1972 article text-3761-1-10-20200307 (1)

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Studies in Indian Place Names
(UGC Care Journal) ISSN: 2394-3114
Vol-40-Issue-36-February-2020
Copyright ⓒ 2020
Authors
An Empirical Study on Customers’ Extensive Usage of Netbanking Facility in Gobichettipalayam, Erode
District
Dr. T. A. Jayachitra1
and Nandini Jagannarayan2
Assistant Professor1
, Department of Economics, Avinashilingam Institute for Home Science and Higher
Education for Women, Coimbatore
Department of B.com (Banking & Insurance)2
, Avinashilingam Institute for Home Science and Higher
Education for Women, Coimbatore
ABSTRACT
Indian economy is moving towards the cash less transaction. The world of cashlessness is possible
through digital banking. Subsequently, steps towards demonetization of the economy has resulted in
tremendous growth in digital transactions in India .The government has encouraged more transparency
in transactions and increased internet facilities towards empowering the country’s economy. The
government’s focus on cashless transactions and globalization has forced to adopt digital banking, but,
there still is apprehensions on the users. This study focuses on customer’s perceptive on adaptability to
these revolutionary changes in banking. A primary survey was conducted using a structured
questionnaire on the 100 respondents in Coimbatore, district in Tamil Nadu. The collected data
through the questionnaire were analyzed statistically by using chi square technique. The results
indicate that the motivations for adopting digital banking have association with income levels of the
consumer usage of digital banking. The attitude towards the banks’ digital usage was mainly
determined by easy usage, time saving, banking services, the reliability and security and safety of
transaction accounted 68 percent. The study finally analyses the satisfaction level of the consumers
using digital banking services. The main factors which determine customer satisfaction in digital
banking are safety, accessibility, risk and safety level, easy reach of service, amenable service. There is
a significant relationship among customer experience, satisfaction and loyalty, which is related to
banking performance. The study establishes the fact that customers are in the process of getting
accustomed with digital banking and that despite all the challenges, their perception towards
digitalization is fast changing.
Keywords: Customers’ Perception, Digital Banking, Adaptability, usage, Consumer motivations,
Customers’ satisfaction.
INTRODUCTION
Digitalisation of banking services is a move towards providing banking services online which offers a
lot of advantages to the banks involved as well as to its customers. The shift from traditional to digital
banking is, to an extent, measured as the degree of civilisation.
Financial liberalisation and technological revolution have allowed the developments of new and more
efficient delivery and processing channels as well as more innovative products and services in banking
industry. Many banks, today, have digitalized their services and have offered more convenience to their
customers in accessing them. Customer retention and satisfaction have been their focus, of late. The
acceptance of online has become challenging in rural part of the country where people need awareness
and need to be more educated in availing the facilities.
Recognition to electronic transactions is provided by the Government of India as per its Information
Technology Act, 2000. The Reserve Bank of India regulates and supervises all the transactions put
through, electronically. The RBI has also issued its guiding principles with regard to risk and exercised
control on the computer and telecommunication system.
Jackfen S and Nattika (2016), bankers consider ‘minimizes inconvenience’, ‘minimizes cost of
transactions’ and ‘time saving’ to be important benefits and ‘chances of government access’, ‘chances
of fraud’ and ‘lack of information security’ to be vital risks associated with electronic banking. Banking
industry is also one of the influenced industries adopting technologies which are helpful in providing
better services to customers. Quality of service is improved by using technological innovations and has

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Authors
been made cost effective. But, however, customers’ adoption of these facilities is still posing to be a
challenge in such rural areas.
Many studies focused on customer preferences of specific banks have proved that they go in for
attributes like ease of banking, facilities offered by the banks, reputation of the bank and their interest
rates. Customers, today, do not prefer physically going to the banks and availing their services or
facilities. They prefer handiness. Hence, they prefer banking from home or using digital banking
services offered by their banks.
The service-quality attributes that the Internet banks must offer to induce consumers to switch to online
transactions and keep using them are perceived usefulness, ease of use, reliability, responsiveness,
security, and continuous improvement.
REVIEW OF LITERATURE
Sathye (1999) in a study attempted to observe the factors which may affect the adaptation and usage of
Internet banking by customers in Australia and found that’s absence of awareness and concerns about
security of information were the prime reasons coming in the way of adaptation to Internet Banking
among the customers. He recommended ways to overcome the said obstacles and said that
distribution/delivery of financial services should be made part of wholesome customer service strategy.
Tan and Teo (2000) in their research analysed the factors influencing the adoption of Internet Banking
by the users in Singapore using Theory of Diffusion Model (Rogers, 1983) and the Theory of Planned
behaviour (Ajzen, 1985). The research study aimed at analysing the factors like social norms and
perceived behaviour control influencing the adoption and use of internet banking. They concluded that
attitudinal and perceived behaviour control factors were more as compared to social influence factors
that affected them from adopting internet banking. The users had perceived it to be risky to use internet
banking but their confidence in the government’s support helped them overcome this fear and adopt
internet banking.
Suganthi, Balachandher, & Balachandran (2001)in their study in understanding the factors influencing
adoption of internet banking in Malaysia, found that convenience, ease and cost of accessibility were
most influencing factors for adoption of internet banking services. They recommended that awareness
among the consumers be increased by conducting campaigns for the same.
OBJECTIVE OF THE STUDY
The objectives of the current study are –
1. To ascertain the perception of digital banking in rural areas of Erode district
2. To assess the factors influencing the customers to adopt digital banking.
3. To ascertain the level of satisfaction of customers on digital banking.
METHODOLOGY INVOLVED
The Study: Period of the study was from May 2019 to December 2019. The study comprised of
different malls, university students, business people of Gobichettypalayam, Erode district in Tamilnadu.
Secondary: M.Phil / PhD Thesis, Journals and other periodicals.
Sample and Design: The study is designed to find the factors contributing to the customer adoptability
and usage regarding net banking with regard to their services provided br their respective banks. 100
banking customers of various banks were surveyed. The respondents belonged to the age group of 18 to
60years. Demographic and socio-economic factors like age, gender, occupation and income were
considered to be independent variables.
Tool for Data Collection: An interview schedule was administered to banking customers residing in
Gobichettipalayam. Snow ball sampling technique was adopted for the purpose
Tools for Data Analysis: Data has been analyzed using statistical packages. Frequency analysis was
used to analyse the demographic profile of the respondents. Hypothesis testing was done using Chi-
Squared test for socio-economic and banking habits at 5% significance level. Factor analysis was

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conducted to reduce 27 statements into factors five factors. Factor analysis was adopted to capture the
banking services mix on customer satisfaction in adopting the digital tool.. Factor analysis used to
analyse the data based on PCA with varimax rotation.
Bartlett’s test of sphericity and Kaiser-Olkin (KMO) measure were used to find out the suitability of
data set for factor analysis. The values that were high between 0.5 and 1 confirmed their suitability for
factor analysis, and any value lower than 0.5 showed their inappropriateness for the analysis.
Impact of Demographic Factors on Customer Satisfaction
RESULTS AND DISCUSSIONS
I. SOCIO ECONOMIC AND DEMOGRAPHIC PROFILE OF THE RESPONDENTS
Figure 1: Age wise/ gender-wise classification of the respondents
Figure 1 shows that, from among the respondents using digitalised banking services, a majority (59 per
cent) turned out to be males in the age group of 18-30 while, the older group constituted only 4 percent
and none among them were female.
Figure 2 :Gender-wise educational level of the respondents
It can be seen from the above figure that most of the male repondents (48 percent) are graduates.

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Authors
Figure 3: Genderwise occupation of the respondents
A Majority of the male respondents (29 percent) had their own business while 19 percent of the female
respondents were working.
II.SOCIO ECONOMIC PROFILE AND BANKING HABITS OF THE RESPONDENTS
Figure 4: Income profile of the respondents
The above figure shows that over 70 percent of the respondents earned between rs 20,00 andRs 30,000
and only one of the respondents earned above rs 30,000. Eighty three respondents saved their incomes
and were sixty seven percent of them held savings bank account while twenty five percent of them held
both saving and current account. Almost all of them used mobile banking. Majority (89 per cent) of the
respondents have been using mobile banking between one and three years. It should also be noted that
55 percent of the respondents held their accounts with reputed public sector banks.
HYPOTHESES TESTING USING CHI-SQUARE ANALYSIS
H0:There is no significant impact of customers income on usage of net banking.
Table 1 Age- wise usage of net banking
Income Usage of Net banking Total Chi-
Square
Df P value
Yes No
Below2500 2 0 2
13.39 6 .0.05
2500-5000 20 0 20
5000-10000 42 1 43
10000-15000 27 0 27
15000-20000 4 0 4
25000-30000 3 0 3
Above 30000 1 0 1
Total 99 1 100
From the above table it is observed that p<0.05, income plays an important role in the adoption of
digital usage and proved that this is positively correlated with the income level of the respondent.
H0:There is no significant impact of customers education on usage of digital banking.

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Table 2 Educational profile of the respondents using net banking
Income Usage of net banking Total Chi-
Square
Df P value
Yes No
High school 10 1 2
8.173 2 0.017UG 61 0 20
PG 28 0 43
Total 99 1 27
From the above table it is observed that p<0.05, education plays an essential role in the adoption of
digital usage of the respondent. More Educated people are expected to have more favorable attitudes
towards adoption of innovations. Therefore the null hypothesis is rejected.
H0:There is no significant impact of customers age on usage of digital banking.
Table 3 Income profile of the respondents using net banking
Income
(in Rs 000)
Usage of digital anking Total Chi-
Square
Df P value
Yes No
18-30 59 0 59
13.030 3 0.03
30-40 24 1 25
40-50 12 0 12
ABOVE 50 4 0 4
Total 99 1 100
From the above table it is observed that p<0.05, age plays an significant role in the adoption of digital
usage level of the respondent.
H0:There is no significant impact of customers education on the frequency of usage of digital banking.
Table 4 Educational profile and their usage of net banking
Educati
on
Frequently do you use net bank
Daily-
once
Daily
Several
times
Weekly-
Once
Weeklys
everal
times
Monthly
-once
Total Chi-
Square
Df P
value
High
school
6 2 3 0 0 11
UG 22 13 25 0 1 61 23.507 8 .006
PG 3 5 19 1 0 28
Total 31 20 47 1 1 100
From the above table it is observed that p<0.05, education also plays an significant role in the frquency
of digital usage and proved that this is positively correlated with level of the respondent.
EFFECTS OF DEMOGRAPHIC FACTORS ON CUSTOMER SATISFACTION
III. FACTORS INFLUENCING THE RESPONDENTS TO USE DIGITAL BANKING
SERVICES
All the respondents used digital banking services. They all used mobile banking which confirms their
awareness. From among the respondents surveyed, a majority(54 per cent) of the respondents are aware
about mobile banking through their friends and relatives and a significant amount of them (48 percent)
came to know about mobile mobile banking from the personnels of the banks with which they hold their
accounts.
IV. CUSTOMER PERCEPTION ABOUT DIGITAL BANKING
1.Popularity of digital banking

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Table 5: Reasons to use digital using on Convenience factor
Reasons for preferring mobile banking Number of respondents
24*7 Access 89
Time saving 83
Prompt service 67
Easy and quick transactions 72
Highly reliable 69
Easy to learn and use 81
Table 6 Reliability Statistics for Convenience factor
Cronbach's Alpha Cronbach's Alpha Based on Standardized Items No of Items
.649 .692 6
Table 6 shows us the reliability statistics of convenience factor. It can be said that based on the six
factors of convenience, they been contributing the popularity of mobile banking the below listed are the
sub-factors under convenience factor.
Table 7 Inter Correlation Matrix for Convenience factor
Inter-Item Correlation Matrix
24*7
access
Time
saving
Prompt
service
Easy and
quick
transactions
Highly
reliable
Easy to
learn and
use
24*7 access 1.000 .777 .415 .474 .157 .351
Time saving .777 1.000 .238 .372 -.011 .218
Prompt service .415 .238 1.000 .092 .121 .197
Easy and quick
transactions
.474 .372 .092 1.000 .227 .254
Highly reliable .157 -.011 .121 .227 1.000 .205
Easy to learn and use 81 .218 .197 .254 .205 1.000
Over 80 percent of the respondents prefer using digital banking as it gives them 24*7 access, time
saving and its easy to learn and use the app. While over 60 percent of them opined that they use digital
banking because of its propmt service, ease of transactions, high reliability and simple service.
Cronbach’s reiabilty show the factors resonsible for the popularity of digital banking. These six factors
have contributed greatly to the popularity of digital banking among the respondents of the are.
Table 8 depicts the problems or concerns of digital opined by the respondentsas perceived by them
Table 8 Reliability Statistics for Accessibility factors
.710 .716 4
Table 8 shows the reliability test for accessibility factors put together. From the above table, it can be
said that accessibility is one of the factors which has contributed to the popularity of mobile banking.
The below given are the sub-factors of accesibility.
Table-9 Accessibility factors
Concerns of the users No of respondents
Safety of personal information and hacking 76
Worried about security IN transaction 77

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Digital battery consumption of the apps 70
Customer queries getting resolved promptly 69
Over 70 percent of the respondents were worried about their safety and personal information getting
leaked, how secure would their transactions be, avoiding getting hacked and dicsconnection of network
or the specific transaction while transacting. They were a;so concerned about the receptivity of the
services and how soon their queries would addressed by the customer care executives.
Their satisfaction parameters could be measured by frequency of usage. About 51 percent of them put
through banking transactions using their mobile phones everyday. While over forty per cent of them
used it several times a day and they opine that ease of use, time saving factor and user friendly are the
aspect that made them use net banking extensively.
Table 11 Reliability Statistics for Risk factors
.663 .675 2
Table 11 shows the reliability statistics for risk factors. This confirms the risks, as opined the
respondents are prevalent in net banking.
The reliability statistics table
Table 10 Inter-Item Correlation Matrix for Risk factors
Factors
Safety of personal
information and
Hacking
Worried about
security IN
transaction
Digital
battery
consumption
of the apps
Customer queries
getting resolved
promptly
Safety of personal
information
and hacking
1.000 .684 .376 .374
Worried about security
IN transaction
.684 1.000 .238 .272
Digital battery
consumption of the
apps
.376 .238 1.000 .374
Customer queries
getting resolved
promptly
.374 .272 .374 1.000
Table 12 Reliability Statistics for Receptive factor
Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items
.747 .731 4
Table 13 Item-Total Statistics for Receptive factor
Factors
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Squared Multiple
Correlation
Cronbach'
s Alpha if
Item
Deleted
Safety of personal information
and hacking
11.3700 2.417 .654 .623 .620
Worried about security IN
transaction
11.3600 2.374 .717 .699 .583

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Digital battery consumption of
the apps
11.6400 2.293 .652 .463 .619
Customer queries getting
resolved promptly
12.0400 3.635 .182 .096 .846
Table 14 Reliability Statistics for availability
Cronbach's Alpha
Cronbach's Alpha Based on
Standardized Items No of Items
.744 .744 7
Table 15 Item-Total Statistics for availability
Factors Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected
Item-
Total
Correlation
Squared
Multiple
Correlation
Cronbac
h's
Alpha if
Item
Deleted
A high number of softwares 20.4600 5.705 .491 .356 .706
Wide range of anytime, anywhere access
to financial services
20.4600 5.867 .484 .449 .708
Bank providing information /data 20.4700 5.646 .615 .457 .677
Banks provides material associated with
its services
20.9000 6.394 .367 .219 .733
Address security concerns by outlining
security measures
21.0600 6.340 .397 .194 .727
Front-line staff in promotion of mobile
banking
21.1200 6.187 .493 .292 .707
Websites that allow an easy visualization 21.0300 6.474 .369 .210 .732
Table 16 CRONBACH'S RELIABILITY TEST
S.No Groups Cronbach's Alpha
1 Convenience 0. 649
2 Accessibility 0.710
3 Risk 0.663
4 Receptive 0.747
5 Available 0.744
Table 16 depicts that customer satisafaction is based on the above four factors as the Cronbach’s Alpha
is above 65% for Convenience, Accessibility, Risk, Receptive, Available.

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Figure -5 path diagram for consumer usage of net banking
Table -17 Chi-Square Test of Model Fit
Value 444.08
Degrees of Freedom 239
P-Value 0.00
/df
1.86
The null hypothesis is that there is no difference between the patterns observed in these data and the
model specified. So, unlike many cases where you are hoping to reject the null hypothesis, in this case
the investigators certainly do NOT want to reject the hypothesis that this is a good fit. As you can see
from my chi-square value above, this model is acceptable.
The Chi-Square Test shows the model fit and p value shows its signifinance level, Although the seems
good, it is also appropriate to check the value of Chi-Square divided by df (Wheaton, Muthen, Alwin
and Summers,1977) as the Chi-Square statistic is particularly sensitive to sample sizes (that is, the
probability of model rejection increases with increasing sample size, even if the model is minimally
false), and hence chi-square divided by degrees of freedom is suggested as a better fit metric (Bentler

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and Bonnett, 1980). It is recommended that this metric not exceed five for models with good fit
(Bentler, 1989). For the current CFA model, as shown in above table Chi-Square is 1.86, suggesting
acceptable model fit.
Another measure of goodness of fit is the root mean square error of approximation (RMSEA).
Table-18 RMSEA Test of Model Fit
Estimate 0.093
90 Percent C.I. 0.079 0.11
Probability RMSEA < 0.05 0.00
An acceptable model should have an RMSEA less than .05. You can see above that the estimate for
RMSEA is .093, the 90 percent confidence interval is 0.11, .079 and the probability that the population
RMSEA is less than .05.Again, consistent with our chi-square, the model appears to fit. This can be
interpreted as meaning that the model explains the correlation to within an average error of 0.093 (Hu
and Bentler, 1990). Hence the model shows an overall acceptable fit. The model is an over identified
model.
Table-19 Inter Construct Correlation Matrix
Convenience Accessibility Risk Receptive Available
Convenience 1
Accessibility 0.63 1
Risk 0.01 0 1
Receptive 0.07 0.26 -0.05 1
Available 0.48 0.4 0.01 0.4 1
Table 19 depicts the correlation matrix of independent the hypotheses is tested relating to the pattern of
causal structure linking several variables that bear on the construct of usage intention of internet
banking. Usage Intention is influenced by the Convenience, Accessibility, Risk, Receptive
andAvailable on Internet Banking.
Table-20
Hypotheses β Supported/ not supported
Convenience related to the
usage of net banking
-0.26* supported
Accessibility related to the
-0.022* supported
Risk related to the usage
of net banking
0.42* supported
Receptive related to the
-0.036* supported
Available related to the
0.68* supported
*Significant at 0.01 level
All hypotheses are accepted. Consumer intention to use internet banking is influenced by Convenience
(β=- 0.26), Accessibility (β=0.22), Risk (β=0.42), Receptive (β=0.036), and
Available (β=0.68).
Hypotheses Latent construct β Supported/ not
supported
24h Access related to the usage of net banking Convenience 0.32* supported
Time saving related to the usage of net banking Convenience 0.29* supported
prompt service related to the usage of net banking Convenience 0.20* supported

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Authors
in speedy retrieval of account information related to
the usage of net banking
Convenience
0.31*
supported
services ;easy and quick related to the usage of net
banking
Convenience
0.071*
supported
Reliable related to the usage of net banking Convenience 0.19* supported
does not need much training related to the usage of
net banking
Accessibility
0.58*
supported
not require a mental effort related to the usage of net
banking
Accessibility
0.47*
supported
Learning IS easy related to the usage of net banking Accessibility 0.26* supported
Simpler/clearer service related to the usage of net
banking
Accessibility
0.31*
supported
Free of unsafe personal information related to the
Risk
2.53*
supported
Worried about security IN transaction related to the
Risk
0.063*
supported
Mobile banking inquiries receive responses within the
stipulated turnaround time related to the usage of net
banking
Receptive
0.58*
supported
Employees are knowledgeable to queries related to
Receptive
0.66*
supported
customer concerns v related to the usage of net
banking
Receptive
0.52*
supported
flexible to customers’ need related to the usage of net
banking
Receptive
0.067*
supported
a high number of software’s related to the usage of
net banking
Receptive
0.45*
supported
wide range of anytime, anywhere access to financial
services related to the usage of net banking
Available
0.44*
supported
Bank providing information /data related to the usage
of net banking
Available
0.47*
supported
Banks provides material associated with its services
related to the usage of net banking
Available
0.21*
supported
Address security concerns by outlining security
measures related to the usage of net banking
Available
0.23*
supported
Front-line staff in promotion of mobile banking.
related to the usage of net banking
Available
0.31*
supported
Websites that allow an easy visualization related to
Available
0.29*
supported
*Significant at 0.01 level
All hypotheses are accepted. Consumer intention to use internet banking is influenced by Convenience
factor which contains 24h Accessability (β=0.32), Time saving (β=0.29), prompt service (β= 0.20),
speedy retrieval of account information services (β=0.31),;easy and quick (β=0.071) and reliable
(β=0.19 ). In according to accessibility is influenced by not much training (β=0.58), not require a mental
effort (β=0.47), easy learning (β=0.26), and Simpler/clearer service (β=0.31). Under risk factors safe
personel information (β= 2.53),security in transaction (β=0.063). Under Receptive factor Mobile
banking inquiries receive responses within the stipulated turnaround time (β= 0.58), Employees are
knowledgeable to queries (β=0.66), customer concerns (β=0.52) and flexible to customers’
need (β=0.067). In respective to availability factor, a high number of software’s (β=0.45), wide range of
anytime, anywhere access to financial services (β=0.44), Bank providing information /data
(β=0.47), Banks provides material associated with its services (β=0.21), Address security concerns by

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Authors
outlining security measures (β= 0.23), Front-line staff in promotion of mobile banking.( β= 0.31)
and Websites that allow an easy visualization (β=.29).
To sum up, the research were carried to have better understanding on the movitational factor that
influence the usage of net banking. Here we classified the factors under five factors say
convenience, accessibility, risk, receptive and availablility which helps to judge the intensity to adopt
net banking were emprically validated with model fit for internet banking acceptance was successfully
verified.
CONCLUSION
The empirical results of the current study show that there is a direct relationship between internet
banking service quality, customer perception and satisfaction of the customers in a semi-urban area
(Gobichettipalayam, Erode District) dimensions and customer satisfaction in the banking industry. An
understanding of the factors, revealed in the study, though there were security concerns, the advantages
were more prominent than the drawbacks. This has led to the popularity of usage of net banking among
the customers of banks in Gobichettipalayam.
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1972 article text-3761-1-10-20200307 (1)