The banking industry heavily relies on technology. One industry that consistently looks for ways to use technology to improve customer services is banking. A growing interchange route for the delivery of banking services is e-payment. India, the second largest telecom market in the world, has significant opportunity for growing online banking services. The factors influencing the extent of e-payment system acceptance in banking have been looked at in this paper. The survey captures the viewpoints of 225 customers of new generation private banks situated in the Cuddalore district. The level of e-payment system acceptability in banking has been determined using factor analysis. Accessibility was found to be the most important element on the acceptance level of epayment systems in banking in the study area, followed by adaptability, attentiveness, and security, according to the study.

1. https://iaeme.com/Home/journal/IJM 1944 editor@iaeme.com
International Journal of Management (IJM)
Volume 11, Issue 9, September 2020, pp. 1944-1950. Article ID: IJM_11_09_185
Available online at https://iaeme.com/Home/issue/IJM?Volume=11&Issue=9
ISSN Print: 0976-6502 and ISSN Online: 0976-6510
DOI: https://doi.org/10.17605/OSF.IO/ANK3D
© IAEME Publication Scopus Indexed
FACTORS OF ACCEPTANCE LEVEL OF
E-PAYMENT SYSTEM IN CUDDALORE
DISTRICT
Dr. V. Dheenadhayalan
Associate Professor, (On Deputation from Annamalai University),
P.G. Department of Commerce, Sri Subramaniyaswamy Govt. Arts College,
Tiruttani, Tamil Nadu, India
A. Yogalakshmi
Ph.D. Research Scholar, Department of Commerce,
Annamalai University, Annamalai Nagar, Tamil Nadu, India
ABSTRACT
The banking industry heavily relies on technology. One industry that consistently
looks for ways to use technology to improve customer services is banking. A growing
interchange route for the delivery of banking services is e-payment. India, the second-
largest telecom market in the world, has significant opportunity for growing online
banking services. The factors influencing the extent of e-payment system acceptance in
banking have been looked at in this paper. The survey captures the viewpoints of 225
customers of new generation private banks situated in the Cuddalore district. The level
of e-payment system acceptability in banking has been determined using factor analysis.
Accessibility was found to be the most important element on the acceptance level of e-
payment systems in banking in the study area, followed by adaptability, attentiveness,
and security, according to the study.
Key words: Financial inclusion, digital economy, cashless economy, e-banking, online
banking, mobile banking, e-payments.
Cite this Article: V. Dheenadhayalan and A. Yogalakshmi, Factors of Acceptance Level
of E-Payment System in Cuddalore District, International Journal of Management,
11(9), 2020, pp 1944-1950.
https://iaeme.com/Home/issue/IJM?Volume=11&Issue=9
1. INTRODUCTION
The conventional or traditional banking paradigm, which relies on human procedures, is no
longer followed by banks. The transition of banks from a distributed to a centralised
environment demonstrates the influence of technology on banks. In order to meet their clients'
needs and ensure their pleasure, banks are utilising innovative technologies and techniques and
providing them with specialised goods and services. Service providers are scrambling to bow

2. Factors of Acceptance Level of E-Payment System in Cuddalore District
https://iaeme.com/Home/journal/IJM 1945 editor@iaeme.com
down to the client, who is king. The financial service providers are attempting to offer their
services to clients while they are at home. The convenience of e-banking has made it a popular
channel for these service providers.
E-banking, often known as electronic banking, is a service that enables users to access their
bank accounts online, carry out financial transactions, make deposits and withdrawals, and pay
bills without having to physically visit their bank. One of the most recent technical
advancements, e-banking, is becoming a "Need to Have" service since it is becoming a need
for the average person. It speeds up and expedites routine client interactions while requiring
little to no paper work. In order to better understand how the acceptance level of banking
customers in the Cuddalore District E-banking services, the current study is being conducted.
2. REVIEW OF LITERATURE
Dixit (2010) says that technology development is modernising the way business is done. It
seems like internet banking has conquered the banking transactions among banking customers.
It was noted that Internet banking is a form of self-service technology.
E-banking was recognised as a crucial delivery channel that provided all-inclusive services
and information units to acquire a competitive edge in the banking industry, according to Malek
and Nik Kamariah (2011).
Eriksson et al. (2005) examined whether the banks' websites gave information solely or also
provided the option to do any transactions that did not meet the criteria for online banking
services. Many banking customers accept internet banking services due to a variety of reasons.
Wungwanit-Chakorn (2002) stated that compatibility and complexity of web banking affected
the acceptance of the usage.
3. OBJECTIVES OF THE STUDY
The main purpose of this study is to examine the factor of acceptance of e-payment system.
The following are the specific objectives of the study:
• To identify the factors of acceptance level of customer in respect of e-payment system.
• To rank the factors affecting customer acceptance level towards e-payment system.
4. RESEARCH METHODOLOGY
The customers who use new generation private banking services in the Cuddalore area made
up the study's target group. The customers were chosen using the convenient sampling
technique. 225 people made up the sample. The core data was gathered using a well-structured
questionnaire. The information was gathered during May and June of 2018.
The present study is based on both primary and secondary data. Secondary data has been
collected from journals, magazines, and the internet. The collected data were analysed using
descriptive statistics, reliability analysis, and exploratory factor analysis with the principal
component method and varimax rotation.
5. RESULTS AND DISCUSSION
The main objective of the present study is to find out the factors acceptance level of e- payment
system in Cuddalore district. The results of the data are presented below.

3. V. Dheenadhayalan and A. Yogalakshmi
https://iaeme.com/Home/journal/IJM 1946 editor@iaeme.com
Table 1 Response of Level of Acceptance on E-payment System
Statements
Strongly
Disagree Disagree Neutral Agree
Strongly
Agree
Frequency
Percentage
Frequency
Percentage
Frequency
Percentage
Frequency
Percentage
Frequency
Percentage
saves your time and Money
9 4 - - 9 4 73 32.4 134 59.6
Better than offline payment system.
9 4 2 0.9 20 8.9 107 47.6 87 38.7
Open 24 hours a day.
3 1.3 11 4.9 8 3.6 92 40.9 111 49.3
Transfer of money from one place
to another place is very easy. 3 1.3 6 2.7 7 3.1 96 42.7 113 50.2
Large numbers of user are satisfied
2 0.9 23 10.2 78 34.7 83 36.9 39 17.3
Get quick response 4 1.8 1 0.4 26 11.6 126 56 68 30.2
Reduce paper work 2 0.9 - - 2 0.9 63 28 158 70.2
It is very reliable service.
3 1.3 8 3.6 41 18.2 108 48 65 28.9
Hacker can access the information
9 4 31 13.8 56 24.9 79 35.1 50 22.2
Customer gets immediate alert
4 1.8 1 0.4 21 9.3 88 39.1 111 49.3
Need internet
2 0.9 1 0.4 30 13.3 127 56.4 65 28.9
Gateway play important role in e-
payment system. 2 0.9 2 0.9 32 14.2 142 63.1 47 20.9
Chance of making mistakes.
7 3.1 21 9.3 60 26.7 105 46.7 32 14.2
greater freedom to individual
2 0.9 5 2.2 48 21.3 123 54.7 47 20.9
Can be easily understood and
readily adopted.
2 0.9 27 12 44 19.6 131 58.2 21 9.3
Source: Primary Data
The study sought to establish the perceived usefulness of the e-payment system and the
findings show that the majority of the respondents (59.6%) strongly agree that the e-payment
system saves you time and money. 47.6 per cent agree that e-payment systems are better than

4. Factors of Acceptance Level of E-Payment System in Cuddalore District
https://iaeme.com/Home/journal/IJM 1947 editor@iaeme.com
offline payment systems, 49.3 per cent strongly agree that e-payment systems are open 24 hours
a day, and 50.2 per cent strongly agree that exchanging money from one location to another is
very easy. Further, 36.9 per cent agree that a large number of users are satisfied with the use of
e-payments, 56 per cent agree that e-payments get quick response, 70.2 per cent strongly agree
that e-payments reduce paper work, and 48 per cent agree that e-payments are a very reliable
service. About 35.1 per cent agree that hackers can access the information and records of e-
payment and 49.3 per cent strongly agree that customers have to be alert; they must deal with
only secured sites in which they are using an e-payment system. 56.4 per cent agree that we
need the internet and e-payment systems to use the experience. 63.1 percent of respondents
agree that gateways play an important role in the e-payment system; 46.7 percent of respondents
agree that there is a chance of making mistakes; 54.7 percent of respondents agree that e-
payment gives individuals more freedom in paying their taxes, licenses, fees, funds, and so on;
and 58.2 percent of respondents agree that the e-payment system is easily understood and easily
adopted.
To investigate the appropriateness of factor analysis, Kaiser-Meyer-Olkin (KMO) and
Bartlett’s test statistics were used. If the KMO value is greater than 0.6, it is considered
adequate. A value of greater than 0.5 is desirable. Bartlett’s test measures the correlation of
variables. A probability of less than 0.5 is acceptable. We found that the value of the Kaiser-
Meyer-Olkin measure of sampling adequacy is 0.702. That is greater than 0.06, which indicates
the value of Kaiser-Meyer is acceptable and the value of Bartlett's Test of Sphericity is also
statistically significant and acceptable.
Table 2 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .702
Bartlett's Test of Sphericity
Approx. Chi-Square 1310.363
DF 105
Sig. .000
Source: Computed Data.
In order to combine the variables into common factors, the factor analysis technique is
useful. Each variable is paired with the factor that it is most closely related to linearly. As a
result, factor analysis can show how a phenomenon is really put together. However, it should
be highlighted that only variables with linear relationships can be grouped using the factor
analysis. It may not be impossible for certain variables to have a nonlinear connection. The
number of variables resulting from the 15 variables of the acceptance of e-payments is displayed
in the following table.
Table 3 Total Variance Explained
Component
Initial Eigenvalues Extraction Sums of Squared
Loadings
Rotation Sums of Squared
Loadings
Total % of
Variance
Cumulativ
e
%
Total
% of
Variance
Cumulativ
e %
Total % of
Variance
Cumulativ
e
%
1
1
4.559 30.392 30.392 4.559 30.392 30.392 3.079 20.529 20.529
2
2
2.151 14.338 44.730 2.151 14.338 44.730 2.482 16.550 37.078
3
3
1.329 8.862 53.591 1.329 8.862 53.591 2.216 14.776 51.854
4
4
1.243 8.289 61.880 1.243 8.289 61.880 1.504 10.026 61.880
5 .978 6.522 68.402
6 .846 5.639 74.041
7 .824 5.491 79.532
8 .621 4.138 83.670

5. V. Dheenadhayalan and A. Yogalakshmi
https://iaeme.com/Home/journal/IJM 1948 editor@iaeme.com
9 .571 3.809 87.479
10 .488 3.251 90.730
11 .421 2.806 93.536
12 .313 2.089 95.625
13 .273 1.821 97.446
14 .221 1.476 98.922
15 .162 1.078 100.000
Source: Computed Data, Extraction Method: Principal Component Analysis
It is noted from the above table that 15 variables are converted into four predominant factors
with Eigen values of 3.079, 2.482, 2.216, and 1.504 and individual variances of 20.529
percentage, 16.55 percentage, 14.776 percentage and 10.026 percentage. The sum of the 15
variables' variance is 61.88 percent, which is statistically significant at the 5% level. It also
shows that the origins of four factors have something to do with how people feel about e-
payments. Scores are computed from the rotated factor transformation matrix, then these scores
are taken as independent variables, and overall satisfaction is taken as an independent variable
for the multiple regression analytic approach. Four factor scores for 15 statements are given in
Table 4.
Table 4 Rotated Component Matrix
Variables
Factors
Component
1 2 3 4
Better than offline payment system.
Accessibility
.876 .113 .048 .085
Exchange money from one place to
another place is very easy. .756 .077 .288 -.101
Saves time and money.
.722 .098 -.106 .292
provide greater freedom
.558 .306 .164 .088
Open 24 hours a day.
.519 .241 .112 -.188
Easily understood and readily adopted.
Adaptability
.007 .804 .063 .299
Large numbers of user are satisfied
.278 .789 .108 -.118
It is very reliable service. .338 .619 -.050 -.168
Get quick response .471 .549 .265 -.256
Gateway play important role in E-
payment
System. Alertness
.083 .103 .860 .019
Customer gets immediate alert
.214 .122 .667 .105
Chance of making mistakes.
-.059 -.441 .637 .195
Reduce paper work .404 .299 .460 -.102
Hacker can access the information
Security
.077 -.145 -.005 .823
Need internet
-.006 .133 .436 .651
Source: Computed Data.

6. Factors of Acceptance Level of E-Payment System in Cuddalore District
https://iaeme.com/Home/journal/IJM 1949 editor@iaeme.com
Table 4 highlights the prime four components which played a great role in adopting the e-
payment system. The rotated component helps in making a broad interpretation of five
parameters, namely, accessibility, adaptability, alertness, and security. The mean value of each
factor is calculated based on the mean value of all variables included under a particular factor
and presented in Table 4.
Table 5 Ranking of Factors
Factors Mean Rank
Accessibility 4.24 1
Adaptability 3.84 4
Alertness 4.16 2
Security 3.85 3
Source: Computed Data.
Table 5 shows the mean values of the factors. Among the four factors, the most significant
factor in e-payment is accessibility (4.24), followed by alertness (4.16), security (3.85) and
adaptability (3.84).
6. CONCLUSION
Over the past decade, a number of innovations have taken place in retail payments due to the
contribution of the telecommunication sector. These have reshaped payment processes and
changed the retail payments landscape by influencing users' choice of payment instruments. In
conclusion, e-payment systems have improved a number of factors that are crucial for the
competitiveness of banks, including the creation of new markets and the reduction of
operational, administrative, and manpower expenses. Therefore, banks should utilise these
benefits of e-payment in the Indian economy and offer their clients better services. Therefore,
the NGPS banks should concentrate and factor on the factors of accessibility, alertness, security,
and adaptability for the reach of banking facilities to the common people.
REFERENCES
[1] Dheenadhayalan, V. (2010). Automation of banking sector in India. Yojana A Development
Monthly, 54, 32-35.
[2] Dixit, N., (2010). Acceptance of e-banking among adult customers: an empirical investigation
in India. Journal of Internet Banking and Commerce, 15(2), pp. 1-16.
[3] Eriksson, K., Kerem, K., Nilsson, D., (2005). Customer acceptance of internet banking in
Estonia, International Journal of Bank Marketing, 23, 2, 200-2016.
[4] Malek AL-Majali & Nik Kamariah Nik Mat (2011). Modelling the antecedents of Internet
banking service adoption (IBSA) in Jordan: A Structural Equation Modeling (SEM) approach,
Journal of Internet Banking and Commerce, 16(1),1-13.
[5] Nabi, N. (2012). Customer expectations of service quality: A study on private banks of
Bangladesh. World Review of Business Research, 2 (4), 172-186.
[6] Prerna Dawar (2013). A study of factors affecting customer satisfaction in present highly
competitive banking industry. Asia Pacific Journal of Marketing & Management Review, 2 (2),
172-182.

7. V. Dheenadhayalan and A. Yogalakshmi
https://iaeme.com/Home/journal/IJM 1950 editor@iaeme.com
[7] Rajeev Kumar, & Anil Mittal (2015). Customer satisfaction and service quality perception
of technology based-banking services: A study on selected public sector banks in India. Global
Journal of Management and Business Research, 15 (5), 38-45.
[8] Timothy, A. (2012). Electronic banking services and customer satisfaction in the Nigerian
banking industry. International Journal of Business and Management Tomorrow, 2 (3), 1-8.
[9] Virk, N.,& Mahal, P.K. (2012). Customer satisfaction: A comparative analysis of public and
private sector banks in India. Information and Knowledge Management, 2, 1-8.
[10] Wungwanit-Chakorn, A., (2000). Adoption intention of banks’ customer on Internet banking
service, ABAC Journal, 22 (3), pp.63-80.