Table 7 Predictive power assessment...

Table 7

Predictive power assessment

PLS-predict out-of-sample	Q² predict	PLS-SEM_ RMSE	PLS-SEM_MAE	LM_RMSE	LM_MAE	Error Dif. RMSE PLS-LM	Error diff. MAE PLS-LM	Absolute values of skewness
Assumption	0.146	0.931	0.762	0.912	0.734	0.019	0.028	−0.654
Proactivity	0.203	0.903	0.745	0.950	0.780	−0.047	−0.035	−0.407
Trend	0.317	0.836	0.687	0.862	0.699	−0.026	−0.012	−0.312
Autonomy	0.201	0.903	0.696	0.901	0.709	0.002	−0.013	−0.220
Recognition	0.381	0.793	0.638	0.829	0.658	−0.036	−0.020	−0.576
Support	0.374	0.799	0.640	0.796	0.636	0.003	0.004	−0.585
Time	0.313	0.839	0.674	0.864	0.703	−0.025	−0.029	−0.292
ECS	0.276	0.858	0.683	0.882	0.698	−0.024	−0.015	−0.484
ENS	0.122	0.944	0.749	0.966	0.756	−0.022	−0.007	−0.916
SOCS	0.260	0.867	0.705	0.864	0.707	0.003	−0.002	−0.469
	1^st. Step					2^rd. Step		3^nd. Step

PLS-predict out-of-sample	Q² predict	PLS-SEM_ RMSE	PLS-SEM_MAE	LM_RMSE	LM_MAE	Error Dif. RMSE PLS-LM	Error diff. MAE PLS-LM	Absolute values of skewness
Assumption	0.146	0.931	0.762	0.912	0.734	0.019	0.028	−0.654
Proactivity	0.203	0.903	0.745	0.950	0.780	−0.047	−0.035	−0.407
Trend	0.317	0.836	0.687	0.862	0.699	−0.026	−0.012	−0.312
Autonomy	0.201	0.903	0.696	0.901	0.709	0.002	−0.013	−0.220
Recognition	0.381	0.793	0.638	0.829	0.658	−0.036	−0.020	−0.576
Support	0.374	0.799	0.640	0.796	0.636	0.003	0.004	−0.585
Time	0.313	0.839	0.674	0.864	0.703	−0.025	−0.029	−0.292
ECS	0.276	0.858	0.683	0.882	0.698	−0.024	−0.015	−0.484
ENS	0.122	0.944	0.749	0.966	0.756	−0.022	−0.007	−0.916
SOCS	0.260	0.867	0.705	0.864	0.707	0.003	−0.002	−0.469
	1^st. Step					2^rd. Step		3^nd. Step

Note(s): PLS_predict: K = 4; n = 30; 1st. Step: Q² predict >0; 2nd. Step: error difference RMSE – PLS LM < 1 for most indicators; 3rd. Step: absolute value of skewness <1. Abbreviations: ECS: economic sustainability; ENS: environmental sustainability; SOCS: social sustainability; MAE: mean absolute error and PLS-LM: difference between the PLS-SEM model and the linear model (LM)

Source(s): Authors' own work

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