]
and Yang et al., [50] research have shown that the
danger of privacy is a significant issue for customers
to decide whether to utilize it.
Security risk (SER) may be the most damaging
drawback of services with the external infringement
effect of the money taken Accounts and personal
details on financial inspections. With regard to online
banking, the danger of security arises when banks are
entered. Fraud or hackers may occur. Earlier studies
such as Chen C.S. [10], Aldás-Manzano et al., [5] and
Yang et al., [50] etc. have shown that security risk has
effects on Internet banking adoption.
Social risk (SOR) the potential for unfavorable
reactions from the consumer social webs has to do
with the social risk (SOR). Online banking involves
social risk as a result of a lack of contact or
engagement with the employees of the bank. The
research conducted by Chen C.S. [10], Featherman &
Pavlou [18], and Martins et al. [31] have shown the
detrimental effect of social risk.
Performance risk (PER) relates to concerns about the
performance of services or goods not as anticipated.
The risk of performance in the online banking
environment refers to harmful damage caused by the
bank failure or weakness. In research conducted by
Featherman & Pavlou [18], Litter & Melathiou,
Martins et al. [31] and Roy S.K. et al., [41] and others,
performance risk was addressed as an impediment to
on-line banking intention.
Financial risk (FIR) “The possible budgetary
expenditure not only linked to the original purchase
price but also the future product maintenance cost has
to do with the financial risk (FIR) or economic risk.
Financial risk may be seen as the investment cost of
computers or of the Internet in the context of online
banking. The financial risk is a major hazard in the
online adoption of banking, according to Chen C.S.
[10], Featherman & Pavlou [18], Martins et al. [31],
Roy S.K. et al., [41]”
Time Risk (TIR) is related to the impression that the
service is used and adoption is going to take too long.
Time risk refers to the duration of navigation time, the
learning of how to utilize online banking or the
repairing of erroneous transactions inside an online
banking environment. The study findings of Martins
et al. [31], Featherman & Pavlou [18] and Yang et al.,
[50], proved that the usage of internet banking
purpose is prejudiced by time risks.
Online banking speculated that perceived risks are
comprised of the aspects termed “privacy risk, security risk,
social risk, financial risk, time risks and performance risk”:
Chen C.S [10], Featherman & Pavlou [18], Littler &
Melanthiou [29], Martins et al. [31]. Therefore, we
assume:
H1: A second component to the perceived risk includes
six risks: risk to privacy, danger to security, social risk,
financial risk, time risk and risk to performance.
H1a: Privacy risk has positively related to perceived
risk.
H1b: Security risk has positively related to perceived
risk.
H1c: Social risk has positively related to perceived risk.
H1d: Performance risk positively related to perceived
risk.
H1e: Financial risk has positively related to perceived
risk.
H1f: Time risk has positively related to perceived risk.
(2) Intention to Use
The intention to use it (ITU), as consumers
unconsciously and intentionally perceive risks during the
conjecture or adoption of services or products, is
considered essential to include measurements of a
perceived danger of technology adoption. The combination
of loss probability – considered to enhance the danger - has
been discovered by Featherman & Pavlou [18] to prevent
the usage of internet banking. The perceived negative risk
impacts on intent according to Martins et al. [31] We thus
believe that:
H2: “Perceived risk negative effect on intention to use.”
3.2. Research Methods
The data will be reviewed in a study utilizing all
indications of research design skills for model
accreditation and research hypotheses. An investigation
was carried out using simple sampling to gather study data.
The surveys have been delivered through e-mail and
Google documents to respondents wishing to use and
employ online banking activities. 238 responses of female
were collected and 226 might be utilized (12 invalid
respondents). All variables evaluated using a 5 point Likert
Universal Journal of Accounting and Finance 10(1): 62-71, 2022
scale: (1) - a strong disagreement; (2) – a disagreement; (3)
a strong disagreement; (4) a strong disagreement;
responses were tested with IBM software including AMOS
and SPSS have been investigated using SEM (structural
equation modeling).
17.6% is less than 1 to 5 years. Bank account: accounts
with commercial banks (SBI, HDFC etc.) constitute 64.1%,
38.6%, and external banks (HSBC, Citibank, etc.) 6.2%”.
B.
Factor analysis exploratory and confirmatory
1)
4. Research Results
A.
Sample Statistics
The age group: 18-22 years is 61.7 percent plurality;
23-29 years old are 19.2 percent comparatively lower;
other age groups are relatively low. Gender: with 100%
female, there is no substantial difference. Education: in
terms of graduates of universities, graduates of various
degree programs and postgraduate degrees, the highest of
which is about 78.2%, “followed by university students of
13.7%, 8.1%, respectively. Revenue: 42-10% of the Indian
Rupee 5 million, Indian Rupee 5-10 million, Indian Rupee
11-20 million and Indian Rupee 11.2%. And lower
amounts of the other categories. Indian Rupee 5-10 million.
Job: about 45.0% of students, approximately 24.7% of
employees, 9.3% of managers at a lower level, and a
smaller proportion of other employers are employed. Use
Experience: 38.1% is 1 to 5 years, 23.4% is 1 to 5 years and
67
Exploratory factor
“The first EFRE (exploratory factor analysis) with EFA
factor loading <0.50[14] after removing six items - SOR4,
PER4, FIR3, FIR5 and TIR2 of Social Risk (SOR) and
TIR2, Time risk (TIR), Performance Risk (PER) and
Financial Risk (FIR)”. The second EFA, including 22
items, sorted according to the model, by each component.
It still contains one element – PER3 of the primary order
dimension of PER is combined into the first order element
Security Risk (SER). Four articles - PER1 and PER2 are
coupled with FIR1 and FIR2 of financial risk (FIR), and
this articulation is called "Financial risk performance risk"
(F-PR). “The F-PR component implies that the financial
risk interaction with the perceived risk performance risk.
All indicators range from 0.580 to 0.870 (> 0.5) to EFA
Factor Loading. The CR of the dimensions is also 0.691 to
0.880 (> 0.6) Composite reliability (CR) (Table I). H1d,
H1e and H1 are thus repurposed with the H1d-e and H1'
hypotheses”:
Table 1. Results of factor analysis
Talent/Indicators
PRR
SER
SOR
F-PR
TIR
ITU
PRR4
PRR2
PRR3
PRR1
SER1
SER2
SER3
PER3
SOR2
SOR1
SOR3
PER1
FIR2
PER2
FIR1
TIR3
TIR4
TIR1
ITU3
ITU4
ITU2
ITU1
“CR=0.849;AVE=0.613”
The bank may share user information to other parties
Payment information for users on OB may be exposed
OB user account may be taken by hackers
Others may use user information unlawfully
“CR=0.776;AVE=0.516”
The Internet is not financially secure
Bank systems may readily be used by hackers
Financial information and user information are not secure
OB cannot function as a publicity
“CR=0.691; AVE=0.504”
People surrounding OB are not appreciated
Other persons affect the usage of OB adversely
Think badly of the user who is incorrect
“CR=0.700;AVE=0.502”
Bank systems may decrease OB's performance
Money danger may arise if sloppy information is entered
OB may be a failure in the payment procedure
Money risk may arise if third party unlawful conduct
“CR=0.695;AVE=0.506”
It takes a long time to register/learn OB
It takes a long time to repair OB problems
It takes a long time to trade online
“CR=0.880;AVE=0.648”
Will utilize OB to do out bank transactions
Next time plan to utilize OB
Will frequently utilize OB in the future
Take OB for future usage
Table 2. Modeling results of structural equation
Factorloading
EFA
CFA
0.795
0.760
0.741
0.652
0.867
0.782
0.770
0.670
0.737
0.731
0.723
0.580
0.813
0.715
0.612
Eliminated
0.755
0.693
0.676
0.794
0.678
0.647
0.741
0.674
0.625
0.607
0.737
0.676
Eliminated
Eliminated
0.780
0.774
0.635
0.746
0.723
0.661
0.870
0.865
0.852
0.787
0.869
0.839
0.817
0.684
68
The Effect of Perceived Risk on Intention to Use Online Banking
H
Paths
Estimate
p-value
Result
H1a
RIS- PRR
0.863
***
Accepted
H1b
RIS- SER
0.788
***
Accepted
H1c
RIS- SOR
0.556
***
Accepted
H1d-e
RIS-F-PR
0.606
***
Accepted
H1f
RIS- TIR
0.486
***
Accepted
H2ITU
RIS
–0.228
0.028
Accepted
H1’: “A second dimension of five risks – privacy risk,
security risk, social risks, time risk and financial
performance risk is seen as a risk”.
H1d-e: Financial risk linked favorably to perceived risk.
Therefore, a revised model scale includes five first order
dimensions following the analysis of the exploratory factor:
risk of privacy, security risk, social risk, time risk and
financial risk, known as the perceived risk-induced
variable and the first-order-intensive risk-induced variable.
C.
Modeling of structural equation
Maximum likelihood (ML) estimations were carried out
in the SEM (structural equation modeling). This model
shows: “TLI = 0,934; RMSEA = 0.050 (p = 0,000),”
therefore the model shows acceptable adaptabilities. The
model theory displays: TLI = 0.934. Table II details the
SEM findings.
Of course, it was noted that the coefficients of β were
0,861, 0.786, 0,554, 0,604 and €0.484 (p<0,001)
correspondingly, “with PRR, SER, SOR, F-PR and TIR.
2) Confirmatory Factor Analysis
The analytical findings show that the risks perceived are
First-order— the first CFA, with a CFA loading factor considerably affected in all five areas - privacy risk, safety
less than 0.50 is removed after three indications - SER, risk, social risk, time risks and financial performance risk.
FIR1, PER2. The second CFA shows the following 19 The H1a, H1b, H1c, H1d-e and H1f theories will thus be
elements in its measuring model: “Chi-square (Translation supported. Furthermore, RIS has a negative impact on ITU,
2) (χ2)/dF = 1.572; CFI =0.945; TLI = 0.933; RMSEA where μ is -0.226 (p=0.028) and this is confirmed by H2 in
=.050 (P = 0.000). Then the measuring model is data turn. All assumptions have been demonstrated by the
compatible”. All CFA loading indices vary from 0.612 and findings of the analysis”. Figure 1 generally illustrates the
0.869 (> 0.5). The AVE accounts for 0.502 to 0.748 (> 0.50) perceived risk model of online banking purposes, including
of the average variance retrieved (Table I). The the model structure.
measurements are discriminating, because the AVE is
higher than the respective square correlation coefficients
(r2), thus achieving the scales. The measurements are thus 5. Result Discussions
qualified - the model has discrimination.
The analysis results revealed that the risk perceived
Second-order— The reflective second order factor reflects the second order of dangers in five prime order
CFA calculates relative Risk in the five risk categories of variables: privacy risk, security risk, social risk,
the display models - privacy hazards, security, social, time-related risks and financial performance risk. This
transitory, and financial concerns: “χ2/d = 0.933; research added to Bauer, R.A. [8] perceived risk theory via
TLI=0.945; RMSEA=0.050 (p=0.000)”, This indicates the a perceived risk factor and was compared to previous
model meets data extremely well. CFA calculates relative relevant studies, such as Chen C.S. [10], Featherman &
risk to measurement models of the measurement items with Pavlou [18], Littler & Melanthiou [29]; Aldás-Manzano et
perceived risk: H1' is thus supported Hypothesis.
al., [5].
Universal Journal of Accounting and Finance 10(1): 62-71, 2022
69
Figure 1. Risk perceived for online banking purposes
“Adjusted model The SEM findings showed the greatest
connection between the risk factors in terms of privacy and
perceived risk (μ=0,861), followed by the risk for security
(μ=0,786), the risk of financial performance (0,604), the
social risk (0,554) and the risk of time (0.484)”. In addition,
the perceived danger had an intentional impact (μ = 0.226).
Although this result is minor in comparison with Chen C.S.
[10], in the connection between online banking intention
and perceived risk, α is estimated to be -0.590 and -0.252
for two instances of regular and unusual users. Nonetheless,
these findings have a higher impact on the intention for
using online banks of a perceptive risk dimension than the
research by Featherman and Paulov [18], “Aldás-Manzano
et al., [5] or Martins et al. [31] ( in μ are –0,146, –0,200 and
–0,22010 respectively”.
This research adds to the perceived risk theory that
reflects the second order, models and decomposes it into
first order components – “privacy risk, security risk, social
risk, time risk and financial performance risk”. Another
reason why the study results explain the relatively
accomplished function of perceived risk in India's desire to
use online banking - This adds to the link between other
variables and online banking purpose and the whole theory
of IT adoption. Furthermore, the study results offer
management data for the Indian banks in their strategy.
purpose of usage”, are given by the EFA (Exploratory
Factor Analysis) retrieved under the suggested model. Two
components of first order known as financial risk and
performance risk are separated into one factor and a new
term is suggested as financial risk. Therefore, seven
original assumptions are downgraded. The first-order
factors of the CFA and Second Order Reflective (CFA)
demonstrate that measures are qualified — the model has a
distinctive value. The SEM (Structural Equation Modeling)
showed that a perceived risk (i.e., risk to privacy, risk of
safety, social risk, and risk of time and financial
performance) component has been modeled and broken
down into components of first order as a composite
variable. The perceived risk affects internet banking
intention. Of course, 7 out of seven theories presented are
accepted. The results of this research also show that the
perceived risk plays a relatively high influence in using
internet banking in India.
Although this research found how essential it was for the
intention to utilize online banking that the perceived risk
effect, certain limitations remain in the study. In future, a
bigger sample will be acquired, the study scope will be
expanded and measurements will be adjusted to take into
account developments in India and globally. It also must
include additional dimensions to IT adoption, including
demographic factors in the model, and not just perceive the
danger or desire to use as a study.
6. Conclusions
The results of the study revealed that all measurements
of the first and second order variables were recognized as
an independent variable, and the desire to utilize them as a
dependent variable that stabilizes confidence was termed a
first order factor. Five “primary variables, including
privacy risk, security risk, social risk, risk in time and
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