Role of Excellence Awards on Business Excellence

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This paper discusses the results of a survey conducted on a population of size 30,000 to explore the impact of excellence awards on business excellence. The survey targeted those employed in the government sector and gathered information on organizational context such as strategy, organizational structure, technology, and leadership. The study found that strategy and structure had a significant positive association with business excellence, while technology and excellence awards had a moderate association. The paper provides detailed analysis and results of the survey.

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Running head: ROLE OF EXCELLENCE AWARDS ON BUSINESS EXCELLENCE
ROLE OF EXCELLENCE AWARDS ON BUSINESS EXCELLENCE
Name of Student
Name of University
Author Note

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1.0 Analysis
Introduction
A survey was conducted on a population of size 30,000. The questionnaire was
designed to target those who were employed in the government sector. The key objective of
the survey was to gather information for a study on how ‘organizational context’ such as
strategy, organizational structure, technology being used and leadership relates to the level of
business excellence being experienced by the organization with respect to the implementation
of excellence awards policy. Due to time and resource constraints, it would have not been
feasible to take into account all of the 30,000 population members. Therefore a sample of 380
individuals was considered as respondents for the survey questionnaire. 284 out of these
individuals were found to have responded to the survey and the current paper discusses the
results of the analysis based on the data collected from the same.
Research Methodology
A survey research method was followed in this case. The questionnaire consisted of a
number of items, including those referring to demographic attributes of the respondents,
followed by a number on items measuring their ratings of their work environment with
respect to organizational context, namely four on leadership, five on strategy of the
organization, four on technology and a four on structure of the organization. Following this
item 24 to item 41 addressed their opinion and perception on the excellence awards policy at
work in their workplace. The final item is a rating of their perception of the level of business
excellence at their workplaces. For the purpose of the analysis, this rating of excellence is the
dependent variable. The independent variables considered are scores measured as medians of
the items addressing strategy, leadership, structure and technology respectively.
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Results
1. Construct Validity
The data collected contained 284 observations on six items addressing demographic
factors, such as their gender, age, nationality, educational qualification, job level at the
organization and the length of time that the respondent had been employed there.
Out of the 284 respondents 40.5 percent were found to be female and 59.5 percent
male.
1. Gender
Frequency Percent Valid Percent Cumulative
Percent
Valid
Female 115 40.5 40.5 40.5
Male 169 59.5 59.5 100.0
Total 284 100.0 100.0
Table 1
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Figure 1: Distribution of Gender
Out of all the respondents in the survey 7.7 percent were Egyptians, 0.4% were
French, 8.1 percent were Indians. Iraqi, Lebanese and those from Oman held 0.7 percent
participation percentage each.3.2 percent of the participants were Lebanese. 2.1 percent were
from Sudan, 57.8 percent were from the UAE and those from UK and USA were 2.5 and 8.5
percent respectively. So it is seen that majority of the participants hail from the Middle East.
2. Nationality
Frequency Percent Valid Percent Cumulative
Percent
Valid Egypt 22 7.7 7.7 7.7
France 1 .4 .4 8.1
India 23 8.1 8.1 16.2
Iraq 2 .7 .7 16.9
Jordan 2 .7 .7 17.6
Lebanon 9 3.2 3.2 20.8

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Oman 2 .7 .7 21.5
Sudan 6 2.1 2.1 23.6
Syria 22 7.7 7.7 31.3
Uae 3 1.1 1.1 32.4
UAE 161 56.7 56.7 89.1
UK 7 2.5 2.5 91.5
US 15 5.3 5.3 96.8
USA 9 3.2 3.2 100.0
Total 284 100.0 100.0
Table 2: Nationality
Figure 2: Distribution of Age
Among all the respondents 15.5 percent were aged between 20 to 30 years, 50 percent
were aged between 31 and 40 years, 26.1 percent were between 41 years and 50 years and 8.5
percent were older than 50 years. Hence 65.5 percent were less than 40 years of age in the
survey.
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3. Current Age
Frequency Percent Valid Percent Cumulative
Percent
Valid
20 -30 44 15.5 15.5 15.5
31-40 142 50.0 50.0 65.5
41-50 74 26.1 26.1 91.5
More than 50 24 8.5 8.5 100.0
Total 284 100.0 100.0
Table 3: Age of respondents
Figure 3: Distribution of Age
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The survey found that 37.3 percent of the respondents had at most a Bachelors
Degree, 14.1 percent had at most a Doctorate degree, 44.7 percent were at most graduates
with Master degree and only 3.9 percent were just high school graduates. The sample thus
consists of mostly highly educated individuals.
4. Educational Level
Frequency Percent Valid Percent Cumulative
Percent
Valid
Bachelor degree 106 37.3 37.3 37.3
Doctorate degree 40 14.1 14.1 51.4
High School 11 3.9 3.9 55.3
Master degree 127 44.7 44.7 100.0
Total 284 100.0 100.0
Table 4: Qualification
Figure 4: Distribution of Education Category

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Among all the responses, 19 percent reported that they were junior employees, 22.2
percent said that they were employed at lower management. 14.1 percent were at middle
management, 35.9 percent were senior employees and 8.8 percent reported that were at the
top management level. Therefore it is seen that most of the responses are from the lower
levels and that suits the study fine.
5. Job Level
Frequency Percent Valid Percent Cumulative
Percent
Valid
Junior Employee 54 19.0 19.0 19.0
Lower Management 63 22.2 22.2 41.2
Middle Management 40 14.1 14.1 55.3
Senior Employee 102 35.9 35.9 91.2
Top Management 25 8.8 8.8 100.0
Total 284 100.0 100.0
Table 5: Job Level
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Figure 5: Distribution of Job Categories
21.1 percent of the respondents reported that they had worked 2 to 8 years in the
organization, 60.2 percent had experience of 9 to 15 years, 8.8 percent had more than 15
years of experience and 9.9 percent had less than one year of experience. So the sample
consists of at least 60.2 percent having more than 9 years of experience.
6. Total number of working years
Frequency Percent Valid Percent Cumulative
Percent
Valid
2 to 8 years 60 21.1 21.1 21.1
9 to 15 years 171 60.2 60.2 81.3
More than 15 years 25 8.8 8.8 90.1
One year or less 28 9.9 9.9 100.0
Total 284 100.0 100.0
Table 6: Years Working
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Figure 6: Distribution of years of experience
The descriptive measures of the computed independent and moderator variables from
the items and the dependent variable are given in the following table. The measures of central
tendency, mean, median and mode as well as the dispersion measure of standard deviation are
given hence. The mean rating for business excellence of all the organizations by all the
respondents was found to be 3.5 on a scale of 4. The mean leadership style was seen to be
2.86. It was 2.75 for Strategy, 2.84 for structure, 3.02 for technology and 2.76 for the
excellence awards. The median was 3 for all. The modes for the variables were also 3 each
except for strategy which had slightly better rating of 3.5. Therefore the ratings for the
independent and moderator variable was high all lying in the vicinity of a rating score of 3.
The variation n the business excellence ratings was found to be high with3.5 so this variable
show high variability, however standard deviation for leadership, strategy, structure,
technology and excellence awards were found to be low, with the values being 0.56, 0.71,
0.77, 0.53 and 0.52 respectively.
Statistics
Business
Excellence
Leadership Style Strategy Structure Technology Excellence
Awards
N Valid 284 284 284 284 284 284
Missing 4 0 0 0 0 0
Mean 3.50 2.8662 2.7500 2.8451 3.0229 2.7676
Median 3.00 3.0000 3.0000 3.0000 3.0000 3.0000
Mode 3 3.00 3.50 3.00 3.00 3.00
Std. Deviation 3.500 .56679 .71765 .77319 .53368 .52554
Minimum 4 1.50 1.00 1.00 1.50 2.00
Maximum 3 4.00 4.00 4.00 4.00 4.00
Table 7: Descriptive Measures of Dependent Variable
The following figure shows the distribution of the business excellence ratings which
is the dependent variable. The distribution seems to be skewed towards left.

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Figure 7: Histogram of Dependent Variable
The following figure shows the distribution of the leadership ratings by the employees
which is an independent or predictor variable. The distribution seems to be slightly skewed
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towards left with location centred around 3.
Figure 8: Histogram of Leadership scores
The following figure shows the distribution of the strategy ratings score by the
employees which is an independent or predictor variable. The distribution seems to be close
to symmetry with slight tilt towards left with location close to 2.
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Figure 9: Histogram of Strategy ratings score
The following figure shows the distribution of the structure ratings score of the
organization by the employees which is an independent or predictor variable. The distribution
seems to be left skewed with location around 3.

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Figure 10: Histogram of Structure Ratings Scores
The following figure shows the distribution of the technology ratings score by the
employees which is an independent or predictor variable. The distribution seems to be left
skewed with location around 3. The technology ratings are therefore towards the higher
values.
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Figure 11: Technology
The following figure shows the distribution of the excellence award ratings score by
the employees which is the moderator variable. The distribution seems to be centred mainly
between 2 and 3. So the performance of the organization on this count seems to be between
divided between those who agree with the policies and those who agree. The scores are
primarily moderate.
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Figure 12: Histogram of excellence awards rating scores
The following table shows the correlation between the independent and dependent
variables and the moderator variable. The spearman’s rho metric was used to compute the
correlation owing to the ordinal nature of the data. The correlation between business
excellence and strategy was found to be significant at 0.05 level and negative and equal to -
0.127. The correlation between structure and business excellence was also found to be
significant at 0.05 level which assumed a positive value 0.371 (Larson-Hall 2015). Thus
these two are considered to have significant association with the dependent variable.
Correlations
Business
Excellenc
e.
Leadershi
p Style
Strateg
y
Structur
e
Technolo
gy
Excellenc
e Awards

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Spearman
's rho
Business Excellence
Correlatio
n
Coefficie
nt
1.000 -.060 -.127* .371** .018 -.060
Sig. (2-
tailed) . .315 .033 .000 .764 .314
N 284 284 284 284 284 284
Leadership Style
Correlatio
n
Coefficie
nt
-.060 1.000 .052 .150* .190** .022
Sig. (2-
tailed) .315 . .379 .011 .001 .715
N 284 284 284 284 284 284
Strategy
Correlatio
n
Coefficie
nt
-.127* .052 1.000 -.334** -.239** -.079
Sig. (2-
tailed) .033 .379 . .000 .000 .186
N 284 284 284 284 284 284
Structure
Correlatio
n
Coefficie
nt
.371** .150* -.334** 1.000 .022 .259**
Sig. (2-
tailed) .000 .011 .000 . .706 .000
N 284 284 284 284 284 284
Technology
Correlatio
n
Coefficie
nt
.018 .190** -.239** .022 1.000 .021
Sig. (2-
tailed) .764 .001 .000 .706 . .725
N 284 284 284 284 284 284
Moderator_ExcelAwa
rds
Correlatio
n
Coefficie
nt
-.060 .022 -.079 .259** .021 1.000
Sig. (2-
tailed) .314 .715 .186 .000 .725 .
N 284 284 284 284 284 284
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*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
Table 12: Correlation measures
2. Reliability
The reliability test procedure for verifying the internal consistency of the data was conducted.
The Cronbach’s alpha measure was used to test for reliability. The value of the statistic was
found to be 0.673 which implied that there is reasonable consistency in the data for the
analysis (Bonett and Wright 2015).
Reliability Statistics
Cronbach's Alpha Cronbach's Alpha Based on
Standardized Items
N of Items
.673 .634 35
Table 13: Reliability Test Output
3. Factor Analysis
The factor analysis initially was found to be problematic due to presence of high multi
collineaity in the data (Katrutsa and Strijov 2017). Therefore the items numbered 20, 23, 25,
34, 38 and 40 were discarded by running collinearity diagnostics. The factor analysis was
then done using the remaining variables. Kaiser-Meyer-Olkin measure was found to be 0.233
and therefore factor analysis was not deemed acceptable (Baglin 2014). Even so and in light
of this the factor analysis and its results is given as follows.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .233
Bartlett's Test of Sphericity
Approx. Chi-Square 6825.796
df 406
Sig. .000
Table 14: KMO Test
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The results of the factor analysis as done using SPSS showed that 19 components had
eigen values greater than zero. Clearly that is too many components. Out of these 19
variables, the first 11 components explain about 80.48% of the variation (Yong and Pearce
2013). Considering the rotation sum of squared loadings these 11 are then decided to be
considered. The method that was considered was principal component method.
Total Variance Explained
Component Initial Eigenvalues Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 4.789 16.514 16.514 2.374 8.187 8.187
2 2.819 9.721 26.235 2.367 8.163 16.350
3 2.600 8.967 35.202 2.322 8.008 24.359
4 2.491 8.589 43.791 2.222 7.664 32.022
5 1.986 6.847 50.638 2.183 7.528 39.551
6 1.962 6.767 57.405 2.170 7.482 47.032
7 1.694 5.842 63.246 2.136 7.367 54.399
8 1.493 5.147 68.393 2.133 7.356 61.755
9 1.331 4.588 72.981 1.875 6.466 68.221
10 1.141 3.934 76.916 1.839 6.340 74.561
11 1.035 3.569 80.484 1.718 5.923 80.484
12 .894 3.081 83.566
13 .844 2.910 86.476
14 .724 2.496 88.972
15 .643 2.216 91.188
16 .483 1.664 92.852
17 .454 1.566 94.418
18 .351 1.210 95.628
19 .302 1.042 96.670
20 .222 .766 97.436
21 .208 .716 98.152
22 .141 .487 98.639
23 .122 .422 99.060
24 .093 .320 99.380
25 .071 .244 99.624
26 .048 .167 99.791
27 .037 .128 99.919
28 .015 .051 99.970

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29 .009 .030 100.000
Extraction Method: Principal Component Analysis.
Table 15: Total Variance Explained
The scree plot is a diagnostic tool to identify the optimum number of components for
a factor analysis. The point of inflection after which the curve flattens out is supposed to be
the indicator of number of factors. The scree plot shows a gradual but slow decline which
flattens approaches towards flattening from after 11 on the x-axis. However it still seems to
be not be able to clearly show any sharp decline to stabilize.
Figure 13: Scree Plot
The following plot shows the rotated component matrix from the result output of
factor analysis. The items which show component scores of greater than 0.5 are taken to be
key contributors of the respective components from the table (Weaver and Maxwell 2014).
The Varimax and Kaiser Normalization method was used for its computation.
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Rotated Component Matrixa
Component
1 2 3 4 5 6 7 8 9 10 11
32. An Excellence Award seeks to
raise awareness of the culture of
excellence as well as the quality
assurance of the organization work
environment.
.866 .203 .127 .244
33. An Excellence culture is the
solutions for work process problems
in any organization.
.663 .160 -.20
0
-.16
0 .238 .242 .237
28. Has your department applied for
any excellence award in your
organization?
-.412 .219 .132 -.11
7 .152 -.31
9 .337 -.36
2
-.28
0
37. The effectiveness of the decision-
making process becomes stronger
through an innovation and excellence
culture.
.162 .846 .120 -.17
1 .224
39. Applying an Excellence or
innovation award in the organization
will encourage employees to work
more effectively in a knowledge-
sharing environment.
.622 .147 .456 .123 .369 -.16
2 .191
19. It is essential to have excellence
or innovation awards in all
organizations.
.136 .605 -.306 .156 .144 .130 -.13
0
-.21
1 .116 -.18
1 .275
15. The policies and procedures of
my organization support and
encourage creativity and excellence
in the work.
.849 .148 .175 .161
10. My manager trusts and
appreciates my work. .376 .702 -.12
0
-.25
8 .273
14. Strategic results of the
organization are available for the
staff.
-.162 .514 .253 -.17
5
-.15
9 .440
17. The relationship between staff
and managers are highly formal. .116 .828 .301 -.11
5
-.13
2
-.15
7
18. There is a strong relationship
between excellence award and the
organization performance?
.791 -.16
2
-.15
6 .164 .134
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22. Using innovation techniques in
the organization will improve the
operational work and raise the level
of the performance.
.189 .265 .816 -.11
4
-.10
8 .166
41. The Excellence Award
performance will improve and
support the collaborative work
environment in the organization.
.170 .258 .688 -.11
4 .104 .258
11. The strategic plan of my
organization is clear and
documented.
-.377 -.36
8
-.42
2 .282 .410 .232 .149 .222
26. The leaderships of my
organization believe in creativity,
honors and motivates creative
employees.
-.133 -.14
7 .879 .226 -.10
4
24. Our work environment
encourages staff to participate in
excellence award to support
creativity and innovation.
.281 .411 .221 .693 -.14
2 .167
36. Excellence Awards can build the
capacities of employees and qualify
them for the best management
practices for the future.
.281 .464 -.151 .111 .508 -.26
8
-.12
1
-.26
8
35. Excellence Awards are limited to
a certain employee or unit in my
organization.
.314 .161 .349 .363 .406 -.39
7 .116 .145 -.22
5
29. The method of submission of the
excellence award in my organization
is known by all employees and
documented.
-.208 .217 .824 -.23
4 .101
21. Knowledge-sharing culture
provides innovative solutions to
improve products and enhance
services.
.249 -.277 -.17
3
-.20
0 .725 -.25
3 .108 -.14
3
12. The strategic goals of my
organization are concentrating on
creativity and excellence
performance.
-.132 -.23
2 .853
30. The competitive environment to
win the excellence award will result in
successful performance among the
staff.
-.333 -.242 .307 .364 .644 -.17
0 .210

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31. An Excellence Award competition
shall raise the awareness of the
importance of innovations in the work
process.
.381 -.182 .373 -.22
2 .453 .408 -.22
5
9. I can speak comfortably with my
direct manager about any new ideas
to change some work process.
.205 .865
16. The procedures of the
organization are complex. -.304 .263 .250 -.20
0
-.36
2 .588 .282
13. The managers have the ability to
direct the employees to work towards
common goals.
.228 .166 -.22
0 .193 .824
27. As an employee, I accept any
feedback and learn from mistakes,
which is part of learning improvement
that leads to developing the
organization.
.103 .435 .172 .138 .356 .595 -.21
3
8. The communication with the
managers in my organization is easy .159 .143 .124 .880
7. The manager has done a lot to
encourage the employees to
participate in any internal excellence.
-.406 -.259 .463 .154 -.17
5 .513
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 53 iterations.
Table 16: Rotational Component
Based on the results of the rotated component matrix the following table shows the
variables as contributors to each of the 11 factors. The first factor seems to deal with items
related to the recognition of the importance of excellence awards. Factor 2 seems to incluecd
items which refer to the positive perception of excellence and innovation awards in boosting
employee morale and competitiveness. Factor 3 seems to speak about the organization’s
policy and structure in relation to the well being of its employees. Factor 4 talks about intent
of between managerial level in rewarding employees to perform better and create healthy
environment. Factor 5 deals with promoting and improving upon technology and innovation
in the workspace and through excellence award policy. Moving onto factor 6 it is seen that
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the items falling under it speak about tendency of company to reward all employees and offer
scope for upward mobility within the organization through it. Factor 7 again deals with items
which together suggest that the factor is that of the structure and technology used within the
organization to promote communication and knowledge sharing among all levels. Factor 8 is
suggested to be dealing with the attitude of the company to further their strategic agenda
using excellence awards policy. Factor 9 is seen to suggest the policy of the organization in
structuring itself so that together with excellence awards as incentive they could increase
employee involvement in tasks and nurture innovation culture. Factor 10 suggests leadership
as the factor, or rather how well the management guides its employees. Factor 11 again
speaks about leadership, in that how management communicates with employees. It is
understood that due to the problematic nature of the data the analysis might still be faulty and
the factors could be reduced further upon more thorough investigation. The following table
specifies the factors and its components that have been selected.
Factor 1 32. An Excellence Award seeks to raise awareness of the culture of excellence as well as the quality
assurance of the organization work environment.
33. An Excellence culture is the solutions for work process problems in any organization.
28. Has your department applied for any excellence award in your organization?
Factor 2 37. The effectiveness of the decision-making process becomes stronger through an innovation and
excellence culture.
39. Applying an Excellence or innovation award in the organization will encourage employees to work
more effectively in a knowledge-sharing environment.
19. It is essential to have excellence or innovation awards in all organizations.
Factor 3 15. The policies and procedures of my organization support and encourage creativity and excellence
in the work.
10. My manager trusts and appreciates my work.
14. Strategic results of the organization are available for the staff.
Factor 4 17. The relationship between staff and managers are highly formal.
18. There is a strong relationship between excellence award and the organization performance?
Factor 5 22. Using innovation techniques in the organization will improve the operational work and raise the
level of the performance.
41. The Excellence Award performance will improve and support the collaborative work environment
in the organization.
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Factor 6 36. Excellence Awards can build the capacities of employees and qualify them for the best
management practices for the future.
35. Excellence Awards are limited to a certain employee or unit in my organization.
Factor 7 29. The method of submission of the excellence award in my organization is known by all employees
and documented.
21. Knowledge-sharing culture provides innovative solutions to improve products and enhance
services.
Factor 8 12. The strategic goals of my organization are concentrating on creativity and excellence
performance.
30. The competitive environment to win the excellence award will result in successful performance
among the staff.
31. An Excellence Award competition shall raise the awareness of the importance of innovations in
the work process.
Factor 9 31. An Excellence Award competition shall raise the awareness of the importance of innovations in
the work process.
9. I can speak comfortably with my direct manager about any new ideas to change some work
process.
16. The procedures of the organization are complex.
Factor
10
13. The managers have the ability to direct the employees to work towards common goals.
27. As an employee, I accept any feedback and learn from mistakes, which is part of learning
improvement that leads to developing the organization.
Factor
11
8. The communication with the managers in my organization is easy
7. The manager has done a lot to encourage the employees to participate in any internal excellence.
Table 17: Factors List
Linear Regression
It is of interest for the study to scrutinize the relationship of organizational strategy,
structure, technology used and the leadership with the performance or business excellence of
the organization while moderating with the presence or absence of excellence awards within
the organization. The null hypothesis and alternative hypothesis that may be
framed for this particular problem is given as follows:
Null Hypothesis (H0): Internal Excellence awards toward organization context has no
influence the successful business excellence in the organization.

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Alternate Hypothesis (H1): Internal Excellence awards toward organization
context will influence the successful business excellence in the
organization.
A linear model was fitted from the regression analysis that was obtained which shows
relationship of the business excellence of the organization with that of its organizational
leadership style, its structure, strategy and technology with the moderator variable Excellence
awards. This means that the model takes into account the interaction effect of independent
variables with the moderator (Bolin 2014). The estimated model is given as follows:
Business Excellence = -0.209 + 0.118 Leadership - 0.360 strategy + 0.903 Structure
-0.209 Technology +0.734 Excellence Awards – 0.530 Excellence Awards*
Leadership+1.87 Excellence Awards*strategy - 0.152 Excellence Awards*
Structure+0.144 Excellence Awards* Technology
The coefficient of determination, that is the R squared statistic for the model, where
excellence awards are not present was obtained as 0.519 as seen from table . This means that
the variation in the performance of the firm or business excellence is explained up to only
51.91 percent by this model with only the independent variables as main effects. The F test
for significance of the model, as shown in the ANOVA table below was found to be
significant at 0.05 level (Chatterjee and Hadi 2015). The model indicates that moderation
effect of excellence awards with leadership style and the main effect of leadership styles are
significant at 5 percent level in explaining variation in business excellence of an organization.
The following plots show the partial regression plots for each pair of independent
with dependent variable.
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Figure 14
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Figure 15

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Figure 17
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Figure 18
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Figure 19
No notable outliers or influential points could be identified from the scatter plots of
independent variable or moderator variable with that of the dependent variable.
Now looking at the scatter plots of dependent with the interaction effect variables
where X1M is the interaction of moderator with leadership, X2M is that of strategy with
moderator, X3M is that with structure, and X4M is that with Technology, no such data points
could be identified either as shown in the plots below.

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Figure 20
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Figure 21
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Figure 22

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Figure 23
Next the scatter plot of the standardised residuals against the standardized predicted
values shows a funnel like patter and this indicates that the data may have presence of
hetersocedasticity. The figure below gives the plot as mentioned.
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Figure 24
Then the QQ plot of the standardized residuals shows that the errors although mostly
lie along the 45 degree line on the plot of observed errors against the theoretical values from
a standard normal distribution. The residuals are therefore close to normal. However there
may be some deviation present.
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Figure 25
The VIF values which denote the multicollinearity however shows high values above
the threshold of 5 for all variables. Therefore it is probable that the results are not reliable and
the standard errors are inflated. The following tables shows the results, that is the goodness of
fit, estimated coefficients and ANOVA tests.
The table number 20 shows the 95 percent confidence intervals for the beta
coefficients for the model, as highlighted in mauve.
Model Summaryb
Model R R
Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
R Square
Change
F Change df1 df2 Sig. F
Change
1 .519a .269 .245 .668 .269 11.208 9 274 .000

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a. Predictors: (Constant), X4M, Strategy, LeadershipStyle, Structure, Technology, Moderator_ExcelAwards,
X1M, X2M, X3M
b. Dependent Variable: 42. The organization facilitates a work environment that enhances the concepts of
quality, excellence, innovation and consolidation of creative practices.
Table 18
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 44.990 9 4.999 11.208 .000b
Residual 122.207 274 .446
Total 167.197 283
a. Dependent Variable: 42. The organization facilitates a work environment that enhances the concepts of
quality, excellence, innovation and consolidation of creative practices.
b. Predictors: (Constant), X4M, Strategy, LeadershipStyle, Structure, Technology,
Moderator_ExcelAwards, X1M, X2M, X3M
Table 19
Coefficientsa
Model Unstandardized
Coefficients
Stand
ardize
d
Coeffi
cients
t Sig. 95.0%
Confidence
Interval for B
Collinearity
Statistics
B Std.
Error
Beta Lower
Bound
Upper
Bound
Tolerance VIF
1
(Constant) -.209 2.221 -.094 .925 -4.582 4.163
LeadershipStyle 1.118 .498 .824 2.243 .026 .137 2.099 .020 50.640
Strategy -.360 .465 -.336 -.773 .440 -1.275 .556 .014 70.683
Structure .903 .465 .908 1.941 .053 -.013 1.818 .012 82.031
Technology -.209 .398 -.145 -.525 .600 -.992 .575 .035 28.624
Moderator_ExcelAwards .734 .766 .502 .959 .338 -.773 2.242 .010 102.711
X1M -.530 .187 -1.493 -2.826 .005 -.899 -.161 .010 104.723
X2M .187 .153 .604 1.217 .225 -.115 .489 .011 92.471
X3M -.152 .169 -.560 -.897 .370 -.485 .181 .007 146.038
X4M .144 .150 .429 .965 .336 -.150 .439 .013 74.107
a. Dependent Variable: 42. The organization facilitates a work environment that enhances the concepts of
quality, excellence, innovation and consolidation of creative practices.
Table 20
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2. Discussion
The analysis was found to be primarily focussed around people from the Middle East. This
could imply that the results could very well be affected by cultural standards of how
governments work from that region. The analysis on its own encountered a number of
problems. The primary one being of multicollinearity in the data and this has raised concerns
about how reliable the results maybe. However the study forms the basis of key challenges in
business today and the moderation model could provide invaluable insights even so(Cortina,
Köhler and Nielsen 2015). The current results indicate that leadership as a factor or rather
the proactive attitude of leadership has a significant role to play in improving the
performance of an organization, which in this case in a government organization since the
target population was that of government employees. Leadership is thus inferred to have a
key effect in improving performance and this is echoed by the research done by Fu et al.
(2015) wherein they concluded that managers ought to invest in nurturing their employee’s
innovation work behaviour. The interaction with excellence awards suggests that this could
be an effective way to o just that. The questionnaire had quizzed these subjects on a number
of issues, involving their opinion on structure, strategy, leadership, technology and the reward
system in the format of excellence rewards. Initially upon conducting a correlation analysis it
was seen that structure has a moderate yet significant association with business excellence. A
factor analysis of the information revealed a number of factors that could be identified.
However due to the same issue of multi collinearity the factor analysis failed to provide clear
cut definition of factors. The dimension was however reduced to 11 factors from 35 items.
Perception of reward system as a influencer of employee motivation, innovation and a means
of allowing employees to rise above their current job were some of the ideas that was felt to
be made clear. As also discussed by Peterson (2009) , technology facilitating open
communication and knowledge sharing, leadership which is open to sharing knowledge and
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guide and communicate employees in a positive way could be identified as notable ideas that
were perceived through studying the factor analysis. As Amin et al. (2014) in their study of
employee performance found that performance depends on a number of factors such as
training, appraisal, participation , kind of job and compensation , so these factors could be
related to a behavioural attitude of the management towards the facilitation of employee
behaviour and output by means of these aspects within its strategic , structural and approach
to leadership. This could be done by studying the items that came under leadership related
factor in the factor analysis and hence making inference regarding how one aspect addressed
by an item could be controlled to control performance. This can be related to the findings of
Peterson et al. (2009) who identified traits among upper level management that could
positively impact performance. This gives way for future research ideas whereby the problem
could be dealt with using some other technique such as decision trees which would not be
affected by the distributional assumptions as in this case which failed in terms of
homoscedasticity. Although the results failed to give distinctive results owing to the
complications in the data, it can be utilised as a guideline to carry forward the study in light
of the insights as discussed in this section.
4. Practical Implication
The results as explained before, due to certain complications are limited in that it fails
to give distinctive answers however the results point towards certain points which may help
in improving performance. results of the analysis as discussed in the previous section implies
that the business performance of an organization could benefit from having to nurture an
environment of innovation and learning thorough its leadership and organizational structure.
Leadership or management could look into introducing a reward system which recognizes
employees in terms of knowledge sharing, innovation and dedication as well as overall

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performance output by not only by means of financial but also through other kinds of rewards
such as chance to gain position and skills within the organization. It is to be noted that
Selemani (2014) has presented his findings on the same. Organizational structure is found to
have a association with performance. Shin (2015) had also discussed something similar along
these lines in their paper on effects of ethical leadership on firm performance. Therefore an
organization which has the infrastructural capability aside from the will to implement reward
system should also be kept in mind. The administration could look into advising its managers
to be more open to idea sharing and guiding employees and in turn making sure to recognize
achievements in appropriate manner.
5. Conclusion
The paper is a report on an attempt to study the moderating effect of excellence
awards at government offices on the relationship between organizational contexts such as
structure, strategy, leadership and the technology that is used in the organizational
framework. The study had been done using primary data on a group of people most of whom
hail from Middle east. The paper concluded that excellence awards has significant a
moderating effect on the relationship between the independent variable leadership score
which is a measure computed to denote the summary of leadership ratings of all items
relating to the same in the survey questionnaire instrument and the dependent variable
business which is the rating of business excellence, a measure of overall organizational
performance. The study also suggested a significant relationship between business excellence
with that of the structure of the organization. However more through scrutiny of the data need
to be addressed to root out the problem of correlation between independent variables arising
out of correlation between the observations on the items. The study however gave pointers
about further research into the matter and gave insights about organizational attitudes and its
effect on its employees. It also explored how controlling certain behaviours in the managerial
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level such as leadership approach and communication could lead to positive impact on
overall business performance via the prosperity and thus motivation of its employees.
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References
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