RESULT AND ANALYSIS
4.5 Measurement Model Evaluation
4.5.1 CFA Results for Job Control
The CFA results of the model were as follows: the 2 value was 45.799 with a degree of freedom of 14 at a p-value of 0.000, while the 2/df was 3.271. The CFI = 0.989, IFI = 0.989, TLI = 0.978 and the RMSEA = 0.065. This shows that the data fit the model well. Critical Ratio (CRs) values were greater than 1.96, which indicated that all of the estimates were statistically different from zero and the null hypothesis that all estimates equals 0.0 can be rejected. Additionally, the parameter estimates were positive and within the logical anticipated range of values (i.e. no estimate exceeded the value of 1.00). Again, the path coefficient from each latent construct to the observed indicators was significant (p < 0.000) and the standardized regression weight ranged from 0.73 to 0.87. This supported the validity and reliability of the items (Hair et al., 2010).
Table 4.4 Parameter Estimates of Job Control
Figure 4.2 Measurement Model for Job Control
4.5.2 CFA Results for Social Support
The CFA results of the model were as follows: the 2 value was 113.712 with a degree of freedom of 46 at a p-value of 0.000, while the 2/df was 2.472. The CFI = 0.989, IFI = 0.989, TLI = 0.985 and the RMSEA = 0.052. This shows that the data fit the model well. CRs values were greater than 1.96, which indicated that all of the
Latent Manifest Estimate S.E. C.R. p AVE
Job Control JC1 0.814 0.9909
JC2 0.823 0.037 27.101 ***
JC3 0.870 0.047 23.285 ***
JC4 0.817 0.043 24.103 ***
JC5 0.781 0.048 20.187 ***
JC6 0.576 0.054 13.814 ***
JC7 0.735 0.051 18.638 ***
JC8 0.635 0.052 15.523 ***
estimates were statistically different from zero and the null hypothesis that all estimates equals 0.0 can be rejected. Additionally, the parameter estimates were positive and within the logical anticipated range of values (i.e. no estimate exceeded the value of 1.00). Again, the path coefficient from each latent construct to the observed indicators was significant (p < 0.000) and the standardized regression weight ranged from 0.701 to 0.94. This supported the validity and reliability of the items (Hair et al., 2010).
Table 4.5 Parameter Estimates of Social Support
Latent Manifest Estimate S.E. C.R. p AVE
Social Support
SS9 0.791 0.9955
SS10 0.800 0.040 25.394 ***
SS11 0.848 0.047 22.513 ***
SS12 0.837 0.047 22.597 ***
SS13 0.860 0.046 22.901 ***
SS14 0.900 0.046 24.407 ***
SS15 0.859 0.045 22.915 ***
SS16 0.747 0.048 18.774 ***
SS17 0.696 0.049 17.384 ***
SS18 0.740 0.049 18.767 ***
SS19 0.726 0.042 18.318 ***
SS20 0.675 0.047 16.737 ***
Figure 4.3 Measurement Model for Social Support
4.5.3 CFA Results for Job Demand
The CFA results of the model were as follows: the 2 value was 51.111 with a degree of freedom of 19 at a p-value of 0.000, while the 2/df was 2.690. The CFI = 0.993, IFI = 0.993, TLI = 0.986 and the RMSEA = 0.056. This shows that the data fit the model well. CRs values were greater than 1.96, which indicated that all of the estimates were statistically different from zero and the null hypothesis that all estimates equals 0.0 can be rejected. Additionally, the parameter estimates were positive and within the logical anticipated range of values (i.e. no estimate exceeded the value of 1.00). Again, the path coefficient from each latent construct to the observed indicators was significant (p < 0.000) and the standardized regression
weight ranged from 0.74 to 0.85. This supported the validity and reliability of the items (Hair et al., 2010).
Table 4.6 Parameter Estimates of Job Demand
Latent Manifest Estimate S.E. C.R. p AVE Psychological
Demand
PD33 0.823 0.040 23.466 *** 0.946 PD34 0.813 0.041 22.912 ***
PD35 0.825 0.040 23.554 ***
PD36 0.787 0.041 21.734 ***
PD37 0.849 0.035 27.843 ***
PD38 0.852
PD39 0.797 0.039 25.236 ***
PD40 0.815 0.041 23.069 ***
PD41 0.745 0.039 20.173 ***
Figure 4.4 Measurement Model for Job Demand
4.5.4 CFA Results for Burnout
The CFA results of the model were as follows: the 2 value was 38.419 with a degree of freedom of 14 at a p-value of 0.000, while the 2/df was 2.744. The CFI = 0.994, IFI = 0.994, TLI = 0.988 and the RMSEA = 0.134. This shows that the data fit the model well. CRs values were greater than 1.96, which indicated that all of the estimates were statistically different from zero and the null hypothesis that all estimates equals 0.0 can be rejected. Additionally, the parameter estimates were positive and within the logical anticipated range of values (i.e. no estimate exceeded the value of 1.00). Again, the path coefficient from each latent construct to the observed indicators was significant (p < 0.000) and the standardized regression weight ranged from 0.76 to 0.91. This supported the validity and reliability of the items (Hair et al., 2010).
Table 4.7 Parameter Estimates of Burnout
Latent Manifest Estimate S.E. C.R. p AVE
Burnout BO25 0.738 0.9904
BO26 0.682 0.034 25.850 ***
BO27 0.753 0.041 24.676 ***
BO28 0.686 0.047 19.617 ***
BO29 0.881 0.059 21.115 ***
BO30 0.912 0.060 21.809 ***
BO31 0.887 0.060 21.547 ***
BO32 0.906 0.064 21.136 ***
Figure 4.5 Measurement Model for Burnout
4.5.5 CFA Results for Self-efficacy
The CFA results of the model were as follows: the 2 value was 8.858 with a degree of freedom of 6 at a p-value of 0.000, while the 2/df was 1.476. The CFI = 0.999, IFI = 0.999, TLI = 0.997 and the RMSEA = 0.030. This shows that the data fit the model well. CRs values were greater than 1.96, which indicated that all of the estimates were statistically different from zero and the null hypothesis that all estimates equals 0.0 can be rejected. Additionally, the parameter estimates were positive and within the logical anticipated range of values (i.e. no estimate exceeded the value of 1.00). Again, the path coefficient from each latent construct to the observed indicators was significant (p < 0.000) and the standardized regression weight ranged from 0.77 to 0.89. This supported the validity and reliability of the items (Hair et al., 2010).
Table 4.8 Parameter Estimates of Self-efficacy
Latent Manifest Estimate S.E. C.R. p AVE
Self-efficacy Self42 0.769 0.938
Self43 0.875 0.053 22.127 ***
Self44 0.888 0.056 22.521 ***
Self45 0.861 0.056 21.692 ***
Self46 0.824 0.050 22.121 ***
Self47 0.859 0.054 21.629 ***
Figure 4.6 Measurement Model for Self-efficacy
4.5.6 CFA Results for Informal Learning
The CFA results of the model were as follows: the 2 value was 59.042 with a degree of freedom of 17 at a p-value of 0.000, while the 2/df was 3.473. The CFI = 0.970, IFI = 0.970, TLI = 0.951 and the RMSEA = 0.068. This shows that the data fit the model well. CRs values were greater than 1.96, which indicated that all of the estimates were statistically different from zero and the null hypothesis that all estimates equals 0.0 can be rejected. Additionally, the parameter estimates were positive and within the logical anticipated range of values (i.e. no estimate exceeded the value of 1.00). Again, the path coefficient from each latent construct to the
observed indicators was significant (p < 0.000) and the standardized regression weight ranged from 0.63 to 0.79. This supported the validity and reliability of the items (Hair et al., 2010).
Table 4.9 Parameter Estimates of Informal Learning
Latent Manifest Estimate S.E. C.R. p AVE Informal Learning IFL48 0.678 0.050 12.756 *** 0.887
IFL49 0.624 0.057 13.841 ***
IFL50 0.795
IFL51 0.691 0.065 15.385 ***
IFL52 0.711 0.069 11.080 ***
IFL53 0.785 0.067 10.437 ***
IFL54 0.707 0.057 15.728 ***
IFL55 0.639 0.068 11.860 ***
Figure 4.7 Measurement Model for Informal Learning
4.5.7 CFA Results for Job Performance
The CFA results of the model were as follows: the 2 value was 1.407 with a degree of freedom of 1 at a p-value of 0.000, while the 2/df was 1.407. The CFI =
1.000, IFI = 1.000, TLI = 0.999 and the RMSEA = 0.027. This shows that the data fit the model well. CRs values were greater than 1.96, which indicated that all of the estimates were statistically different from zero and the null hypothesis that all estimates equals 0.0 can be rejected. Additionally, the parameter estimates were positive and within the logical anticipated range of values (i.e. no estimate exceeded the value of 1.00). Again, the path coefficient from each latent construct to the observed indicators was significant (p < 0.000) and the standardized regression weight ranged from 0.88 to 0.91. This supported the validity and reliability of the items (Hair et al., 2010).
Table 4.10 Parameter Estimates of Job Performance
Latent Manifest Estimate S.E. C.R. p AVE In-Role
Behavior
IR21 0.894 0.944
IR22 0.915 0.032 31.512 ***
IR23 0.903 0.035 27.916 ***
IR24 0.882 0.032 29.315 ***
Figure 4.8 Measurement Model for Job Performance