According to table 4-1 most of our respondents were from the GEN Y (age 25 to 39) group coming in at 55.8% of total respondents. Our second largest group was GEN Z (age 18 to 24) coming in at 24.9%. Our smallest group was GEN X (age 40 to 55) coming in at 16.3%.
Additionally 16 of the participants had failed to identify their age.
Table 4-1 Generations
Frequency Percent
Gen Z (18 to 24) 133 24.9
Gen Y (25 to 39) 298 55.8
Gen X (40 to 55) 87 16.3
Missing 16 3.0
Total 534 100.0
When it came to gender, as you can see in table 4-2 we had a pretty even split when it came to male vs female. Male respondents made up 49.6% of our sample size, while female respondents made up 49% of our sample size. It is also noted that 7 respondents failed to disclose their gender.
Table 4-2 Gender
Frequency Percent
Male 265 49.6
Female 262 49.0
Prefer not to respond 7 1.0
Total 534 100.0
Descriptive Statistics and Correlations
Table 4-3 reported Pearson correlations between two variables for all data (N = 534). The engagement variable was significantly correlated with Transformational Leadership,
Transactional Leadership, CSR, WLB, Autonomy, Technology (p < 0.01).
Table 4-3
Pearson Correlation Results for All Data (N = 534)
Mean SD N (1) (2) (3) (4) (5) (6) (7) Note: *p<0.05, **p<0.01 Lead_TF = Transformational Leadership Lead_TS = Transactional Leadership
Regression Model Results for All Data (N = 534)
The first regression model tested all data (N = 534) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace.
The model was statistically significant [R2 = 0.570, Adjusted R2 = 0.565, F(6, 527) = 116.512, p
= 0.000; CI = 22.674]. The regression model explained 57.0% of the variance in the employee engagement outcome (R2 = 0.570). Transformational Leadership, CSR, WLB and Autonomy were significantly related to Engagement (p < 0.01), and Technology was marginally significant (p < 0.10) while Transactional Leadership factor showed no statistical significance. According to the standardized regression coefficient BETA, transformational leadership impacted the most on the employee engagement (.414), followed by employee autonomy (.212), WLB (.154), CSR (.129), technology (.062), and transactional leadership (.035). No serious multicollinearity was present in the regression model because all VIFs were less than 10 (Vittinghoff et al., 2012), and the condition index was less than 30 (Kennedy, 2003). Table 4-4 reported the results on the full regression model for all data.
Table 4-4
Regression Model Results for All Data
DV = Engagement; R2 =0.570, Adjusted R2 = 0.565; F(6, 527) = 116.512, p = 0.000; CI = 22.674
Note: DV = Dependent variable; CI = Condition Index, B = Regression Coefficient, SE = Standard error, BETA = Standardized regression coefficient, VIF = Variance Inflation Factor
Correlation & Regression Model Results for Gen X Employees (N = 87)
Table 4-4a reported Pearson correlations between two variables for Gen X employees (N = 87). Based on this sample, the employee engagement variable was significantly correlated with 4 out of 6 of the independent variables in the study: transformational leadership, transactional leadership, corporate social responsibility, autonomy, and technology. All of these variables have a p-value that is equal to or less than 0.01 which indicates a significant relationship exists
between those variables.
Table 4-4a
Pearson Correlation Results for GEN X (N = 87)
Mean SD N (1) (2) (3) (4) (5) (6) (7)
(1) Engagement 5.069 1.714 87 1
(2) Lead_TF 4.791 1.512 87 .747** 1
(3) Lead_TS 4.226 1.094 87 .475** .670** 1
(4) CSR 5.041 1.189 87 .530** .589** .395** 1
(5) WLB 4.995 1.574 87 .681** .546** .229* .352** 1
(6) Autonomy 5.015 1.717 87 .574** .529** .480** .388** .457** 1
(7) Technology 5.590 1.381 87 .371** .379** .340** .233** .216** .444** 1
Note: *p<0.05, **p<0.01
The second regression model tested only GEN X (N = 87) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace.
The model was statistically significant [R2 =0.693, Adjusted R2 = 0.670, F(6, 86) = 30.058, p = 0.000; CI = 22.995 ]. The regression model explained 69.3% of the variance in the employee engagement outcome (R2 = 0.693). Transformational Leadership and WLB were significantly related to Engagement (p < 0.01), while Transactional Leadership, CSR, Autonomy, and
Technology factors showed no statistical significance. According to the standardized regression coefficient BETA, transformational leadership impacted the most on the employee engagement (.400), followed by WLB (.354), employee autonomy (.136), CSR (.105), and technology (.059).
No serious multicollinearity was present in the regression model because all VIFs were less than 10 (Vittinghoff et al., 2012), and the condition index was less than 30 (Kennedy, 2003). Table 4-4a reported the results on the full regression model for all data.
Table 4-4b
Regression Model Results for GEN X
DV = Engagement; R2 =0.693, Adjusted R2 = 0.670; F(6, 86) = 30.058, p = 0.000; CI =22.995
B SE BETA t p VIF
(Constant) -.863 .652 -1.325 .189
Lead_TF .453 .124 .400 3.648 .000 3.124
Lead_TS -0.00004 .139 .000 .000 1.00 2.059
CSR .151 .111 .105 1.354 .179 1.554
WLB .382 .087 .351 4.416 .000 1.643
Autonomy .135 .082 .136 1.654 .102 1.751
Technology .074 .088 .059 .841 .403 1.302
Note: DV = Dependent variable; CI = Condition Index, B = Regression Coefficient, SE = Standard error, BETA = Standardized regression coefficient, VIF = Variance Inflation Factor
Bootstrap Regression Results for Gen X Employees
As you can see in table 4-4c the regression model was bootstrapped in an attempt to see what differences there might be with a wider population. Results were similar still showing that transformational leadership and work life balance were most positively correlated to employee engagement.
Table 4-4c
Bootstrap Regression Model Results for GEN X
DV = Engagement; R2 =0.693, Adjusted R2 = 0.670; F(6, 86) = 30.058, p = 0.000; CI = 22.995
B Bias SE Bootsrap p Lower Upper
(Constant) -.863 -.046 .741 .239 -2.315 .534
Lead_TF .453 -.013 .164 .010 .121 .753
Lead_TS -0.00004 .006 .142 1.00 -.262 .291
CSR .151 .009 .130 .253 -.094 .417
WLB .382 .006 .103 .003 .194 .586
Autonomy .135 -.004 .093 .146 -.045 .317
Technology .074 .005 .097 .435 -.098 .283
Note: 1000 bootstrap samples; DV = Dependent variable; CI = Condition Index, B = Regression Coefficient, SE = Standard error
Correlation & Regression Model Results for Gen Y Employees (N = 298)
Table 4-4d reported Pearson correlations between two variables for Gen Y employees (N=298). Based on this sample, the employee engagement variable was significantly correlated with the 6 independent variables in the study: transformational leadership, transactional
leadership, corporate social responsibility, work-life balance, autonomy, and technology. All of these variables have a p-value that is equal to or less than 0.01 which indicates a significant relationship exists.
Table 4-4d
Pearson Correlation Results for GEN Y (N = 298)
Mean SD N (1) (2) (3) (4) (5) (6) (7)
(1) Engagement 4.942 1.529 298 1
(2) Lead_TF 4.783 1.432 298 .709** 1
(3) Lead_TS 4.476 1.102 298 .475** .656** 1
(4) CSR 5.114 1.083 298 .543** .663** .497** 1
(5) WLB 4.595 1.681 298 .220** .135** -.221** .317** 1
(6) Autonomy 5.131 1.441 298 .539** .518** .313** .392** .183** 1
(7) Technology 5.396 1.377 298 .453** .520** .419** .530** .155** .392** 1
Note: *p<0.05, **p<0.01
The third regression model tested only GEN Y (N = 298) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace.
The model was statistically significant [R2 =0.565, Adjusted R2 = 0.556, F(6, 297) = 63.077, p = 0.000; CI = 24.401]. The regression model explained 56.5% of the variance in the employee engagement outcome (R2 = 0.565). Transformational Leadership, WLB and Autonomy were significantly related to Engagement (p < 0.01), while Transactional Leadership, CSR, and Technology factors showed no statistical significance. According to the standardized regression coefficient BETA, transformational leadership impacted the most on the employee engagement (.449), followed by employee autonomy (.206), WLB (.130), CSR (.100), transactional
leadership (.083) and technology (.031). No serious multicollinearity was present in the
regression model because all VIFs were less than 10 (Vittinghoff et al., 2012), and the condition index was less than 30 (Kennedy, 2003). Table 4-4a reported the results on the full regression model for all data.
Table 4-4e
Regression Model Results for GEN Y
DV = Engagement; R2 =0.565, Adjusted R2 = 0.556; F(6, 297) = 63.077, p = 0.000; CI = 24.401
B SE BETA t p VIF
(Constant) -.434 .392 -1.106 .270
Lead_TF .479 .071 .449 6.744 .000 2.964
Lead_TS .115 .079 .083 1.442 1.00 2.195
CSR .141 .077 .100 1.842 .065 1.964
WLB .118 .040 .130 2.974 .003 1.280
Autonomy .218 .049 .206 4.451 .000 1.429
Technology .035 .054 .031 .639 .523 1.586
Note: DV = Dependent variable; CI = Condition Index, B = Regression Coefficient, SE = Standard error, BETA = Standardized regression coefficient, VIF = Variance Inflation Factor
Bootstrap Regression Results for Gen Y Employees
As you can see in table 4-4f the regression model was bootstrapped in an attempt to see what differences there might be with a wider population. Results were similar still showing that transformational leadership was most positively correlated to employee engagement.
Table 4-4f
Bootsrap Regression Model Results for GEN Y
DV = Engagement; R2 =0.565, Adjusted R2 = 0.556; F(6, 297) = 63.077, p = 0.000; CI = 24.401
Note: 1000 bootstrap samples; DV = Dependent variable; CI = Condition Index, B = Regression Coefficient, SE = Standard error
Correlation & Regression Model Results for Gen Z Employees (N = 133)
Table 4-4g reported Pearson correlations between two variables for Gen Z employees (N=133). Based on this sample, the employee engagement variable was significantly correlated with the 6 independent variables in the study: transformational leadership, transactional
leadership, corporate social responsibility, autonomy, and technology. All of these variables have a p-value that is equal to or less than 0.01 which indicates a significant relationship exists.
Table 4-4g
Pearson Correlation Results for GEN Z (N = 133)
Mean SD N (1) (2) (3) (4) (5) (6) (7)
The fourth regression model tested only GEN Z (N = 133) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace.
The model was statistically significant [R2 =0.591, Adjusted R2 = 0.572, F(6, 132) = 30.393, p = 0.000; CI = 22.153]. The regression model explained 59.1% of the variance in the employee engagement outcome (R2 = 0.591). Transformational Leadership, WLB and Autonomy were significantly related to Engagement (p < 0.01), while Transactional Leadership, CSR, and Technology factors showed no statistical significance. According to the standardized regression
coefficient BETA, transformational leadership impacted the most on the employee engagement (.296), followed by employee autonomy (.270), CSR (.241), WLB (.146), technology (.032), and transactional leadership (.030). No serious multicollinearity was present in the regression model because all VIFs were less than 10 (Vittinghoff et al., 2012), and the condition index was less than 30 (Kennedy, 2003). Table 4-4a reported the results on the full regression model for all data.
Table 4-4h
Regression Model Results for GEN Z
DV = Engagement; R2 =0.591, Adjusted R2 = 0.572; F(6, 132) = 30.393, p = 0.000; CI = 22.153
B SE BETA t p VIF
(Constant) -1.225 .600 -2.706 .008
Lead_TF .361 .116 .296 3.115 .002 2.791
Lead_TS .052 .135 .030 .383 .702 1.937
CSR .376 .120 .241 3.127 .002 1.829
WLB .176 .077 .146 2.289 .024 1.260
Autonomy .312 .093 .270 3.345 .001 2.013
Technology .036 .084 .032 .425 .672 1.697
Note: DV = Dependent variable; CI = Condition Index, B = Regression Coefficient, SE = Standard error, BETA = Standardized regression coefficient, VIF = Variance Inflation Factor
Bootstrap Regression Results for Gen Z employees
As you can see in table 4-4i the regression model was bootstrapped in an attempt to see what differences there might be with a wider population. Results were similar still showing that autonomy was most positively correlated to employee engagement.
Table 4-4i
Bootsrap Regression Model Results for GEN Z
DV = Engagement; R2 =0.591, Adjusted R2 = 0.572; F(6, 132) = 30.393, p = 0.000; CI = 22.153
B Bias SE Bootsrap p Lower Upper
(Constant) -1.625 .027 .600 .018 -2.870 -.169
Lead_TF .361 .002 .116 .014 .060 .632
Lead_TS .052 -.004 .135 .705 -.202 .343
CSR .376 .005 .120 .008 .123 .680
WLB .176 .000 .077 .032 .026 .350
Autonomy .312 -.006 .093 .001 .099 .512
Technology .036 -.002 .084 .688 -.138 .222
Note: 1000 bootstrap samples; DV = Dependent variable; CI = Condition Index, B = Regression Coefficient, SE = Standard error
Discriminant Model Results
Discriminant Model All Data (N = 534)
The first discriminant model tested all data (N = 534) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace.
Test results indicated that the model was statistically significant [Box’s M = 174.672, F(21, 694801.620) = 8.210, p < .001; Eigen value = .696, Canonical Correlation = .641, Wilks’
Lambda = .590, Chi-square = 279.445, p < .001]. According to the standardized canonical discriminant function coefficients, transformational leadership impacted the most on the
employee engagement (.536), followed by employee autonomy (.321), CSR (.300), WLB (.161), transactional leadership (.052), and technology (.092). According to the classification results the model had an overall accuracy rate of 82.0%. The tables below reported the results on the full discriminant model for all data.
Total L_TF_All 4.7617 1.44787
L_TS_All 4.3836 1.08341
Tests of Equality of Group Means
Wilks' Lambda F df1 df2 Sig.
Table 4-5b
Pooled within-groups 6 1.066
Table 4-5d Eigenvalues
Function Eigenvalue % Of Variance Cumulative % Canonical Correlation
1 .696a 100.0 100.0 .641
Table 4-5e Wilks' Lambda
Test of Function(s) Wilks' Lambda Chi-square df Sig.
1 .590 279.445 6 <.001
Auto .241
Tech .039
(Constant) -6.064
Table 4-5h
Functions at Group Centroids Mean (4.8901) Function
.00 1 -1.055
1.00 .657
Table 4-5i Classification Resultsa
Mean (4.8901) Predicted Group Membership
Total
.00 1.00
Original Count .00 151 54 205
1.00 42 287 329
% .00 73.7 26.3 100.0
1.00 12.8 87.2 100.0
a. 82.0% of original grouped cases correctly classified. (151 + 287) / 534 = 82.0%
Discriminant model Gen X Employees (N=87)
The second discriminant model tested Gen X employees (N = 87) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace. Test results indicated that the model was statistically significant [Box’s M = 55.504, F(21, 9998.462) = 2.393, p < .001; Eigen value = 1.497, Canonical Correlation = .774, Wilks’
Lambda = .401, Chi-square = 75.025, p < .001]. According to the standardized canonical
discriminant function coefficients, WLB impacted the most on the employee engagement (.512), followed by transformational leadership (.512), CSR (.331), Technology (.252), employee autonomy (.064), and transactional leadership (-.058). According to the classification results the model had an overall accuracy rate of 90.8%. The tables below reported the results on the full logistic discriminant model for Gen X employees.
Table 4-6 Group Statistics
Mean (4.8901) Mean Std. Deviation
.00 L_TF_All 3.2562 1.51311
Total L_TF_All 4.7912 1.51152
L_TS_All 4.2261 1.09408
Tests of Equality of Group Means
Wilks' Lambda F df1 df2 Sig.
Pooled within-groups 6 .977
Table 4-6d Eigenvalues
Function Eigenvalue % Of Variance Cumulative % Canonical Correlation
1 1.497a 100.0 100.0 .774
Table 4-6e Wilks' Lambda
Test of Function(s) Wilks' Lambda Chi-square df Sig.
1 .401 75.025 6 <.001
Table 4-6f
Standardized Canonical Discriminant Function Coefficients Function
L_TF_All 1 .512
L_TS_All -.058
CSR .331
WLB .523
Auto .064
Tech .252
Table 4-6g
Canonical Discriminant Function Coefficients Function
L_TF_All 1 .462
L_TS_All -.057
CSR .330
WLB .421
Auto .042
Tech .196
(Constant) -7.045
Unstandardized coefficients
Table 4-6h
Functions at Group Centroids
Mean (4.8901) Function
.00 1 -1.803
1.00 .811
Unstandardized canonical discriminant functions evaluated at group means
Table 4-6i Classification Resultsa
Mean (4.8901) Predicted Group Membership
Total
a. 90.8% of original grouped cases correctly classified.
Discriminant Model Gen Y Employees (N = 298)
The third discriminant model tested only Gen Y employees (N = 298) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace. Test results indicated that the model was statistically significant [Box’s M = 152.441, F(21, 231006.44) = 7.093, p < .001; Eigen value = .686, Canonical Correlation = .638, Wilks’
Lambda = .593, Chi-square = 152.982, p < .001]. According to the standardized canonical discriminant function coefficients, transformational leadership impacted the most on the
employee engagement (.456), followed by employee autonomy (.393), CSR (.304), transactional leadership (.247), WLB (.082), and technology (-.047). According to the classification results the model had an overall accuracy rate of 80.9%. The tables below reported the results on the full discriminant model for Gen Y employees.
Table 4-7 Group Statistics
Mean (4.8901) Mean Std. Deviation
.00 L_TF_All 3.7493 1.40400
Total L_TF_All 4.7836 1.43214
L_TS_All 4.4760 1.10244
CSR 5.1147 1.08265
WLB 4.5946 1.68134
Auto 5.1309 1.44108
Tech 5.3960 1.37742
Table 4-7a
Tests of Equality of Group Means
Wilks' Lambda F df1 df2 Sig.
Notes: TF_L indicates transformational leadership, TS_L indicates transactional leadership.
Table 4-7c Log Determinants
Mean (4.8901) Rank Log Determinant Box’ M F df1, df2 p-value
.00 6 1.924 152.441 7.093 21, 231006.440 < 0.001
1.00 6 -.749
Pooled within-groups 6 .823
The ranks and natural logarithms of determinants printed are those of the group covariance matrices.
Table 4-7d Eigenvalues
Function Eigenvalue % Of Variance Cumulative % Canonical Correlation
1 .686a 100.0 100.0 .638
a. First 1 canonical discriminant functions were used in the analysis.
Table 4-7e Wilks' Lambda
Test of Function(s) Wilks' Lambda Chi-square df Sig.
1 .593 152.982 6 <.001
Table 4-7f
Standardized Canonical Discriminant Function Coefficients Function
L_TF_All 1 .456
L_TS_All .247
CSR .304
WLB .082
Auto .393
Tech -.046
Table 4-7g
Canonical Discriminant Function Coefficients Function
L_TF_All 1 .392
L_TS_All .251
CSR .323
WLB .049
Auto .308
Tech -.036
(Constant) -6.264
Unstandardized coefficients
Table 4-7h
Functions at Group Centroids
Mean (4.8901) Function
.00 1 -1.019
1.00 .668
Unstandardized canonical discriminant functions evaluated at group means
Table 4-7i Classification Resultsa
Mean (4.8901) Predicted Group Membership
Total
a. 80.9% of original grouped cases correctly classified.
Discriminant Model Gen Z Employees
The third discriminant model tested only Gen Z employees (N = 133) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace. Test results indicated that the model was statistically significant [Box’s M = 49.153, F(21, 47685.017) = 2.220, p < .001; Eigen value = .802, Canonical Correlation = .667, Wilks’
Lambda = .555, Chi-square = 75.372, p < .001]. According to the standardized canonical discriminant function coefficients, transformational leadership impacted the most on the
employee engagement (.489), followed by CSR (.402), WLB (.290), employee autonomy (.251), transactional leadership (.061), and technology (-.033). According to the classification results the model had an overall accuracy rate of 84.2%. The tables below reported the results on the full discriminant model for Gen Y employees.
Table 4-7 Group Statistics
Mean (4.8901) Mean Std. Deviation
.00 L_TF_All 3.6698 1.39715
Total L_TF_All 4.7224 1.46367
L_TS_All 4.2857 1.04377
CSR 4.8772 1.14139
WLB 4.5504 1.47677
Auto 4.8972 1.54188
Tech 5.1253 1.56487
Table 4-7a
Tests of Equality of Group Means
Wilks' Lambda F df1 df2 Sig.
Pooled within-groups 6 .886
The ranks and natural logarithms of determinants printed are those of the group covariance matrices.
Table 4-7d Eigenvalues
Function Eigenvalue % Of Variance Cumulative % Canonical Correlation
1 .802a 100.0 100.0 .667
a. First 1 canonical discriminant functions were used in the analysis.
Table 4-7e Wilks' Lambda
Test of Function(s) Wilks' Lambda Chi-square df Sig.
1 .555 75.372 6 <.001
Table 4-7f
Standardized Canonical Discriminant Function Coefficients Function
L_TF_All 1 .489
L_TS_All .061
CSR .402
WLB .290
Auto .251
Tech .033
Table 4-7g
Canonical Discriminant Function Coefficients Function
L_TF_All 1 .415
L_TS_All .063
CSR .414
WLB .206
Auto .188
Tech .023
(Constant) -6.220
Unstandardized coefficients
Table 4-7h
Functions at Group Centroids
Mean (4.8901) Function
.00 1 -1.075
1.00 .735
Unstandardized canonical discriminant functions evaluated at group means
Table 4-7i Classification Resultsa,b
Mean (4.8901) Predicted Group Membership
Total
.00 1.00
Cases Selected Original Count .00 42 12 54
1.00 9 70 79
% .00 77.8 22.2 100.0
1.00 11.4 88.6 100.0
Cases Not Selected Original Count .00 104 47 151
1.00 29 221 250
% .00 68.9 31.1 100.0
1.00 11.6 88.4 100.0
a. 84.2% of selected original grouped cases correctly classified.
Logistic Regression Model Results Logistic Regression all data (N = 534)
The first logistic regression model tested all data (N = 534) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy,
Technology to estimate the dependent variable, that is, employee engagement in the workplace.
The model was deemed accurate at 82.2% classification Accuracy. The model was also found to be statistically significant as [Chi-square = 266.820, p < 0.01; -2 Log likelihood = 444.403, Cox
& Snell R2 = .393, Nagelkerke R2 = .534]. Transformational Leadership, CSR, WLB and Autonomy were significantly related to Engagement (p < 0.01), while Technology and
Transactional Leadership factor showed no statistical significance. The tables below reported the results on the full logistic regression model for all data.
Table 4-8
Logistic Regression Model Results for All Data
B S.E. Wald df Sig. Exp(B)
a. Variable(s) entered on step 1: L_TF_All, L_TS_All, CSR, WLB, Auto, Tech.
Logistic Regression Gen X Employees (N = 87)
The second logistic regression model tested Gen X employees (N = 87) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace. The model was deemed accurate at 94.3% classification Accuracy. The model was also found to be statistically significant as Chi-square = 77.253, p < 0.01; -2 Log likelihood = 30.518, Cox & Snell R2 = .589, Nagelkerke R2 = .829. Transformational Leadership, CSR, WLB and Autonomy were significantly related to Engagement (p < 0.01), while Technology was marginally related and Transactional Leadership factor showed no statistical significance. The tables below reported the results on the full logistic regression model for Gen X employees.
Table 4-9
-2 Log likelihood Cox & Snell R Square Nagelkerke R Square
30.518a .589 .829
Overall model accuracy is 94.3%.
Table 4-9b
Logistic Regression Results for Gen X
B S.E. Wald df Sig. Exp(B)
a. Variable(s) entered on step 1: L_TF_All, L_TS_All, CSR, WLB, Auto, Tech.
Logistic Regression Gen Y Employees (N = 298)
The third logistic regression model tested only Gen Y (N = 298) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace. The model was deemed accurate at 80.9% classification Accuracy. The model was also found to be statistically significant as Chi-square = 146.839, p < 0.01; -2 Log likelihood = 253.283, Cox & Snell R2 = .389, Nagelkerke R2 = .527. Transformational Leadership, CSR, and Autonomy were significantly related to Engagement (p < 0.01), while Transactional Leadership was marginally related and WLB and Technology factors showed no statistical significance. The tables below reported the results on the full logistic regression model for Gen Y employees.
Table 4-10
a. Variable(s) entered on step 1: L_TF_All, L_TS_All, CSR, WLB, Auto, Tech.
Logistic Regression Gen Z Employees (N = 133)
The fourth logistic regression model tested Gen Z only (N = 133) and included six independent variables - transformational leadership, transactional leadership, CSR, WLB, Autonomy, Technology to estimate the dependent variable, that is, employee engagement in the workplace. The model was deemed accurate at 85.7% classification Accuracy. The model was also found to be statistically significant as Chi-square = 75.502, p < 0.01; -2 Log likelihood = 104.148, Cox & Snell R2 = .433, Nagelkerke R2 = .585. Transformational Leadership, CSR, and WLB were significantly related to Engagement (p < 0.01), while Autonomy, Technology and Transactional Leadership factor showed no statistical significance. The tables below reported the results on the full logistic regression model for Gen Z employees.
Table 4-11
Chi-square df Sig.
Step 1 Step 75.502 6 <.001
Block 75.502 6 <.001
Model 75.502 6 <.001
Table 4-11a -2 Log likelihood Cox & Snell R
Square Nagelkerke R Square
104.148a .433 .585
Overall accuracy of this model is 85.7%
Table 4-11b
Logistic Regression Results for Gen Z
B S.E. Wald df Sig. Exp(B)
L_TF_All .772 .309 6.244 1 .012 2.165
L_TS_All .085 .356 .057 1 .811 1.089
CSR .854 .327 6.797 1 .009 2.348
WLB .479 .210 5.200 1 .023 1.614
Auto .263 .225 1.360 1 .244 1.301
Tech -.016 .206 .006 1 .938 .984
Constant -11.056 2.249 24.176 1 <.001 .000
a. Variable(s) entered on step 1: L_TF_All, L_TS_All, CSR, WLB, Auto, Tech.
Cluster Model Results
Cluster Model Results for all data (N = 534)
The first cluster model was run using all data. The cluster model produced two clusters in which one has 205 cases (38.4%) while the other has 329 (61.6%). The results show the Engagement4 was the most important factor to cluster the data into two groups, followed by L_TF_All, CSR, Auto, L_TS_All, Tech, and WLB.
Category Silhouette measure of cohesion and separation V3
1 0.432 0.4
Cluster percent(values) percent(values) V4 V5
1 61.6105 329 1 61.61048689138577
2 38.3895 205 2 38.38951310861423
Predictor Importance Results
Nodes Importance Importance V4 V5
WLB 0.058 0.0580 WLB 0.0580
Tech 0.1521 0.1521 Tech 0.1521
L_TS_All 0.187 0.1870 L_TS_All 0.1870
Auto 0.2562 0.2562 Auto 0.2562
CSR 0.2873 0.2873 CSR 0.2873
L_TF_All 0.4351 0.4351 L_TF_All 0.4351
Engage4 1 1 Mean (4.8901) 1
Model Summary
V1 V
2 V3 Cell
Numeric1 mean V6 V7 V8 V9 V10 V11 V12
2 1 Label yes
1 10 Inputs no Mean 4.95 0.0580 WLB 4.95 WLB 0.0580
2 10 Inputs no Mean 4.21 0.0580 WLB 4.21 WLB 0.0580
1 1 Label yes
1 4 Inputs no Most
Frequent Category
1.00
(100.0%) 1.0 Engage4 1.00
(100.0%) Engage4 1.0
2 5 Inputs no Mean 3.68 0.4350 L_TF_All 3.68 L_TF_All 0.4350
1 5 Inputs no Mean 5.44 0.4350 L_TF_All 5.44 L_TF_All 0.4350
2 6 Inputs no Mean 4.35 0.2873 CSR 4.35 CSR 0.2873
2 4 Inputs no Most
Frequent Category
0.00
(100.0%) 1.0 Engage4 0.00
(100.0%) Engage4 1.0
1 8 Inputs no Mean 4.73 0.1869 L_TS_All 4.73 L_TS_All 0.1869
2 9 Inputs no Mean 4.72 0.1520 Tech 4.72 Tech 0.1520
1 9 Inputs no Mean 5.80 0.1520 Tech 5.80 Tech 0.1520
1 3 Size yes (329) 61.6% (329) 61.6%
1 6 Inputs no Mean 5.48 0.2873 CSR 5.48 CSR 0.2873
2 7 Inputs no Mean 4.17 0.2562 Auto 4.17 Auto 0.2562
2 3 Size yes (205) 38.4% (205) 38.4%
1 7 Inputs no Mean 5.63 0.2562 Auto 5.63 Auto 0.2562
2 8 Inputs no Mean 3.83 0.1869 L_TS_All 3.83 L_TS_All 0.1869
1 2 Description yes 2 2 Description yes
Cluster Model for Gen X Employees (N = 87)
The second cluster model was run using Gen X employees only. The cluster model produced two clusters in which one has 27 cases (31%) while the other has 60 (69%). The results show the Engagement4 was the most important factor to cluster the data into two groups, followed by L_TF_All, WLB, CSR, Auto, L_TS_All, and Tech.
Category Silhouette measure of cohesion and separation V3
1 0.4959 0.5
Cluster percent(values) percent(values) V4 V5
1 31.0345 27 1 31.03448275862069
2 68.9655 60 2 68.96551724137932
Predictor Importance Results
Predictor Importance Results