Towards Sustainable Human Resources: How Generational Differences Impact Subjective Wellbeing in the Military?
Abstract
:1. Introduction
2. Materials and Methods
2.1. Developing Hypothesis
2.2. Sample and Data Collection
2.3. Measures
2.4. Method for Data Analysis
3. Results
3.1. Measurement and Structural Model Analysis Verification of Convergent Validity
3.2. Overall Fit for Models
3.3. Model 2 Construct Convergent Validity Assessment for Three Generations
3.4. Path Coefficients for Generations
3.4.1. Subjective Wellbeing for GenX
3.4.2. Subjective Wellbeing for Gen Y
3.4.3. Subjective Wellbeing for Gen Z
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
References
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Category | Description | Number of Respondents, N | Percentage, % | |
---|---|---|---|---|
Age | 18–25 | 336 | 37.8 | |
26–40 | 429 | 48.2 | ||
41–56 | 125 | 14.0 | ||
Length of service | Up to 5 years | 441 | 49.6 | |
6–15 | 278 | 31.2 | ||
16–25 | 153 | 17.2 | ||
More than 26 | 18 | 2.0 |
Construct (Endogenous Variable) | Exogenous Variables | Code | Factor Loading | Cronbach’s Alpha (CA) |
---|---|---|---|---|
PE | a2.1 | PE1 | 0.562 | 0.755 |
a2.3 | PE2 | 0.611 | ||
a2.5 | PE3 | 0.481 | ||
a2.9 | PE4 | 0.729 | ||
a2.6 | PE5 | 0.719 | ||
a2.8 | PE6 | 0.724 | ||
a2.10 | PE7 | 0.617 | ||
RP | a22_1 | RP1 | 0.848 | 0.833 |
a22_3 | RP2 | 0.693 | ||
a22_4 | RP3 | 0.699 | ||
a22_7 | RP4 | 0.592 | ||
a22_8 | RP5 | 0.668 | ||
AP | a28_1 | AP1 | 0.928 | 0.986 |
a28_2 | AP2 | 0.927 | ||
a28_3 | AP3 | 0.926 | ||
a28_4 | AP4 | 0.922 | ||
a28_5 | AP5 | 0.922 | ||
a28_6 | AP6 | 0.919 | ||
a28_7 | AP7 | 0.915 | ||
RL | a22_2 | RL1 | 0.706 | 0.761 |
a22_5 | RL2 | 0.751 | ||
a22_6 | RL3 | 0.630 | ||
EN | a29_1 | EN1 | 0.895 | 0.868 |
a29_2 | EN2 | 0.669 | ||
a29_3 | EN3 | 0.666 | ||
a29_4 | EN4 | 0.664 | ||
a29_5 | EN5 | 0.629 | ||
a29_6 | EN6 | 0.612 | ||
a29_7 | EN7 | 0.567 |
Construct | Index | Std. Loading | Unstd. Loading | S.E. | C.R. (t-Value) | p Value | SMC | CR | AVE |
---|---|---|---|---|---|---|---|---|---|
PE | PE4 | 0.635 | 0.803 | 0.050 | 16.173 | *** | 0.462 | 0.780 | 0.640 |
PE5 | 0.698 | 0.910 | 0.056 | 16.115 | *** | 0.456 | |||
PE6 | 0.675 | 1 | 0.528 | ||||||
PE7 | 0.550 | 0.812 | 0.055 | 14.727 | *** | 0.358 | |||
RP | RP1 | 0.746 | 0.868 | 0.041 | 21.315 | *** | 0.567 | 0.830 | 0.705 |
RP2 | 0.766 | 1 | 0.611 | ||||||
RP3 | 0.721 | 0.918 | 0.044 | 20.743 | *** | 0.527 | |||
RP4 | 0.694 | 0.855 | 0.046 | 18.611 | *** | 0.430 | |||
RP5 | 0.643 | 0.838 | 0.052 | 16.011 | *** | 0.347 | |||
AP | AP1 | 0.955 | 0.984 | 0.013 | 72.888 | *** | 0.913 | 0.976 | 0.923 |
AP2 | 0.957 | 1 | 0.916 | ||||||
AP3 | 0.96 | 1.003 | 0.011 | 88.768 | *** | 0.921 | |||
AP4 | 0.969 | 1.005 | 0.014 | 72.676 | *** | 0.939 | |||
AP5 | 0.935 | 0.957 | 0.016 | 61.333 | *** | 0.873 | |||
AP6 | 0.940 | 0.961 | 0.015 | 63.184 | *** | 0.884 | |||
AP7 | 0.933 | 0.950 | 0.016 | 59.959 | *** | 0.870 | |||
RL | RL1 | 0.701 | 0.873 | 0.045 | 19.513 | *** | 0.488 | 0.739 | 0.698 |
RL2 | 0.742 | 1.02 | 0.048 | 21.149 | *** | 0.668 | |||
RL3 | 0.783 | 1 | 0.619 | ||||||
EN | EN1 | 0.719 | 1.073 | 0.055 | 19.494 | *** | 0.517 | 0.854 | 0.679 |
EN2 | 0.745 | 0.941 | 0.049 | 19.044 | *** | 0.556 | |||
EN3 | 0.657 | 0.865 | 0.048 | 17.892 | *** | 0.430 | |||
EN4 | 0.730 | 1.092 | 0.058 | 18.699 | *** | 0.535 | |||
EN5 | 0.690 | 0.982 | 0.046 | 21.273 | *** | 0.472 | |||
EN6 | 0.706 | 1 | 0.498 | ||||||
EN7 | 0.585 | 0.801 | 0.044 | 18.145 | *** | 0.344 |
Parameter | All Generations | |||||
---|---|---|---|---|---|---|
Model 1 | Model 2 | |||||
RW 1 | Bias-Corrected 2 [Lower; Upper] | P 3 | RW 1 | Bias-Corrected 2 [Lower; Upper] | P 3 | |
AP <--- EN | 0.667 | [0.478; 0.819] | 0.004 | 0.660 | [0.467; 0.807] | 0.003 |
RL <--- RP | 0.516 | [0.355; 0.680] | 0.002 | 0.516 | [0.355; 0.681] | 0.002 |
RP <--- AP | 0.042 | [0.018; 0.067] | 0.001 | 0.043 | [0.020; 0.069] | 0.001 |
RP <--- EN | 0.340 | [0.24; 0.481] | 0.001 | 0.330 | [0.231; 0.466] | 0.001 |
SW <--- RP | −0.058 | [−0.286; 0.187] | 0.675 | −0.107 | [−0.341; 0.140] | 0.407 |
SW <--- EN | 0.180 | [0.032; 0.346] | 0.022 | 0.113 | [−0.036; 0.259] | 0.125 |
SW <--- AP | 0.028 | [−0.013; 0.069] | 0.172 | 0.028 | [−0.014; 0.071] | 0.192 |
SW <--- RL | 0.182 | [−0.061; 0.416] | 0.158 | 0.191 | [−0.055; 0.437] | 0.139 |
SW <--- PE | −0.220 | [−0.336; −0.113] | 0.002 | --- | ---- | ---- |
PE <--> EN | 0.164 | [0.478; 0.819] | 0.001 | --- | ---- | ---- |
Model fit | Recommended Value | All Generations | |
---|---|---|---|
Model 1 | Model 2 | ||
χ2 | Lower is better | 619.605 (p = 0.000) | 425.085 (p = 0.000) |
χ2/df | <3 | 2.093 (df = 296) | 2.085 (df = 204) |
RMSEA | <0.08 | 0.035 | 0.035 |
1 CI | [0.031; 0.039]1 | [0.030; 0.040]1 | |
TLI | >0.9 | 0.979 | 0.984 |
IFI | >0.9 | 0.982 | 0.987 |
CFI | >0.9 | 0.967 | 0.987 |
PNFI | Higher is better | 0.815 | 0.787 |
ECVI | Lower is better | 0.941 | 0.691 |
AIC | Lower is better | 837.605 | 615.085 |
BCC | Lower is better | 844.686 | 620.351 |
Sample Z (n = 336) | ||||
Latent Variable’s Code | Factor loading [Lower; Upper] | Cronbach’s Alpha | CR | AVE |
RL (3) | [0.533; 0.718] | 0.825 | 0.685 | 0.651 |
RP (5) | [0.411; 0.578] | 0.813 | 0.658 | 0.530 |
AP (7) | [0.943; 0.970] | 0.988 | 0.977 | 0.961 |
EN (7) | [0.408; 0.686] | 0.871 | 0.753 | 0.522 |
Sample Y (n = 429) | ||||
Latent Variable | Factor loading [Lower; Upper] | Cronbach’s Alpha | CR | AVE |
RL (3) | [0.574; 0.650] | 0.812 | 0.636 | 0.607 |
RP (5) | [0.610; 0.712] | 0.845 | 0.791 | 0.657 |
AP (7) | [0.910; 0.945] | 0.984 | 0.960 | 0.931 |
EN (7) | [0.607; 0.756] | 0.869 | 0.836 | 0.601 |
Sample X (n = 125) | ||||
Latent Variable | Factor loading [Lower; Upper] | Cronbach’s Alpha | CR | AVE |
RL (3) | [0.645; 0.685] | 0.728 | 0.700 | 0.661 |
RP (5) | [0.501; 0.743] | 0.820 | 0.789 | 0.658 |
AP (7) | [0.871; 0.965] | 0.983 | 0.960 | 0.931 |
EN (7) | [0.418; 0.791] | 0.853 | 0.842 | 0.608 |
Construct | Std. Weight | Unstd. Weight | S. E. | C.R. (t-Value) | p Value |
---|---|---|---|---|---|
AP <--- EN | 0.260 | 0.66 | 0.092 | 7.170 | *** |
RP <--- AP | 0.116 | 0.043 | 0.013 | 3.238 | 0.001 |
RP <--- EN | 0.352 | 0.33 | 0.038 | 8.588 | *** |
RL <--- RP | 0.589 | 0.516 | 0.038 | 13.636 | *** |
SW <--- RP | −0.522 | −0.107 | 0.093 | −1.156 | 0.248 |
SW <--- EN | 0.585 | 0.113 | 0.066 | 2.704 | 0.044 |
SW <--- AP | 0.368 | 0.028 | 0.023 | 1.232 | 0.218 |
SW <--- RL | 0.815 | 0.191 | 0.099 | 2.923 | 0.034 |
Construct | Std. Weight | Unstd. Weight | S. E. | C.R. (t-Value) | p Value |
---|---|---|---|---|---|
AP <--- EN | 0.201 | 0.479 | 0.233 | 2.055 | 0.040 |
RP <--- AP | 0.213 | 0.087 | 0.038 | 2.271 | 0.023 |
RP <--- EN | 0.353 | 0.342 | 0.104 | 3.297 | *** |
RL <--- RP | 0.427 | 0.267 | 0.076 | 3.506 | *** |
SW <--- RP | −0.078 | −0.025 | 0.137 | −0.179 | 0.858 |
SW <--- EN | 0.715 | 0.218 | 0.114 | 3.917 | *** |
SW <--- AP | −0.214 | −0.027 | 0.041 | −0.666 | 0.506 |
SW <--- RL | 0.671 | 0.337 | 0.21 | 2.609 | 0.018 |
Construct | Std. Weight | Unstd. Weight | S. E. | C.R. (t-Value) | p Value |
---|---|---|---|---|---|
AP<--- EN | 0.338 | 0.832 | 0.131 | 6.366 | *** |
RP <--- AP | 0.117 | 0.050 | 0.023 | 2.140 | 0.032 |
RP<--- EN | 0.243 | 0.255 | 0.062 | 4.083 | *** |
RL<--- RP | 0.676 | 0.553 | 0.052 | 10.727 | *** |
SW<--- RP | −0.617 | −0.105 | 0.117 | −0.902 | 0.367 |
SW<--- EN | 0.650 | 0.117 | 0.084 | 6.784 | *** |
SW<--- AP | 0.461 | 0.034 | 0.031 | 1.075 | 0.282 |
SW<--- RL | 0.651 | 0.136 | 0.141 | 2.967 | 0.024 |
Construct | Std. Weight | Unstd. Weight | S. E. | C.R. (t-Value) | p Value |
---|---|---|---|---|---|
AP <--- EN | 0.207 | 0.538 | 0.151 | 3.568 | *** |
RP <--- AP | 0.127 | 0.038 | 0.017 | 2.310 | 0.021 |
RP <--- EN | 0.480 | 0.375 | 0.053 | 7.131 | *** |
RL <--- RP | 0.524 | 0.540 | 0.071 | 7.646 | *** |
SW <--- RP | 0.333 | 0.107 | 0.193 | 0.553 | 0.580 |
SW <--- EN | 0.293 | 0.074 | 0.123 | 0.598 | 0.55 |
SW <--- AP | −0.096 | −0.009 | 0.038 | −0.245 | 0.807 |
SW <--- RL | 0.642 | 0.200 | 0.158 | 9.268 | *** |
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Smaliukiene, R.; Bekesiene, S. Towards Sustainable Human Resources: How Generational Differences Impact Subjective Wellbeing in the Military? Sustainability 2020, 12, 10016. https://doi.org/10.3390/su122310016
Smaliukiene R, Bekesiene S. Towards Sustainable Human Resources: How Generational Differences Impact Subjective Wellbeing in the Military? Sustainability. 2020; 12(23):10016. https://doi.org/10.3390/su122310016
Chicago/Turabian StyleSmaliukiene, Rasa, and Svajone Bekesiene. 2020. "Towards Sustainable Human Resources: How Generational Differences Impact Subjective Wellbeing in the Military?" Sustainability 12, no. 23: 10016. https://doi.org/10.3390/su122310016