Table Correlation between TD and competitiveness
University
Competitiveness
Training and
Development
Pearson Correlation
1
.230**
University Competitiveness Sig. (2-tailed) .000
N
316 316
Pearson
Correlation
.230**
1
Training and Development Sig. (2-tailed) .000
N
316 316
**. Correlation is significant at the 0.01 level (2-tailed).
4.1.1 Regression analysis of Training & development and university competitiveness
Table 4. 12: Model Summary for Training and D evelopment
The results as shown in the table 4.12 indicates that the coefficient of regression, R= 0.230
shows a good strength of the relationships between training & development and
competitiveness of the universities. The coefficient of determination R2= 0.053 shows the
predictive power of the model and in this case 5.3% of variations in the Universities’
competitiveness is explained by the training and development variable. The adjusted
coefficient of determination R2 shows the predictive power when adjusted for degrees of
freedom and sample size. In this case, after the adjustments 0.050% of the variations in the
Universities’ competitiveness is explained by training and development. These findings
concur with Tettey (2006) who observed that training and development is the engine that
keeps the universities true to their mandate as centers of ideas and innovation in enhancing
competitiveness.
Table : ANOVAa
Model Sum of Squares df Mean Square
F
Sig.
Regression 147.682
1
147.682 17.598 .000b
1
Residual 2635.065 314 8.392
Total 2782.747 315
a. Dependent Variable: University Competitiveness
Model
R
R Square Adjusted R
Square
Std. Error of the
Estimate
1
.230a.053 .050 2.89688
b. Predictors: (Constant), Training and Development
ANOVA findings as explained by the P-Value of 0.000 which is less than 5% significance
level confirms the significant existence of correlation between training and development
and university competitiveness. The model shows the model fitness i.e. how well the
variable fit the regression model. From the results, the F ratio of 17.598 and the
significance of 0.000 shows that there was not much difference in means between
dependent and independent variables. The sum of squares gives the model fit and hence
the variable fit the regression model.
Table: Regression Coefficient
Unstandardized
Coefficients
Standardize
d
Coefficients
T Sig. Correlations
B Std. Error Beta Zero-
order
Partial Part
(Constant) 32.734 .853 38.370 .000
1Training and
Development
.168 .040 .230 4.195 .000 .230 .230 .230
a. Dependent Variable: University Competitiveness
A simple regression model was also applied to determine the relative importance of
training & development as a talent retention strategy on university competitiveness. The
regression model was as follows: y =β0+β1TD + e. Using the values of the coefficients
(β) from the regression coefficients the established linear regression equation took the
form of; Y= 32.734 +0.168TD. Where; Constant = 32.734; when value of the independent
variables are zero, the Universities’ competitiveness would take the value 32.734.
TD=0.168; one unit increase in training and development results in 0.168 units increase in
the Universities’ competitiveness.
Hypothesis (H02): Posited that training and developmenthas no significant effect on
competitiveness in Public Universities. The results reveal that the standardized beta
coefficient is 0.230 with the t-value of 4.195 and P value of 0.000. Since the P value is
less than the significance level we reject the null hypothesis and accept the alternative.
This indicates that the training and development affects the competitiveness in public
Universities.
Correlation analysis for Reward System and University Competitiveness Pearson’s
product moment correlation analysis In order to establish the strength and direction
of the relationship between reward system and competitiveness of public universities in
Western Region of Kenya, the results showed there existed a weak but positive
correlation between reward system and competitiveness of public universities in
Western Region of Kenya(r = 0.193) as shown in table 4.15
Table : Correlation of reward system and university competiveness
Reward system University Competitiveness
Pearson Correlation
1
.193**
Reward system Sig. (2-tailed) .001
N
316 316
Pearson Correlation .193**
1
University Competitiveness Sig. (2-tailed) .001
N
316 316
**. Correlation is significant at the 0.01 level (2-tailed).
Regression analysis for Reward System and competitiveness of the university
Table Model Summary
Mode
l
R R Square Adjusted R Square Std. Error of the Estimate
1 .193a.037 .034 2.92083
The results as shown in the table 4.16 indicates that the coefficient of regression, R= 0.193
shows a good strength of the relationships between reward system and competitiveness of
the universities. The coefficient of determination R2= 0.037 shows the predictive power of
the model and in this case 3.7% of variations in the Universities’ competitiveness is
explained by the reward system variable. The adjusted coefficient of determination R2
shows the predictive power when adjusted for degrees of freedom and sample size. In this
case, after the adjustments 3.4% of the variations in the Universities’ competitiveness is
explained by reward system. The results of the study are in line with many previous
studies. Previous studies have highlighted that rewards system can be used
as a
strategy to retain competent employees and for enhancing
organizational
competitiveness (Medcof & Rumpel, 2007).
In modern globalized world, the role of universities has become wider than
ever,
and universities are expected to play their role in economic
development
knowledge sharing and talent development (Comunian, Taylor and Smith, 2013). They
further points out that it is essential to have rewards systems in the university that not only
retains employees but also should enable them to produce talented
workforce.
Table : ANOVA
Model Sum of Squares Df Mean Square
F
Sig.
Regression 103.933 1 103.933 12.183 .001b
1 Residual 2678.814 314 8.531
Total 2782.747 315
a. Dependent Variable: University Competitiveness
b. Predictors: (Constant), Reward system
Table is ANOVA findings as explained by the P-Value of 0.001 which is less than 5%
significance level confirms the existence of correlation between reward system and
university competitiveness. The model shows the model fitness i.e. how well the variable
fit the regression model. From the results, the F ratio of 12.183 and the significance of
0.001 shows that there was not much difference in means between dependent and
independent variables. The sum of squares gives the model fit and hence the variable fit
the regression model.
Table : Regression Coefficient
Model Unstandardized
Coefficients
Standardized
Coefficients
T Sig. Correlations
B Std. Error Beta Zero-
order
Partial Part
(Constant) 30.917 1.536 20.129 .000
1Reward
system
.198 .057 .193 3.490 .001 .193 .193 .193
a. Dependent Variable: University Competitiveness
