Table 8

Model's predictive power

ConstructItemTraditionalPrefabricationComplete
Q2predictRMSEVarianceQ2predictRMSEVarianceQ2predictRMSEVariance
ConstructItemPLS-SEMLMConstructItemPLS-SEMLMConstructItemPLS-SEMLM
IRSIR10.009−0.0031.5191.586−0.0670.0760.0471.1851.462−0.277−0.0120.0001.3971.470−0.074
IR30.0111.5341.776−0.2420.0381.3871.852−0.465−0.0161.4951.598−0.103
IR40.0671.5161.696−0.1800.0321.5871.894−0.307−0.0081.6271.649−0.022
IR5−0.0341.6501.6010.0490.0761.5321.681−0.1480.0021.6311.6140.017
IR6−0.0101.7061.908−0.2010.0361.7262.159−0.433−0.0071.7551.807−0.052
IR70.0031.7412.023−0.2820.0441.5571.811−0.253−0.0111.7181.784−0.065
IR80.0121.7671.989−0.2220.0201.8422.623−0.781−0.0111.8801.972−0.092
MSMS1−0.055−0.0401.6171.772−0.155−0.078−0.0671.3971.772−0.374−0.041−0.0301.5791.667−0.088
MS2−0.0151.6311.881−0.250−0.0541.4201.888−0.468−0.0241.6131.712−0.099
MS3−0.0441.9052.153−0.249−0.0451.4211.641−0.220−0.0221.7161.868−0.153
MS4−0.0521.7562.043−0.287−0.0561.5572.058−0.501−0.0321.6861.828−0.142
MS5−0.0331.8112.133−0.322−0.0671.3371.607−0.270−0.0311.6511.851−0.200
MS6−0.0171.7482.012−0.264−0.0691.5301.839−0.309−0.0391.6991.837−0.138
MS7−0.0521.8642.005−0.140−0.0571.7162.289−0.573−0.0241.7961.932−0.136
PHSPHS1−0.056−0.0261.5601.828−0.267−0.066−0.0501.5952.129−0.535−0.033−0.0271.5561.652−0.096
PHS2−0.0551.7662.145−0.378−0.0601.3631.572−0.210−0.0231.6031.732−0.129
PHS3−0.0461.6221.799−0.178−0.0571.6281.947−0.320−0.0251.6191.656−0.038
PSPS1−0.061−0.0511.4961.841−0.345−0.057−0.0541.6572.121−0.464−0.037−0.0261.5271.710−0.183
PS2−0.0651.4471.625−0.178−0.0781.3841.530−0.146−0.0331.3871.453−0.066
PS3−0.0231.7121.947−0.235−0.0251.3841.569−0.185−0.0261.5911.726−0.135
PS4−0.0211.6121.726−0.114−0.0161.6102.217−0.607−0.0171.6161.719−0.103
PS5−0.0411.5811.790−0.208−0.0481.3111.563−0.252−0.0241.4691.531−0.062
PS6−0.0571.8682.098−0.231−0.0441.5741.917−0.343−0.0241.7351.887−0.152
PS7−0.0441.9362.065−0.129−0.0641.1961.434−0.238−0.0271.6491.715−0.066
MHMH2−0.076−0.0441.3611.633−0.273−0.077−0.0871.4021.703−0.302−0.044−0.0221.3701.534−0.164
MH3−0.0541.5311.640−0.109−0.0311.5061.838−0.332−0.0231.5091.555−0.046
MH4−0.0531.6011.792−0.191−0.0511.6372.145−0.509−0.0241.6051.798−0.194
MH5−0.0562.0452.059−0.014−0.0451.5191.857−0.338−0.0271.8581.945−0.087
MH6−0.0381.7751.948−0.174−0.0571.7532.298−0.545−0.0441.7821.939−0.156
MH7−0.0611.7981.851−0.054−0.0471.3801.673−0.293−0.0321.6861.810−0.124
MH8−0.0501.9822.007−0.025−0.0461.2631.603−0.339−0.0301.7501.788−0.038
SEWEW0.2310.1780.9131.061−0.1480.033−0.0310.8791.029−0.1490.2310.1880.9110.989−0.077
SW0.2170.8120.905−0.0920.0481.0241.216−0.1920.2200.8930.967−0.074
PWPW10.1870.0481.2801.502−0.2220.001−0.0071.0231.251−0.2290.1990.1251.2181.317−0.099
PW20.1471.4571.516−0.0580.0261.2411.645−0.4050.1531.3521.470−0.117
PW30.0201.6021.704−0.102−0.0391.2431.551−0.3080.0771.4751.553−0.078
PW40.2271.2831.442−0.1590.0251.2611.477−0.2170.2071.2561.367−0.111
PW50.0991.3731.3100.062−0.0431.2081.324−0.1160.1151.3251.402−0.077
PW60.1491.5831.704−0.121−0.0131.3151.513−0.1980.1451.4881.592−0.104
CWCW10.0820.0641.5071.541−0.035−0.031−0.0371.0641.294−0.2310.1130.0881.3721.412−0.040
CW20.0011.6551.948−0.293−0.0401.3931.691−0.2980.0541.5651.663−0.098
CW30.0821.9222.131−0.209−0.0151.5431.968−0.4250.1061.7761.821−0.045

Note(s): Variance = The difference between PLS-SEM and LM RMSE (PLS-SEM RMSE – LM RMSE); RMSE = Root Mean Square Error; LM = Linear Regression Model

IRS: Industry-related stressors; MS: Management stressors; PHS: Physical Health and Safety Stressors; PS: Personal stressors; MH: Poor mental health

SEW: Socioemotional well-being; PW: Psychological well-being; CW: Cultural and religious well-being

Source(s): Authors' creation

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