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International Journal of Management (IJM)
Volume 11, Issue 12, December 2020, pp. 4343-4350, Article ID: IJM_11_12_416
Available online at https://iaeme.com/Home/issue/IJM?Volume=11&Issue=12
ISSN Print: 0976-6502 and ISSN Online: 0976-6510
© IAEME Publication Scopus Indexed
DETERMINANTS AFFECTING THE USER'S
INTENTION TO USE MOBILE BANKING
APPLICATIONS
S.J. Sureya
Part Time Research Scholar, Assistant Professor, Department of Commerce,
Cauvery College for Women (Autonomous), Affiliated to Bharathidasan University,
Tiruchirappalli, Tamil Nadu, India.
Dr. V. Josephine Lourdes De Rose
Assistant Professor, Department of Commerce, Holy Cross College (Autonomous),
Affiliated to Bharathidasan University, Tiruchirappalli, Tamil Nadu, India.
ABSTRACT
The banking and financial services industries are experiencing increased
technology penetration. Among them, the banking industry has made technological
advancements to better serve the general populace. The economy focused on
transforming the banking sector's system into a cashless, paperless, and faceless one.
The researcher wants to evaluate the user's intention for utilising a mobile banking
application. The study also examines the variables affecting the user's behaviour
intention when selecting specific applications for financial transactions. The researcher
employed a well-structured questionnaire and a descriptive study methodology to
gather the respondents' primary data utilising the snowball sampling technique. The
study includes variables like performance expectations, effort expectations, social
impact, enabling circumstances, and perceived risk. Each of the aforementioned
variables has a major impact on how users utilise mobile banking applications. The
outcome will assist the service provider in comprehending the user's history with mobile
banking applications.
Key words: Mobile Banking Application, NEFT, RTGS, ECS, Net banking, SMS
banking, behavior intention, cashless transaction.
Cite this Article: S.J. Sureya and V. Josephine Lourdes De Rose, Determinants
Affecting the User's Intention to use Mobile Banking Applications, International
Journal of Management (IJM), 11(12), 2020, pp. 4343-4350.
https://iaeme.com/Home/issue/IJM?Volume=11&Issue=12

2. Determinants Affecting the User's Intention to use Mobile Banking Applications
https://iaeme.com/Home/journal/IJM 4344 editor@iaeme.com
1. INTRODUCTION
The banking crisis has been around for a very long time; the system begins with a deposit of
funds before granting an advance. Industrialization, socialisation, and the passing of time
reduced the quantity of services offered to satisfy customers while increasing the variety of
goods available. The institutions that were founded to transact in and accomplish money have
had a long and arduous journey. In 1991, the Indian economy had a great change in each sector
of economy and the changes affected the business, industries and Commerce. Among them
banking which is the backbone of an Indian economy also showed a notable development not
only in privatization, foreign investment, and globalization but also in implementation of
Technology. Electronic banking has replaced traditional banking in our era. It is the result of
technological development and contests. With the help of electronic banking, items are
marketed through a variety of channels, including phones, computers, automated teller
machines, mobile banking, and prospective services like NEFT, RTGS, ECS, Net banking,
SMS banking, and mobile banking. With the rapid expansion of smartphones, mobile banking
has become an essential component of the banking industry. The banks were able to create their
own mobile banking application thanks to the advancement in technology, which will benefit
the customer. Even private providers build their own payment gateways connected to banks to
serve the general market. These services were identified during the demonetization period in
preparation for a transformational space for the application of cutting-edge technology to
develop the economy into a paperless, faceless, and cashless system. Utilizing an IFSC code, a
mobile number, or a VPA over the UPI interface, a mobile banking application enables users
to send and receive money. The researcher is particularly interested in the elements that affect
users' intentions to utilise mobile banking applications for online transactions.
2. REVIEW OF RELATED LITERATURE
Erkek Ismail burak and altinbasak-farina ipek (2021) studied to understand the attitude and
intention of customers using mobile banking application for Digital transactions during covid-
19 lockdown. The researcher aimed at identifying generation differences in terms of usage of
mobile banking application. The study used comprehensive model derived from TAM. The
factors such as usability, ease of use, enjoyment, self efficacy, personal innovativeness,
security, performance, trust, attitude and intention were used in the study to evaluate the
generation difference in the usage of mobile banking application. The finding of the study
reveals that usability, financial risk, security, performance and enjoyment have positive impact
on the intention and attitude of using mobile banking application among the gender generations.
Ayesha akhter et al (2020) examined the factors affecting the intention of user to use
mobile banking services. The researcher examine six variables such as perceived usefulness,
perceived ease of use, trust, security, perceived privacy and Technology competency to analyse
the behaviour intention of Banking customers who use mobile banking services. The researcher
found that perceived usefulness, security and Technology competency found to be significant
influencer while user using mobile banking services in Bangladesh. Hence the researcher
suggests the financial institution to provide service more effectively to develop the organisation
goal and to accelerate customer willingness to accept and adopt mobile banking services.
Saji T.G and Deepa Paul (2018) examine the factors influencing the behaviour intention
of user using mobile banking in Kerala. The researcher used classical Technology acceptance
model to investigate the factors. Among the factors exogenous construct are used such as
perceived usefulness, perceived ease of use, perceived creditability, and perceived self efficacy.
The result reveals that all the factors have positive impact on the behaviour intention of the
users. Hence the financial institutions and bankers should focus on the attributes to raise their
product awareness among the users.

3. S.J. Sureya and V. Josephine Lourdes De Rose
https://iaeme.com/Home/journal/IJM 4345 editor@iaeme.com
Abhipsa Pal et al., (2017) analyzed the security concern in mobile payment system. The
researcher focused on the factor associated with mobile banking. The study examined that
responsibility plays a vital role in the mobile banking. Privacy concerns in the application
demand the user in adoption of MPS. This makes the user to find it stiff to adopt these
technologies in a fully trusted farm. Andy Oduro Boadu (2017) studied the factors
influencing the payment system in Ghana. The reveals that short term usage of money through
mobile banking application shows a positive impact on the volume of transaction. Hence the
study suggests having long term relationship between banking and financial institution and
progress towards cashless society.
AdityaSamant(2016) examine the technology and improvement in the quality of cashless
transaction. The structure drives the user to accept new payment technology for making
payments and other service like cash on delivery. The researcher found that users are awake of
cashless transaction, but certain concern like network issue, level of acceptance and transaction
charges are holding back the users from the adoption of new technology.
Junadi and Sfenrianto (2015) had studied on model factors influencing user acceptance
level of Electronic payment system. The researcher investigated intention level of users and
development a model by extending the unified theory of acceptance and usage of technology.
This model was constructed with perceived usefulness and perceived ease of use factors used
to identify the behavioural intention and the use of technology. While evaluating the model they
added two variables that are culture and security measures to know the impact of electronic
payment system. The study reveals that the two external factors such as culture and security
explains habit of user using electronic payment system and how secure the electronic payment
system in accordance with the condition of Indonesia society.
Ali AlSoufi and Hayat Ali (2014) had studied on perception of M-banking. The study
aimed at evaluating the factors influencing the customer perception in the adoption of mobile
banking. The study was extended using Technology acceptance model to identify its impact in
Bahrain. The researcher used slovin’s formula to determine the number of sample size. The
factors such as customer service, quality of service, alternative, perceived cost, risk, perceived
usefulness, and perceived ease of use used to measure its impact on M-banking. The result
reveals that perceived usefulness and ease of use have significant impact in influencing the
adoption of M-banking. The researchers suggest that service provider should consider the
above factors that will increase implementation of mobile banking service.
Ngoc Doan (2014) had studied on user adoption in mobile wallets and also evaluated the
market situation about mobile user towards wallets in Finland. The study reveals that at the
beginning of innovation decision process the adoption of mobile wallets increased. After that
user started to move to decision stage about adoption of mobile wallets became a challenge in
Finland. Security issues in transaction and privacy plays a dominant role in influencing the user.
Where users receive information mainly through internet and it has positive effect in increasing
usage of mobile wallets. The future research should focus not only new technologies, user’s
adoption level, merchant and so on. It is suggested to study the user satisfaction level towards
mobile wallet.
GaladimaTalatuet al (2014) had examined the impact on knowledge based trust on
adoption and acceptability of cashless economy. The study evaluated the impact of integrity
Technology Acceptance Model (TAM) with knowledge based technology. The study
recognized that both technology and trust based issues plays important role in influence the
adoption of cashless payment system. The result reveal that perceived risk has negative impact
on adoption of cashless economy and knowledge based technology helps to reduce the fear and
risk to live in smooth environment. In order to have additional support the individual’s

4. Determinants Affecting the User's Intention to use Mobile Banking Applications
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behaviour was evaluated by the impact of trust and risk on attitude and behavioural intention
towards acceptance and adoption of cashless system.
Seungjae Shin et al (2014) made a comparative analysis about users perception and
preference towards mobile payment methods in the US and Korea. The researcher aimed at
analyzing the Smartphone user’s perceptions and preferences toward mobile payment methods.
The variables such as security, convenience and cost are considering the main influencing
factors. The study reveals that mobile security has strong influencing power among the
Smartphone users in both countries. The service providers should provide the service in best
way and more secure transaction of mobile payment.
Sanghita Roy and Dr.Indrajitsinha (2014) had studied on customer’s acceptance of
electronic payment system in Indian banking sector. The study used to determine the popularity
and unpopularity of EPS, reasons and the level of awareness. The researcher finds various
factors which influencing the acceptance level such as perceived ease of use, perceived
usefulness , perceived Risk, perceived credibility and customer attitude are analyzed. It
conclude by indicating most and least influencing factor as perceived ease of use and custom
attitude in adoption of electronic payment system. However the customer should use more of
online payment system as if all technology will be friendlier with us.
Dr. Mohammad O. Al-Smadi(2012) had emphasised on factors affecting adoption of
electronic banking. The researcher aims in identifying the factors and would like to understand
the customer usage of electronic banking services. The study was analyzed using TAM model
with TPB and incorporates culture and perceives the risk to develop research model which
examine the factor that affects customer intention towards acceptance of electronic banking.
The findings reveal that perceived ease of use and perceived usefulness has positive impact on
uncertainty avoidance, where perceived risk have strong impact on customer's intention to use
electronic banking services.
Amir AbbasJovallahi (2013) examined the Customers confidence of electronic payment
system use in northern Cyprus. The researcher understood the level of trust on this island, the
study conducted with various nationalities with different academic levels. In order to increase
electronic payments among customers, the provider should concentrate on perceived trust and
perceived security and it provides an appropriate network to follow up the payment process.
Akhavan Saffar (2012) studied the service quality of electronic banking. The study
evaluated the network connectivity and the tech deployment is ease of use with banks. The
result reveals that trust, convenience, safety, liability and cash performance influence the
quality of banking service. The future study should on concern with transaction failure and
updating in banking sites.
Augsstine Takyi et al (2012) evaluated security system in online payments. The researcher
took online protocols and develops a conceptual framework to exist authentication of a
cardholder. This ensures to provide safety, ease, cardholder authentication, verification of
online will make easy to implement without any complication for online payment.
Jerry Gao et al (2009) this study presents an innovative mobile payment system based on
2- Dimensional bar code for mobile users. This system uses one standard 2D Bar code (Date
matrix’s) to deal with mobile business workflow, mobile transaction, and security issues and
also discuss system architecture
Singh Sumanject (2009) evaluated the emergence of payment systems in the age of
electronic commerce. In this research, the study explore that interested parties are exploring
various types of electronic payment system and issues in EPS and digital currency. The
researcher focused on EPS based on what is being transmitted over the network and analysis
the difference of each EPS factors.

5. S.J. Sureya and V. Josephine Lourdes De Rose
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3. OBJECTIVE OF THE STUDY
• To recognize the user's intention while utilizing a mobile banking application.
• To determine the elements impacting the user's intention when using a mobile banking
application.
3.1. Hypothesis of the Study
• There is no significant difference between the performance expectancy, effort
expectancy, social influence, and facilitating conditions with the behavioural intention
of the user using a mobile banking application.
4. RESEARCH METHODOLOGY
Using a descriptive research approach, the researcher created the study. The responders to the
study were given a standardised questionnaire to gather their initial data. The response from the
respondents is gathered using the snowball sampling approach.
5. ANALYSIS AND INTERPRETATION OF DATA
5.1. Regression Analysis
H0: There is no significant difference between the Performance expectancy, Effort expectancy,
Social influence and Facilitating conditions with the behavior intention of the user using mobile
banking application.
Table 1 ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 2488.623 4 622.156 100.893 .000b
Residual 1467.632 238 6.167
Total 3956.255 242
a. Dependent Variable: BI
b. Predictors:(Constant), FC, SI, PE, EE
Table 2 Model Summaryb
Model
R
R
Square
Adjusted
R
Square
Std.
Error
of
the
Estimate
Change Statistics
R
Squar
e
Chan
ge
F
Chan
ge
df1
df2
Sig.
F
Chan
ge
1 .793a
.629 .623 2.483 .629
100.
893
4 238 .000
a. Predictors: (Constant), FC, SI, PE, EE
b. Dependent Variable: BI

6. Determinants Affecting the User's Intention to use Mobile Banking Applications
https://iaeme.com/Home/journal/IJM 4348 editor@iaeme.com
Table 3 Coefficientsa
Model
Unstandar
dized
Coefficient
s
Standardi
zed
Coefficient
s
t
Sig.
Collinearit
y
Statistics
B
Std.
Error
Beta
Tolerance
VIF
1
(Constant)
-.899
.952
-.944
.326
FC .116 .073 .110 1.594 .112 .327 3.026
SI .310 .073 .298 4.225 .000 .312 3.041
PE .311 .069 .252 4.530 .000 .504 1.923
EE .395 .092 .254 4.283 .000 .442 2.246
a. Dependent Variable: BI
Inference
Regression analysis is used to assess the correlation between the user's behaviour intention and
the Performance expectation, Effort expectancy, Social Influence, and Facilitating
circumstances of a mobile banking application. The difference in mean group is explained by
an ANOVA table. F(4,238)=100.893, p=0.000 is the result. which is below the significance
level of 5%. As a result, it is evident that the regression model can adequately account for the
Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions with
Behavior Intention for the Study. Simple R and R squared correlation is displayed in the model
summary table. High levels of correlation between the variables are shown by the R value of
0.793, and R squared is 0.629, or 63 percent. Demonstrates the relationship between the
behaviour intention dependent variable and the performance independent variable The basic
association between R and R square is shown in the model summary table. The R value is 0.793,
indicating a high degree of correlation between the variables (Performance expectancy, Effort
expectancy, Social influence and Facilitating conditions). The constant B, also known as the
non-standardized regression coefficient, is explained in the coefficient table. It displays the
regression line's slope and describes the anticipated change in the variable of one unit. The
impact of the variable shifts by one unit, according to the coefficient result. The respondent's
behaviour intentions affect the user's expectations for performance, effort, social impact, and
enabling circumstances when utilising a mobile banking application. Hence the study reveals
that is significant difference between the Performance expectancy, Effort expectancy, Social
influence and Facilitating conditions with the behavior intention of the user using mobile
banking application.
6. FINDINGS OF THE STUDY
The factors influences the user using mobile banking application are Performance expectancy,
Effort expectancy, Social influence and facilitating conditions. Regression analysis shows the
relationship between the variables and also explains the impact level using coefficient table.
The result reveals that Behavior intention has strong impact on Performance expectancy, Effort
expectancy and Social influence of the user rather than facilitating conditions while preferring
application for transferring money. Hence the study reveals that is significant difference

7. S.J. Sureya and V. Josephine Lourdes De Rose
https://iaeme.com/Home/journal/IJM 4349 editor@iaeme.com
between the Performance expectancy, Effort expectancy, Social influence and Facilitating
conditions with the behavior intention of the user using mobile banking application.
7. CONCLUSION
Technology is being developed to persuade users to transact money online. The advancement
of technology penetration increases across the industries as banking and financial service
sectors. Among them banking sectors geared up to serve the people in the economic with tech
deployment. The economy concentrated to move the system of banking sector to be cashless
paperless and faceless system. The researcher identifies that performance expectancy, effort
expectancy, and social influence have an impact on the behaviour intention of the user. whereas
facilitating conditions has less impact on the intention of the user to prefer transferring funds
through a mobile banking application. Hence, the service provider should understand the
precedence of the user while developing a strategy for mobile banking applications.
REFERENCES
[1] Burak, E. İ. (2021). Covid-19’s Impact on Attitude & Intention to Use Mobile Banking
Applications. International Journal of Recent Technology and Engineering, ISSN: 2277-3878
(Online), Volume-10 Issue-2, 135-144. https://doi.org/10.35940/ijrte.B6226.0710221
[2] Saji, T. G., & Paul, D. (n.d.). Behavioral Intention to the Use of Mobile Banking in Kerala: An
Application of Extended Classical Technology Acceptance Model Author Information
Behavioral Intention to the Use of Mobile Banking in Kerala: An Application of Extended
Classical Technology Acceptance Model Behavioral Intention to the Use of Mobile Banking in
Kerala: An Application of Extended Classical Technology Acceptance Model. In
Metamorphosis: A Journal of Management Research (Vol. 17, Issue 2). SagePublication.
https://doi.org/10.1177%2F0972622518792802
[3] Akhter, A., Asheq, A. al, Hossain, M. U., & Karim, M. M. (2020). Exploring customer
intentions to adopt mobile banking services: Evidence from a developing country. Banks and
Bank Systems, 15(2), 105–116. https://doi.org/10.21511/bbs.15(2).2020.10
[4] Abhipsa Pal, S. D. ( 2017, March). Security in Mobile Payments:A Report on User Issues.
Indian Institute of Management Bangalore, 1-15
[5] Terán, L., Horst, C., & Rodriguez, B. F. (2016, April 28 ). Public Electronic Payments. A Case
Study of the Electronic Cash System in Ecuador. 2016 Third International Conference on
eDemocracy & eGovernment (ICEDEG),1-15.
[6] ABOLFAZL ALIZADEH, S. S. (2018, September ). Effects of Adoption and Satisfaction on
Word of Mouth In The Internet Banking Of Iran. Journal of Internet Banking and Commerce,
23(3),1-30.
[7] Aditya Samant, M. K. (2016). Cashless Transaction enabled by Technology and Improvement
in Quality of Services. Economy and Finance, 9-11.
[8] Junadi, &Sfenrianto. (2015). A Model of Factors Influencing User’s Intention to Use E-payment
System in Indonesia. Procedia Computer Science, 59(Iccsci), 214–220.
https://doi.org/10.1016/j.procs.2015.07.557
[9] Alsoufi, A., & Ali, H. (2014). Customers’ Perception of M-Banking Adoption in Kingdom of
Bahrain: An Extended of TAM. International Journal of Managing Information Technology
(IJMIT), 6(1), 1–13. https://arxiv.org/ftp/arxiv/papers/1403/1403.2828.pdf

8. Determinants Affecting the User's Intention to use Mobile Banking Applications
https://iaeme.com/Home/journal/IJM 4350 editor@iaeme.com
[10] Doan, N. (2014). User Adoption In Mobile Wallet: A Study of Users In Finland. Turku
Universisty of Applied Sciences International Business Bachelor’s Thesis,1–42.
https://www.theseus.fi/bitstream/handle/10024/86343/Ngoc_Doan.pdf?sequence=1
[11] Talatu O, G., Ibidapo O, A., & Emmanuel O, A. (2014). The Impact of Knowledge-Based Trust
(Kbt) on The Adoption and Acceptability of Cashless Economy in Nigeria. International
Journal of Computer Science and Information Technology, 6(2), 171–180.
https://doi.org/10.5121/ijcsit.2014.6213
[12] Shin, S., Lee, W., Korea, S., & Odom, D. (2014). A Comparative Study Of Smartphone User’s
Perception And Preference Towards Mobile Payment Methods In The U.S. And Korea. 30(5),
1365–1376
[13] Roy, S., & Sinha, I. (2014). Determinants of Customers’ Acceptance of Electronic Payment
System in Indian Banking Sector–A Study. International Journal of Scientific and Engineering
Research, 5(1), 177–187.
[14] Al-Smadi, M. O. (2012). Factors Affecting Adoption of Electronic Banking : An Analysis of
the Perspectives of Banks ’ Customers. International Journal of Business and Social Science,
67(4), 294–309.
[15] Chavosh, A. (2011). Comparing the Satisfaction with the Banks E-payment Services between
Degree Holder and Non-Degree Holder Customers in Penang-Malaysia. International Journal
of E-Education, e-Business, e-Management and e-Learning,1(2),103-109.
.https://doi.org/10.7763/ijeeee.2011.v1.21
[16] Al-Laham, A.-T. &. ( 2009). Development of Electronic Money and Its Impact on the Central
Bank Role and Monetary Policy . Informing Science and Information Technology , 6, 339-349
[17] Sumanjeet, S. (2009). Emergence Of Payment Systems In The Age Of Electronic Commerce :
The State Of Art University of Delhi , India. 2(2), 17–36.