G. CHAPTER 4

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CHAPTER 4: ANALYSIS

4.1. DESCRIPTIVE STATISTICSFor the research, descriptive statistics include the numbers, charts and graphs used to

describe, organize and present data on each variable. For the research five variables were

determined: IT System, IT Skill, IT Training, IT Training, Empowerment and Performance.

Values of the variables were derived after averaging five questions under each variable.

Mean, standard deviation, variance, minimum & maximum value for each value is shown in

the following table.

TABLE 1: Descriptive Statistics of all variables

DESCRIPTIVE STATISTICS

N Minimu

m

Maximum Mean Std.

Deviation

Variance

It.System 110 1.20 4.60 3.1091 .83045 .690

It.Skill 110 1.40 4.60 3.2618 .76614 .587

It.Training 110 1.00 5.00 3.0927 .94303 .889

Empowerment 110 1.20 4.80 3.2873 .78450 .615

Performence 110 1.00 5.00 3.2036 .85455 .730

Valid N (listwise) 110

This table provides the basic statistical information about the data set, such as showing the

mean response for average of five questions for each variable individual questions and its

deviation from the mean. For this information, for instance we find that the among the 110

participants 59 were male and 51 were female which is equal to 53.6% male & 46.4% female.

Participants of the research came from various age groups. Age range of the participants is 20

to above 40. But most of the participants belongs to the age group 25 -34 & 31 -35. These

descriptive statistics of the entire data set has been represented in Table 1 (given in

Appendix)

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4.2. GRAPHICAL REPRESENTATION OF DATA ANDFREQUENCY DISTRIBUTION

TABLE 1: Gender of the employees in Citibank N.A

Frequency Percent Valid Percent Cumulative Percent

Valid Male 59 53.6 53.6 53.6

Female 51 46.4 46.4 100.0

Total 110 100.0 100.0

Figure:1 Histogram showing the frequency distribution of the employees gender

DATA ANALYSIS

There were 110 respondents of which 59 were male and 51 were female. These respondents

are all employees in Citibank, N.A. from various departments.

INTERPRETATION

From the sample size of 110 employees working in Citibank N.A. the number of male are

more than the female.

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TABLE 2: Employees Age Distribution


Valid 20 -24 7 6.4 6.4 6.4

25-30 42 38.2 38.2 44.531-35 45 40.9 40.9 85.5

35-40 10 9.1 9.1 94.5

40 6 5.5 5.5 100.0

Total 110 100.0 100.0

Figure 2: Bar chart showing the frequency age distribution of the employees at

Citibank, N.A.

DATA ANALYSIS

Out of 110 employees, 44.5% of the employees belong to 20 - 30 age range, 50% of the

employees are in the age group of 30 40 and the rest 5.5% of the employees age are above

40.

INTERPRETATION

The numbers of employees working in Citibank N.A. are mostly in their mid thirties.

However, there is also a significant number of employees who are at their mid twenties. This

shows that Citibank N.A. has a young labour force as there are only few employees who are

above forties.

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TABLE 3: Satisfied with the IT systems that are used in the current process.

Frequency Percent Valid Percent

Cumulative

Percent

Valid Strongly Agree 11 10.0 10.0 10.0

Agree 27 24.5 24.5 34.5Neutral 31 28.2 28.2 62.7

Disagree 23 20.9 20.9 83.6

Strongly disagree 18 16.4 16.4 100.0

Total 110 100.0 100.0

Figure 3: Bar chart showing the frequency distribution

DATA ANALYSIS

Of the respondents 10% strongly agreed to the satisfaction in the current IT system used in

the current process, 25% agreed, 28% are neutral about the satisfaction with the IT system,

21% disagreed that there is no satisfaction and 16.4% strongly disagreed.

INTERPRETATION

Most of the employees are indifferent about the IT systems that are being used in their current

process. Although a significant number of employees are satisfied with their current process

IT system. It is because, employees arent aware of the different method or software used in

the job.

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TABLE 4: The IT system used in our current process can be improved.


Cumulative

Percent


Agree 28 25.5 25.5 30.9

Neutral 26 23.6 23.6 54.5

Disagree 35 31.8 31.8 86.4


Total 110 100.0 100.0

Figures 4: Bar chart and line curve shows the frequency distribution

DATA ANALYSIS

Of the respondents 5.5% strongly agreed to the improvement in IT system, 26% agreed, 24%

are neutral about the improvement in IT system, 32% disagreed that there is no need for

improvement and 14% strongly disagreed.

INTERPRETATION

Majority of the employees said that the IT system used in their current system doesnt need to

be improved. However, a significant number of employees feel the need of improvement in

their current IT system.

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TABLE 5: An improve IT system is needed to enhance skills.


Cumulative

Percent


Agree 37 33.6 33.6 41.8Neutral 26 23.6 23.6 65.5

Disagree 31 28.2 28.2 93.6


Total 110 100.0 100.0

Figure 5: Area curve shows the frequency distribution

DATA ANALYSIS

Of the respondents 8.2% strongly agreed to the enhancement in skills, 34% agreed, 24% are

neutral about the enhancement, 28% disagreed that there is no need for enhancement and 6%

strongly disagreed.

INTERPRETATION

Most of the employees said that their skill can be improved if there is an improvement in the

IT system. It is because the current IT system used by the employees of Citibank, N.A. isnt

satisfactory for which their skills arent able to enhance.

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TABLE 6: An improve IT system helps to perform effectively by saving time


Cumulative

Percent


Agree 19 17.3 17.3 35.5

Neutral 22 20.0 20.0 55.5Disagree 32 29.1 29.1 84.5


Total 110 100.0 100.0

Figure 6: Histogram showing the frequency distribution

DATA ANALYSIS

Of the respondents 18% strongly agreed to perform effectively by saving time, 17% agreed,

20% are neutral about the performance, 29% disagreed that IT system helps to perform

effectively and 16% strongly disagreed.

INTERPRETATION

From the graph, it can be seen that most of the employees believe that improvement in IT

system doesnt help them to perform effectively by saving time. It is because they are not

aware of other method of doing the work. Hence, the employees dont know the effect of

business process reengineering on the performance of their work.

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TABLE 7: Improve IT system helps to perform efficiently by minimizing errors.


Cumulative

Percent


Agree 19 17.3 17.3 27.3Neutral 24 21.8 21.8 49.1

Disagree 43 39.1 39.1 88.2


Total 110 100.0 100.0

Figure 7: Line graph showing the frequency distribution

DATA ANALYSIS

Of the respondents 10% strongly agreed to perform efficiently by minimizing errors, 17%

agreed, 22% are neutral about the performance, 39% disagreed that IT system helps to

perform efficiently and 12% strongly disagreed.

INTERPRETATION

From the graph, it can be seen that most of the employees believe that improvement in IT

system doesnt help them to perform efficiently by minimizing errors. It is because they are

not aware of other method of doing the work. Hence, the employees dont kn ow the effect of

business process reengineering on the performance of their work.

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TABLE 8: Satisfied with the number of IT skilled employees in the current process.


Cumulative

Percent


Agree 16 14.5 14.5 20.9Neutral 19 17.3 17.3 38.2

Disagree 41 37.3 37.3 75.5


Total 110 100.0 100.0

Figure 8: Bar chart showing the frequency distribution

DATA ANALYSIS

Of the respondents 6% strongly agreed of their satisfaction with the number of IT skilled

employees in the current process, 15% agreed, 17% are neutral about the satisfaction, 37%

disagreed with the number of IT skilled employees and 25% strongly disagreed.

INTERPRETATION

It can be seen from the graph that the employees arent satisfied with the number of IT skilled

employees working in the current process. The employees believe that there is a need of more

IT skilled employees in their current process in order to enhance their work performance.

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TABLE 9: More of IT skilled employees are needed in the unit


Cumulative

Percent


Agree 36 32.7 32.7 37.3Neutral 9 8.2 8.2 45.5

Disagree 39 35.5 35.5 80.9


Total 110 100.0 100.0

Figure 9: Bar Chart showing the frequency distribution

DATA ANALYSIS

Of the respondents 5% strongly agreed to the need of IT skilled employees in the unit, 33%

agreed, 8% are neutral about the satisfaction, 36% disagreed with more number of IT skilled

employees and 19% strongly disagreed.

INTERPRETATION

Majority of the employees agreed and disagreed to the need of more of IT skilled employees

in the unit. It maybe because the current employees find addition of new employees to the

work as a threat to their job and other welcomes the help of more IT skilled employees as

they believe it can enhance the efficient level of the working environment.

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TABLE 10: IT skills are necessary to maximize the use of the Information Technology


Cumulative

Percent


Agree 36 32.7 32.7 40.9Neutral 29 26.4 26.4 67.3

Disagree 19 17.3 17.3 84.5


Total 110 100.0 100.0

FIGURE 10: Pie chart showing the frequency distribution

DATA ANALYSIS

Of the respondents 9% strongly agreed that IT skills are necessary to maximize the use of the

information technology, 33% agreed, 26% are neutral about the necessity, 17% disagreed

with the necessity of IT skills and 16% strongly disagreed.

INTERPRETATION

From the pie chart, it can be seen that the majority of the employees agreed to the necessity

of IT skills to maximize the use of Information Technology. Since, IT skilled employees are

able to maximize the use of the information technology then the employees who doesnt have

any IT skills.

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TABLE 11: IT skills helps to perform effectively by saving time


Cumulative

Percent


Agree 23 20.9 20.9 26.4Neutral 24 21.8 21.8 48.2

Disagree 53 48.2 48.2 96.4


Total 110 100.0 100.0

FIGURE 11: Histogram showing the frequency distribution

DATA ANALYSIS

Of the respondents 6% strongly agreed that IT skills helps to perform effectively by saving

time, 21% agreed, 22% are neutral about the effectiveness, 48% disagreed with the

effectiveness of IT skills by saving time and 4% strongly disagreed.

INTERPRETATION

From the graph, it can be seen that majority of the employees are being indifferent about the

effectiveness of IT skills in their performance through saving time. The employees arent

aware of the effect of IT skills have on their performance of work. They believe that they

dont need special IT skills to do their job only.

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TABLE 12: IT skills help to perform efficiently by minimizing errors.


Cumulative

Percent


Agree 28 25.5 25.5 31.8Neutral 30 27.3 27.3 59.1

Disagree 29 26.4 26.4 85.5


Total 110 100.0 100.0

FIGURE 12: Area curve showing the frequency distribution

DATA ANALYSIS

Of the respondents 6% strongly agreed that IT skills helps to perform efficiently by

minimizing error, 26% agreed, 27% are neutral about the efficiency, 26% disagreed with the

efficiency of IT skills by minimizing error and 15% strongly disagreed.

INTERPRETATION

It can be seen that majority of the employees are being indifferent about the efficiency of IT

skills in their performance through minimizing errors. The employees arent aware of the

effect of IT skills have on their performance of work. They believe that they dont need

special IT skills to do their job only.

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TABLE 13: Training & Education is necessary after BPR implementation


Cumulative

Percent


Agree 25 22.7 22.7 35.5Neutral 15 13.6 13.6 49.1

Disagree 34 30.9 30.9 80.0


Total 110 100.0 100.0

FIGURE 13: Line curve showing the frequency distribution

DATA ANALYSIS

Of the respondents 13% strongly agreed that training and education is necessary after BPR

implementation, 23% agreed, 14% are neutral about the necessity, 31% disagreed with the

necessity of training and education after BPR implementation and 20% strongly disagreed.

INTERPRETATION

From the line graph, it can be seen that the most of the employees disagreed to the training

and education after BPR implementation. It is because employees dont feel the need of

training and educating themselves about the business process reengineering as it is time

consuming.

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FIGURE 14: Bar chart showing the frequency distribution

DATA ANALYSIS

Of the respondents 6% strongly agreed that training and education will increase flexibility

and adaptability to change in their performance, 35% agreed, 27% are neutral about the

flexibility and adaptability, 17% disagreed with the flexibility to change 15% strongly

disagreed.

INTERPRETATION

Majority of the employees agreed that training and education will increase the flexibility and

adaptability to change their performance. This shows that employees are willing to do

training and educating themselves about the business process reengineering.

TABLE 14: Training & Education will increase flexibility and adaptability to change.


Cumulative

Percent


Agree 38 34.5 34.5 40.9

Neutral 30 27.3 27.3 68.2

Disagree 19 17.3 17.3 85.5


Total 110 100.0 100.0

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TABLE 15: Training and Education assist in developing new skills


Cumulative

Percent


Agree 25 22.7 22.7 33.6Neutral 31 28.2 28.2 61.8

Disagree 30 27.3 27.3 89.1


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 11% strongly agreed that training and education assist in developing new

skills, 23% agreed, 28% are neutral about the assistance in developing new skills, 27%

disagreed with the assistance in developing new skills and 11% strongly disagreed.

INTERPRETATION

Majority of the employees are neutral about the development of new skills assisted through

training and education. It maybe because they believe training and education isnt required to

develop a new skill.

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FIGURE 16: Training & Education helps to perform effectively by saving time


Cumulative

Percent


Agree 30 27.3 27.3 38.2Neutral 19 17.3 17.3 55.5

Disagree 32 29.1 29.1 84.5


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 11% strongly agreed that training and education helps to perform

effectively by saving time, 27% agreed, 17% are neutral about the performing effectively by

saving time, 29% disagreed with the effective performance and 16% strongly disagreed.

INTERPRETATION

From the graph, it can be seen that training and education doesnt help the employees

perform effectively by saving time. It may be because the employees think that training and

education are time consuming and unnecessary, they prefer on the job training.

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TABLE 17:Training & Education helps to perform efficiently by minimizing errors


Cumulative

Percent


Agree 30 27.3 27.3 38.2Neutral 24 21.8 21.8 60.0

Disagree 24 21.8 21.8 81.8


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 11% strongly agreed that training and education helps to perform

efficiently by minimizing error, 27% agreed, 21% are neutral about the performing efficiently

by minimizing errors, 21% disagreed with the efficient performance and 18% strongly

disagreed.

INTERPRETATION

From the graph, it can be seen that majority of the employees agree that training and

education help them to perform efficiently by minimizing errors as it educate them.

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TABLE 18: Employee empowerment is needed to improve performance.


Cumulative

Percent


Agree 13 11.8 11.8 22.7

Neutral 39 35.5 35.5 58.2

Disagree 29 26.4 26.4 84.5


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 11% strongly agreed that employee empowerment is needed to improve

performance, 12% agreed, 35% are neutral about the improvement in performance, 26%

disagreed with the employee empowerment and 16% strongly disagreed.

INTERPRETATION

The graph shows that majority of the employees are neutral about the necessity of employee

empowerment for improve performance. Since the work perform by employees are

centralised they are reluctant to have complete empowerment.

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TABLE 19: Current IT system gives the ability to do the work independently.


Cumulative

Percent


Agree 20 18.2 18.2 20.9Neutral 28 25.5 25.5 46.4

Disagree 39 35.5 35.5 81.8


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 3% strongly agreed that current IT system gives the ability to the

employees to work independently, 18% agreed, 26% are neutral about the ability to do the

work independently, 36% disagreed with the independence of the work in the current system

and 18% strongly disagreed.

INTERPRETATION

From the chart it can be seen that majority employees doesnt have the ability to do the work

independently. This shows that the current IT system doesnt empower the employees to do

the work on their own. Hence, the department work on a centralize method.

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TABLE 20: BPR using IT can help empower.


Cumulative

Percent


Agree 24 21.8 21.8 25.5Neutral 32 29.1 29.1 54.5

Disagree 34 30.9 30.9 85.5


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 3% strongly agreed that business process reengineering using IT can help

empower the employees, 22% agreed, 29% are neutral about the empowerment getting

through business process reengineering, 31% disagreed that employee can be empowered

through BPR implementation and 15% strongly disagreed.

INTERPRETATION

Majority of the employees disagreed that they can business process reengineering can help

them to empowerment. Employees dont believe that BPR implementation can help them to

achieve empowerment on their job.

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TABLE 21: Empowerment through BPR using IT helps to perform effectively by saving

time


Cumulative

Percent


Agree 32 29.1 29.1 35.5

Neutral 28 25.5 25.5 60.9

Disagree 23 20.9 20.9 81.8


Total 110 100.0 100.0

FIGURE 21: Histogram showing the frequency of the distribution

DATA ANALYSIS

Of the respondents 6% strongly agreed that empowerment through BPR using IT helps to

perform effectively by saving time, 29% agreed, 26% are neutral about the effective

performance by saving time, 21% disagreed that employee perform effectively by saving

time through empowerment and 18% strongly disagreed.

INTERPRETATION

Most of the employees agreed that empowerment through business process reengineering

helps to perform effectively by saving time. Empowerment allows the employees to have

more freedom to do their work as there is no dependence on others.

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TABLE 22: Empowerment through BPR using IT helps to perform efficiently by

minimizing errors.


DATA ANALYSIS

Of the respondents 5% strongly agreed that empowerment through BPR using IT helps to

perform efficiently by minimizing errors , 21% agreed, 31% are neutral about the efficient

performance by minimizing error, 32% disagreed that employee perform efficiently by

minimizing error through empowerment and 12% strongly disagreed.

INTERPRETATION

Majority of the employees have both been neutral and disagree on business process

reengineering helps to perform efficiently by minimizing error. Errors are likely to happen

whether the employees are empowered or not.



Agree 23 20.9 20.9 25.5

Neutral 34 30.9 30.9 56.4

Disagree 35 31.8 31.8 88.2


Total 110 100.0 100.0

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TABLE: 23 Performance is mostly based on IT system.


Cumulative

Percent


Agree 25 22.7 22.7 29.1Neutral 29 26.4 26.4 55.5

Disagree 32 29.1 29.1 84.5


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 6% strongly agreed that performance is mostly based on IT system , 23%

agreed, 26% are neutral about the performance, 29% disagreed that employee performance is

based on IT system and 16% strongly disagreed.

INTERPRETATION

Most of the employees disagreed that their performance is based on IT system only. It is

because, employees believe that their performance is based on their own skill rather than

based on IT system. They dont think that their performance is dependent on IT system.

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TABLE 24: Performance can be improved by implementing IT enabled BPR.



Agree 26 23.6 23.6 30.0

Neutral 28 25.5 25.5 55.5

Disagree 31 28.2 28.2 83.6


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 6% strongly agreed that performance can be improved by implementing

IT enabled BPR, 24% agreed, 26% are neutral about the performance, 28% disagreed that

employee performance can be improved and 16% strongly disagreed.

INTERPRETATION

From the curve it can be seen that majority of the employees disagreed that their performance

can be improved by implementing IT enabled business process reengineering. The employees

seem to believe that their performance has nothing to do with the implementation of the IT

enable business process reengineering.

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TABLE 25: Performance is enhanced when empowered by IT.


Cumulative

Percent


Agree 24 21.8 21.8 28.2Neutral 33 30.0 30.0 58.2

Disagree 32 29.1 29.1 87.3


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 6% strongly agreed that performance is enhanced when empowered by

information technology 22% agreed, 30% are neutral about the performance enhancement,

29% disagreed that employee performance can be enhanced and 13% strongly disagreed.

INTERPRETATION

From the chart, it can be seen that majority of the employees are being neutral to the

performance enhancement due to empowerment of the employees. Empowerment of

employees although gives freedom but doesnt ensure better performance

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TABLE 26:IT Education and Training is needed to improve performance.



Agree 27 24.5 24.5 35.5

Neutral 27 24.5 24.5 60.0

Disagree 28 25.5 25.5 85.5


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 11% strongly agreed that IT education and training is needed to improve

performance, 25% agreed, 25% are neutral about the performance improvement, 26%

disagreed that employee performance can be improved through IT education and training and

15% strongly disagreed.

INTERPRETATION

From the chart it can be seen that employees response are spread over agree, neutral and

disagree. Hence, the responses are indefinite which makes it very difficult to evaluate.

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TABLE 27:IT skills enhance performance.


Cumulative

Percent


Agree 22 20.0 20.0 30.0

Neutral 20 18.2 18.2 48.2

Disagree 43 39.1 39.1 87.3


Total 110 100.0 100.0


DATA ANALYSIS

Of the respondents 10% strongly agreed that IT skills enhance performance, 20% agreed,

18% are neutral about the performance enhancement, 39% disagreed that employee

performance can be enhanced through IT skills and 13% strongly disagreed.

INTERPRETATION

Majority of the employees disagreed that information technology skills enhance performance.

Employees believe that they dont need added IT skills in order to enhance their performance.

Their current skills are enough for them to perform well.

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4.3. CROSSTABS CHI-SQUARE TEST

Crosstab, or Cross Tabulation, is a process or function that combines and/or summarizes data

from one or more sources into a concise format for analysis or reporting. Crosstabs display

the joint distribution of two or more variables and they are usually represented in the form of

a contingency table in a matrix. Chi-square test is possible from the crosstabs after finding the

expected value for each cell.

CROSSTAB BETWEEN GENDER AND PERFORMANCE ENHANCEMENTThe cross tabulation between two variables, gender and performance increase due to BPR is

given below

TABLE 1: Crosstab between gender and performance

Figure 1:Comparative bar graph of performance increase in genders

Gender * Performance improve due to IT enabled BPR Cross tabulation

Count

Does your performance improve due to IT

enabled BPR

TotalYes No

What is your

gender?

Male 47 12 59

Female 33 18 51

Total 80 30 110

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From the cross tabulation and the bar chart, it appears that both male and female agreed that

their performance have improved after BPR.

CHI-SQUARE TEST OF GENDER AND PERFORMNCE INCREASENull Hypothesis:Performance increase is not due to gender difference.

Alternative Hypothesis:Performance increase is due to gender difference.

TABLE 2:Chi-Square output for performance increase

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 3.084a 1 .079

Continuity Correctionb 2.377 1 .123

Linear-by-Linear Association 3.056 1 .080

N of Valid Cases 110

Decision: the significance level is higher than 0.05. Therefore null hypothesis should be

accepted. So it can be stated that Performance increase is not due to gender difference.

CROSSTAB BETWEEN GENDER AND SATISFACTION LEVEL WITH IT-SYSTEMThe cross tabulation between two variables, gender and satisfaction level with IT System is

given below

TABLE 3:Cross tabulation between gender and IT system

Gender * Satisfaction level with the IT system.

I am satisfied with the IT system that we are using in

our current process.

Total

Strongly

Agree Agree

Neutra

l Disagree

Strongly

disagree

What is

your

gender?

Male 8 18 12 15 6 59

Female 3 9 19 8 12 51

Total 11 27 31 23 18 110

From the cross tabulation, it appears that most of the employees agree that they are not

satisfied with the current IT System.

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CHI-SQUARE TEST OF GENDER AND SATISFACTION LEVEL WITH IT SYSTEMNull Hypothesis:Employees are satisfied with IT System.

Alternative Hypothesis:Employees are not satisfied with IT System.

TABLE 4: Chi square test of gender and IT system

Chi-Square Tests

Value Df Asymp. Sig. (2-sided)


Likelihood Ratio 10.632 4 .031


N of Valid Cases 110a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.10.

Decision: the significance level is lower than 0.05. Therefore null hypothesis should be

rejected. So it can be stated that employees are not satisfied with IT System.

CROSSTAB BETWEEN GENDER AND ENHANCEMENT OF IT SKILLThe cross tabulation between two variables, gender and enhancement of skill through IT

System is given below

TABLE 5: Crosstab between gender and improvement of IT skill

Gender * Enhance of skills through IT system.

Cross tabulation

An improve IT system is needed to enhance my skills.

Total

Strongly

Agree Agree Neutral Disagree

Strongly

disagree

What is your

gender?

Male 7 19 12 18 3 59

Female 2 18 14 13 4 51

Total 9 37 26 31 7 110

From the cross tabulation, it appears that most of the employees agree that they can enhance

skills through the IT System.

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CHI-SQAURE TEST OF GENDER AND SATISFACTION LEVEL WITH IT SYSTEMNull Hypothesis:Employees can enhance skills through IT System.

Alternative Hypothesis:Employees cannot enhance skills through IT System.

TABLE 6: Chi-square test of gender with IT system

Chi-Square Tests




Linear-by-Linear Association .402 1 .526


a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is 3.25.


accepted. So it can be stated that employees can enhance skills through IT System.

CROSSTAB BETWEEN GENDER AND SATISFACTION LEVEL WITH THE NUMBEROF SKILLED EMPLOYEES

TABLE 7: Crosstab between Gender and Satisfaction level with the number of skilled

Employees

From the cross tabulation, it appears that most of the employees agree that they are not

satisfied with the number of skilled employees.

Gender * Satisfaction level with the number of skilled employees in our current process.

Cross tabulation

Count

I am satisfied with the number of IT skilled employees in

our current process.

Total

Strongly


Strongly

disagree

What is

your

gender?

Male 7 7 10 23 12 59

Fema

le

0 9 9 18 15 51

Total 7 16 19 41 27 110

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CHI-SQUARE TEST OF GENDER AND SATISFACTION LEVEL WITH THE NUMBEROF SKILLED EMPLOYEES

Null Hypothesis:Employees are satisfied with the number of skilled employees.

Alternative Hypothesis:Employees are not satisfied with the number of skilled employees.

TABLE 8: Chi-square test of gender and Satisfaction level with the number of skilled

Employees


rejected. So it can be stated that employees are not satisfied with the number of skilled

employees.

Chi-Square Tests

Value df

Asymp. Sig. (2-

sided)





a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is

3.25.

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CROSSTAB BETWEEN GENDER AND NECESSITY OF USING ITThe cross tabulation between two variables, gender and necessity of using information

technology

TABLE 9: Crosstab between Gender and Necessity of using information technology

From the cross tabulation, it appears that most of the employees agree that it is necessary to

use information technology.


Null Hypothesis:It is necessary to use information technology.

Alternative Hypothesis:It is not necessary to use information technology.


Employees

Gender * Necessity of using information technology.

Crosstabulation

IT skills are necessary to maximize the use of the Information

Technology

Total

Strongly


Strongly

disagree

What is your

gender?

Male 6 20 13 11 9 59

Female 3 16 16 8 8 51

Total 9 36 29 19 17 110

Chi-Square Tests




Linear-by-Linear Association .152 1 .697


a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 4.17.

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accepted. So it can be stated that it is necessary to use information technology.

CROSSTAB BETWEEN GENDER AND NECESSITY OF TRAINING FOR BPRThe cross tabulation between two variables; gender and the necessity of training after BPR is

given below:

TABLE 11: Crosstab between Gender and Necessity of training for BPR

From the cross tabulation, it appears that most of the employees do not agree that training is

necessary after implementing BPR.

Gender * necessity of training after BPR Cross tabulation

Training & Education is necessary after BPR

implementation

Total

Strongly


Strongly

disagree

What is your

gender?

Male 13 16 8 15 7 59

Female 1 9 7 19 15 51

Total 14 25 15 34 22 110

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Null Hypothesis:Training & education is necessary after implementing BPR.

Alternative Hypothesis:Training & education is not necessary after implementing BPR.


Employees


rejected. So it can be stated that Training & education is not necessary after implementing

BPR.

Chi-Square Tests

Value df Asymp. Sig. (2-sided)Pearson Chi-Square 15.191

a 4 .004




a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 6.49.

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4.4. ANOVA

PERFORMANCE AND IT SYSTEMThe ANOVA test was conducted to measure the performance enhancement due to adaptation

of IT System.

Null Hypothesis:Employee performance isnt enhanced due to adaptation of IT System.

Alternative Hypothesis:Employee performance is enhanced due to adaptation of IT System.

Following output was generated after conducting ANOVA test at 95% confidence interval in

SPSS.

TABLE 3: ANOVA Table measuring performance enhancement due to IT System

ANOVAb

Model Sum of Squares Df Mean Square F Sig.

1 Regression 25.563 1 25.563 51.094 .000a

Residual 54.035 108 .500

Total 79.599 109

a. Predictors: (Constant), IT.SYSTEM

b. Dependent Variable: Performance

DECISION:The SPSS output for ANOVA shows that F value is 51.094 and the level of

significance is .000. Because the significance level .000 is lower than acceptable level of

significance .05, we can reject the null hypothesis. Therefore, it can be stated that employee

performance is enhanced due to adaptation of IT System.

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PERFORMANCE AND IT SKILLThis ANOVA test was conducted to measure the performance enhancement due to increase

in IT Skill.

Null Hypothesis:Employee performance isnt enhanced due to increase in IT Skill.

Alternative Hypothesis:Employee performance is enhanced due to increase in IT Skill.


SPSS.

TABLE 4: ANOVA Table measuring performance enhancement due to IT Skill

ANOVA

b

Model Sum of Squares Df Mean Square F Sig.

1 Regression 21.554 1 21.554 40.105 .000a

Residual 58.044 108 .537

Total 79.599 109

a. Predictors: (Constant), IT.SKILL





performance is enhanced due to increase in IT Skill.

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PERFORMANCE AND IT TRAINING AND EDUCATIONThe following ANOVA test was performed to measure the performance enhancement due to

IT Training.

Null Hypothesis:Employee performance isnt enhanced after providing IT Trainings.

Alternative Hypothesis:Employee performance is enhanced after providing IT Trainings.


SPSS.

TABLE 5: ANOVA Table measuring performance enhancement after providing IT

Training

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 12.352 1 12.352 19.838 .000a

Residual 67.246 108 .623

Total 79.599 109

a. Predictors: (Constant), IT.Training





performance is enhanced after providing IT Training.

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PERFORMANCE AND EMPOWERMENTThe following ANOVA test was performed to measure the performance enhancement due to

employee empowerment.

Null Hypothesis:Employee performance isnt enhanced after empowering employees.

Alternative Hypothesis:Employee performance is enhanced after empowering employees.


SPSS.

TABLE 6: ANOVA Table measuring performance enhancement after empowering

employees

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 41.630 1 41.630 118.412 .000a

Residual 37.969 108 .352

Total 79.599 109

a. Predictors: (Constant), Empowerment


DECISON:The SPSS output for ANOVA shows that F value is 118.412 and the level of



performance is enhanced after empowering employees.

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the R-Square value is 0.321. That means 32.1% changes in the employee performance can be

explained by the adaptation of IT System. Value of adjusted R-Square is 0.315 indicates

31.5% variation in performance can be measured by IT System.

Regression was conducted at 95% confidence interval to test the effect of IT System on

employee performance. And the coefficient table of the regression is shown below

TABLE 8: Coefficients table for Performance & IT System

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

T Sig.B Std. Error Beta

1 (Constant) 1.391 .262 5.298 .000

IT.SYSTEM .583 .082 .567 7.148 .000

a. Dependent Variable: Performance

Null Hypothesis:IT System has no effect on employee performance.

Alternative Hypothesis:IT System has an effect on employee performance.

Test Statistic:The value of the for the IT System is .567, value of tstatistic is 7.148 and

the significance level is .000

Decision: Here the significance level .000 is lower than statistical significance .05. Therefore,

we can reject the null hypothesis and it can be concluded that IT System has an effect on

employee performance.

The regression model to predict employee performance through IT System is:

Performance = + (IT System)

The coefficient table shows that value of is 1.391 and value of is .567. Therefore the

model is

Performance = 1.391 + 0.567(IT System)

Now, the model will show how much effect IT system have on performance if the value of IT

system is inserted in the model.

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PERFORMANCE AND IT SKILLPurpose of this regression analysis was to find out whether IT Skill can enhance employee

performance. Here performance is considered as dependent variable and IT Skill is

considered as independent variable. Following Model Summary and Coefficients table was

generated after running the regression analysis is SPSS.

TABLE 9: Summary of the model predicting Performance through IT Skill

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .520a .271 .264 .73311

a. Predictors: (Constant), IT.SKILL

Figure 2: Scatter diagram

Model summary above shows that correlation, r = .520. That means two variables,

Performance & IT Skill, have strong positive correlation. Coefficient of determination or the

R-Square value is 0.271. That means 27.1% changes in the employee performance can be

explained by the adaptation of IT Skill. Value of adjusted R-Square is 0.264 indicates 26.4%

variation in performance can be measured by IT Skill.

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Regression was conducted at 95% confidence interval to test the effect of IT Skill on

employee performance. And the coefficient table of the regression is shown below

TABLE 10: Coefficient table of Performance prediction model through IT Skill

Coefficientsa

Model


Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 1.310 .307 4.268 .000

IT.SKILL .580 .092 .520 6.333 .000


Null Hypothesis:IT Skill has no effect on employee performance.

Alternative Hypothesis:IT Skill has an effect on employee performance.

Test Statistic:The value of the for the IT Skill is .520, value of tstatistic is 6.333 and the

significance level is .000


we can reject the null hypothesis and it can be concluded that IT Skill has an effect on


The regression model to predict employee performance through IT Skill is:

Performance = + (IT Skill)


model is

Performance = 1.310 + 0.520(IT Skill)

Now, the model will show how much effect IT skill have on performance if the value of IT

skill is inserted in the model.

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PERFORMANCE AND IT TRAINING

Purpose of this regression analysis was to find out whether IT Training can enhance

employee performance. Here performance is considered as dependent variable and IT

Training is considered as independent variable. Following Model Summary and Coefficients

table was generated after running the regression analysis is SPSS.

TABLE 11: Summary of the performance predicting model through IT Training

Model Summary

Model R R Square Adjusted R Square

Std. Error of the

Estimate1 .394a .155 .147 .78908

a. Predictors: (Constant), IT.Training



Performance & IT Training, have positive correlation. Coefficient of determination or the R-

Square value is 0.155. That means only 15.5% changes in the employee performance can be

explained by the adaptation of IT Training. Value of adjusted R-Square is 0.147 indicates

only 14.7% variation in performance can be measured by IT Training.

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Regression was conducted at 95% confidence interval to test the effect of IT Training on

employee performance. And the coefficient table of the regression is shown below.

TABLE 12: Coefficient table of performance prediction model through IT Training

Coefficients

Model


Standardized

Coefficients


1 (Constant) 2.100 .259 8.105 .000

IT.Training .357 .080 .394 4.454 .000


Null Hypothesis:IT Training has no effect on employee performance.

Alternative Hypothesis:IT Training has an effect on employee performance.

Test Statistic:The value of the for the IT Training is .394, value of tstatistic is 4.454 and

the significance level is .000


we can reject the null hypothesis and it can be concluded that IT Training has an effect on


The regression model to predict employee performance through IT Training is:

Performance = + (IT Training)


model is

Performance = 2.100 + 0.394(IT Training)

Now, the model will show how much effect IT Training have on performance if the value of

IT Training is inserted in the model.

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PERFORMANCE AND EMPOWERMENT

Purpose of this regression analysis was to find out whether empowerment can enhance

employee performance. Here performance is considered as dependent variable and

empowerment is considered as independent variable. Following Model Summary and

Coefficients table was generated after running the regression analysis is SPSS.

TABLE 13: Summary of performance predicting model through empowerment

Model Summary


Std. Error of the

Estimate1 .723a .523 .519 .59293

a. Predictors: (Constant), Empowerment



Performance & Empowerment, have positive correlation. Coefficient of determination or the

R-Square value is 0.523. That means only 52.3% changes in the employee performance can

be explained by employee empowerment. Value of adjusted R-Square is 0.519 indicates only

51.9% variation in performance can be measured by employee empowerment.

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Regression was conducted at 95% confidence interval to test the effect of empowerment on

employee performance. And the coefficient table of the regression is shown below.

TABLE 14: Coefficient Table of performance prediction model through empowermentCoefficients

a

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .614 .245 2.510 .014

Empowerment .788 .072 .723 10.882 .000


Null Hypothesis:Employee empowerment has no effect on employee performance.

Alternative Hypothesis:Employee empowerment has an effect on employee performance.

Test Statistic:The value of the for employee empowerment is .723, value of tstatistic is

10.882 and the significance level is .000


we can reject the null hypothesis and it can be concluded that employee empowerment has an

effect on employee performance.

The regression model to predict employee performance through empowerment is:

Performance = + (Empowerment)


model is

Performance = 0.614 + 0.723(Empowerment)

Now, the model will show how much effect empowerment have on performance if the value

of empowerment is inserted in the model.

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4.6. MULTIPLE REGRESSION MODELMultiple regression model was used to formulate a model that explains how 4 independent

variables, IT System, IT Skill, IT Training and Employee empowerment affects the employee

performance which is the only dependent variable of this research. In other words, the model

was formulated to understand how employee performance is affected because of all

independent variable together. Following output was generated after conducting multiple

regressions in SPSS.

TABLE 15: Summary of multiple regression models

Model Summary


Std. Error of the

Estimate

1 .758a .575 .558 .56783

a. Predictors: (Constant), Empowerment, IT. Training, IT.SYSTEM, IT.SKILL

Model summary above shows that correlation, r= .758. That means employee performance is

strongly correlated with IT System, IT Skill, IT Training and Employee Empowerment.

Coefficient of determination or the R-Square value is 0.575. That means only 57.5% changes

in the employee performance can be explained by this model. Value of adjusted R-Square is

0.558 indicates only 55.8% variation in performance can be measured by this model after

considering all related factors.

The regression model to predict employee performance is:

Performance = + 1(IT System) + 2(IT Skill) + 3(IT Training) + 4(Empowerment)

Total change in employee performance can be found after inserting the value of constant, ,

all variables and their related beta ().

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The coefficient table of the multiple regressions is shown below.

TABLE 16: Coefficients table for multiple regression model

Coefficientsa

Model


Standardized

Coefficients


1 (Constant) .259 .268 .966 .336

IT.SYSTEM .257 .088 .250 2.931 .004

IT.SKILL .074 .110 .066 .676 .501

IT. Training -.074 .078 -.082 -.950 .344

Empowerment .648 .090 .595 7.184 .000


The coefficients table above shows that significance level for IT Skill and IT Training are

.501 & .344 which are much higher than acceptable significance level of 0.05. Therefore it

can be concluded that these two variables has no effect on the model.

Individually all variables have significant effect on employee performance. But when put

together, IT Skill and IT Training doesnt have much of importance.

After inserting the values of constant and related beta of all variables, the multiple

regressions model is

Performance = 0.259 + .250 (IT System) + .066 (IT Skill)0.082 (IT Training) +

0.595 (Empowerment).

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4.7. RELIABILITY TEST

In statistics, reliability is the consistency of a set of measurements or of a measuring

instrument, often used to describe a test. In the survey of this report, a set of 5 questions was

asked to measure each variable. Here, reliability test is performed in order to check the

consistency in the each set of questions. In SPSS, reliability is measured through Cronbachs

alpha.Cronbach's (alpha) is a coefficient of reliability. It is commonly used as a measure of

the internal consistency or reliability of a psychometric test score for a sample of examinees.

Alpha varies from zero to 1 and it can take any value less than or equal to 1, including

negative values, although only positive values make sense. Higher values of alpha are more

desirable as it represents higher reliability. In most cases, alpha value is needed to be higher

than 0.7 to be considered as reliable.

RELIABILITY TEST ON IT SYSTEMA set of five questions was asked to measure the effectiveness of IT System. After

performing reliability test on these 5 questions, following SPSS output was generated.

TABLE 1: Result of reliability test on IT System

Reliability Statistics

Cronbach's Alpha N of Items

.727 5

The table above shows that Cronbachsalpha is positive and higher than 0.7. Therefore the

questionnaire set measuring the effectiveness of IT System is acceptable and internally

consistent. This also means that the questions for this variable were objective, accurate and

positive.

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RELIABILITY TEST ON IT SKILLA set of five questions was asked to measure the effectiveness of IT Skill. After performing

reliability test on these five questions, following SPSS output was generated.

TABLE 17:Result of reliability test on IT SKILL



.674 5

The table above shows that Cronbachs alpha is positive but it is lower than than 0.7.

Therefore the questionnaire set measuring the effectiveness of IT Skill is not internally

consistent and hence it is not acceptable. Therefore data reduction by conducting Factor

analysis on this questionnaire set is important in order to increase the internal consistency.

Factor analysis of this questionnaire is shown in the next section.

RELIABILITY TEST ON IT TRAININGA set of five questions was asked to measure the importance of IT Training. After performing

reliability test on these 5 questions, following SPSS output was generated.

TABLE 3: Result of reliability test on IT Training



.809 5


questionnaire set measuring the importance of IT Training is acceptable and internally

consistent. This also means that the questions for this variable were objective, accurate and

positive.

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RELIABILITY TEST ON EMPLOYEE EMPOWERMENTA set of five questions was asked to measure the importance of employee empowerment.

After performing reliability test on these 5 questions, following SPSS output was generated.

TABLE 18: Result of reliability test on employee empowerment



.737 5


questionnaire set measuring the importance of employee empowerment is acceptable and

internally consistent. This also means that the questions for this variable were objective,

accurate and positive.

RELIABILITY TEST ON EMPLOYEE PERFORMANCEA set of five questions was asked to measure the degree of employee performanceenhancement. After performing reliability test on these 5 questions, following SPSS output

was generated.

TABLE 19:Result of reliability test on employee performance



.775 5


questionnaire set measuring the degree of employee performance increase is acceptable and

internally consistent. This also means that the questions for this variable were objective,

accurate and positive.

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4.8. FACTOR ANALYSISFactor analysis is a statistical method used to describe variability among observed variables

in terms of a potentially lower number of unobserved variables called factors. The observed

variables are modelled as linear combinations of the potential factors, plus error terms. The

information gained about the interdependencies between observed variables can be used later

to reduce the set of variables in a dataset (Factor analysis, 2011).

Figure 2: Comparison of Cronbach's alpha

Through the reliability test it was found that the alpha value of all variables were positive and

higher than 0.7 except for IT Skill. Following table shows the alpha range for each variable.

IT System IT Skill IT TrainingEmpowerme

ntPerformance

Cronbach's Alpha 0.727 0.674 0.809 0.737 0.775

0

0.2

0.4

0.6

0.8

1

Cronbach's Alpha

TABLE 20: Range of Cronbach's Alpha

0.00 - 0.69 0.70 - 0.89 0.90 - 1.00

Independent Variable

IT System 0.727

IT Skill 0.674

IT Training 0.809

Empowerment 0.737

Dependent Variable

Performance 0.775

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The table shows that Cronbachs alpha for IT Skill is lower than 0.7 which means the

questions asked to measure the variable does not have internal consistency. Hence factor

analysis is important in order to deduct the question which is causing higher variation or

inconsistency in the question set. If the questions or factors with high variation are deducted,

question set will become more consistent and therefore will be more reliable. After

conducting factor analysis on IT skill, following SPSS output was generated.

TABLE 21: Variance in IT Skill

Total Variance Explained

Component

Initial Eigen values Extraction Sums of Squared Loadings

Total % of Variance

Cumulative

% Total % of Variance Cumulative %

1 2.346 46.930 46.930 2.346 46.930 46.930

2 .975 19.491 66.420

3 .664 13.278 79.698

4 .587 11.743 91.441

5 .428 8.559 100.000

Extraction Method: Principal Component Analysis.

The table above shows that first component or the answers of first questions have highest

percentage of variance. That means answers of first question are causing inconsistency in the

question set. It is possible to get rid of 47% variance if the first question is deducted.

After deducting the first question, reliability test on the IT Skill generates following SPSS

output.

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4.8a. SCREE PLOT

Data with high variance creates discrepancy. Therefore only the factors that have eigenvalue

over 1 should be considered for analysis. Scree plot shows the value that should be extracted.

Figure 1: Scree Plot

From the scree plot we can see that first four factors have eigenvalue over 1. Therefore, these

four factors should be excluded from analysis and all remaining factors should be considered

for analysis.

TABLE 22:Reliability test on IT skill after factor analysis



.719 4

The reliability statistics table shows that after deducting the factor with highest variance

Cronbachs alpha have increased to 0.719 from 0.674. As the Cronbachs alpha is now higher

that 0.7, the questionnaire set is internally consistent and reliable.

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4.9. CORRELATION ANALYSISCorrelation analysis measures the relationship between two continuous numeric variables that

indicates both the direction and degree to which they co-vary with one another from case to

case, without implying that one is causing the other. The significance of each correlation

coefficient is displayed in the correlation Table 1. The significance level (or p-value) is the

probability of obtaining results as extreme as the one observed. If the significance level is

very small (less than 0.05) then the correlation is significant and the two variables are linearly

related. If the significance level is relatively large (for example, 0.50) then the correlation is

not significant, hence the two variables are not linearly related.

Null Hypothesis: IT skills and the performance of the employees are correlated

Alternate Hypothesis: IT skills and the performance of the employees are not correlated

In order to do the correlation test, IT skills has been considered as independent variable and

performance as dependent variable.

TABLE 1: Correlation between IT skills and performance of the employees

Performance IT.Skill

Performance Pearson Correlation 1 .520**

Sig. (2-tailed) .000

N 110 110

IT.Skills Pearson Correlation .520** 1


N 110 110

**. Correlation is significant at the 0.01 level (2-tailed).

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Figure1:Scatter diagram of IT skills and performance of the employees

The scatter plot of the variables shows that there is a linear and positive relationship between

IT skills and the performance of the employees.

Bi-variate Regression model is also used to know the actual strength of the co-relation

between Performance and the IT skills of the employees. The table below is showing the

output of bi-variate correlation.

At the 99% confidence, there is a correlation between performance and IT skills. The

correlation value is .520 which shows that there is a strong positive relationship between IT

skills and the performance of the employees. Hence, the performance of the employees can

improve if the IT skills of the employees are enhanced.

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Null Hypothesis: IT system and the performance of the employees are correlated

Alternate Hypothesis: IT system and the performance of the employees are not

correlated

Figure 2: Scatter diagram of IT system and performance of the employees

From the regression graph it is clear that Performance of the employee is positively correlated

with the IT system of an organization.


between Performance and the IT system of the organization. The table below is showing the

output of bi-variate correlation.

TABLE 2: Correlation between IT systems and performance of the employees

Performance It.System

Performance Pearson Correlation 1 .567**


N 110 110

It.System Pearson Correlation .567** 1


N 110 110**. Correlation is significant at the 0.01 level (2-tailed).

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This is the correlation between IT system and performance of the employees. At the 99%

confidence interval there is a correlation between performance and IT system, the

correlation value is .567 which shows that there is a strong positive relationship between IT

system and the performance of the employees. Therefore, if Citibank improve their IT

systems then the performance of the employees are expected to improve as well.

Null Hypothesis: IT training and education and the performance of the employees are

correlated

Alternate Hypothesis: IT training and education and the performance of the employees

are not correlated

Figure 3: Scatter diagram of IT training and performance of the employees

TABLE 3: Correlation between IT Training and performance of the employees

Performance IT Training

Performanc

e

Pearson Correlation 1 .394**


N 110 110

It.Training Pearson Correlation .394

**

1Sig. (2-tailed) .000

N 110 110


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By generating a regression graph through SPSS, it was found that there is a positive

correlation between these two variables.


between Performance and the IT Training and Education of the organization. The table below

is showing the output of bi-variate correlation.

At the 99% confidence interval there is a correlation between performance and IT training,

the correlation value is .384 which shows IT training has a positive but a weak relationship

with the performance of the employees. Therefore, the performance of the employees will

not enhance that significantly if Citibank implement IT training and education.

Null Hypothesis: Empowerment and the performance of the employees are correlated

Alternate Hypothesis: Empowerment and the performance of the employees are not

correlated

TABLE 4: Correlation between empowerment and performance of the employees

Performance EmpowermentPerformance Pearson Correlation 1 .723**


N 110 110

Empowerment Pearson Correlation .723** 1


N 110 110


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Figure 4: Scatter diagram of employee empowerment and performance of the

employees

The scatter plot of the two variable shows that there is a positive and linear relationship

between the performance of the employees and the empowerment in the organization as the

line is going upward.


between performance and the empowerment of the employees in the organization. The table

below is showing the output of bi-variate correlation.

At the 99% confidence interval there is a correlation between performance and

empowerment of the employees. The correlation value is .723 which shows that the

empowerment of the employees has a strong positive relationship with the performance of

the employees. Therefore, if Citibank empowers their employees then their performance

will improve.

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4.10. NORMAL PROBABILITY PLOT

The probability-probability (P-P) plot is a graph of the empirical CDF values plotted against

the theoretical CDF values. It is used to determine how well a specific distribution fits to the

observed data. This plot will be approximately linear if the specified theoretical distribution is

the correct model.

PP PLOT FOR IT SYSTEM

Figure 1: PP Plot for IT System

The PP plot shows an approximate liner curve. Therefore the specified theoretical distribution

is the correct model.

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PP PLOT FOR IT SKILL

Figure 2: PP Plot for IT Skill

Here the PP plot shows an approximate liner curve. Therefore the specified theoretical

distribution is the correct model.

PP PLOT FOR IT TRAINING

Figure 3: PP Plot for IT Training



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PP PLOT FOR EMPOWERMENT

Figure 4: PP Plot for empowerment



PP PLOT FOR PERFORMANCEE

G. CHAPTER 4

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