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CHAPTER-6: AN EMPIRICAL STUDY OF EMPLOYEE’S PERCEPTION
TOWARDS ADOPTION OF BANKING TECHNOLOGY
6.1. Introduction:
The integration of world economies has opened an array of business opportunities as well
as challenges for firms. Increased standardization activity reflects, among other
components, demand by consumers for safer and higher quality products, technical
innovations, the expansion of global commerce and the increased concern by many
governments to society and welfare issues. Firms in service sector such as banking are
under constant pressure to perform better, cheaper and faster. The developments in
information and communication technology (ICT) are radically changing the way
business is done. Electronic commerce is now thought to hold the promise of a new
commercial revolution by offering an inexpensive and direct way to exchange
information and to sell or buy products and services. This revolution in the marketplace
has set in motion a revolution in the banking sector for the provision of a payment system
that is compatible with the demands of the electronic marketplace.
ICT directly affect how managers decide, how they plan and what products and
services are offered in the banking industry. It continues to change the way banks and
their corporate relationships are organized worldwide and the variety of innovative
devices available to enhance the speed and quality of service delivery.According to
Robbins, perception can be defined as ‘A process by which individuals organize and
interpret their sensory impressions in order to give meaning to their environment’ (2004,
p. 132). Perception is not necessarily based on reality, but is merely a perspective from a
particular individual’s view of a situation. The employee perception is important to
because it affect working relationship. The behavior of an employee is influenced by his
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personality, motives and efforts. Improved behavior has better performance and rewards
which provide more satisfaction to the employees. A satisfied employee tries to learn and
work effectively. An organization grows with the developed employees. Perception is an
important and initial step for developing an organizational behavior especially in service
organizations.
As, discussed earlier, four banks is considered to study the perception of bank
employees towards adoption of banking services.ICICI (Industrial Credit and Investment
Corporation of India), HDFC (Housing Development Finance Corporation), AXIS and
INDUSIND Bank. For present study data was collected through Questionnaire,
developed separately for bank employees (enclosed in appendix II).
Questionnaire development for Data Collection from Bank Employees:
The questionnaire consists of four sections. Section 1: Demographic profile of the
Respondents, Section 2: Employment profile of the Respondents, Section 3: Employee’s
opinion about awareness of customers towards banking services, Section 4: It was
developed based on five parameters Relative advantage, Complexity, Potential risk,
Strategic advantage by decision making process and Innovation and development to
ascertain the perception of the employees. 180 copies of questionnaire were distributed
among (Executive, Manager, Officer) of different branches of each bank out of which the
following number of questionnaire returned back with full information.
S.No. Name of the bank Questionnaire Received
1. ICICI 45
2. HDFC 38
3. AXIS 22
4. INDUSIND 24
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6.2. Data Analysis:
This chapter justifies the need of the research and analyzes the employees’ perception
towards adoption of banking technology to satisfy both more sophisticated customers
(who demand the flexibility of interactions with no time and location constraint, security
of information, privacy and convenience) as well as the organization’s own
needs(including more sophisticated services with more profit, security of networks,
hardware and bank application, cost containment or reduction and customer loyalty)
when implementing e-banking technologies.
Following three statistical tools were used by the researcher to analyze the data collected
through questionnaire (Enclosed in Appendix II).
4. Likert Scale
5. Chi Square Test
6. One Way Anova Test
Here Likert scale is useful for the calculation of weighted score and to find out percentile
by comparing calculated weighted score with total score for each question. Five point
Likert scale is used to elicit responses on the questionnaire. The data has collected from
the employees of different branches of each selected private bank from Bikaner to Jaipur
region but it is not representing the whole population of bank employees because the
parameters of the population is not known. Chi-square test for independence is applied
to evaluate the differences between different bank employees perception towards the
adoption of banking services. It is used to determine whether there is a significant
association between the two variables. Null Hypothesis (H0) are formulated for each
attributes such as Relative advantage, Complexity, Potential risk, Strategic advantage by
decision making process and Innovation and development to ascertain the responses of
these attributes on future of IT banking technology and the role of IT to achieve their and
organizational goals. For each section NULL hypothesis is analyzed and accepted and
rejected accordingly.
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One way analysis of variance (One-Way ANOVA) is used to check variability in
response between samples, so that it can be ascertained if there exists considerable
differences due to individual bank’s infrastructure, technology, services and customers.
Null Hypothesis (H0) are formulated for each attributes such as Relative advantage,
Complexity, Potential risk, Strategic advantage by decision making process and
Innovation and development to ascertain the responses. The null hypothesis states that
there are no differences between means of different classes, suggesting that the variance
of the within class samples should be identical to that of the between class samples
(resulting in no between-class discrimination capability).
6.3. Section-1: Demographic Profile of the Respondents
An attempt is made to study the bank employee’s perception towards adoption of e-
banking services in private sector banks. The table given below shows the demographic
profile of respondents.
Table 6.1: Demographic profile of the Respondents
Demographic
Variables
Categories ICICI HDFC AXIS INDUSIND
Sex Male
Female
33 (73)
12 (27)
30 (79)
8 (21)
17 (77)
5 (23)
16 (73)
6 (27)
Age 18 yrs-25 yrs
25yrs-36yrs
36 yrs-50 yrs
50 yrs+
22 (49)
19 (42)
2 (4)
2 (4)
7 (18)
23 (61)
5 (13)
3 (8)
11 (50)
7 (32)
2 (9)
2 (9)
8 (36)
9 (41)
3 (14)
2 (9)
(Figures in brackets denotes % to column total, Source: primary data-Questionnaire)
Findings:The Table 6.1 shows that sex as a personal variable effect employee’s
perception. In the above table, 73% of male and 27% female respondents uses ICICI
banking services, 79% of male and 21% of female respondents uses HDFC bank, 77 % of
male and 23 % of female respondents uses AXIS bank while 73% of male and 27% of
female respondents uses INDUSIND Bank. The survey reveals that the number of male
employees is more than female employees.
The result reveals that there are a number of job opportunities for age group of
25-36 years in private sector banks.
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Following is the graphical representation of Age and sex of the respondents.
Graph 6.1 Sex of the Respondent Graph 6.2: Age of the Respondent
6.4. Section 2: Employment profile of the Respondents
The table given below shows the employment profile of the respondents:
Table 6.2: Employment profile of the Respondents
Employment
Variables
Categories ICICI HDFC AXIS INDUSIND
Designation Executives
Manager
Officer
16 (36)
8 (18)
21 (47)
14 (37)
9 (24)
15 (39)
9 (41)
6 (21)
7 (32)
10 (45)
5 (23)
7 (32)
Experience < 5 yrs
5yrs-10yrs
10 yrs-15 yrs
>15 yrs
22 (19)
19 (42)
2 (4)
2 (4)
7 (18)
23 (61)
5 (13)
3 (8)
11 (50)
7 (32)
2 (9)
2 (9)
8 (36)
9 (41)
3 (14)
2 (9)
Qualification Diploma
Bachelor
Degree
PG Diploma
PG(Professional
Degree)
4 (9)
8 (18)
9 (20)
8 (18)
16 (36)
2 (5)
4 (11)
6 (16)
8 (21)
18 (47)
2 (9)
5 (23)
3 (14)
5 (23)
7 (32)
1 (5)
3 (14)
6 (27)
5 (23)
7 (32)
Timing of
Induction
Training
Program
0-10 hour
11-20 hour
21-40 hour
41 hr & more
13 (29)
4 (9)
10 (22)
18 (40)
18 (47)
5 (13)
7 (18)
8 (21)
3 (14)
5 (23)
8 (36)
6 (27)
3 (14)
4 (18)
5 (23)
10 (45)
Computer and
Internet Training
Program
0-10 hour
11-20 hour
21-40 hour
41 hr & more
21 (47)
3 (7)
8 (18)
13 (29)
23 (61)
4 (11)
4 (11)
7 (18)
3 (14)
3 (14)
7 (32)
9 (41)
2 (9)
5 (23)
7 (32)
8 (36)
Estimated work
by computer
daily
0-2 hour
2-5 hour
5-9 hour
9 hr & more
6 (13)
6 (13)
14 (31)
19 (42)
22 (58)
6 (16)
6 (16)
4 (11)
2 (9)
5 (23)
5 (23)
10 (45)
4 (18)
4 (18)
6 (27)
8 (36)
(Figures in brackets denotes % to column total, Source: primary data-Questionnaire)
0
20
40
60
80
icici hdfc axis ind
Sex
Male
Female
0
20
40
60
80
icici hdfc axis ind
Age
18 - 25
25 - 36
36 - 50
50 yrs +
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Findings: The Table 6.2 shows that designation is the factor that determines the job
position of the employee in the organization. Most of ICICI, HDFC, AXIS & INDUSIND
banks respondents belong to the age group of 25-36 years. The result reveals that the
popularity for banking jobs is between age groups of 25-36 years in private sector banks.
Experience is the factor that determines skill and knowledge of the employees. In
ICICI, HDFC, AXIS & INDUSIND banks most of the respondents belong to the category
between 5-10 years and <5 years. The result reveals that several the talent pools are
increasing in different operational areas of banks.
Qualification is the factor that fulfills the conditions of being qualified. Different
banks check the basic qualification required to appear for the entrance test being
conducted to fulfill their vacancies. Most of educational qualification demanded by banks
is post graduation that includes M.Com, M.B.A., ICWAI and others.47% employee of
HDFC, 36% of ICICI and 32% of AXIS and INDUSIND employees are postgraduate.
Induction training program is organized by the banks for new starter to help them
do their job better and quicker, adjust or acclimatize quickly and effectively in their new
working environment.47% of employees prefer 0-10 hours of induction program in
HDFC, 40% of employees of ICICI, 45% of INDUSIND employees, 27% of AXIS
employees and 21% of HDFC employees prefer more than 41 hours of induction
program.
Computer and internet training program becomes compulsory for an organization
to meet the increasing need of customer data protection and to meet daily task. The
computer is a compulsory paper for the clerks and probationary officer.41% employees
of AXIS bank, 36 % employees of IDUSIND bank, 29% employees of ICICI bank and
18% employees of HDFC bank have attended more than 41 hours of training program.
Working on the computer makes the task easier, save time and provide accuracy.
It improves organizational productivity and efficiency. The study found that most of
respondents are using computers more than 9 hours in their daily task.
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The graphs below represent the employment profile of the respondents
Graph 6.3.1 Designation of the Respondent Graph 6.3.2 Experience of the
Respondent
Graph 6.3.3 Qualification of the
Respondents
Graph 6.3.4 Timing of Induction
Training Program
Graph 6.3.5 Computer and Internet
Training
Graph 6.3.6 Estimated work by
Computer daily Program
0
10
20
30
40
50
icici hdfc axis ind
Designation
Executives
Manager
Officer
0
10
20
30
40
50
60
icici hdfc axis ind
Experience
< 5yr
5 – 10
10 – 15
>15
0 10 20 30 40 50
Qualification
icici
hdfc
axis
ind
0
10
20
30
40
50
icici hdfc axis ind
Timing of Job Training Program
0-10 hour
11-20 hour
21-40 hour
0
20
40
60
80
icici hdfc axis ind
Computer and Internet Training Program
0-10 hour
11-20 hour
21-40 hour 0
20
40
60
icici hdfc axis ind
Estimated work by computer daily
0-2 hr
2-5 hr
5-9 hr
9 hr & more
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6.5. Section 3: Employee’s opinion about awareness of customers towards banking
services
Table 6.3.1: Awareness of Customer about IT enabled banking services
(ICICI Bank)
Services 0-20
(1)
21-40
(2)
41-60
(3)
61-80
(4)
81-100
(5)
Weighted
Score
Percentage
ATM
Banking 3 4 5 15 18 176 78
Branch
Banking 4 5 9 13 14 163 72
Internet
Banking 2 9 16 12 6 146 65
Mobile/Tele
Banking 4 4 15 13 9 154 68
Table 6.3.2: Awareness of Customer about IT enabled banking services
(HDFC Bank)
Services 0-20
(1)
21-40
(2)
41-60
(3)
61-80
(4)
81-100
(5)
Weighted
Score
Percentage
ATM Banking 2 4 7 11 14 145 76
Branch
Banking 2 3 6 11 16 150 79
Internet
Banking 6 1 6 7 18 144 76
Mobile/Tele
Banking 7 2 2 16 11 136 725
Table 6.3.3: Awareness of Customer about IT enabled banking services
(AXIS Bank)
Services 0-20
(1)
21-40
(2)
41-60
(3)
61-80
(4)
81-100
(5)
Weighted
Score
Percentage
ATM Banking 2 1 3 5 11 88 80
Branch
Banking 2 3 3 6 8 81 74
Internet
Banking 2 3 3 6 8 81 74
Mobile/Tele
Banking 1 2 4 6 9 86 78
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Table 6.3.4: Awareness of Customer about IT enabled banking services
(INDUSIND Bank)
Services 0-20
(1)
21-40
(2)
41-60
(3)
61-80
(4)
81-100
(5)
Weighted
Score
Percentage
ATM Banking 2 3 4 4 9 81 74
Branch
Banking 2 3 3 5 9 82 75
Internet
Banking 2 2 5 6 7 80 73
Mobile/Tele
Banking 1 3 7 5 6 78 71
(Here: 1 means very weak, 2 means moderately weak, 3 means neither Strong nor Weak, 4 means
Moderately Strong, 5 means Very Strong)
Table 6.3.5: Composite Table of the awareness of private bank customers towards
IT enabled banking services
Services ICICI HDFC AXIS INDUSIND
ATM Banking 78.222 76.316 80.000 73.636
Branch Banking 72.444 78.947 73.636 74.545
Internet Banking 64.889 75.789 73.636 72.727
Mobile/Tele
Banking 68.444 71.579 78.182 70.909
Figures denotes % to column (Source: primary data-Questionnaire)
Findings: Customer awareness is an important part of an overall information security
education program; consumer awareness programs create more inform buying decisions.
According to employees opinion maximum customers are using ATMs as direct banking
channel.The table 6.4.5 shows that78.94% of customers are using branch banking,
75.77% of customers are using Internet banking and 78.18% of customers are using
mobile/tele banking facilities provided by different private banks.
The study shows the increasing popularity of Internet banking and mobile banking
besides ATMs and branch banking between customers.
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The graphs below represent the responses of respondents towards banking services.
Graph 6.4.1 ATM Banking Graph 6.4.2. Branch Banking
Graph6.4.3. Internet Banking Graph 6.4.4. Mobile/Tele Banking
Section 4: Factors responsible for adoption of banking technology by Bank
employees
6.6. Relative advantages in adopting new technologies:
Relative advantage is an important factor that determines adoption of new innovations.
Likewise, as IT banking services allow customers to access their banking accounts from
any location, at any time of the day, it provides tremendous advantage and convenience
to users. It also gives customers greater control over managing their finances, as they are
able to check their accounts easily
To study the relative advantages received by the employees in adopting new
technology. Seven attributes were taken and labeled as: Safety and convenience, time and
25%
25% 26%
24%
ATM banking
ICICI HDFC AXIS INDUSIND
24%
26% 25%
25%
Branch Banking
ICICI HDFC AXIS INDUSIND
23%
26% 26%
25%
Internet Banking
ICICI HDFC AXIS INDUSIND
24%
25% 27%
24%
Mobile/Tele Banking
ICICI HDFC AXIS INDUSIND
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location constraint; reduce costs, save time of bank customers, daily responsibilities,
higher opportunities and sophisticated services. Four individual weighted scores were
computed for each individual private bank and then a composite score is prepared of the
four banks. The attributes are represented below with the help of table &graphs.
Table 6.4.1: Relative Advantage (ICICI Bank)
S.
N
o.
Relative
Advantage
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Safety and
Convenience 21 15 3 3 3 45 225 183 81
2
Time and
location
constraint
21 9 8 6 1 45 225 178 79
3 Reduce costs 22 15 3 3 2 45 225 187 83
4 Save time of
bank customers 24 14 4 3 0 45 225 194 86
5 Daily
responsibilities 18 11 14 2 0 45 225 180 80
6 Higher
opportunities 19 14 6 4 2 45 225 179 80
7 Sophisticated
services 17 8 3 9 8 45 225 152 68
Table 6.4.2: Relative Advantage (HDFC Bank)
S.
N
o.
Relative
Advantage
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Safety and
Convenience 16 10 5 4 3 38 190 146 77
2
Time and
location
constraint
15 12 3 4 4 38 190 144 76
3 Reduce costs 14 11 5 5 3 38 190 142 75
4 Save time of
bank customers 13 10 6 9 5 43 190 146 77
5 Daily
responsibilities 12 11 6 5 4 38 190 136 72
6 Higher
opportunities 17 11 3 6 1 38 190 151 79
7 Sophisticated
services 12 14 6 4 2 38 190 144 76
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Table 6.4.3: Relative Advantage (AXIS Bank)
S.
N
o.
Relative
Advantage
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Safety and
Convenience 10 5 2 3 2 22 110 84 76
2 Time and
location
constraint
8 5 4 3 2 22 110 80 73
3 Reduce costs 9 6 3 2 2 22 110 84 76
4 Save time of
bank customers 10 5 3 2 3 23 115 86 75
5 Daily
responsibilities 9 6 2 3 2 22 110 83 75
6 Higher
opportunities 7 8 4 3 0 22 110 85 77
7 Sophisticated
services 8 5 4 3 2 22 110 80 73
Table 6.4.4: Relative Advantage (INDUSIND Bank)
S.N
o.
Relative
Advantage
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Safety and
Convenience 8 5 4 3 2 22 110 80 73
2
Time and
location
constraint
6 9 3 2 2 22 110 81 74
3 Reduce costs 7 9 3 2 1 22 110 85 77
4 Save time of
bank customers 5 8 4 3 2 22 110 77 70
5 Daily
responsibilities 6 6 4 3 3 22 110 75 68
6 Higher
opportunities 7 8 3 2 2 22 110 82 75
7 Sophisticated
services 4 7 5 3 3 22 110 72
65
Here S.No. 1 to 4 has a rating scale extremely important (5) to extremely unimportant (1) and S.No. 5 to 10
has a rating scale extremely desirable (5) to extremely undesirable (1).
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Table 6.4.5: Composite table of relative advantages of private banks
S.No. Relative Advantage ICICI HDFC AXIS INDUSIND
1 Safety and
Convenience 81.333 76.842 76.364 72.727
2 Time and location
constraint 79.111 75.789 72.727 73.636
3 Reduce costs 83.111 74.737 76.364 77.273
4 Save time of bank
customers 86.222 76.842 74.783 70.000
5 Daily responsibilities 80.000 71.579 75.455 68.182
6 Higher opportunities 79.556 79.474 77.273 74.545
7 Sophisticated
services 67.556 75.789 72.727 65.455
Findings: The Table 6.5.5 shows that 81% of ICICI employees prefer banking
technology as they are safe and convenient. 79% of ICICI employee says that the
technology remove the time and location constraint. 83% of ICICI, 77% of Indusind,
76% of Axis and 74% of HDFC says the new technology help in reducing costs.86% of
ICICI, 76% of HDFC of technologies help in saving time of their work and as well as of
their customers.80% of ICICI, 75% of HDFC customer find, the relative advantage by
using technology such as efficiency in their routine jobs, more focus on customer
concern. Employees are more discipline and quickly organize their work very efficiently.
80% of ICICI, 79% of HDFC, 77% of Axis and 74% of Indusind employees find new
technology provide an opportunity in diverse areas.75% of HDFC, 72% of Axis, 68% of
ICICI and 65% of employees deal with complexity of banking product and services.
The result shows that ICICI, HDFC, Axis bank advancement in new technologies
has increase efficiency, reduction in cost help in achieving higher levels of productivity.
It has reduced location and time constraint, now employees may work on diversified task,
may adopt them according to the changing environment and customer demands.
Technology helps in empowering employees with new ideas and innovation. Training
and resources are given for the process to evolve; employees are expected to develop
feelings of self-efficacy, job satisfaction, security, confidence and job meaningfulness.
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Following is the graphical representation of Relative advantages in adopting new
technologies:
Graph 6.5.1. Safety and Convenience Graph 6.5.2. Time & location Constraint
6.5.3. Reducing Cost 6.5.4. Save time
6.5.5. Daily Responsibilities
6.5.6. Higher Opportunities
26%
25% 25%
24%
Safety and Convenience
ICICI HDFC AXIS INDUSIND
26%
25% 24%
25%
Time and location constraint
ICICI HDFC AXIS INDUSIND
25%
25% 26%
24%
Reduce costs
ICICI HDFC AXIS INDUSIND
28%
25% 24%
23%
Save time of bank customers
ICICI HDFC AXIS INDUSIND
27%
24% 26%
23%
Daily responsibilities
ICICI HDFC AXIS INDUSIND
26%
25% 25%
24%
Higher opportunities
ICICI HDFC AXIS INDUSIND
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6.5.7.Sophisticated Services
6.7.Complexities faced by employees in adopting IT banking services
Innovation with substantial complexity requires more technical skills and needs greater
implementation and operational efforts to increase its chances of adoption. Bank
continuously monitor the integrity of data, needs adequate investment for adoption of
services in this cut throat competition. Trust, security and privacy are the important
pillars that make the adoption of IT banking services faster. More on, all the banks have
to invest on promotional plans to make the customer feel easy of the complex emerging
technologies.
Table 6.5.1: Complexity (ICICI Bank)
S.N
o.
Complexity 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Monitor the
integrity 24 4 5 6 6 45 225 169 75
2 Adequate
investments 16 15 12 2 0 45 225 180 80
3 Trust -security 21 13 5 3 3 45 225 181 80
4 Promotional
plans 8 6 4 14 13 45 225 117 52
5 Trust –privacy 25 6 5 5 4 45 225 178 79
24%
27% 26%
23%
Sophisticated services
ICICI HDFC AXIS INDUSIND
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Table 6.5.2: Complexity (HDFC Bank)
S.N
o.
Complexity 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Monitor the
integrity 12 6 5 5 10 38 190 119 63
2 Adequate
investments 18 6 7 4 3 38 190 146 77
3 Trust –security 15 12 5 3 3 38 190 147 77
4 Promotional
plans 15 10 4 3 6 38 190 139 73
5 Trust –privacy 13 11 6 5 3 38 190 140 74
Table 6.5.3: Complexity (AXIS Bank)
S.N
o.
Complexity 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Monitor the
integrity 7 9 3 1 2 22 190 84 44
2 Adequate
investments 10 6 2 3 1 22 190 87 46
3 Trust –security 7 9 2 2 2 22 190 83 44
4 Promotional
plans 7 5 6 2 2 22 190 79 42
5 Trust –privacy 7 5 6 2 2 22 190 79 42
Table 6.5.4: Complexity (INDUSIND Bank)
S.N
o.
Complexity 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Monitor the
integrity 5 8 4 2 3 22 110 76 69
2 Adequate
investments 5 9 5 2 1 22 110 81
74
3 Trust -security 6 8 4 2 2 22 110 80 73
4 Promotional
plans 5 10 4 3 0 22 110 83
75
5 Trust -privacy 5 9 5 2 1 22 110 81 74
Here S.No. 2, 4 & 5 has a rating scale extremely important (5) to extremely unimportant (1) and S.No. 1 &
3 has a rating scale Quite necessary (5) to Quite unnecessary (1).
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Table 6.5.5: Composite Table of Complexity of Private Banks
S.No. Complexity ICICI HDFC AXIS INDUSIND
1 Monitor the integrity 75.111 62.632 44.211 69.091
2 Adequate
investments 80.000 76.842 45.789 73.636
3 Trust –security 80.444 77.368 43.684 72.727
4 Promotional plans 52.000 73.158 41.579 75.455
5 Trust –privacy 79.111 73.684 41.579 73.636
Findings: The table 6.5.5 shows that 75% of ICICI, 69% of Indusind, 62% of HDFC and
44% of Axis employees find technology helps in monitoring the integrity of data.80% of
ICICI, 76% of HDFC, 73% of Indusind employees says technology provides adequate
profits of their investment in different product and services. 80% of ICICI employees are
proactive and reactive in security related aspects of customer and this helps in increasing
satisfaction and trust among customers. 75% of Indusind employees are using technology
in promoting their product and services. ICICI bank is lacking in promotional
planning.79% of ICICI employees found the new technology has increase the privacy
between the customers. The customer trust bank as they maintain the privacy of data and
information.
The result shows that ICICI, HDFC and Indusind employees are active in
handling the complex issues related to privacy, security, integrity of data and investment
related aspects. Following is the graphical representation of different attributes faced by
the employees to manage complexity.
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288
6.6.1. Monitoring the Integrity of
security system
6.6.2. Adequate Investment
6.6.3. Trust and security issues 6.6.4. Cost increases in promotional
plans
6.6.5. Trust and Privacy Issues
6.8. Potential risks faced by employees in adopting IT banking service
Rapid changes in technology and the introduction of corporate and retail banking services
through the Internet. The unprecedented speed with which new technologies are being
adopted, the ubiquitous and global nature of electronic networks, the integration of e-
banking platforms with legacy systems and the increasing dependence of banks on third
30%
25% 18%
27%
Monitor the integrity
ICICI HDFC AXIS INDUSIND
29%
28% 16%
27%
Adequate investments
ICICI HDFC AXIS INDUSIND
29%
28% 16%
27%
Trust -security
ICICI HDFC AXIS INDUSIND
22%
30% 17%
31%
Promotional plans
ICICI HDFC AXIS INDUSIND
30%
27% 16%
27%
Trust -privacy
ICICI HDFC AXIS INDUSIND
289
289
party information service providers, all dramatically amplify the magnitude of risks to
which banks are exposed.
Table 6.6.1: Potential Risk (ICICI Bank)
S.N
o.
Potential Risk 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Knowledge 8 7 14 9 7 45 225 135 60
2 Data’s integrity 18 12 4 5 6 45 225 166 74
3 Information
security 16 14 12 2 1 45 225 177 79
4 Expertise and
training 21 2 4 4 14 45 225 147 65
Table 6.6.2: Potential Risk (HDFC Bank)
S.N
o.
Potential Risk 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Knowledge 16 8 6 4 4 38 190 142 75
2 Data’s
integrity 15 12 5 4 2 38 190 148 78
3 Information
security 17 9 5 3 4 38 190 146 77
4 Expertise and
training 20 8 4 3 3 38 190 153 81
Table 6.6.3: Potential Risk (AXIS Bank)
S.N
o.
Potential Risk 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Knowledge 6 7 3 4 2 22 110 77 70
2 Data’s
integrity 8 6 3 2 3 22 110 80 73
3 Information
security 6 5 4 4 3 22 110 73 66
4 Expertise and
training 6 5 3 4 4 22 110 71 65
Table 6.6.4: Potential Risk (INDUSIND Bank)
S.N
o.
Potential Risk 5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Knowledge 5 8 4 3 2 22 110 77 70
290
290
2 Data’s
integrity 5 7 6 2 2 22 110 77 70
3 Information
security 6 7 6 2 1 22 110 81 74
4 Expertise and
training 5 8 4 3 2 22 110 77 70
Here S.No. 1&3 has a rating scale quite necessary (5) to quite unnecessary (1) and S.No. 2&4 has a rating
scale extremely desirable (5) to extremely undesirable (1).
Table 6.6.5: Composite Table of Potential Risk associated with Private Banks
S.No. Potential Risk ICICI HDFC AXIS INDUSIND
1 Knowledge 60.000 74.737 70.000 70.000
2 Data’s integrity 73.778 77.895 72.727 70.000
3 Information security 78.667 76.842 66.364 73.636
4 Expertise and
training 65.333 80.526 64.545 70.000
Findings: The Table 6.6.5 shows that 74% of HDFC employees have the knowledge to
manage different types of risk.77% of HDFC, 74% of ICICI, 73% of Axis and 70% of
Indusind employee have maintained the integrity of data.79% of ICICI, 77% of HDFC,
74% of Indusind and 66% of Axis bank manage the information security risk from
malicious hacker or insider attacks, viruses, denial-of-service attacks, data theft, data
destruction and fraud. 81% HDFC, 70% of Indusind, 65% of ICICI and 65% of Indusind
employees are train in security control and risk management techniques. The result shows
that HDFC and Indusind bank has well trained their employee to manage different types
of risk. The information produced or processed during the risk analysis should be
categorized according to its sensitivity to loss or disclosure. Following is the graphical
representation of different attributes of Potential risks faced by employees in adopting IT
banking service.
6.7.1. Knowledge of e-banking 6.7.2. Maintaining data integrity
291
291
6.7.3.Importance of information security 6.7.4 Expertise and Training
6.9. Role of information technology in strategic decision making process
The dependency on information technology (IT) has increased progressively for
organizations as a strategically important competitive advantage. If planned, developed,
and managed properly, IT can bring about greater efficiency in organizational operations,
better working environments, and effective decision-making processes. Therefore, many
organizations are trying to catch up the development gap with the industry by means of
technology acquisition.For an organization, the major reason of acquiring IT applications
is to effectively and efficiently support one or more business process.
22%
27% 26%
25%
Knowledge
ICICI HDFC AXIS INDUSIND
25%
26% 25%
24%
Data’s integrity
ICICI HDFC AXIS INDUSIND
27%
26% 22%
25%
Information security
ICICI HDFC AXIS INDUSIND
23%
29% 23%
25%
Expertise and training
ICICI HDFC AXIS INDUSIND
292
292
Table 6.7.1: Role of information technology in strategic decision making
(ICICI Bank)
S.N
o.
Strategic
decision
making
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Information
network 15 14 12 2 2 45 225 173 77
2 Selection
criteria 24 5 4 7 5 45 225 172 77
3 Financial tools 23 9 2 4 7 45 225 170 76
4 IT by
competitor 13 6 15 3 8 45 225 147 65
5
Impact on
function of
bank
17 4 15 2 7 45 225 155 69
6 Information on
web page 13 6 15 2 9 45 225 147 65
7 Choice of IT 24 8 3 3 8 45 225 173 77
8
Problems-
implementatio
n
13 6 17 2 7 45 225 151 67
9
Results
financial
feasibility
study
15 11 6 4 9 45 225 154 68
10
Sources of
resistance to
change
19 8 9 6 3 45 225 169 75
Table 6.7.2: Strategic Decision making (HDFC Bank)
S.N
o.
strategic
decision
making
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Information
network 11 16 4 3 4 38 190 141 74
2 Selection
criteria 14 13 4 4 3 38 190 145 76
3 Financial
tools 11 14 4 5 4 38 190 137 72
4 IT by
competitor 14 12 5 4 3 38 190 144 76
5
Impact on
function of
bank
16 12 8 2 0 38 190 156 82
6 Information
on web page 13 10 6 5 4 38 190 137 72
7 Choice of IT 14 9 6 5 4 38 190 138 73
8 Problems-
implementati15 8 6 4 5 38 190 138 73
293
293
on
9
Results
financial
feasibility
study
14 8 7 5 4 38 190 137 72
10
Sources of
resistance to
change
12 9 8 5 4 38 190 134 71
Table 6.7.3: Strategic Decision making (AXIS Bank)
S.N
o.
strategic
decision
making
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Information
network 5 4 5 5 3 22 110 69 63
2 Selection
criteria 5 6 4 4 3 22 110 72 65
3 Financial
tools 5 4 4 5 4 22 110 67 61
4 IT by
competitor 7 5 4 3 3 22 110 76 69
5
Impact on
function of
bank
5 5 4 4 4 22 110 69 63
6 Information
on web page 8 6 4 2 2 22 110 82 75
7 Choice of IT 6 5 4 3 4 22 110 72 65
8
Problems-
implementati
on
5 6 5 3 3 22 110 73 66
9
Results
financial
feasibility
study
7 5 4 3 3 22 110 76 69
10
Sources of
resistance to
change
6 7 4 3 2 22 110 78 71
294
294
Table 6.7.4: Strategic Decision making (INDUSIND Bank)
S.N
o.
strategic
decision
making
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Information
network 7 5 5 3 2 22 110 78 71
2 Selection
criteria 6 4 6 3 3 22 110 73
66
3 Financial
tools 6 5 5 4 2 22 110 75
68
4 IT by
competitor 6 8 5 2 1 22 110 82
75
5
Impact on
function of
bank
5 7 5 3 2 22 110 76 69
6 Information
on web page 6 6 4 3 3 22 110 75
68
7 Choice of IT 7 6 5 2 2 22 110 80 73
8
Problems-
implementati
on
5 7 4 3 3 22 110 74 67
9
Results
financial
feasibility
study
6 8 4 3 1 22 110 81 74
10
Sources of
resistance to
change
5 4 5 4 4 22 110 68 62
Here S.No. 1 to 4 has a rating scale extremely important (5) to extremely unimportant (1) and S.No. 5 to 10
has a rating scale extremely desirable (5) to extremely undesirable (1)
Table 6.7.5: Composite Table of Strategic Decision making Process of Private Banks
S.No. Strategic Decision making ICICI HDFC AXIS INDUSIND
1 Information network 76.889 74.211 62.727 70.909
2 Selection criteria 76.500 76.316 65.455 66.364
3 Financial tools 75.611 72.105 60.909 68.182
4 IT by competitor 65.389 75.789 69.091 74.545
5 Impact on function of bank 69.056 82.105 62.727 69.091
6 Information on web page 65.111 72.105 74.545 68.182
7 Choice of IT 76.667 72.632 65.455 72.727
8 Problems-implementation 67.111 72.632 66.364 67.273
9 Results financial feasibility
study 68.333 72.105 69.091 73.636
10 Sources of resistance to
change 75.056 70.526 70.909 61.818
295
295
Findings: The Table 6.7.5 shows that 76% of ICICI employee found the application of
information technology has improved decision making for development of networks. IT
infrastructure provides the layer of technology to perform the data storage and analysis
processing. 77% of ICICI employee use information technology in strategic selection of
software, hardware and other IT equipments. 75% of ICICI employees make their
financial analysis with the help of software.76% of ICICI, 75% of Indusind employee has
a competitive advantage by decision making.
82% of HDFC employee uses IT in different functional areas. 75% of Axis, 72% of
HDFC update their all the necessary information on the web site.77% of ICICI, 73% of
HDFC employee are satisfied with the use of information technology in the decision
making process.73% of HDFC employee have properly implemented IT application by
which critical process has controlled. 73% of Indusind, 72% of HDFC employee has
maintained their financial feasibility. 75% of ICICI, 71% of HDFC, 71% of Axis
employee found information technology decision has provided resistance to changes.
The business objectives should be identified for the solution being sought and the
management decision whether building, leasing, or buying the IT application such as
Management information system, knowledge based system, business intelligence and
data warehousing. Following is the graphical representation of different attributes of Role
of information technology in strategic decision making process.
6.8.1 External Information Network 6.8.2. Selection criteria for new
information Systems
27%
26% 22%
25%
Information network
ICICI HDFC AXIS INDUSIND
27%
27% 23%
23%
Selection criteria
ICICI HDFC AXIS INDUSIND
296
296
6.8.3. Financial tools in planning process 6.8.4. Knowing of IT used by your
Competitor
6.8.5. Impact of IT on bank’s function 6.8.6. Disseminating Information on web
page
6.8.7 Choice of Information Technology 6.8.8. Evaluating potential problems
27%
26% 22%
25%
Financial tools
ICICI HDFC AXIS INDUSIND
23%
27% 24%
26%
IT by competitor
ICICI HDFC AXIS INDUSIND
24%
29% 22%
25%
Impact on function of bank
ICICI HDFC AXIS INDUSIND
23%
26% 27%
24%
Information on web page
ICICI HDFC AXIS INDUSIND
27%
25% 23%
25%
Choice of IT
ICICI HDFC AXIS INDUSIND
24%
27% 24%
25%
Problems-implementation
ICICI HDFC AXIS INDUSIND
297
297
6.8.9. Knowing the results of feasibility
study
6.8.10. Sources of resistance to
change
6.10. Innovation and Development
Technology plays a key role in the performance of banks. Pushed by growing consumer
demand and the fear of losing market share, banks are investing heavily in PC banking
technology. Collaborating with hardware, software, telecommunications and other
companies, banks are introducing new ways for consumers to access their account
balances, transfer funds, pay bills, and buy goods and services without using cash,
mailing a check, or leaving home.
Table 6.8.1: Innovation and Development (ICICI Bank)
S.N
o.
Innovation
and
Development
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1
Reduce
transaction
cost
22 8 3 3 9 45 225 164 73
2 Substantial
savings 23 7 3 3 9 45 225 167 74
3 Improve
productivity 21 10 4 3 7 45 225 170 76
4
Quality of
products or
services
24 7 2 3 9 45 225 169 75
24%
26% 24%
26%
Results financial feasibility study
ICICI HDFC AXIS INDUSIND
27%
25% 26%
22%
Sources of resistance to change
ICICI HDFC AXIS INDUSIND
298
298
Table 6.8.2: Innovation and Development (HDFC Bank)
S.N
o.
Innovation
and
Development
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1
Reduce
transaction
cost
13 15 3 3 4 38 190 144 76
2 Substantial
savings 12 10 5 6 5 38 190 132 69
3 Improve
productivity 13 6 13 6 0 38 190 139 73
4
Quality of
products or
services
13 14 5 6 0 38 190 148 78
Table 6.8.3: Innovation and Development (AXIS Bank)
S.N
o.
Innovation
and
Development
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1 Reduce
transaction
cost
6 7 5 3 1 22 110 80 73
2 Substantial
savings 7 5 5 3 2 22 110 78 71
3 Improve
productivity 7 5 4 4 2 22 110 77 70
4
Quality of
products or
services
7 5 5 3 2 22 110 78 71
Table 6.8.4: Innovation and Development (INDUSIND Bank)
S.N
o.
Innovation
and
Development
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1
Reduce
transaction
cost
6 7 4 3 2 22 110 78 71
2 Substantial
savings 4 5 5 4 4 22 110 67
61
3 Improve
productivity 5 6 4 4 3 22 110 72
65
4
Quality of
products or
services
5 6 4 4 3 22 110 72 65
Here S.No. 1 to 4 has a rating scale extremely important (5) to extremely unimportant (1)
299
299
Table 6.8.5: Composite Table of Innovation and Development of Private Banks
S.No. Innovation and
Development
ICICI HDFC AXIS INDUSIND
1 Reduce transaction cost
72.889 75.789 72.727 70.909
2 Substantial savings
74.389 69.474 70.909 60.909
3 Improve productivity
75.556 73.333 70.000 65.455
4 Quality of products or
services 75.278 77.895 70.909 65.455
Findings: The Table 6.8.5 shows that 78% of HDFC employees find innovative
technologies has reduces transaction cost.74% of ICICI, 71% of HDFC employees says
that their customer are benefited by innovative technologies because of enhance customer
delivery services.76% of ICICI, 73% of HDFC has improve its productivity by the
development of innovative product and service features.78% of HDFC , 75% of ICICI,
71% of Axis and 65% of Indusind employees has improve the quality of product and
services with the help of innovation and development.
The result shows that ICICI and HDFC bank are growing faster with innovative
technologies.ICICI bank has introduced kiosks and smart cards in rural areas, this has
reduced transaction cost. ICICI, HDFC and Axis banks are successful in driving the
development of innovative product features, reducing operating costs, enhancing
customer service delivery and minimizing the inherent risks. Following is the graphical
representation of attributes of innovation and development.
6.9.1. Reduce production costs 6.9.2. Make substantial savings
6.8.3. Improve firm's product 6.8.4. Improve the quality of products
or services
25%
26% 25%
24%
Reduce production costs
ICICI HDFC AXIS INDUSIND
27%
25% 26%
22%
Substantial savings
ICICI HDFC AXIS INDUSIND
300
300
6.10 Confidentiality of data and Usage of IT services
Table 6.9.1: Confidentiality of data and Usage of IT services (ICICI Bank)
S.
N
o.
Confidentiality
of data and
Usage of IT
services
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1
Unawareness
and inadequate
Knowledge
7 4 5 16 13 45 225 111 49
2 Slow transfer
speed 4 6 6 13 16 45 225 104 46
3
Delay in
transmission due
to machine
breakdown
5 7 5 11 17 45 225 107 48
4
Increase in fraud
due to inefficient
safety and
security features
5 6 7 13 14 45 225 110 49
Table 6.9.2: Confidentiality of data and Usage of IT services (HDFC Bank)
S.N
o.
Confidentiality
of data and
Usage of IT
services
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1
Unawareness
and inadequate
Knowledge
4 4 5 16 9 38 190 92 48
2 Slow transfer
speed
5 5 7 7 14 38 190 94 49
3
Delay in
transmission
due to machine
breakdown
5 6 8 12 7 38 190 104 55
26%
26% 25%
23%
Improve firm's productivity
ICICI HDFC AXIS INDUSIND
26%
27% 24%
23%
Quality of products or services
ICICI HDFC AXIS INDUSIND
301
301
4
Increase in
fraud due to
inefficient
safety and
security
features
3 7 6 11 11 38 190 94 49
Table 6.9.3: Confidentiality of data and Usage of IT services (AXIS Bank)
S.N
o.
Confidentialit
y of data and
Usage of IT
services
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1
Unawareness
and inadequate
Knowledge
3 2 3 8 6 22 110 54 49
2 Slow transfer
speed
2 3 4 5 8 22 110 52 47
3
Delay in
transmission
due to machine
breakdown
2 4 3 8 5 22 110 56 51
4
Increase in
fraud due to
inefficient
safety and
security
features
2 3 3 6 8 22 110 51 46
Table 6.9.4: Confidentiality of data and Usage of IT services (INDUSIND Bank)
S.N
o.
Confidentiality
of data and
Usage of IT
services
5 4 3 2 1 Total
Score
(T.S.)
(T.S.*5) Weighted
score
(W.S.)
%
1
Unawareness
and inadequate
Knowledge
2 3 3 6 8 22 110 51 46
2 Slow transfer
speed
3 3 4 5 7 22 110 56 51
3
Delay in
transmission
due to machine
breakdown
2 3 4 7 6 22 110 54 49
4
Increase in
fraud due to
inefficient
safety and
3 2 3 6 8 22 110 52 47
302
302
security
features
(Here, 1: Strongly Agreed (S.A.)/ 2: Agreed (A)/ 3: Undecided (UD)/ 4: Disagreed (DS)/5: Strongly Disagreed (SDA))
Table 6.9.5: Composite Table of Confidentiality of data and Usage of IT services of
Private Banks
S.No. Confidentiality of
data and Usage of
IT services
ICICI HDFC AXIS INDUSIND
1 Unawareness and
inadequate
Knowledge
49.333 48.421 49.091 46.364
2 Slow transfer speed
46.222 49.474 47.273 50.909
3 Delay in transmission
due to machine
breakdown
47.556 54.737 50.909 49.091
4 Increase in fraud due
to inefficient safety
and security features
48.889 49.474 46.364 47.273
Findings: The Table 6.9.5 shows that 46% of Indusind, 48% of HDFC, 49% of Axis and
49% of ICICI employees find that lack of confidentiality of data is due to unawareness
and inadequate knowledge.46% of ICICI, 47% of Axis employee find that confidentiality
of data leak due to slow transfer speed.51% of Axis, 55% of HDFC, 49% of Indusind and
48% of ICICI employees says confidentiality of data decreases due to machine
breakdown and technical failure.49% of HDFC and ICICI find fraud increases due to
inefficient safety and security features.
The result shows that all the banks face difficulty to protect the confidentiality of data
due to slow transfer speed, machine breakdown, technical failures etc. also frauds have
increased due to inefficient safety and security features.
Following is the graphical representation of attributes of Confidentiality of data and
usage of IT services.
303
303
6.10.1. Unawareness and Inadequate
knowledge
6.10.2. Slow transfer speed
6.10.3. Delay in transmission 6.10.4. Inefficient safety and security
Features
A. Chi-Square Test for Independence
Chi-square test for independence is applied to evaluate group differences when the test
variable is nominal, dichotomous, ordinal, or grouped interval. It is used to determine
whether there is a significant association between the two variables. This test is applied to
both customer and employee analysis. For example, in an election survey, voters might
be classified by gender (male or female) and voting preference (Democrat, Republican, or
Independent). We could use a chi-square test for independence to determine whether
gender is related to voting preference.
The test procedure is appropriate when the following conditions are met:
26%
25% 25%
24%
Unawareness and inadequate Knowledge
ICICI HDFC AXIS INDUSIND
24%
26% 24%
26%
Slow transfer speed
ICICI HDFC AXIS INDUSIND
24%
27% 25%
24%
Delay in transmission due to
machine breakdown
ICICI HDFC AXIS INDUSIND
25%
26% 24%
25%
Increase in fraud due to
inefficient \security features
ICICI HDFC AXIS INDUSIND
304
304
The sampling method is simple random sampling.
Each population is at least 10 times as large as its respective sample.
The variables under study are each categorical.
This approach consists of four steps:
(1) State the hypotheses,
(2) Formulate an analysis plan,
(3) Analyze sample data, and
(4) Interpret results.
State the Hypotheses
Formulate an Analysis Plan
The analysis plan describes how to use sample data to accept or reject the null hypothesis.
The plan should specify the following elements.
Significance level: Often, researchers choose significance levelsequal to 0.01,
0.05, or 0.10; but any value between 0 and 1 can be used.
Test method: Use the chi-square test for independence to determine whether
there is a significant relationship between two categorical variables.
Analyze Sample Data
Using sample data, find the degrees of freedom, expected frequencies, test statistic, and
the P-value associated with the test statistic. The approach described in this section is
illustrated in the sample problem at the end of this lesson.
Degrees of freedom. The degrees of freedom (DF) is equal to:
DF = (r - 1) * (c - 1)
where r is the row variable, and c is the column variable.
305
305
Expected frequencies. The expected frequency counts are computed separately
for each level of one categorical variable at each level of the other categorical
variable. Compute r * c expected frequencies, according to the following formula.
Er,c = (nr * nc) / n
where Er,c is the expected frequency count for level r of Variable A and level c of
Variable B, nr is the total number of sample observations at level r of Variable A,
nc is the total number of sample observations at level c of Variable B, and n is the
total sample size.
Test statistic: The test statistic is a chi-square random variable (Χ2) defined by
the following equation.
Χ2 = Σ [ (Or,c - Er,c)
2 / Er,c ]
where Or,c is the observed frequency count at level r of Variable A and level c of
Variable B, and Er,c is the expected frequency count at level r of Variable A and
level c of Variable B.
Significance level-The amount of evidence required to accept that an event is
unlikely to have arisen by chance is known as the significance level.
P-value: The P-value is the probability of observing a sample statistic as extreme
as the test statistic. Since the test statistic is a chi-square, use the Chi-Square
distribution calculator to assess the probability associated with the test statistic.
Use the degrees of freedom computed above.
Interpret Results
If the sample findings are unlikely, given the null hypothesis, the researcher rejects the
null hypothesis. Typically, this involves comparing the P-value to the significance level,
and rejecting the null hypothesis when the P-value is less than the significance level.In
Present study we have used Chi- Square Test of Independence. The analysis along with
result has calculated as below:
6.11. Relative Advantage
Relative advantage is an important component in determining adoption of new
innovations. It gives customers greater control over managing their finances, as they are
306
306
able to check their accounts easily. Following is the meaning of F1 to F8 for the table
below. F1 is safety and convenience, F2 is removing time and location constraint, F3 is
reduce costs of bank’s daily performance, F4 is save time of bank customers, F5 is save
time on daily responsibilities by e-banking, F6 is higher opportunities, F7 is sophisticated
services. The hypothesis is as follows:
H06a: There is no significant difference between relative advantages and adoption of IT
banking services.
Ha6a: There is a significant difference between relative advantages and adoption of IT
banking services.
Table 6.10.1.Observed Frequency (Relative Advantage)
Observed Frequency
Row
Variables
Components Column Variable
ICICI HDFC AXIS INDUSIND
F1 81.333 76.842 76.364 72.727
F2 79.111 75.789 72.727 73.636
F3 83.111 74.737 76.364 77.273
F4 86.222 76.842 74.783 70.000
F5 80.000 71.579 75.455 68.182
F6 79.556 79.474 77.273 74.545
F7 67.556 75.789 72.727 65.455
Table 6.10.2.Expected Frequency (Relative Advantage)
Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 80.887 77.135 76.356 72.888
F2 79.307 75.628 74.864 71.465
F3 81.998 78.194 77.404 73.889
F4 81.040 77.280 76.500 73.026
F5 77.715 74.109 73.361 70.030
F6 81.830 78.034 77.246 73.738
F7 74.111 70.673 69.960 66.783
307
307
Table 6.10.3.Difference between Observed and Expected Frequency
(Relative Advantage)
Observed Frequency-Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 0.446 -0.293 0.008 -0.161
F2 -0.196 0.162 -2.137 2.172
F3 1.113 -3.457 -1.041 3.384
F4 5.182 -0.438 -1.718 -3.026
F5 2.285 -2.530 2.093 -1.848
F6 -2.274 1.440 0.027 0.808
F7 -6.556 5.116 2.768 -1.328
Table 6.10.4. (Observed Frequency-Expected Frequency)2/ Expected Frequency
(Relative Advantage)
(Observed Frequency-Expected Frequency)2/ Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND TOTAL
F1 0.002 0.001 0.000 0.000 0.004
F2 0.000 0.000 0.061 0.066 0.128
F3 0.015 0.153 0.014 0.155 0.337
F4 0.331 0.002 0.039 0.125 0.498
F5 0.067 0.086 0.060 0.049 0.262
F6 0.063 0.027 0.000 0.009 0.099
F7 0.580 0.370 0.109 0.026 1.086
TOTAL 1.060 0.640 0.283 0.431 2.413
Table 6.10.5: Chi square test for Relative Advantage
Level of
Significanc
e (5%)
Numb
er of
Rows
Number
of
Columns
Degrees
of
Freedom
p-Value Calculat
ed value
Tabula
ted
value
Result
0.05 7 4 18 1.000 2.413 28.869 Accept
(Source: primary data-Questionnaire)
Findings: The Table 6.10.5 shows that p-value is greater than Level of significance and
the calculated value is less than the tabulated value. So, the null hypothesis H06a
(formulated above) is accepted. This reveals that there is no significant difference
between the relative advantages provided by different private banks to the adoption of IT.
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6.12. Complexities faced by Respondents in adopting banking services
Innovation with substantial complexity requires more technical skills and needs greater
implementation and operational efforts to increase its chances of adoption. Trust, security
and privacy are the important pillars that make the adoption of IT banking services faster.
Banks have to invest on promotional plans to make the customer feel easy of the complex
emerging technologies.
Following is the meaning of F1 to F5 for the table below. F1 is constantly monitor the
integrity of their security systems, F2 is opinion, adequate and appropriate investments on
hardware, software and banking application, F3 is making trust among bank employees
on security of networks, hardware and bank application, F4 is training programs and
promotional plans to provide e-banking culture, F5 is making trust among bank
customers on their privacy. The Hypothesis is as follows:
H06b: There is no significant difference between complexity and adoption of IT banking
services.
Ha6b: There is a significant difference between complexity and adoption of IT banking
services.
Table 6.11.1 Observed Frequency (Complexity)
Observed Frequency
Row
Variables
Components Column Variable
ICICI HDFC AXIS INDUSIND
F1 75.111 62.632 44.211 69.091
F2 80.000 76.842 45.789 73.636
F3 80.444 77.368 43.684 72.727
F4 52.000 73.158 41.579 75.455
F5 79.111 73.684 41.579 73.636
Table 6.11.2 Expected Frequency (Complexity)
Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 70.174 69.603 41.500 69.768
F2 77.224 76.596 45.670 76.778
F3 76.653 76.030 45.332 76.210
F4 67.699 67.148 40.036 67.307
F5 74.916 74.307 44.305 74.483
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Table 6.11.3. Difference between Observed and Expected Frequency (Complexity)
Observed Frequency-Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 4.937 -6.971 2.711 -0.677
F2 2.776 0.246 0.120 -3.141
F3 3.791 1.339 -1.648 -3.483
F4 -15.699 6.009 1.543 8.147
F5 4.195 -0.623 -2.726 -0.847
Table 6.11.4: (Observed Frequency-Expected Frequency)2/ Expected
Frequency(Complexity)
(Observed Frequency-Expected Frequency)2/ Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND TOTAL
F1 0.347 0.698 0.177 0.007 1.229
F2 0.100 0.001 0.000 0.129 0.229
F3 0.188 0.024 0.060 0.159 0.430
F4 3.641 0.538 0.059 0.986 5.224
F5 0.235 0.005 0.168 0.010 0.417
TOTAL 4.510 1.266 0.464 1.290 7.530
Table 6.11.5 Chi square test for Complexity
Level of
Significanc
e (5%)
Numb
er of
Rows
Number of
Columns
Degrees
of
Freedom
p-Value Calculat
ed value
Tabulat
ed
value
Result
0.05 5 4 15 0.110 7.530 24.996 Accept
(Source: primary data-Questionnaire)
Findings: The Table 6.11.5 shows that p-value is greater than Level of significance and
the calculated value is less than the tabulated value. So, the null hypothesis H06b
(formulated above) is accepted. This reveals that there is no significant difference
between the complexities faced by employees of different private banks to the adoption
of IT banking services.
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6.13. Potential Risk faced by employees in adopting banking technology
Risk is an additional dimension in the diffusion and adoption. A common and widely
recognized obstacle to electronic commerce adoption has been the lack of security and
privacy over the Internet. Thus, it is expected that only individuals who perceive using
Internet banking as a low risk undertaking should be inclined to adopt it.
Following is the meaning of F1 to F4 for the table below. F1 is knowledge of the e-
banking technology, F2 is Access to certain data should be minimized to keep data’s
integrity, F3 is importance of information security, and F4 is Bank’s employee’s need
expertise and training.
The hypothesis is as follow:
H06c: There is no significant difference between potential risk and adoption of IT banking
services.
Ha6c: There is a significant difference between potential risk and adoption of IT banking
services.
Table 6.12.1. Observed Frequency (Potential Risk)
Observed Frequency
Row
Variables
Components Column Variable
ICICI HDFC AXIS INDUSIND
F1 60.000 74.737 70.000 70.000
F2 73.778 77.895 72.727 70.000
F3 78.667 76.842 66.364 73.636
F4 65.333 80.526 64.545 70.000
Table 6.12.2. Expected Frequency (Potential Risk)
Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 66.648 74.380 65.655 68.054
F2 71.418 79.703 70.354 72.925
F3 71.687 80.003 70.619 73.199
F4 68.023 75.914 67.009 69.458
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Table 6.12.3. Difference between Observed and Expected Frequency
(Potential Risk)
Observed Frequency-Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 -6.648 0.357 4.345 1.946
F2 2.359 -1.808 2.374 -2.925
F3 6.979 -3.161 -4.255 0.437
F4 -2.690 4.612 -2.464 0.542
Table 6.12.4: (Observed Frequency-Expected Frequency)2/ Expected Frequency
(Potential Risk)
(Observed Frequency-Expected Frequency)2/ Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND TOTAL
F1 0.663 0.002 0.288 0.056 1.008
F2 0.078 0.041 0.080 0.117 0.316
F3 0.679 0.125 0.256 0.003 1.063
F4 0.106 0.280 0.091 0.004 0.481
TOTAL 1.527 0.448 0.715 0.180 2.869
Table 6.12.5: Chi square test for Potential Risk
Level of
Significance
(5%)
Numb
er of
Rows
Number
of
Columns
Degrees
of
Freedom
p-Value Calculat
ed value
Tabulat
ed
value
Result
0.05 4 4 9 0.412 2.869 16.919 Accept
(Source: primary data-Questionnaire)
Findings: The Table 6.12.5 shows that p-value is greater than Level of significance and
the calculated value is less than the tabulated value. So, the null hypothesis H06c
(formulated above) is accepted. This reveals that there is no significant difference
between potential risks faced by employees of different private banks to the adoption of
IT banking services.
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6.14. IT Strategic decision making
Information Technology in banks helps in setting IT infrastructure for information
network to provide the layer of technology necessary to perform the data storage and
analysis processing. Constant evaluation of alternatives ,displaying Information on web
page, financial feasibility study helps in overcoming the competition pressure and
smoothening the decision making process.
Following is the meaning of F1 to F10 for the table below. F1 is external information
network to identify requirements in Information Technology, F2 is specific selection criteria
for the acquisition of new information systems, F3 is financial tools in planning the
acquisition of new information systems, F4 is Knowing the Information Technology used
by your competition, F5 is Knowing the impact that IT will have on the different
functions of your bank, F6 is Disseminating Information on web page, F7 is Ensuring that
choice of Information Technology follows the evolution of your environment, F8 is
Evaluating potential problems related with the implementation of a new system, F9 is
results of a financial feasibility study before the acquisition, F10 is Identification of
possible sources of resistance to change before implementation.
The Hypothesis is as follows:
H06d: There is no significant difference between strategic decision making and adoption
of IT banking services.
Ha6d: There is a significant difference between strategic decision making and adoption of
IT banking services.
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Table 6.13.1. Observed Frequency (Strategic decision making)
Observed Frequency
Row
Variables
Components Column Variable
ICICI HDFC AXIS INDUSIND
F1 76.889 74.211 62.727 70.909
F2 76.500 76.316 65.455 66.364
F3 75.611 72.105 60.909 68.182
F4 65.389 75.789 69.091 74.545
F5 69.056 82.105 62.727 69.091
F6 65.111 72.105 74.545 68.182
F7 76.667 72.632 65.455 72.727
F8 67.111 72.632 66.364 67.273
F9 68.333 72.105 69.091 73.636
F10 75.056 70.526 70.909 61.818
Table 6.13.2. Expected Frequency (Strategic decision making)
Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 72.363 74.871 67.464 70.038
F2 72.337 74.844 67.440 70.013
F3 70.348 72.786 65.586 68.088
F4 72.383 74.891 67.483 70.057
F5 71.916 74.409 67.048 69.606
F6 71.145 73.611 66.329 68.859
F7 73.060 75.592 68.115 70.713
F8 69.477 71.884 64.774 67.244
F9 71.964 74.458 67.092 69.652
F10 70.730 73.181 65.942 68.457
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Table 6.13.3. Difference between Observed and Expected Frequency
(Strategic decision making)
Observed Frequency-Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 4.526 -0.660 -4.737 0.871
F2 4.163 1.472 -1.986 -3.649
F3 5.263 -0.681 -4.677 0.094
F4 -6.994 0.898 1.608 4.488
F5 -2.861 7.697 -4.321 -0.515
F6 -6.034 -1.505 8.217 -0.677
F7 3.606 -2.961 -2.660 2.014
F8 -2.366 0.747 1.590 0.028
F9 -3.631 -2.353 1.999 3.985
F10 4.326 -2.654 4.967 -6.639
Table 6.13.4: (Observed Frequency-Expected Frequency) 2
/ Expected Frequency
(Strategic decision making)
(Observed Frequency-Expected Frequency)2/ Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND TOTAL
F1 0.283 0.006 0.333 0.011 0.632
F2 0.240 0.029 0.058 0.190 0.517
F3 0.394 0.006 0.333 0.000 0.734
F4 0.676 0.011 0.038 0.288 1.012
F5 0.114 0.796 0.278 0.004 1.192
F6 0.512 0.031 1.018 0.007 1.567
F7 0.178 0.116 0.104 0.057 0.455
F8 0.081 0.008 0.039 0.000 0.127
F9 0.183 0.074 0.060 0.228 0.545
F10 0.265 0.096 0.374 0.644 1.379
TOTAL 2.924 1.173 2.636 1.428 8.161
Table 6.13.5: Chi square test- Strategic Advantage by Decision making Process
Level of
Significance
(5%)
Numb
er of
Rows
Number
of
Columns
Degrees
of
Freedom
p-Value Calculat
ed value
Tabula
ted
value
Result
0.05 10 4 27 0.5179 8.162 40.113 Accept
(Source: primary data-Questionnaire)
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315
Findings: The Chi-square test was used at 5 percent significant level. The Table 6.13.5
shows that p-value is greater than Level of significance and the calculated value is less
than the tabulated value. So, the null hypothesis H06d (formulated above) is accepted. This
reveals that there is no significant difference between strategies adopted by employees of
different private banks in smoothening their decision making process to the adoption of
IT banking services.
6.15. Innovation and Development
An innovation is an idea, practice, or object that is perceived to be new by a person or
adopting entity. Pushed by growing consumer demand and the fear of losing market
share, banks are investing heavily in PC banking technology. Collaborating with
hardware, software, telecommunications and other companies, banks are introducing new
ways for consumers.
Following is the meaning of F1 to F4 for the table below. F1 is Reduce production costs,
F2 is Make substantial savings, F3 is Improve firm's productivity, F4 is Improve the
quality of products or services. The hypothesis is as follows:
H06e: There is no significant difference between innovation and development &adoption
of IT banking services.
Ha6e: There is a significant difference between innovation and development &adoption of
IT banking services.
Table 6.14. Observed Frequency (Innovation & Development)
Observed Frequency
Row
Variables
Components Column Variable
ICICI HDFC AXIS INDUSIND
F1 72.889 75.789 72.727 70.909
F2 74.389 69.474 70.909 60.909
F3 75.556 73.333 70.000 65.455
F4 75.278 77.895 70.909 65.455
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Table 6.14.2. Expected Frequency (Innovation & Development)
Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 76.315 75.900 72.842 67.257
F2 71.972 71.581 68.697 63.430
F3 74.234 73.831 70.856 65.423
F4 75.590 75.179 72.150 66.618
Table 6.14.3Difference between Observed and Expected Frequency
(Innovation & Development)
Observed Frequency-Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 -3.426 -0.111 -0.115 3.652
F2 2.416 -2.108 2.212 -2.521
F3 1.322 -0.497 -0.856 0.032
F4 -0.312 2.716 -1.241 -1.163
Table 6.14.4: (Observed Frequency-Expected Frequency)2/ Expected
Frequency(Innovation & Development)
(Observed Frequency-Expected Frequency)2/ Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND TOTAL
F1 0.154 0.000 0.000 0.198 0.352
F2 0.081 0.062 0.071 0.100 0.315
F3 0.024 0.003 0.010 0.000 0.037
F4 0.001 0.098 0.021 0.020 0.141
TOTAL 0.260 0.164 0.103 0.319 0.845
Table 6.14.5: Chi square test for Innovation and Development
Level of
Significanc
e (5%)
Numb
er of
Rows
Number
of
Columns
Degrees
of
Freedom
p-Value Calculat
ed value
Tabula
ted
value
Result
0.05 7 4 18 1.000 2.413 28.869 Accept
(Source: primary data-Questionnaire)
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317
Findings: The Table 6.14.5 shows that p-value is greater than Level of significance and
the calculated value is less than the tabulated value. So, the null hypothesis H06e
(formulated above) is accepted. This reveals that there is no significant difference
between Innovation and Development adopted by different private banks to the adoption
of IT banking services.
6.16. Confidentiality of data and usage of IT services
Following is the meaning of F1 to F4 for the table below. F1 is Unawareness and
inadequate Knowledge, F2 is Slow transfer speed, F3 is Delay in transmission due to
machine breakdown/ Machine complexity/ Technical failure, F4 is Increase in fraud due
to inefficient safety and security features. The hypothesis is as follows:
The hypothesis is formulated for Confidentiality of data and usage of IT services:
H07: There is no significant difference between Confidentiality of data and usage of IT
services.
Ha7: There is no significant difference between Confidentiality of data and usage of IT
services.
Table 6.15.1.Observed Frequency (Confidentiality of data and usage of IT services)
Observed Frequency
Row
Variables
Components Column Variable
ICICI HDFC AXIS INDUSIND
F1 49.333 48.421 49.091 46.364
F2 46.222 49.474 47.273 50.909
F3 47.556 54.737 50.909 49.091
F4 48.889 49.474 46.364 47.273
Table 6.15.2.Expected Frequency (Confidentiality of data and usage of IT services)
Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 53.315 47.922 47.446 44.526
F2 53.499 48.088 47.610 44.680
F3 55.821 50.175 49.677 46.620
F4 52.981 47.622 47.149 44.247
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Table 6.15.3. Difference between Observed and Expected Frequency
(Confidentiality of data and usage of IT services)
Observed Frequency-Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND
F1 -3.981 0.499 1.645 1.837
F2 -7.277 1.385 -0.337 6.229
F3 -8.266 4.562 1.233 2.471
F4 -4.092 1.851 -0.785 3.025
Table 6.15.4: (Observed Frequency-Expected Frequency) 2
/ Expected Frequency
(Confidentiality of data and usage of IT services)
(Observed Frequency-Expected Frequency)2/ Expected Frequency
Row
Variable
Column Variable
ICICI HDFC AXIS INDUSIND TOTAL
F1 0.297 0.005 0.057 0.076 0.297
F2 0.990 0.040 0.002 0.868 0.990
F3 1.224 0.415 0.031 0.131 1.224
F4 0.316 0.072 0.013 0.207 0.316
TOTAL 2.827 0.532 0.103 1.282 2.827
Table 6.15.5: Chi square test for Confidentiality of data and usage of IT services
Level of
Significance
(5%)
Number
of Rows
Number
of
Columns
Degrees
of
Freedom
P-
Valu
e
Calculated
value
Tabulated
value Result
0.05 4 4 9 0.85
6
4.743 16.919 Accept
(Source: primary data-Questionnaire)
Findings:Chi-square test was used at 5 percent significant level. The table 6.15.5 shows
that p-value is greater than Level of significance and the calculated value is less than the
tabulated value. So, the null hypothesis H07 (Formulated above) is accepted. This reveals
that there is no significant difference between Confidentiality of data and usage of IT
services by different private banks to the adoption of IT banking services.
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B. One way ANOVA (Analysis of Variance)
Following tool is used to analysis the present study:
Analysis of variance (Analysis of Variance) is a general method for studying sampled-
data relationships. The method enables the difference between two or more sample means
to be analyzed, achieved by subdividing the total sum of squares. The purpose is to test
for significant differences between class means, and this is done by analyzing the
variances. The basis of ANOVA is the partitioning of sums of squares into between-class
(SSB) and within-class (SSW). It enables all classes to be compared with each other
simultaneously rather than individually; it assumes that the samples are normally
distributed. The one way analysis is calculated in three steps, first the sum of squares for
all samples, then the within class and between class cases. For each stage the degrees of
freedom (df) are also determined, where df is the number of independent `pieces of
information' that go into the estimate of a parameter. These calculations are used via the
Fisher statistic to analyze the null hypothesis.
The null hypothesis states that there are no differences between means of different
classes, suggesting that the variance of the within-class samples should be identical to
that of the between-class samples (resulting in no between-class discrimination
capability). It must however be noted that small sample sets will produce random
fluctuations due to the assumption of a normal distribution.
Grand Mean
The grand mean of a set of samples is the total of all the data values divided by the total
sample size. This requires all of the sample data. It turns to find a one-way analysis of
variance is the number of samples, the sample means, the sample variances, and the
sample sizes.
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320
Another way to find the grand mean is to find the weighted average of the sample means.
The weight applied is the sample size.
Total Variation
The total variation (not variance) is comprised the sum of the squares of the differences
of each mean with the grand mean.
There is the between group variation and the within group variation. The whole idea
behind the analysis of variance is to compare the ratio between group variance to within
group variance. If the variance caused by the interaction between the samples is much
larger when compared to the variance that appears within each group, then it is because
the means aren't the same.
Between Group Variation
The variation due to the interaction between the samples is denoted SS (B) for Sum of
Squares Between groups.
If the sample means are close to each other (and therefore the Grand Mean) this will be
small. There are k samples involved with one data value for each sample (the sample
mean), so there are k-1 degrees of freedom. The variance due to the interaction between
the samples is denoted MS (B) for Mean Square Between groups. This is the between
group variation divided by its degrees of freedom. It is also denoted by Sb2.
Within Group Variation
The variation due to differences within individual samples denoted SS (W) for Sum of
Squares Within groups. SS(W)=∑ df .S2
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Each sample is considered independently, no interaction between samples is involved.
The degree of freedom is equal to the sum of the individual degrees of freedom for each
sample. Since each sample has degrees of freedom equal to one less than their sample
sizes, and there are k samples, the total degrees of freedom is k less than the total sample
size: df = N - k. The variance due to the differences within individual samples is denoted
MS (W) for Mean Square Within groups. This is the within group variation divided by its
degrees of freedom. It is also denoted by Sw2. It is the weighted average of the variances
(weighted with the degrees of freedom).
F test statistic
F variable is the ratio of two independent chi-square variables divided by their respective
degrees of freedom. Also F test statistic is the ratio of two sample variances, well; it turns
out that's exactly what we have here. The F test statistic is found by dividing the between
group variance by the within group variance. The degrees of freedom for the numerator
are the degrees of freedom for the between group (k-1) and the degrees of freedom for the
denominator are the degrees of freedom for the within group (N-k).
SS df MS F
Between SS(B) k-1 SS(B)
-----------
k-1
MS(B)
--------------
MS(W)
Within SS(W) N-k SS(W)
-----------
N-k
.
Total SS(W) + SS(B) N-1 .
Here the calculated value is compared with the tabulated values of each group. If F
exceeds the tabulated value at some significant level (usually 0.05) it means that there is
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evidence to reject the null hypothesis in favor of the alternate hypothesis. In present study
One way ANOVA is used for each segment.
Following five segments in the questionnaire:
I. Relative advantage
II. Complexities
III. Potential risk
IV. IT Strategic Decision making process
V. Innovation and development
There can be Two types of hypothesis coming from One Way ANOVA.
i. H0:All mean of responses are equal (Null Hypothesis)
ii. Ha: Not all mean of responses are equal (Alternate Hypothesis)
6.17: Relative advantage (One Way ANOVA Test)
The hypothesis for relative advantage is as follows:
H08a: There is no difference between the mean of relative advantages among different
bank groups.
Ha8a: There is a difference between the mean of relative advantages among different bank
groups.
Table 6.16.1: Composite Table of Relative Advantages of Private Banks
S.No. Relative Advantage ICICI HDFC AXIS INDUSIND
1 Safety and
Convenience 81.333 76.842 76.364 72.727
2 Time and location
constraint 79.111 75.789 72.727 73.636
3 Reduce costs 83.111 74.737 76.364 77.273
4 Save time of bank
customers 86.222 76.842 74.783 70.000
5 Daily responsibilities 80.000 71.579 75.455 68.182
6 Higher opportunities 79.556 79.474 77.273 74.545
7 Sophisticated services 67.556 75.789 72.727 65.455
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Anova: Single Component
Table 6.16.2: Average and Variance (Relative Advantage)
Groups Count Sum Average Variance
Column 1 7 556.889 79.556 34.107
Column 2 7 531.053 75.865 5.764
Column 3 7 525.692 75.099 3.233
Column 4 7 501.818 71.688 16.371
Table 6.16.3: One Way Anova (Relative Advantage)
Source of Variation SS Df MS F P-value F crit
Between Groups 218.818 3.000 72.939 4.905 0.008 3.009
Within Groups 356.858 24.000 14.869
Total 575.675 27.000
Findings: Here for this segment F value is greater than the F critical value; hence
difference is significant and null hypothesis is rejected. There is a difference between the
mean of relative advantages among different bank groups.
6.18. Complexities (One Way ANOVA Test)
The hypothesis for complexities faced by the employees is as follows:
H08b: There is no difference between the mean of complexity among different bank
groups.
Ha8b: There is a difference between the mean of complexity among different bank groups.
Table 6.17.1: Composite Table of Complexity of Private Banks
S.No. Complexity ICICI HDFC AXIS INDUSIND
1 Monitor the integrity 75.111 62.632 44.211 69.091
2 Adequate
investments 80.000 76.842 45.789 73.636
3 Trust –security 80.444 77.368 43.684 72.727
4 Promotional plans 52.000 73.158 41.579 75.455
5 Trust –privacy 79.111 73.684 41.579 73.636
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Anova: Single Component
Table 6.17.2: Average and Variance (Complexity)
Groups Count Sum Average Variance
Column 1 5 366.667 73.333 146.667 Column 2 5 363.684 72.737 35.374 Column 3 5 216.842 43.368 3.269 Column 4 5 364.546 72.909 5.537
Table 6.17.3: One Way Anova (Complexity)
Source of Variation SS df MS F P-value F crit
Between Groups 3292.021 3.000 1097.340 22.999 0.000 3.239
Within Groups 763.386 16.000 47.712
Total 4055.407 19.000
Findings: Here for this segment F value is greater than the F critical value; hence
difference is significant and null hypothesis is rejected. The Complexity faced by bank
employees in managing e-banking system is not same for all four banks.
6.19. Measures adopted by employees to reduce Potential Risk
The hypothesis for measures taken by employees to reduce potential risk is as follows:
H08c: There is no difference between the mean of potential risk among different bank
groups.
Ha8c: There is a difference between the mean of potential risk among different bank
groups.
Table 6.18.1: Composite Table of Potential Risk associated with Private Banks
S.No. Potential Risk ICICI HDFC AXIS INDUSIND
1 Knowledge 60.000 74.737 70.000 70.000
2 Data’s integrity 73.778 77.895 72.727 70.000
3 Information security 78.667 76.842 66.364 73.636
4 Expertise and training 65.333 80.526 64.545 70.000
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Anova: Single Component
Table 6.18.2: Average and Variance (Potential Risk)
Groups Count Sum Average Variance
Column 1 4 277.778 69.444 69.975
Column 2 4 310.000 77.500 5.794
Column 3 4 273.636 68.409 13.430
Column 4 4 283.636 70.909 3.306
Table 6.18.3: One Way Anova (Potential Risk)
Source of Variation SS df MS F P-value F crit
Between Groups 200.444 3.000 66.815 2.889 0.079 3.490
Within Groups 277.515 12.000 23.126
Total 477.959 15.000
Findings: Here for this segment F value is less than the F critical value; hence difference
is insignificant and null hypothesis is accepted. Bank’s employees understanding of
information security to avoid potential risk is same for four banks.
6.20. IT Strategic Advantage by Decision Making:
The hypothesis for IT Strategic advantage by decision making is as follows:
H08d: There is no difference between the mean of strategic decision making among
different bank groups.
Ha8d: There is a difference between the mean of strategic decision making among
different bank groups.
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Table 6.19.1: Composite Table for Strategic Decision Making Process
S.No
.
Strategic Advantage
by Decision making
ICICI HDFC AXIS INDUSIND
1 Information network 76.889 74.211 62.727 70.909
2 Selection criteria 76.500 76.316 65.455 66.364
3 Financial tools 75.611 72.105 60.909 68.182
4 IT by competitor 65.389 75.789 69.091 74.545
5 Impact on function of
bank 69.056 82.105 62.727 69.091
6 Information on web
page 65.111 72.105 74.545 68.182
7 Choice of IT 76.667 72.632 65.455 72.727
8 Problems-
implementation 67.111 72.632 66.364 67.273
9 Results financial
feasibility study 68.333 72.105 69.091 73.636
10 Sources of resistance
to change 75.056 70.526 70.909 61.818
Anova: Single Component
Table 6.19.2: Average and Variance (IT Strategic Advantage)
Groups Count Sum Average Variance
Column 1 10 715.722 71.572 24.851
Column 2 10 740.526 74.053 11.207
Column 3 10 667.273 66.727 17.668
Column 4 10 692.727 69.273 14.656
Table 6.19.3: One Way Anova (IT Strategic Advantage)
Source of Variation SS df MS F P-value F crit
Between Groups 294.753 3.000 98.251 5.747 0.003 2.866
Within Groups 615.422 36.000 17.095
Total 910.176 39.000
Findings: Here for this segment F value is greater than the F critical value; hence
difference is significant and null hypothesis is rejected. Role of Technology in strategic
decision making process is same for all four banks.
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6.21: Innovation and Development (One Way ANOVA Test)
The hypothesis for Innovation & development among different banks is as follows:
H08e: There is no difference between the mean of innovation & development among
different bank groups.
Ha8e: There is a difference between the mean of innovation & development among
different bank groups.
Table 6.20.1: Composite Table for Innovation and Development among
Private Banks
S.No. Innovation and Development ICICI HDFC AXIS INDUSIND
1 Reduce production costs 72.889 75.789 72.727 70.909
2 Substantial savings 74.389 69.474 70.909 60.909
3 Improve firm's productivity 75.556 73.333 70.000 65.455
4 Quality of products or services 75.278 77.895 70.909 65.455
Anova: Single Component
Table 6.16.2: Average and Variance (Innovation & Development)
Groups Count Sum Average Variance
Column 1 4 298.111 74.528 1.441 Column 2 4 296.491 74.123 13.081 Column 3 4 284.546 71.136 1.309 Column 4 4 262.727 65.682 16.736
Table 6.16.3: One Way Anova (Innovation & Development)
Source of Variation SS df MS F P-value F crit
Between Groups 199.838 3.000 66.613 8.182 0.003 3.490
Within Groups 97.699 12.000 8.142
Total 297.537 15.000
Findings: Here for this segment F value is greater than the F critical value; hence
difference is significant and null hypothesis is rejected. Role of Information Technology
in making innovations and developments is same for all four banks.
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6.22. Important Findings:
Sex as a personal variable was found to have a significant effect on employee’s
preferences. The survey revealed that the numbers of male employees are more than
female employees. Age is the component that determines job opportunity according to
different age category & experience of the employees. There is several job opportunities
for age group of 25-36 years in private sector banks. Designation is the component that
determines job position of the employee in the organization. Popularity for banking jobs
is between age group of 25-36 years in private sector banks. Experience determines skill
and knowledge of the employees. There is increasing number of talent pool in different
operational areas of banks. Most of educational qualification being demanded by banks is
post graduation that includes M.Com, M.B.A., ICWAI and others.
Induction training program is organized by the banks for new starter to help them
do their job better and quicker, adjust or acclimatize quickly and effectively into their
new working environment. HDFC employees prefer more than 41 hours of induction
program.
Computer and internet training program becomes compulsory for organization to
meet the increasing need of customer data protection and to meet daily task.41%
employees of AXIS bank, 36 % employees of IDUSIND bank, 29% employees of ICICI
bank and 18% employees of HDFC bank have attended more than 41 hours of training
program.
Working on computer makes the task easier, save time and provide accuracy. It
improves organizational productivity and efficiency. The study found that most of
respondents are using computers more than 9 hours in their daily task.
Customer awareness must be an important part of an overall information security
education program; consumer awareness programs create more informed buying
decisions. The study shows the increasing popularity of Internet banking and mobile
banking besides ATMs and branch banking among customers.
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ICICI, HDFC, Axis bank advancement in new technologies has increase
efficiency, reduction in cost help in achieving higher level of productivity. It has reduced
location and time constraint, now employees may work on diversified task, may adopt
them according to the changing environment and customer demands. Technology helps in
empowering employees with new ideas and innovation. Training and resources are given
for the process to evolve; employees are expected to develop feelings of self-efficacy, job
satisfaction, security, confidence and job meaningfulness.
ICICI, HDFC and Indusind employees are active in handling the complex issues
related to privacy, security, integrity of data and investment related aspects. Employees
are proactive and reactive in security related aspects of customer and this help in
increasing satisfaction and trust among customers. The customer trust bank as they
maintain privacy of data and information.
ICICI, HDFC and Indusind bank has well trained their employee to manage
different types of risk from malicious hacker or insider attacks, viruses, denial-of-service
attacks, data theft, data destruction and fraud by security control and risk management
techniques. The information produced or processed during the risk analysis should be
categorized according to its sensitivity to loss or disclosure information security.
ICICI, HDFC and Axis employee found that application of information
technology has improved decision making related to the development of networks. IT
infrastructure provides the layer of technology to perform the data storage and analysis
processing. Employee use information technology in strategic selection of software,
hardwares and other IT equipments. Employee found information technology decision
has provided resistance to changes. The business objectives should be identified for the
solution being sought and the management decision whether building, leasing, or buying
the IT application such as Management information system, knowledge based system,
business intelligence and data warehousing.
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ICICI, HDFC and Axis banks are successful in driving the development of
innovative product features, reducing transaction costs, enhancing customer service
delivery and minimizing inherent risks. It has improved its productivity by the
development of innovative product and service features. ICICI bank has introduced
kiosks and smart cards in rural areas, this has reduced transaction cost.
Indusind, HDFC, Axis and ICICI employees found that lack of confidentiality of
data is because of unawareness and inadequate knowledge. Confidentiality of data leak
due of slow transfer speed, machine break down and technical failure. Fraud increases
because of inefficient safety and security features.
Chi square test was applied to know the association between two attributes. Chi-square
was used tested at 5 percent significant level. The result reveals that p-value is greater
than level of significance and the calculated value is less than the tabulated value. So, the
null hypotheses were accepted. This reveals that there is no significant difference
between the relative advantages provided by different private banks to the adoption of IT.
There is no significant difference between complexities faced by employees of different
private banks to adoption of IT banking services. There is no significant difference
between potential risks faced by employees of different private banks to the adoption of
IT banking services. There is no significant difference between strategies adopted by
employees of different private banks in smoothening their decision making process to the
adoption of IT banking services. There is no significant difference between Innovation
and Development adopted by different private banks to the adoption of IT banking
services.There is no significant difference between Innovation and Development adopted
by different private banks to the adoption of IT banking services.
One way ANOVA is to test significant differences between class means, and this
is done by analyzing the variances. It is use to test the following segments. Segment I:
Relative advantage- F value is greater than the F critical value, null hypothesis of equal
mean is rejected. There is significant differences among the population means The
relative advantages provided by the emergence of technology in not same for four banks.
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Segment II: Complexities - F value is greater than the F critical value; hence difference is
significant and null hypothesis is rejected. Complexity faced by bank employees in
managing e-banking system is not same for all four banks. Segment III: Potential Risk- F
value is less than the F critical value; hence difference is insignificant and null hypothesis
is accepted. Bank’s employees understanding of information security to avoid potential
risk is same for four banks. Segment IV: Strategic Advantage by Decision making- F
value is greater than the F critical value; hence difference is significant and null
hypothesis is rejected. Role of Technology in strategic decision making process is same
for all four banks. Segment V: Innovation and Development - F value is greater than the
F critical value; hence difference is significant and null hypothesis is rejected. Role of
Information Technology in making innovations and developments is same for all four
banks.
This study evaluates the perceptions of banking employees regarding the effect of
technological innovations on banking services. The dependency on information
technology (IT) has increased progressively for organizations as a strategically important
competitive advantage. If planned, developed, and managed properly, IT can bring about
greater efficiency in organizational operations, better working environments, and
effective decision-making processes. Commercial banks can increase their performance
by employing new technologies. Innovative firms grow faster in terms of employment
and profitability. They should employ new information technologies to raise their service
capability in the e-commerce age.