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4 ANALYSIS
4.1
INTRODUCTION
This chapter will analyze the data obtained from the survey and will test the different
hypotheses developed. This is an important chapter as it is the basis for a researcher to
analyze the data obtained, test various hypotheses in relation to the research objectives
and draw conclusive inferences as a further step toward making feasible
recommendations.
4.2 Gender
A gender analysis has been carried out on the respondents. This is presented in the table below and illustrated using a bar chart
Frequenc
y
Percent
male 53 54.6
female 41 42.3
Total 94 96.9
System 3 3.1
97 100.0
gender
femalemaleMissing
C o u n t
60
50
40
30
20
10
0
\
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4.3 Age
The age group of the respondents are given below :
Age
Frequency
Percent
less than
20
31 32.0
20 to 35 40 41.2
35 to 50 16 16.5
above 50 7 7.2
Total 94 96.9
It is noted that 32 % are less than 20 years , 41 percent are between 20 to 35 while 24 %are above 35 years old .This information is shown below :
Age
above 5035 to 5020 to 35less than 20Missing
C o u n t
50
40
30
20
10
0
4.4 Education
The level of education is an important factor in the use of internet . In this respect a crosstabulation has been carried out to identify the level of education of the respondents . This
is shown below :
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lessthan 20
20 to 35 35 to 50 above 50 TOTAL
primarylevel
4 6 10
up to SC 19 9 4 32up to HSC 11 18 5 6 40
university 1 9 1 1 12
31 40 16 7 94
From the above table , it is noted 10 respondents have received primary education and
10 respondents are university graduates .
32 and 40 respondents have read up to School certificate and Higher School certificate .
The distribution of the level of education of the respondents are given below :
Education
universityup to hscup to scprimary levelMissing
C o u n t
50
40
30
20
10
0
4.5 Occupation
Occupation is also a determining factor in the use of internet . In order to obtain a better
understanding of the profile of the respondents , a cross tabulation has been carried out
between employment and education . This is shown in the table below:
Employed Employed Student unemploy self
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public
sector
Private
sector
ed employed
primary
level
4 1 3 2 10
up to sc 13 9 1 2 7 32
up to hsc 15 16 3 3 3 40universit
y
2 7 3 12
34 33 4 8 15 94
Most of the respondents are either employees of the public sector ( N=34 ) or employeesof the private sector ( N=33)
4 respondents are students , 8 are unemployed and 15 have their own businesses.
The distribution of the level of education of the respondents are given below
occupation
sel employed
unemployed
Student
Employed Private sec
Employed piublic sec
Missing
C o u n t
40
30
20
10
0
4.6 Frequency of usage
Respondents were required to state the frequency of using internet banking . rthis isshown in the table below
Frequency Percent
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rare 10 10.6often 40 42.6regularly 44 46.8
Total 94 100.0
10 respondents rarely used this service , 40 respondents. often use the service and 44respondents use the service on a regular basis
This information a has been illustrated in a bar chart below
How often you use the service
regularlyoftenrare
C o u n t
50
40
30
20
10
0
Type of services
The type of services used by the respondents are given below
Services Number of
respondents
Inter bank fund
transfer
46
Payment to other 23
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personal account
Payment to other
local bank
13
Verifying my
account details
74
Order checks book 12Stop lost/stolen
check
4
apply for credit limit
change
5
standing order
transaction
45
Saving/current/fixed
deposit account
67
foreign account 17
debit/credit card 24
From the above table , it is noted that three services are widely used by respondents :
Verifying my account details N=74
Saving/current/fixed deposit account N=67
standing order transaction N=45
The services which are rarely used are
(a) Stop lost/stolen check N=4(b) apply for credit limit change N=5
(c) Payment to other local bank N=13
4.6 INTERNET BANKING
4.6.1 Ease of Use
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Ease of use is a factor that determine the frequency and intensity in the use of internet
banking .in this respect respondents were required to give their views on a set of 8
statements . The result from the analysis is given in the table below :
S.D D N A S.A MEAN S.DI find internet banking to beflexible to interact with
2 26 2 64 0 3.2766 1.0308
I can use internet banking
without anyone around to showme
1 34 0 56 3 3.3617 .9600
I can access various servicessimultaneously
2 26 2 64 3.3191 .8578
I find it easy to learn to useInternet Banking
1 21 19 53 3.7128 .6819
I require further training in
using the internet
12 3 79 3.5106 .8519
Internet banking makes it
easier for me to do my banking
1 16 0 74 3 3.6596 .8367
Generally I find online banking
easy to use
10 20 2 62 0 3.2340 1.1209
In order to interpret the above data , the following scale has been used
Mean :between 1 and 2 very low
Mean : between 2 and 3 lowMean : between 3 and 4 moderate to high
Mean between 4 and 5 very high
It is found out that mean scores fall in the range of 3.2340 to 3.7128. This demonstratethat ease of use is not a factor that inhibit the use of internet banking . The highest mean
score relates to learning while the lowest factor relate to the ease of using internet
banking
The information above has been further analyzed through hypothesis testing . The aims is
to identify the critical factor that determine the use of and accessibility to internet banking in term of
(a) Gender
(b) Age group(c) Level of Education
(d) Occupation
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The result from the tests are discussed below:
The first test seek to determine as to whether gender is a factor that determine the ease of
use or accessibility to internet banking
H0 : Gender is a factor that determine the ease of using internet banking
H1 : Gender is I not a factor that determine the ease of using internet banking
The test result is given below :
Ranks
gender N Mean
Rank
male 53 44.43female 41 51.46
Total 94
Test Statistics
EASET
Chi-
Square
1.565
df 1
Asymp.Sig. .211
a Kruskal Wallis Test
b Grouping Variable: gender
A Kruskal Wallis Test has been carried out to determine whether gender is a factor
that influence the ease of use or accessibility to internet banking At the statistical significance level of p=.05. , the test give evidence for accepting the
null hypothesis ( p= . .211) . As such there is not sufficient evidence to reject the null
hypothesis i.e Gender is a factor that determine the ease of using internet banking
Age
The second test seek to determine as to whether age is a factor that determine the ease of
use or accessibility to internet banking
H0 : Age is a factor that determine the ease of using internet banking
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H1 : Age is not a factor that determine the ease of using internet banking
The test result is given below
Ranks
Age N MeanRank
EASET less than
20
31 45.69
20 to 35 40 45.94
35 to 50 16 60.66
above 50 7 34.36
Total 94
Test StatisticsEASET
Chi-
Square
5.723
df 3
Asymp.
Sig.
.126
a Kruskal Wallis Test
b Grouping Variable: Age
A Kruskal Wallis Test has been carried out to determine whether age is a factor thatinfluence the ease of use or accessibility to internet banking At the statistical significance level of p=.05. , the test give evidence for accepting the
null hypothesis ( p= . .126) . As such there is not sufficient evidence to reject the null
hypothesis i.e Age is a factor that determine the ease of using internet banking
Education
The third test seeks to determine as to whether age is a factor that determine the ease of
use or accessibility to internet banking
H0 : Education is a factor that determine the ease of using internet banking
H1 : Education is not a factor that determine the ease of using internet banking
The test result is given below
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Ranks
Education N MeanRank
primary
level
10 61.75
up to sc 32 44.50
up to hsc 40 43.79
university
12 56.00
Total 94
Test Statistics
EASET
Chi-Square 5.120
df 3Asymp.
Sig.
.163
a Kruskal Wallis Test
b Grouping Variable: Education
A Kruskal Wallis Test has been carried out to determine whether education is a
factor that influence the ease of use or accessibility to internet banking At the statistical significance level of p=.05. , the test give evidence for accepting the
null hypothesis ( p= . .163) . As such there is not sufficient evidence to reject the null hypothesis i.e Education e is a factor that determine the ease of using internet banking
Occupation
The fourth test seeks to determine as to whether occupation is a factor that determine
the ease of use or accessibility to internet banking
H0 : Occupation is a factor that determine the ease of using internet banking
H1 : Occupation is not a factor that determine the ease of using internet banking
The test result is given below :
Ranks
occupation
N MeanRank
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Employe
d piublicsector
34 45.96
Employed Private
sector
33 52.94
Student 4 32.25
unemplo
yed
8 54.81
sel
employed
15 39.20
Total 94
Test Statistics
EASETChi-
Square
4.725
df 4
Asymp.
Sig.
.317
a Kruskal Wallis Test
b Grouping Variable: occupation
A Kruskal Wallis Test has been carried out to determine whether occupation is afactor that influence the ease of use or accessibility to internet banking At the statistical significance level of p=.05. , the test give evidence for accepting thenull hypothesis ( p= . .163) . As such there is not sufficient evidence to reject the null
hypothesis i.e Occupation is a factor that determine the ease of using internet banking
Summary of findings :
The above results shoe that the age , gender , occupations ans education are factors
that determine the ease that respondents use of internet banking
AWARENESS OF THE SERVICE
This section deals with the level at which respondents are informed on the use of internet banking .
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The responses are tabulated below:
S.D D N A S.A MEAN S.D
I have enough information
about Internet Banking
1 18 3 69 3 3.5851 .8726
I'm aware of the benefits&
risks in Internet Banking
34 21 39 2.4681 1.3496
I have enough informationabout how to use Internet
banking
0 16 7 69 2 3.6064 .7927
I have received information on
internet banking from various
means and sources
0 5 3 78 8 3.9468 .5749
The mean score on three statements are in the range of 3.5851 and 3.9468. This showsthat respondents have a high amount of information on the use of internet banking .
However , a poor score( M=2.4681) has been achieved on the statement dealing with
information on risk . As such , respondents feel that they are not well informed on therisk of using internet banking
As with the previous analysis , the relationship between information and the followingfactors (i.e gender , age , occupation and education have been further explored . These are
discussed below:
Gender
The aim of this test is to determine as to whether male and female respondents share acommon view on the above four statements
As such , the first test is as follows:
H0 : Gender is a factor that determine the awareness of using internet banking
H1 : Gender is I not a factor that determine the awareness of using internet banking
The test result is given below
Ranks
gender N Mean
Rank
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male 53 45.63
female 41 49.91
Total 94
Test Statistics
AWETChi-Square .589
df 1
Asymp. Sig. .443a Kruskal Wallis Test
b Grouping Variable: gender
A Kruskal Wallis Test has been carried out to determine whether gender is a factor
that influence the extent that respondents are informed on the use internet banking At the statistical significance level of p=.05. , the test give evidence for accepting the null
hypothesis ( p= ) . As such there is not sufficient evidence to reject the null hypothesis .as such , gender is a factor that influence the extent that respondents are informed on
the use internet banking
Age
The aim of this test is to determine as to whether there is a relationship between age andthe extent that respondents have a high information
H0 : Age is a factor that determine the of awareness ing internet banking
H1 : Age is not a factor that determine of using awareness internet banking
The test result is given below
Ranks
Age N Mean
Rank
AWET less than20
31 50.32
20 to 35 40 48.44
35 to 50 16 35.31above 50 7 57.50
Total 94
Test Statistics
AWET
Chi-
Square
4.668
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df 3
Asymp.
Sig.
.198
a Kruskal Wallis Test
b Grouping Variable: Age
A Kruskal Wallis Test has been carried out to determine whether age is a factor that
influence the extent that respondents are informed on the use internet banking At the statistical significance level of p=.05. , the test give evidence for accepting the null
hypothesis ( p= ) . As such there is not sufficient evidence to reject the null hypothesis .
As such , age is a factor that influence the extent that respondents are informed on the
use internet banking
Education
In the previous analysis , it was found out that respondents are not too much aware of the
risk of using internet banking . As such , this test aim at determining as to whether thereis a relationship between age and the extent that respondents have a high information
H0 : Education is a factor that determine awareness using internet banking
H1 : Education is not a factor that determine of awareness using internet banking
The test result is given below
Ranks
Education N Mean Rank
primary
level
10 44.90
up to sc 32 43.58
up to hsc 40 50.69
universit
y
12 49.50
Total 94
Test Statistics
AWET
Chi-Square
1.409
df 3
Asymp.Sig.
.703
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a Kruskal Wallis Test
b Grouping Variable: Education
A Kruskal Wallis Test has been carried out to determine whether education is a
factor that influence the extent that respondents are informed on the use internet banking At the statistical significance level of p=.05. , the test give evidence for accepting the
null hypothesis ( p=.703 ) . As such there is not sufficient evidence to reject the null hypothesis . As such , education is a factor that influence the extent that respondentsare informed on the use internet banking
Occupation
The statistics shows that most of respondents are employed in both the private and public
sector . Mauritius is a country which rank among the top country in Africa whose
population have a high level of literacy rate on the usage of internet . As such , the thirdtest seeks to determine as to whether occupation is a determining factor with respect to
the extent and level of awareness on the use of internet banking
H0 : Occupation is a factor that determine awareness of using internet banking
H1 : Occupation is not a factor that determine awareness of using internet banking
The result of the test is shown below
Ranks
occupation N Mean Rank
Employed public sector 34 45.24Employed Private sector 33 50.12
Student 4 50.63
unemployed 8 57.06
sell employed 15 40.93
Total 94
Test Statistics
AWET
Chi-
Square
2.527
df 4
Asymp.
Sig.
.640
a Kruskal Wallis Test
b Grouping Variable: occupation
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A Kruskal Wallis Test has been carried out to determine whether occupation is a
factor that influence the extent that respondents are informed on the use internet banking At the statistical significance level of p=.05. , the test give evidence for accepting the
null hypothesis ( p=..640 ) . As such there is not enough evidence to reject the null
hypothesis . As such , occupation is a factor that influence the extent that respondentsare informed on the use internet banking
Summary of findings
The overall inference that can be drawn is that there is a multidimensional factors thatdetermine the general awareness on the use of internet banking .Security is an area that
has been given a low rating by the respondents
Security
With increasing online services, banks face challenges in identifying and addressingconsumer concerns about: transacting online; identifying areas of exposure or
vulnerability due to insufficient disclosures; building and sustaining the confidence of
customers; persuading customers to accept the impact of secure access technologies; andthe carrying the cost of secure access technologies
It is along these lines that respondents were required to give their views on a set of 4statements , the result from the surveys are given below :
S.D D N A S.A MEAN S.D
I trust in the ability of the bank to protect my confidentiality
17 34 1 37 5 2.7766 1.2881
Use of digital signatures,encryption & authorization
mechanisms provide a more
secured Online Banking
18 11 53 12 3.6277 .9388
I know there is some risk to use
internet banking
19 33 4 38 3.6277 .9388
I trust in the technology the
bank is using for internet
14 13 56 11 2.6489 1.2067
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banking
From the above information , respondents have given a high rating to
(a)Use of digital signatures, encryption & authorization mechanisms provide a moresecured Online Banking ( M=3.6277)
(b)I know there is some risk to use internet banking(M=3.6277)
On the other hand , there is still some apprehension on the bank” ability to create a highlevel of trust among its customers , This is reflected on the low score achieved on 2
factors as set out below :
(a) I trust in the ability of the bank to protect my confidentiality ( M=2.7766)
(b) I trust in the technology the bank is using for internet banking(M=2.6489)
In line with the previous analysis , hypothesis testing have been carried out using thefollowing factors :
(a) Gender
(b) Age(c) Education
(d) Profession
with a view to determine respondents views on the security of using internet banking
The result is summarized below :
Factor p S/NS
Gender .953 NS
Age .086 NS
Education .654 NS
Profession .756 NS
On the basis of the result obtained, it can be safely inferred that the respondents perception on the security aspects of using internet banking are closely related to the
following factors
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(a) Gender
(b) Age
(c ) Education and(d) Profession
Perceived Benefits
Respondents were required to state the degree that they have benefited from that
internet banking on a set of 4 statements: The statistics are given below :
S.D D N A S.A MEAN S.D
Internet banking enables me to
carry out my banking tasks
more quickly
1 16 0 74 3 3.6596 .8367
Online banking gives me more
financial control
10 20 2 62 0 3.2340 1.1209
I find internet banking useful 0 34 0 59 1 3.2872 .9796
Accounts paid & funds are
transferred without queues
2 26 2 64 3.3617 .9600
From the above table , it is noted that the mean scores are in the range of 3.2340 to3.6596. This indicate that more respondents find the use of internet banking to be beneficial
In line with the previous analysis , hypothesis testing have been carried out using thefollowing factors :
(e) Gender
(f) Age(g) Education
(h) Profession
with a view to determine they influenced respondents views on the benefits of using
internet banking
The result is summarized below :
Factor P value S/NS
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Gender ,310 Not Significant
Age .598 Not Significant
Education .086 Not Significant
Profession .654 Not Significant
On the basis of the above figures it can be safely concluded that gender , age , educationand occupation are determinants factors with respect to perceived benefits of using
internet banking
Convenience
Respondents were asked to opine on the convenience of internet banking . The resultfrom the analysis is given below :
S.D D N A S.A MEAN S.D
A wide range of services are
offered
1 21 19 53 0 3.3191 .8578
It is a convenient way of doing
transaction
0 12 3 79 0 3.7128 .6819
There is a lot of time saving 0 22 2 70 0 3.5106 .8519
From the above , respondents have given a high rating to all statements and the means arein the range of 3.7128 to 3.3191.
The factor convenience of doing business has received the highest rating (M=3.7128) and thefactor relating to the variety of services has received the lowest rating (M=3.3191)
Overall , customers find internet banking to be convenient
In line with the previous analysis , hypothesis testing have been carried out using the
following factors :
(i) Gender (j) Age
(k) Education(l) Profession
with a view to determine they influenced respondents views on the benefits of using
internet banking
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The result is summarized below :
Factor P value S/NS
Gender .250 Not significant
Age .076 Not significant
Education .423 Not significant
Profession .201 Not significant
On the basis of the above figures it can be safely concluded that gender , age , education
and occupation are determinants factors with respect to convenience of using internet
banking
CUSTOMER SATISFACTION
In addition to the above analysis , this part of the analysis will consider the perception of
respondents on their bank on a set of 5 dimensions :
(a) Empathy
( b) Assurance
(a) Empathy
Empathy is about giving customers individual attention andemployees dealing with customers in a caring fashion. In this respect , respondents views were sought on this aspect on a setof 3 statements .
The table below provides mean difference between expected level of satisfaction and the derived level of satisfaction on the various aspectsof empathy and the p-value.
Expectation
(Mean)
Perception
(Mean )
Mean
Difference
P
value
S/NS
The bank understand the 3.5106 3.6596 0.149 .209 NS
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need of their customers
The bank responses to my
queries are personalized
3.2340 3.2872 0.0532 .722 NS
The bank shows genuine
concern and sympathy to
my problem
3.8085 3.1277 -0.6808 .000 S
Overall score 3.5177 3.3582 -0.1595 .029 S
S-significant ( p value <= 0.05); NS- Not significant (p value >0.005)
Table
It is found from table that the overall mean difference value is negative ( MeanDifference: -0.1595) , thus indicating that respondents do not perceived the their bank to
be empathic to their individual need . ,i.e the expected level of satisfaction is
significantly ( p=..029) more than the derived level of satisfaction of the respondents
However , Positive differences are noted for the banks understanding of the need of their customers and are responsive to their customers personal queries. However, it is found
out that banks do not show genuine concern and sympathy to their customer’s problem.
The number of customers for each individual bank has been grouped using the mean
differences between expectation and perception for each bank. This is shown in the table below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 1 10 8 3 4
Bank B 4 11 5 2 1
Bank C 1 5 1 1 0
Bank D 0 2 6 5 2
Bank E 1 3 4 5 0
Others 0 5 2 1 1TOTAL 7 36 26 17 8
% 0.07 0.38 0.28 0.18 0.09
From the above table it is noted that 45 % of the respondents are dissatisfied , 28% areindifferent while 27 % are satisfied on the empathy dimension .
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The above data has been further analysed and the percentage of customers for each
bank falling in the different categories is shown below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 0.04 0.38 0.31 0.12 0.15
Bank B 0.17 0.48 0.22 0.09 0.04
Bank C 0.13 0.63 0.13 0.13 0.00
Bank D 0.00 0.13 0.40 0.33 0.13
Bank E 0.08 0.23 0.31 0.38 0.00
Others 0.00 0.56 0.22 0.11 0.11Total 0.07 0.38 0.28 0.18 0.09
%
From the above , it is noted that
(a) Bank B has the highest percentages of the most dissatisfied customers(b) Both bank B and “other bank “has the highest percentage of dissatisfied
customers
(c) Bank D has the highest percentage of indifferent customers(d) Bank E has the highest percentage of satisfied customers(e) Bank A has the highest percentage of the most satisfied customers
On the basis of the above , a weighted mean score has been worked to determine the
overall performance of the bank . The weight is taken to be the number of customersfalling within a range . The median of a range has been taken to compute the overall
mean score . This methodology will be also be used for other dimensions in this study .
MeanDifference
Median Scare Interpretation
-2 to -1 -1.5 Most
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dissatisfied
-1 to 0 -.5 Dissatisfied
0 0 Indifferent
0 to 1 .5 Satisfied
1 to 2 1.5 Most
Dissatisfied
The data has been ranked and this is shown in the table below :
Average Mean Score Ranking
Bank A 0.2 2 ndBank B -1.8 6 th
Bank C -0.7 5th
Bank D 0.9 1 st
Bank E -0.1 3 rd
Others -0.1 3 rd
On the criterion of fulfillment , Bank D has achieved the highest rank and Bank B hasachieved the lowest rank
The above findings have been confirmed by conducting a hypothesis testing :
H0 : There is no difference on customers level of satisfaction on the empathy dimensionbetween banks
H1 : There is a difference on customers level of satisfaction on the empathy dimension
between banks
The result of the findings are given below :
Ranks
Bank N Mean Rank
Bank A 26 49.71
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Bank B 23 32.85
Bank C 8 40.13
Bank D 15 65.43Bank E 13 54.08
Others 9 45.72
Total 94
Test Statistics
empathy
Chi-Square 15.315
df 5
Asymp. Sig. .009
a Kruskal Wallis Test
b Grouping Variable: Choose your main bank
A Kruskal Wallis Test to find out as to whether customers find their bank to be
empathetic to their needs . At the statistical significance level of p=.05. , the test giveevidence for rejecting the null hypothesis ( p=.009 )) . As such there is sufficient
evidence to reject the null hypothesis i.e There is a difference on customers level of
satisfaction on the empathy dimension between banks
Responsiveness
Although service organizations may imagine the Internet as a remote service, with
opportunities to maintain a standardized approach in service delivery, customers do notregard the Internet as a remote service. They expect a lot of straightforward, honest and
timely communication, strong interactivity, good interfacing with backstage activities and
adequate support. In other word , they want their banks to be responsive .Responsivenessis about prompt service to customers, willingness to help customers and
readiness to respond to customers' requests
The table provides mean difference between expected level of satisfactionand the derived level of satisfaction on the various aspects of responsiveness ,
together with the p-value. The aspects considered are level of care , information to
customers ,on line help and solving both technical and non technical problem
Expectation
(Mean)
Perception
(Mean )
Mean
Difference
P
value
S/NS
The bank takes care of the 3.8085 3.1277 -0.6808 .000 S
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online problems promptly
When a problem occurs
the bank provide
appropriate information tocustomers
3.2766 3.4681 0.1915 .166 S
Information is given onwhat to do if the
transaction is not
processed
3.4149 2.6809 -0.734 .000 S
In case of a problem, the
site offers live help with a
person
3.8617 3.5000 -0.3617 .000 S
The bank's website
contains a section tohelp/guide me for
common problems
3.2447 2.5106 -0.7341 .000 S
Bank helps quickly intechnical & non-technical
issues
3.3191 3.7128 0.3937 .004 S
Overall 3.4876 3.1667 -0.3209 .004 S
S-significant ( p value <= 0.05); NS- Not significant (p value >0.005)
Overall , the difference between the expected and perceived level are significant at the
5% significance level
It is found from the table that 5 out of the 6 mean difference values are negative
indicating that the perceived level of satisfaction is less than the desired level of
satisfaction:
(a) Caring about online problem Mean Difference (-0.6808)
(b) Giving information for self help Mean Difference (-0.734)
( c) on line help Mean Difference (-0.3617)
(d) Content of website Mean Difference (-0.7341)
(e) Solving technical and non technical problem Mean Difference (-0.7341)
On the other hand , customers are satisfied with respect to that bank giving anappropriate information to the customers when there is a problem
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Overall , It is concluded that the respondents’ expectation are significantly more than
their perception on the responsiveness dimension
The number of customers falling in each range for each individual bank is shown in the
table below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 1 18 6 1 0
Bank B 1 17 2 3 0
Bank C 0 5 2 1 0
Bank D 0 8 1 6 0
Bank E 1 7 2 3 0
Others 0 5 1 3 0
TOTAL 7 36 26 17 8
% 0.07 0.38 0.28 0.18
On the basis of the above , it is noted that 45 respondents are dissatisfied with their bank
, 28 % are indifferent and 18 % are satisfied
The above data has been further analysed and the percentage of customers for each
bank falling in the different categories are shown below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 0.04 0.69 0.23 0.04 0.00
Bank B 0.04 0.74 0.09 0.13 0.00Bank C 0.00 0.63 0.25 0.13 0.00
Bank D 0.00 0.53 0.07 0.40 0.00
Bank E 0.08 0.54 0.15 0.23 0.00
Others 0.00 0.56 0.11 0.33 0.00
Total 0.07 0.38 0.28 0.18 0.00
%
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From the above , it is noted that
(f) Bank E has the highest percentages of the most dissatisfied customers
(g) Both bank A and bank B have the highest percentage of dissatisfied customers(h) Bank C has the highest percentage of indifferent customers
(i) Bank D has the highest percentage of satisfied customers
On the basis of the above , a weighted mean score has been worked to determine the
overall performance of the bank . The data has been ranked and this is shown in the table below :
Average Mean Score Ranking
Bank A -2 6 nd
Bank B -1.7 5th
Bank C -0.4 3th
Bank D -0.2 1 st
Bank E -0.7 4th
Others -0.2 1 st
On the criterion of responsiveness , “other bank” and Bank D have achieved the highest
ranking and Bank A has achieved the lowest rank
The above finding is confirmed through the following test
H0 : There is no difference on customers level dissatisfaction on the responsiveness
dimension between banks
H1 : There is a difference on customers level of dissatisfaction on the responsivenessdimension between banks
The findings are given below :
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Ranks
Choose your main bank
N Mean Rank
Bank A 26 45.67
Bank B 23 35.43
Bank C 8 52.50Bank D 15 54.37
Bank E 13 55.88
Others 9 55.61
Total 94
Test Statistics
Responsiveness
Chi-Square 7.986
df 5
Asymp. Sig. .157
a Kruskal Wallis Test b Grouping Variable:
A Kruskal Wallis Test to find out as to whether customers opinion on the
responsiveness dimension differs beteeen bank . At the statistical significance level of
p=.05. , the test does not give evidence for rejecting the null hypothesis ( p=.009 )) .i.e There is no difference on customers level of dissatisfaction on the responsiveness
dimension between banks
Fulfillment
Privacy concerns and the protection of users from the risk of fraud and financial loss
have a strong impact on attitude toward use of online financial services (Montoya-Weisset al., 2003). Depth of information content and availability has been found to be an
important factor as it enables users to control the content.
Customer perceptions of online shopping are also largely affected by issues such as the
graphic style of the web site, including color, layout, print size and type, number of photographs and graphics, and animation (Hoffman and Novak, 1996; Hoque and Lohse,
1999).
On this basis , respondents were required to opine on a set of 7 statements . The result is
given below :
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Expectation(Mean)
Perception(Mean )
MeanDifference
Pvalue
S/NS
It allows transactions to be conducted quickly
3.6170 3.4149-0.2021
.106 NS
Pages load promptly 3.9362 3.5213 -0.4149 .003 SGetting on the site is swift 3.4681 3.2766 -0.1915 .142 NS
This site is alwaysaccessible for business
2.8617 3.73400.8723
.373 NS
This site initiates andoperates immediately
2.4468 3.01060.5638
.009 S
This site never crashes 3.1809 1.4468 -1.7341 .000 S
After entering my
transaction information,the page neither locks nor
freezes
3.7340 2.7128
-1.0212
.000 S
Overall 3.3207 2.9088 -0.4119 000 S
S-significant ( p value <= 0.05); NS- Not significant (p value >0.005)
It is found out that the result is significantly different on 4 statements i.e loading of pages,
the responsiveness of the site , the reliability of the site and the usability of the site
It is found from the table that 5 out of the 7 mean difference values are negative
indicating that the perceived level of satisfaction is less than the desired level of satisfaction: These are :
(a) It allows transactions to be conducted quickly M.D =-0.2021
(b) Pages load promptly M.D=-0.4149
© Getting on the site is swift M.D=-0.1915
(d) This site never crashes M.D=-1.7341
(e) The page neither locks nor freezes M.D=-1.0212
However , positive difference have been noted ( i.e customers are satisfied ) on the
accessibility of the site ( M.D= 0.8723 ) and responsiveness of the site (M.D =0.5638)
Overall . the customers are dissatisfied on this dimension of the service . The mean
difference is -0.4119
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The mean differences for each bank is shown in the table below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 3 20 2 1 0
Bank B 3 18 0 2 0
Bank C 0 5 2 1 0
Bank D 0 11 0 4 0
Bank E 0 9 3 1 0
Others 0 7 0 2 0
Total 6 70 7 11 0
% 0.06 0.74 0.07 0.12
From the above table it is noted that 80 % of the respondents are dissatisfied , 7 % are
indifferent while 12 % are satisfied with the internet services provided by banks .
The above data has been further analysed and the percentage of customers for each
bank falling in the different categories is shown below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 12 77 8 4 0
Bank B 13 78 0 9 0
Bank C 0 63 25 13 0
Bank D 0 73 0 27 0
Bank E 0 69 23 8 0
Others 0 78 0 22 0
Total 6 74 7 12 0
%
From the above , it is noted that
(j) Bank B has the highest percentages of the most dissatisfied customers
(k) Both bank B and “other bank “has the highest percentage of dissatisfiedcustomers
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(l) Bank C has the highest percentage of indifferent customers
(m)Bank D has the highest percentage of satisfied customers
On the basis of the above , a weighted mean score has been worked to determine the
overall performance of the bank . The data has been ranked and this is shown in the table
below :
Average Mean Score Ranking
Bank A -2.8 6 th
Bank B -2.5 5 th
Bank C -0.4 Ist
Bank D -0.7 3rd
Bank E -0.8 4 th
Others -0.5 2 nd
On the criterion of fulfiment , Bank C has achieved the highest rank and Bank A has
achieved the lowest rank
The above findings have been confirmed by conducting a hypothesis testing :
H0 : There is no difference on customers level of satisfaction on the fulfillment dimension between banks
H1 : There is a difference on customers level of satisfaction on the fulfillment dimension between banks
The result is shown below
Ranks
Choose your main bank N Mean Rank Bank A 26 35.27
Bank B 23 42.46
Bank C 8 61.25
Bank D 15 57.77
Bank E 13 58.73
Others 9 50.17
Total 94
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Test Statistics
Fulfillment
Chi-Square 12.654
df 5Asymp. Sig. .027
a Kruskal Wallis Test b Grouping Variable: Choose your main bank
A Kruskal Wallis Test to find out as to whether customers opinion on theresponsiveness dimension differs between bank . At the statistical significance level of
p=.05. , the test give evidence for rejecting the null hypothesis ( p=.02 )) . i.e Thereis a difference on customers level of satisfaction on the fulfillment dimension
between banks
Assurance
Expectation
(Mean)
Perception
(Mean )
Mean
Difference
P
value
S/NS
When I access my accountI feel secure. Bank X's
web site instills
confidence
3.0532 4.5000 1.4468 .000 S
Bank X is very accurate in
their responses to myqueries/requests
3.2766 3.1170 -0.1596 .416 NS
Bank x keep accuraterecords of my account
transactions
3.6596 3.2340 -0.4256 .004 S
Overall Score 3.3298 3.6170 0.2872 .002 S
It is found from the table that all the mean difference values arepositive for the confidence dimension (M.D =1.4468) and they are negative
for the accuracy dimension ( M.D =-0.1596) and ( M.D =0.4256)
Overall , customers appear to be satisfied on this dimension ( M.D =0.2872)
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The mean differences for each bank has bean grouped in 5 categories and is shown in the
table below :
Between -2and -1 Between-1 and 0 0 Between 0and 1 Between 1and 2
Bank A 2 6 2 10 6
Bank B 4 5 8 6
Bank C 0 4 3 1
Bank D 5 3 6 1
Bank E 3 2 6 2
Others 6 2 1 0
Total
%
From the above table it is noted that 80 % of the respondents are dissatisfied , 7 % are
indifferent while 12 % are satisfied with the internet services provided by banks .
The above data has been further analysed and the percentage of customers for each
bank falling in the different categories is shown below :
Between -2and -1
Between-1 and 0
0 Between 0and 1
Between 1and 2
Bank A 0.08 0.23 0.08 0.38 0.23
Bank B 0.00 0.17 0.22 0.35 0.26
Bank C 0.00 0.00 0.50 0.38 0.13
Bank D 0.00 0.33 0.20 0.40 0.07
Bank E 0.00 0.23 0.15 0.46 0.15
Others 0.00 0.67 0.22 0.11 0.00
Total 0.02 0.26 0.19 0.36 0.17
%
From the above , it is noted that
(n) Bank A has the highest percentages of the most dissatisfied customers
(o) “other bank “has the highest percentage of dissatisfied customers
(p) Bank C has the highest percentage of indifferent customers(q) Bank E has the highest percentage of satisfied customers
(r) Both Bank A and bank B have the most satisfied customer
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On the basis of the above , a weighted mean score has been worked to determine theoverall performance of the bank . The data has been ranked and it is shown in the table
below :
Average Mean Score Ranking
Bank A 1.6 2 nd
Bank B 2.2 1 st
Bank C
0.6 4 th
Bank D
0.45 th
Bank E 0.9 3rd
Others -0.5 6 th
On the criterion of fulfiment , Bank A has achieved the highest rank and “ other banks”
has achieved the lowest rank
The above findings have been confirmed by conducting a hypothesis testing :
H0 : There is no difference on customers level of satisfaction on the assurance
dimension between banks
H1 : There is a difference on customers level of satisfaction on the assurance
dimension between banks
Choose your main bank N Mean Rank
Bank A 26 50.38Bank B 23 55.15
Bank C 8 48.31
Bank D 15 43.80
Bank E 13 49.65
Others 9 21.94
Total 94
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AST
Chi-Square 10.544df 5
Asymp. Sig. .061
A Kruskal Wallis Test to find out as to whether customers opinion on the
responsiveness dimension differs beteeen bank . At the statistical significance level of
p=.05. , the test give evidence for accepting the null hypothesis ( p=..061 ) . i.e
There is no significant difference on customers level of satisfaction on the assurance
dimension between banks
Reliability
Reliability is judged by the ability of the service provider to deliver theservices as promised, dependability in handling customers' serviceproblems, performing services right the first time, providing services atthe promised time and Keeping customers informed of any changes .
Un this respect ,respondents were required to give their views on a setof 5 statements . The result is shown below:
Expectation(Mean)
Perception(Mean )
MeanDifference
Pvalue
S/NS
The links on the websitesare problem free, accurate
and the pages download
quickly
3.5957 3.3191
-0.2766
.092 NS
The bank's website is
running all the time/
always accessible
3.2766 3.3191
0.0425
.619 NS
Information content and
text on the website areeasy to understand
3.9362 3.3191
-0.6171
.000 S
Service is delivered 3.8404 3.3191 -0.5213 .000 S
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exactly as promised
The bank always provides
the service at the
promised time
3.8298 3.3191
-0.5107
.000 S
Overall 3.6957 3.3191 -.3766 .003 S
It is found from table that the overall mean difference value is negative ( Mean
Difference: -.3766 ) , thus indicating that respondents do not perceived the their bank service to be reliable
Positive differences is noted on the accessibility to the website (M.D=0.0425) However,it is found out customers are dissatisfied with respect of the following
(a) Downloading M.D= -0.2766
(b) Information content M.D=-0.6171
© Meeting promises M.D=-0.5213
(d) Timeliness M.D=-.3766
In addition, the result is significant at the 5 % significance level on the statements dealing
with information content ,meeting promises and the timeliness of the service . In view
that the mean difference are negative , this indicate a high level of dissatisfaction .
The mean differences for each bank has bean grouped in 5 categories and is shown in the
table below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 7 9 2 4 4
Bank B 8 3 2 9 1
Bank C 3 1 0 4 0
Bank D 3 3 2 7 0
Bank E 3 4 2 4 0
Others 1 4 2 2 0
Total 25 24 10 30 5%
From the above table , it is noted that 49 respondents are dissatisfied , 10 respondents are
indifferent and 35 respondents are satisfied .
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The above data has been further analyzed and the percentage of customers for each
bank falling in the different categories is shown below :
Between -2
and -1
Between
-1 and 0
0 Between 0
and 1
Between 1
and 2
Bank A 0.27 0.35 0.08 0.15 0.15
Bank B 0.35 0.13 0.09 0.39 0.04
Bank C 0.38 0.13 0.00 0.50 0.00
Bank D 0.20 0.20 0.13 0.47 0.00
Bank E 0.23 0.31 0.15 0.31 0.00
Others 0.11 0.44 0.22 0.22 0.00
Total 0.27 0.26 0.11 0.32 0.05
From the above , it is noted that
(s) Bank B and Bank C has the highest percentages of the most dissatisfiedcustomers
(t) Bank A and “other bank “have the highest percentage of dissatisfied customers
(c ) “other bank has the highest percentage of indifferent customers
(u) Bank C has the highest percentage of satisfied customers
(v) Bank A have the most satisfied customer
On the basis of the above , a weighted mean score has been worked to determine the
overall performance of the bank . The data has been ranked and this is shown in the table below :
Average Mean Score Ranking
Bank A -1.4 5th
Bank B -1.5 6 th
Bank C-0.6 3rd
Bank D -0.5 1 st
Bank E -0.9 4th
Others -0.5 1 st
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Although the weighted mean score is negative for all banks , Bank D and :other banks
are giving a relatively better service than the other banks
The above findings have been confirmed by conducting a hypothesis testing :
H0 : There is no difference on customers level of satisfaction on the reliabilitydimension between banks
H1 : There is a difference on customers level of satisfaction on the reliability
dimension between banks
Bank N Mean Rank
Bank A 26 45.52
Bank B 23 46.28Bank C 8 42.44
Bank D 15 54.33
Bank E 13 50.42
Others 9 45.22
Total 94
Reliability
Chi-Square 1.623
df 5
Asymp. Sig. .898
A Kruskal Wallis Test to find out as to whether customers opinion on the
responsiveness dimension differs between bank . At the statistical significance level of
p=.05. , the test give evidence for accepting the null hypothesis ( p=.898 ) . i.e
There is a no difference on customers level of satisfaction on the reliability
dimension between banks
Summary of findings :
The above analysis has shown that customer satisfaction is a multi dimension issue and itis dependent on various factors such as
(a) age(b) education
(c) gender and
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(d) occupation
The analysis also shows that there is a difference on the quality of the internet banking
services provided by banks in Mauritius . The next chapter will make some
recommendations to address those issues.
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5.0 Recommendations
5.1 Introduction
In this chapter, appropriate recommendations have been made to deal with the identified
apprehension raised by respondents s on the use of internet banking .
5.2 Security
The analysis has shown that respondents are not well aware on the inherent risk of usinginternet banking . Banks should inform their customers on state of the art technology
they are using to address this issue and these should be regularly communicated to their
customers
5.3 Empathy
Respondents are of the view that bank do not show genuine concern and sympathy totheir problem From the analysis , it is found out that Bank B and :other banks have
received a poor rating on the empathy dimension. In order to overcome these
weaknesses , it is important for these banks to :to hire people who like people. tochallenge them to develop better method, to give them the authority to solve problem , to
provide adequate training and to recognize and reward them for their performance
5.4 Assurance
Most respondents have stated that banks do not takes care of the online problems promptly, information is not given on what to do if the transaction is not processed.Moreover , , the site does not offers on line help and the website does contain a
section to help/guide users for common problems. These problems occur mainly with
Bank A , B and E . In this respect , these bank should reengineer their website to containthose features
5.5 Accessibility
Many respondents have shown concern on to the accessibility to web site . These
problems are more common at B and the “other banks”. In this respect , these banksshould address these problems using state of the art technology . In addition , these bank
could resort to a benchmarking exercise with the other banks ,
5.6 Accuracy
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Accuracy is also an area which causes some dissatisfaction among the respondents . A
priori , banks should investigate into the factors that are causing customers to loose
confidence in their bank . In addition , these banks should improve their mechanism tohandle customer complaints , From the analysis , these problems occur mainly at A and
the “ other bank
5.7 Reliability
From the previous analysis , Bank A , Bank B and the “other banks “ have been given alow rating on the reliability dimension .This can arise from the technology being used by
the bank as well as inadequate management commitment to service quality and the
perception of infeasibility – that is not all customer expectations can be met
In this respect , it is recommended that banks should give a high priority to this issue
5.8 Risk
The study has also shown that respondents are still uncertain on the following issues :
risk of using internet banking and confidentiality of information . In this respect , it isrecommend that all the banks should intensify these aspect in the promotion of their
services and should regularly communicate to their customers on the bank initiative to
address those factors
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6 CONCLUSION
6.1 Introduction
Overall, the findings has shown that people have still some apprehension on the use of
internet banking . Moreover , there is some difference on the quality of internet bankingservices among banks .In this respect , appropriate recommendations have been made in
this study .
6.2 Area for further study
In view that there are wide difference in the internet banking services among banks ,
further research could be done on the use of benchmarking to improve the quality of services in the area of internet banking