CHAPTER-6: AN EMPIRICAL STUDY OF EMPLOYEE'S

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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


(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


(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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(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


23%

26% 26%

25%

Internet Banking


24%

25% 27%

24%

Mobile/Tele Banking


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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


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


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


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


26%

25% 24%

25%

Time and location constraint


25%

25% 26%

24%

Reduce costs


28%

25% 24%

23%

Save time of bank customers


27%

24% 26%

23%

Daily responsibilities


26%

25% 25%

24%

Higher opportunities


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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


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Table 6.5.2: Complexity (HDFC Bank)

S.N

o.


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.


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.


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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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


29%

28% 16%

27%

Adequate investments


29%

28% 16%

27%

Trust -security


22%

30% 17%

31%

Promotional plans


30%

27% 16%

27%

Trust -privacy


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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.


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.


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.


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


25%

26% 25%

24%

Data’s integrity


27%

26% 22%

25%

Information security


23%

29% 23%

25%

Expertise and training


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


27%

27% 23%

23%

Selection criteria


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


23%

27% 24%

26%

IT by competitor


24%

29% 22%

25%

Impact on function of bank


23%

26% 27%

24%

Information on web page


27%

25% 23%

25%

Choice of IT


24%

27% 24%

25%

Problems-implementation


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


27%

25% 26%

22%

Sources of resistance to change


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


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


27%

25% 26%

22%

Substantial savings


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


26%

27% 24%

23%

Quality of products or services


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


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


24%

26% 24%

26%

Slow transfer speed


24%

27% 25%

24%

Delay in transmission due to

machine breakdown


25%

26% 24%

25%

Increase in fraud due to

inefficient \security features


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.

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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

http://stattrek.com/Tables/ChiSquare.aspx

http://stattrek.com/Tables/ChiSquare.aspx

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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


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


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


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.

308

308

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



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


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)


Row

Variable

Column Variable


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)


Row

Variable

Column Variable


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



the calculated value is less than the tabulated value. So, the null hypothesis H06b


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



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


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)


Row

Variable

Column Variable


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)


Row

Variable

Column Variable


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



the calculated value is less than the tabulated value. So, the null hypothesis H06c


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


Ha6d: There is a significant difference between strategic decision making and adoption of


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Table 6.13.1. Observed Frequency (Strategic decision making)

Observed Frequency

Row

Variables



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


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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(Strategic decision making)


Row

Variable

Column Variable


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)


Row

Variable

Column Variable


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


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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


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


Ha6e: There is a significant difference between innovation and development &adoption of


Table 6.14. Observed Frequency (Innovation & Development)

Observed Frequency

Row

Variables



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


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)


Row

Variable

Column Variable


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)


Row

Variable

Column Variable


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


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the calculated value is less than the tabulated value. So, the null hypothesis H06e


between Innovation and Development adopted by different private banks to the adoption


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



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


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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(Confidentiality of data and usage of IT services)


Row

Variable

Column Variable


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)


Row

Variable

Column Variable


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


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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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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Table 6.17.2: Average and Variance (Complexity)


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


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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Table 6.18.2: Average and Variance (Potential Risk)


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)


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


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Table 6.19.1: Composite Table for Strategic Decision Making Process

S.No

.

Strategic Advantage

by Decision making


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


Table 6.19.2: Average and Variance (IT Strategic Advantage)


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)


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


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


Ha8e: There is a difference between the mean of innovation & development among


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


Table 6.16.2: Average and Variance (Innovation & Development)


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)


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


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.

Documents

CHAPTER-6: AN EMPIRICAL STUDY OF EMPLOYEE'S