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8/13/2019 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
Frequency Percent Valid Percent Cumulative Percent
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 6 5.5 5.5 5.5
Agree 28 25.5 25.5 30.9
Neutral 26 23.6 23.6 54.5
Disagree 35 31.8 31.8 86.4
Strongly disagree 15 13.6 13.6 100.0
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 9 8.2 8.2 8.2
Agree 37 33.6 33.6 41.8Neutral 26 23.6 23.6 65.5
Disagree 31 28.2 28.2 93.6
Strongly disagree 7 6.4 6.4 100.0
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 20 18.2 18.2 18.2
Agree 19 17.3 17.3 35.5
Neutral 22 20.0 20.0 55.5Disagree 32 29.1 29.1 84.5
Strongly disagree 17 15.5 15.5 100.0
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 11 10.0 10.0 10.0
Agree 19 17.3 17.3 27.3Neutral 24 21.8 21.8 49.1
Disagree 43 39.1 39.1 88.2
Strongly disagree 13 11.8 11.8 100.0
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 7 6.4 6.4 6.4
Agree 16 14.5 14.5 20.9Neutral 19 17.3 17.3 38.2
Disagree 41 37.3 37.3 75.5
Strongly disagree 27 24.5 24.5 100.0
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 5 4.5 4.5 4.5
Agree 36 32.7 32.7 37.3Neutral 9 8.2 8.2 45.5
Disagree 39 35.5 35.5 80.9
Strongly disagree 21 19.1 19.1 100.0
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 9 8.2 8.2 8.2
Agree 36 32.7 32.7 40.9Neutral 29 26.4 26.4 67.3
Disagree 19 17.3 17.3 84.5
Strongly disagree 17 15.5 15.5 100.0
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 6 5.5 5.5 5.5
Agree 23 20.9 20.9 26.4Neutral 24 21.8 21.8 48.2
Disagree 53 48.2 48.2 96.4
Strongly disagree 4 3.6 3.6 100.0
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 7 6.4 6.4 6.4
Agree 28 25.5 25.5 31.8Neutral 30 27.3 27.3 59.1
Disagree 29 26.4 26.4 85.5
Strongly disagree 16 14.5 14.5 100.0
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 14 12.7 12.7 12.7
Agree 25 22.7 22.7 35.5Neutral 15 13.6 13.6 49.1
Disagree 34 30.9 30.9 80.0
Strongly disagree 22 20.0 20.0 100.0
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 7 6.4 6.4 6.4
Agree 38 34.5 34.5 40.9
Neutral 30 27.3 27.3 68.2
Disagree 19 17.3 17.3 85.5
Strongly disagree 16 14.5 14.5 100.0
Total 110 100.0 100.0
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TABLE 15: Training and Education assist in developing new skills
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 12 10.9 10.9 10.9
Agree 25 22.7 22.7 33.6Neutral 31 28.2 28.2 61.8
Disagree 30 27.3 27.3 89.1
Strongly disagree 12 10.9 10.9 100.0
Total 110 100.0 100.0
FIGURE 15: Pie chart showing the frequency distribution
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 12 10.9 10.9 10.9
Agree 30 27.3 27.3 38.2Neutral 19 17.3 17.3 55.5
Disagree 32 29.1 29.1 84.5
Strongly disagree 17 15.5 15.5 100.0
Total 110 100.0 100.0
FIGURE 16: Histogram showing the frequency distribution
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 12 10.9 10.9 10.9
Agree 30 27.3 27.3 38.2Neutral 24 21.8 21.8 60.0
Disagree 24 21.8 21.8 81.8
Strongly disagree 20 18.2 18.2 100.0
Total 110 100.0 100.0
FIGURE 17: Line curve showing the frequency distribution
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 12 10.9 10.9 10.9
Agree 13 11.8 11.8 22.7
Neutral 39 35.5 35.5 58.2
Disagree 29 26.4 26.4 84.5
Strongly disagree 17 15.5 15.5 100.0
Total 110 100.0 100.0
FIGURE 18: Bar chart showing the frequency distribution
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 3 2.7 2.7 2.7
Agree 20 18.2 18.2 20.9Neutral 28 25.5 25.5 46.4
Disagree 39 35.5 35.5 81.8
Strongly disagree 20 18.2 18.2 100.0
Total 110 100.0 100.0
FIGURE 19: Pie chart showing the frequency distribution
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 4 3.6 3.6 3.6
Agree 24 21.8 21.8 25.5Neutral 32 29.1 29.1 54.5
Disagree 34 30.9 30.9 85.5
Strongly disagree 16 14.5 14.5 100.0
Total 110 100.0 100.0
FIGURE 20: Area curve showing the frequency distribution
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
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 7 6.4 6.4 6.4
Agree 32 29.1 29.1 35.5
Neutral 28 25.5 25.5 60.9
Disagree 23 20.9 20.9 81.8
Strongly disagree 20 18.2 18.2 100.0
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.
FIGURE 22: Line curve showing the frequency distribution
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.
Frequency Percent Valid Percent Cumulative Percent
Valid Strongly Agree 5 4.5 4.5 4.5
Agree 23 20.9 20.9 25.5
Neutral 34 30.9 30.9 56.4
Disagree 35 31.8 31.8 88.2
Strongly disagree 13 11.8 11.8 100.0
Total 110 100.0 100.0
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TABLE: 23 Performance is mostly based on IT system.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 7 6.4 6.4 6.4
Agree 25 22.7 22.7 29.1Neutral 29 26.4 26.4 55.5
Disagree 32 29.1 29.1 84.5
Strongly disagree 17 15.5 15.5 100.0
Total 110 100.0 100.0
FIGURE 23: Bar chart showing the frequency distribution
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.
Frequency Percent Valid Percent Cumulative Percent
Valid Strongly Agree 7 6.4 6.4 6.4
Agree 26 23.6 23.6 30.0
Neutral 28 25.5 25.5 55.5
Disagree 31 28.2 28.2 83.6
Strongly disagree 18 16.4 16.4 100.0
Total 110 100.0 100.0
FIGURE 24: Area curve showing the frequency distribution
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 7 6.4 6.4 6.4
Agree 24 21.8 21.8 28.2Neutral 33 30.0 30.0 58.2
Disagree 32 29.1 29.1 87.3
Strongly disagree 14 12.7 12.7 100.0
Total 110 100.0 100.0
FIGURE 25: Pie chart showing the frequency distribution
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.
Frequency Percent Valid Percent Cumulative Percent
Valid Strongly Agree 12 10.9 10.9 10.9
Agree 27 24.5 24.5 35.5
Neutral 27 24.5 24.5 60.0
Disagree 28 25.5 25.5 85.5
Strongly disagree 16 14.5 14.5 100.0
Total 110 100.0 100.0
FIGURE 26: Histogram showing the frequency distribution
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.
Frequency Percent Valid Percent
Cumulative
Percent
Valid Strongly Agree 11 10.0 10.0 10.0
Agree 22 20.0 20.0 30.0
Neutral 20 18.2 18.2 48.2
Disagree 43 39.1 39.1 87.3
Strongly disagree 14 12.7 12.7 100.0
Total 110 100.0 100.0
FIGURE 27: Line curve showing the frequency distribution
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)
Pearson Chi-Square 10.457a 4 .033
Likelihood Ratio 10.632 4 .031
Linear-by-Linear Association 3.689 1 .055
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
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 3.344a 4 .502
Likelihood Ratio 3.494 4 .479
Linear-by-Linear Association .402 1 .526
N of Valid Cases 110
a. 4 cells (40.0%) have expected count less than 5. The minimum expected count is 3.25.
Decision: the significance level is higher than 0.05. Therefore null hypothesis should be
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
Agree Agree Neutral Disagree
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
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 the number of skilled
employees.
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 7.705a 4 .103
Likelihood Ratio 10.370 4 .035
Linear-by-Linear Association 2.025 1 .155
N of Valid Cases 110
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.
CHI-SQUARE TEST OF GENDER AND SATISFACTION LEVEL WITH THE NUMBEROF SKILLED EMPLOYEES
Null Hypothesis:It is necessary to use information technology.
Alternative Hypothesis:It is not necessary to use information technology.
TABLE 10: Chi-square test of gender and Satisfaction level with the number of skilled
Employees
Gender * Necessity of using information technology.
Crosstabulation
IT skills are necessary to maximize the use of the Information
Technology
Total
Strongly
Agree Agree Neutral Disagree
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
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 1.715a 4 .788
Likelihood Ratio 1.728 4 .786
Linear-by-Linear Association .152 1 .697
N of Valid Cases 110
a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is 4.17.
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Decision: the significance level is higher than 0.05. Therefore null hypothesis should be
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
Agree Agree Neutral Disagree
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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CHI-SQUARE TEST OF GENDER AND SATISFACTION LEVEL WITH THE NUMBEROF SKILLED EMPLOYEES
Null Hypothesis:Training & education is necessary after implementing BPR.
Alternative Hypothesis:Training & education is not necessary after implementing BPR.
TABLE 12: Chi-square test of gender and Satisfaction level with the number of skilled
Employees
Decision: the significance level is lower than 0.05. Therefore null hypothesis should be
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
Likelihood Ratio 17.123 4 .002
Linear-by-Linear Association 14.084 1 .000
N of Valid Cases 110
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.
Following output was generated after conducting ANOVA test at 95% confidence interval in
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
b. Dependent Variable: Performance
DECISION:The SPSS output for ANOVA shows that F value is 40.105 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 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.
Following output was generated after conducting ANOVA test at 95% confidence interval in
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
b. Dependent Variable: Performance
DECISION:The SPSS output for ANOVA shows that F value is 19.838 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 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.
Following output was generated after conducting ANOVA test at 95% confidence interval in
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
b. Dependent Variable: Performance
DECISON:The SPSS output for ANOVA shows that F value is 118.412 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 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
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) 1.310 .307 4.268 .000
IT.SKILL .580 .092 .520 6.333 .000
a. Dependent Variable: Performance
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
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 Skill has an effect on
employee performance.
The regression model to predict employee performance through IT Skill is:
Performance = + (IT Skill)
The coefficient table shows that value of is 1.391 and value of is .567. Therefore the
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
Figure 3: Scatter diagram
Model summary above shows that correlation, r = .394. That means two variables,
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
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) 2.100 .259 8.105 .000
IT.Training .357 .080 .394 4.454 .000
a. Dependent Variable: Performance
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
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 Training has an effect on
employee performance.
The regression model to predict employee performance through IT Training is:
Performance = + (IT Training)
The coefficient table shows that value of is 1.391 and value of is .567. Therefore the
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
Model R R Square Adjusted R Square
Std. Error of the
Estimate1 .723a .523 .519 .59293
a. Predictors: (Constant), Empowerment
Figure 4: Scatter diagram
Model summary above shows that correlation, r = .723. That means two variables,
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
t Sig.B Std. Error Beta
1 (Constant) .614 .245 2.510 .014
Empowerment .788 .072 .723 10.882 .000
a. Dependent Variable: Performance
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
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 employee empowerment has an
effect on employee performance.
The regression model to predict employee performance through empowerment is:
Performance = + (Empowerment)
The coefficient table shows that value of is 1.391 and value of is .567. Therefore the
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
Model R R Square Adjusted R Square
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
Unstandardized Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
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
a. Dependent Variable: Performance
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
Reliability Statistics
Cronbach's Alpha N of Items
.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
Reliability Statistics
Cronbach's Alpha N of Items
.809 5
The table above shows that Cronbachsalpha is positive and higher than 0.7. Therefore the
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
Reliability Statistics
Cronbach's Alpha N of Items
.737 5
The table above shows that Cronbachsalpha is positive and higher than 0.7. Therefore the
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
Reliability Statistics
Cronbach's Alpha N of Items
.775 5
The table above shows that Cronbachsalpha is positive and higher than 0.7. Therefore the
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
Reliability Statistics
Cronbach's Alpha N of Items
.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
Sig. (2-tailed) .000
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.
Bi-variate Regression model is also used to know the actual strength of the co-relation
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**
Sig. (2-tailed) .000
N 110 110
It.System Pearson Correlation .567** 1
Sig. (2-tailed) .000
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**
Sig. (2-tailed) .000
N 110 110
It.Training Pearson Correlation .394
**
1Sig. (2-tailed) .000
N 110 110
**. Correlation is significant at the 0.01 level (2-tailed).
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By generating a regression graph through SPSS, it was found that there is a positive
correlation between these two variables.
Bi-variate Regression model is also used to know the actual strength of the co-relation
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**
Sig. (2-tailed) .000
N 110 110
Empowerment Pearson Correlation .723** 1
Sig. (2-tailed) .000
N 110 110
**. Correlation is significant at the 0.01 level (2-tailed).
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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.
Bi-variate Regression model is also used to know the actual strength of the co-relation
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
Here the PP plot shows an approximate liner curve. Therefore the specified theoretical
distribution is the correct model.
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PP PLOT FOR EMPOWERMENT
Figure 4: PP Plot for empowerment
Here the PP plot shows an approximate liner curve. Therefore the specified theoretical
distribution is the correct model.
PP PLOT FOR PERFORMANCEE
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