Using Probability And Statistics In A Survey Research: Results And Findings

Research Methodology

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.

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.

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.

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	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

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
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

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.

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

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

Gender

Table 4: Qualification

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

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

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.

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 towards left with location centred around 3.

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.

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.

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.

Nationality

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.

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 Excellence.	Leadership Style	Strategy	Structure	Technology	Excellence Awards
Spearman’s rho	Business Excellence	Correlation Coefficient	1.000	-.060	-.127*	.371**	.018	-.060
Sig. (2-tailed)	.	.315	.033	.000	.764	.314
N	284	284	284	284	284	284
Leadership Style	Correlation Coefficient	-.060	1.000	.052	.150*	.190**	.022
Sig. (2-tailed)	.315	.	.379	.011	.001	.715
N	284	284	284	284	284	284
Strategy	Correlation Coefficient	-.127*	.052	1.000	-.334**	-.239**	-.079
Sig. (2-tailed)	.033	.379	.	.000	.000	.186
N	284	284	284	284	284	284
Structure	Correlation Coefficient	.371**	.150*	-.334**	1.000	.022	.259**
Sig. (2-tailed)	.000	.011	.000	.	.706	.000
N	284	284	284	284	284	284
Technology	Correlation Coefficient	.018	.190**	-.239**	.022	1.000	.021
Sig. (2-tailed)	.764	.001	.000	.706	.	.725
N	284	284	284	284	284	284
Moderator_ExcelAwards	Correlation Coefficient	-.060	.022	-.079	.259**	.021	1.000
Sig. (2-tailed)	.314	.715	.186	.000	.725	.
N	284	284	284	284	284	284
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).

Table 12: Correlation measures

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

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

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
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.

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.

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					-.200	-.160	.238	.242	.237
28. Has your department applied for any excellence award in your organization?	-.412	.219	.132	-.117	.152	-.319	.337			-.362	-.280
37. The effectiveness of the decision-making process becomes stronger through an innovation and excellence culture.	.162	.846	.120					-.171		.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	-.162	.191
19. It is essential to have excellence or innovation awards in all organizations.	.136	.605	-.306	.156	.144	.130	-.130	-.211	.116	-.181	.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			-.120	-.258		.273
14. Strategic results of the organization are available for the staff.	-.162		.514		.253		-.175	-.159		.440
17. The relationship between staff and managers are highly formal.			.116	.828	.301				-.115	-.132	-.157
18. There is a strong relationship between excellence award and the organization performance?				.791	-.162			-.156	.164	.134
22. Using innovation techniques in the organization will improve the operational work and raise the level of the performance.	.189		.265		.816		-.114		-.108		.166
41. The Excellence Award performance will improve and support the collaborative work environment in the organization.		.170		.258	.688	-.114	.104		.258
11. The strategic plan of my organization is clear and documented.		-.377		-.368	-.422		.282	.410	.232	.149	.222
26. The leaderships of my organization believe in creativity, honors and motivates creative employees.	-.133				-.147	.879				.226	-.104
24. Our work environment encourages staff to participate in excellence award to support creativity and innovation.	.281		.411		.221	.693				-.142	.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	-.268			-.121	-.268
35. Excellence Awards are limited to a certain employee or unit in my organization.	.314	.161	.349		.363	.406	-.397	.116	.145	-.225
29. The method of submission of the excellence award in my organization is known by all employees and documented.	-.208					.217	.824		-.234		.101
21. Knowledge-sharing culture provides innovative solutions to improve products and enhance services.	.249		-.277	-.173		-.200	.725	-.253	.108		-.143
12. The strategic goals of my organization are concentrating on creativity and excellence performance.	-.132			-.232				.853
30. The competitive environment to win the excellence award will result in successful performance among the staff.		-.333	-.242	.307		.364		.644	-.170	.210
31. An Excellence Award competition shall raise the awareness of the importance of innovations in the work process.	.381		-.182	.373		-.222		.453	.408		-.225
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		-.200	-.362	.588		.282
13. The managers have the ability to direct the employees to work towards common goals.	.228	.166			-.220			.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	-.213
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		-.175	.513
Extraction Method: Principal Component Analysis.  Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 53 iterations.

Current Age

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 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.
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.

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 

Educational Level

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.

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.

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. 

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.

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
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	Standardized Coefficients	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

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 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.

Job Level

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 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.

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 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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