********************************
* General SEM analysis results *
********************************

General project information
---------------------------

Version of WarpPLS used: 7.0
License holder: Jorge Alcaraz
Type of license: Individual license
License start date: 13-Oct-2021
License end date: 13-Oct-2022
Project path (directory): C:\Users\Jorge Luis Garca\Dropbox\Articulos en proceso\Olguin\Ruben\Integrador\Supplementary material\
Project file: Structural equation model.prj
Last changed: 21-Jun-2022 09:26:55
Last saved: 21-Jun-2022 09:29:52
Raw data path (directory): C:\Users\ruben\Documents\SEM_2017\Article\Articulo good ejecucin\Modelo\
Raw data file: DATOS1.xlsx


Model fit and quality indices
-----------------------------

Average path coefficient (APC)=0.443, P<0.001
Average R-squared (ARS)=0.739, P<0.001
Average adjusted R-squared (AARS)=0.733, P<0.001
Average block VIF (AVIF)=3.552, acceptable if <= 5, ideally <= 3.3
Average full collinearity VIF (AFVIF)=4.982, acceptable if <= 5, ideally <= 3.3
Tenenhaus GoF (GoF)=0.769, small >= 0.1, medium >= 0.25, large >= 0.36
Sympson's paradox ratio (SPR)=1.000, acceptable if >= 0.7, ideally = 1
R-squared contribution ratio (RSCR)=1.000, acceptable if >= 0.9, ideally = 1
Statistical suppression ratio (SSR)=1.000, acceptable if >= 0.7
Nonlinear bivariate causality direction ratio (NLBCDR)=1.000, acceptable if >= 0.7


General model elements
----------------------

Missing data imputation algorithm: Arithmetic Mean Imputation
Outer model analysis algorithm: PLS Regression
Default inner model analysis algorithm: Warp3
Multiple inner model analysis algorithms used? No
Resampling method used in the analysis: Stable3
Number of data resamples used: 100
Number of cases (rows) in model data: 79
Number of latent variables in model: 4
Number of indicators used in model: 12
Number of iterations to obtain estimates: 5
Range restriction variable type: None
Range restriction variable: None
Range restriction variable min value: 0.000
Range restriction variable max value: 0.000
Only ranked data used in analysis? No


**********************************
* Path coefficients and P values *
**********************************

Path coefficients
-----------------

 	Plan	Ejec	Control	Benefi

Ejec	0.762	
Control	0.343	0.618	
Benefi	0.010	0.504	0.423	


P values
--------

 	Plan	Ejec	Control	Benefi

Ejec	<0.001	
Control	<0.001	<0.001	
Benefi	0.464	<0.001	<0.001	



*****************************************
* Standard errors for path coefficients *
*****************************************

 	Plan	Ejec	Control	Benefi

Ejec	0.089	
Control	0.101	0.093	
Benefi	0.112	0.096	0.099	



**************************************
* Effect sizes for path coefficients *
**************************************

 	Plan	Ejec	Control	Benefi

Ejec	0.580	
Control	0.276	0.541	
Benefi	0.008	0.444	0.369	



****************************************
* Combined loadings and cross-loadings *
****************************************

 	Plan	Ejec	Control	Benefi	Type (a	SE	P value
lv_Comp	0.838	0.270	-0.145	-0.113	Reflect	0.087	<0.001
lv_Inve	0.898	-0.195	0.165	-0.029	Reflect	0.085	<0.001
lv_Entr	0.913	-0.056	-0.029	0.133	Reflect	0.085	<0.001
lv_Inte	0.135	0.867	0.413	-0.505	Reflect	0.086	<0.001
lv_Gest	0.253	0.871	-0.580	0.038	Reflect	0.086	<0.001
lv_Prod	0.070	0.854	0.508	-0.181	Reflect	0.087	<0.001
lv_Dist	-0.517	0.767	-0.373	0.729	Reflect	0.089	<0.001
lv_Inno	0.273	0.003	0.915	0.051	Reflect	0.085	<0.001
lv_Disp	-0.064	0.318	0.893	-0.232	Reflect	0.086	<0.001
lv_Gest	-0.221	-0.331	0.868	0.186	Reflect	0.086	<0.001
lv_BC	-0.000	-0.103	0.198	0.957	Reflect	0.084	<0.001
lv_BE	0.000	0.103	-0.198	0.957	Reflect	0.084	<0.001

Notes: Loadings are unrotated and cross-loadings are oblique-rotated. SEs and P values are for loadings. P values < 0.05 are desirable for reflective indicators.


***************************************************
* Normalized combined loadings and cross-loadings *
***************************************************

 	Plan	Ejec	Control	Benefi
lv_Comp	0.600	0.303	-0.163	-0.127
lv_Inve	0.614	-0.200	0.169	-0.030
lv_Entr	0.596	-0.063	-0.033	0.149
lv_Inte	0.125	0.555	0.385	-0.470
lv_Gest	0.191	0.577	-0.437	0.029
lv_Prod	0.095	0.543	0.689	-0.246
lv_Dist	-0.400	0.598	-0.289	0.564
lv_Inno	0.394	0.005	0.551	0.073
lv_Disp	-0.067	0.332	0.561	-0.243
lv_Gest	-0.174	-0.261	0.583	0.146
lv_BC	-0.000	-0.115	0.220	0.567
lv_BE	0.000	0.097	-0.186	0.580

Note: Loadings are unrotated and cross-loadings are oblique-rotated, both after separate Kaiser normalizations.


***************************************
* Pattern loadings and cross-loadings *
***************************************

 	Plan	Ejec	Control	Benefi
lv_Comp	0.831	0.270	-0.145	-0.113
lv_Inve	0.941	-0.195	0.165	-0.029
lv_Entr	0.878	-0.056	-0.029	0.133
lv_Inte	0.135	0.843	0.413	-0.505
lv_Gest	0.253	1.165	-0.580	0.038
lv_Prod	0.070	0.498	0.508	-0.181
lv_Dist	-0.517	0.856	-0.373	0.729
lv_Inno	0.273	0.003	0.634	0.051
lv_Disp	-0.064	0.318	0.869	-0.232
lv_Gest	-0.221	-0.331	1.190	0.186
lv_BC	-0.000	-0.103	0.198	0.871
lv_BE	0.000	0.103	-0.198	1.042

Note: Loadings and cross-loadings are oblique-rotated.


**************************************************
* Normalized pattern loadings and cross-loadings *
**************************************************

 	Plan	Ejec	Control	Benefi
lv_Comp	0.930	0.303	-0.163	-0.127
lv_Inve	0.965	-0.200	0.169	-0.030
lv_Entr	0.986	-0.063	-0.033	0.149
lv_Inte	0.125	0.785	0.385	-0.470
lv_Gest	0.191	0.878	-0.437	0.029
lv_Prod	0.095	0.676	0.689	-0.246
lv_Dist	-0.400	0.662	-0.289	0.564
lv_Inno	0.394	0.005	0.916	0.073
lv_Disp	-0.067	0.332	0.909	-0.243
lv_Gest	-0.174	-0.261	0.938	0.146
lv_BC	-0.000	-0.115	0.220	0.969
lv_BE	0.000	0.097	-0.186	0.978

Note: Loadings and cross-loadings shown are after oblique rotation and Kaiser normalization.


*****************************************
* Structure loadings and cross-loadings *
*****************************************

 	Plan	Ejec	Control	Benefi
lv_Comp	0.838	0.659	0.666	0.611
lv_Inve	0.898	0.646	0.718	0.631
lv_Entr	0.913	0.701	0.742	0.685
lv_Inte	0.718	0.867	0.795	0.733
lv_Gest	0.682	0.871	0.706	0.744
lv_Prod	0.707	0.854	0.809	0.766
lv_Dist	0.414	0.767	0.611	0.716
lv_Inno	0.806	0.805	0.915	0.791
lv_Disp	0.701	0.810	0.893	0.769
lv_Gest	0.637	0.717	0.868	0.739
lv_BC	0.716	0.841	0.844	0.957
lv_BE	0.676	0.842	0.800	0.957

Note: Loadings and cross-loadings are unrotated.


****************************************************
* Normalized structure loadings and cross-loadings *
****************************************************

 	Plan	Ejec	Control	Benefi
lv_Comp	0.600	0.471	0.476	0.437
lv_Inve	0.614	0.442	0.491	0.432
lv_Entr	0.596	0.458	0.485	0.447
lv_Inte	0.460	0.555	0.510	0.469
lv_Gest	0.452	0.577	0.468	0.493
lv_Prod	0.450	0.543	0.515	0.487
lv_Dist	0.323	0.598	0.477	0.558
lv_Inno	0.485	0.484	0.551	0.476
lv_Disp	0.440	0.508	0.561	0.483
lv_Gest	0.428	0.481	0.583	0.496
lv_BC	0.424	0.498	0.500	0.567
lv_BE	0.410	0.510	0.485	0.580

Note: Loadings and cross-loadings shown are unrotated and after Kaiser normalization.


*********************
* Indicator weights *
*********************

 	Plan	Ejec	Control	Benefi	Type (a	SE	P value	VIF	WLS	ES
lv_Comp	0.358	0.000	0.000	0.000	Reflect	0.101	<0.001	1.784	1	0.300
lv_Inve	0.383	0.000	0.000	0.000	Reflect	0.100	<0.001	2.571	1	0.344
lv_Entr	0.390	0.000	0.000	0.000	Reflect	0.100	<0.001	2.777	1	0.356
lv_Inte	0.000	0.307	0.000	0.000	Reflect	0.102	0.002	2.454	1	0.266
lv_Gest	0.000	0.308	0.000	0.000	Reflect	0.102	0.002	2.332	1	0.268
lv_Prod	0.000	0.302	0.000	0.000	Reflect	0.103	0.002	2.275	1	0.258
lv_Dist	0.000	0.271	0.000	0.000	Reflect	0.104	0.005	1.661	1	0.208
lv_Inno	0.000	0.000	0.383	0.000	Reflect	0.100	<0.001	2.771	1	0.351
lv_Disp	0.000	0.000	0.374	0.000	Reflect	0.100	<0.001	2.437	1	0.334
lv_Gest	0.000	0.000	0.363	0.000	Reflect	0.101	<0.001	2.052	1	0.315
lv_BC	0.000	0.000	0.000	0.523	Reflect	0.096	<0.001	3.230	1	0.500
lv_BE	0.000	0.000	0.000	0.523	Reflect	0.096	<0.001	3.230	1	0.500

Notes: P values < 0.05 and VIFs < 2.5 are desirable for formative indicators; VIF = indicator variance inflation factor;
  WLS = indicator weight-loading sign (-1 = Simpson's paradox in l.v.); ES = indicator effect size.


********************************
* Latent variable coefficients *
********************************

R-squared coefficients
----------------------

Plan	Ejec	Control	Benefi
 	0.580	0.817	0.821

Adjusted R-squared coefficients
-------------------------------

Plan	Ejec	Control	Benefi
 	0.575	0.812	0.814

Composite reliability coefficients
----------------------------------

Plan	Ejec	Control	Benefi
0.914	0.906	0.921	0.956

Cronbach's alpha coefficients
---------------------------

Plan	Ejec	Control	Benefi
0.859	0.861	0.872	0.908

Average variances extracted
---------------------------

Plan	Ejec	Control	Benefi
0.781	0.707	0.796	0.915

Full collinearity VIFs
----------------------

Plan	Ejec	Control	Benefi
2.922	5.847	5.924	5.236

Q-squared coefficients
----------------------

Plan	Ejec	Control	Benefi
 	0.582	0.816	0.820

Minimum and maximum values
--------------------------

Plan	Ejec	Control	Benefi
-2.802	-2.733	-2.468	-2.729
1.740	1.802	1.667	1.419

Medians (top) and modes (bottom)
--------------------------------

Plan	Ejec	Control	Benefi
0.243	0.191	0.154	0.091
-2.802	0.344	0.331	0.225

Skewness (top) and exc. kurtosis (bottom) coefficients
------------------------------------------------------

Plan	Ejec	Control	Benefi
-0.662	-0.619	-0.261	-0.623
-0.091	-0.073	-0.700	-0.374

Tests of unimodality: Rohatgi-Szkely (top) and Klaassen-Mokveld-van Es (bottom)
--------------------------------------------------------------------------------

Plan	Ejec	Control	Benefi
Yes	Yes	Yes	Yes
Yes	Yes	Yes	Yes

Tests of normality: JarqueBera (top) and robust JarqueBera (bottom)
---------------------------------------------------------------------

Plan	Ejec	Control	Benefi
Yes	Yes	Yes	Yes
No	No	Yes	Yes


***************************************************
* Correlations among latent variables and errors *
***************************************************

Correlations among l.vs. with sq. rts. of AVEs
----------------------------------------------

 	Plan	Ejec	Control	Benefi
Plan	0.884	0.756	0.803	0.727
Ejec	0.756	0.841	0.872	0.879
Control	0.803	0.872	0.892	0.859
Benefi	0.727	0.879	0.859	0.957

Note: Square roots of average variances extracted (AVEs) shown on diagonal.


P values for correlations
-------------------------

 	Plan	Ejec	Control	Benefi
Plan	1.000	<0.001	<0.001	<0.001
Ejec	<0.001	1.000	<0.001	<0.001
Control	<0.001	<0.001	1.000	<0.001
Benefi	<0.001	<0.001	<0.001	1.000

Correlations among l.v. error terms with VIFs
---------------------------------------------

 	(e)Ejec	(e)Cont	(e)Bene
(e)Ejec	1.001	-0.018	0.029
(e)Cont	-0.018	1.000	0.010
(e)Bene	0.029	0.010	1.001

Notes: Variance inflation factors (VIFs) shown on diagonal. Error terms included (a.k.a. residuals) are for endogenous l.vs.


P values for correlations
-------------------------

 	(e)Ejec	(e)Cont	(e)Bene
(e)Ejec	1.000	0.873	0.802
(e)Cont	0.873	1.000	0.930
(e)Bene	0.802	0.930	1.000


************************************
* Block variance inflation factors *
************************************

 	Plan	Ejec	Control	Benefi


Control	2.273	2.273	
Benefi	3.249	4.328	5.637	


Note: These VIFs are for the latent variables on each column (predictors), with reference to the latent variables on each row (criteria).


******************************
* Indirect and total effects *
******************************

Indirect effects for paths with 2 segments
------------------------------
 	Plan	Ejec	Control	Benefi


Control	0.471	
Benefi	0.529	0.262	


Number of paths with 2 segments
------------------------------
 	Plan	Ejec	Control	Benefi


Control	1	
Benefi	2	1	


P values of indirect effects for paths with 2 segments
------------------------------
 	Plan	Ejec	Control	Benefi


Control	<0.001	
Benefi	<0.001	<0.001	


Standard errors of indirect effects for paths with 2 segments
------------------------------
 	Plan	Ejec	Control	Benefi


Control	0.069	
Benefi	0.096	0.073	


Effect sizes of indirect effects for paths with 2 segments
------------------------------
 	Plan	Ejec	Control	Benefi


Control	0.379	
Benefi	0.395	0.231	



Indirect effects for paths with 3 segments
------------------------------
 	Plan	Ejec	Control	Benefi



Benefi	0.199	


Number of paths with 3 segments
------------------------------
 	Plan	Ejec	Control	Benefi



Benefi	1	


P values of indirect effects for paths with 3 segments
------------------------------
 	Plan	Ejec	Control	Benefi



Benefi	<0.001	


Standard errors of indirect effects for paths with 3 segments
------------------------------
 	Plan	Ejec	Control	Benefi



Benefi	0.061	


Effect sizes of indirect effects for paths with 3 segments
------------------------------
 	Plan	Ejec	Control	Benefi



Benefi	0.149	



Sums of indirect effects
------------------------------
 	Plan	Ejec	Control	Benefi


Control	0.471	
Benefi	0.728	0.262	


Number of paths for indirect effects
------------------------------
 	Plan	Ejec	Control	Benefi


Control	1	
Benefi	3	1	


P values for sums of indirect effects
------------------------------
 	Plan	Ejec	Control	Benefi


Control	<0.001	
Benefi	<0.001	<0.001	


Standard errors for sums of indirect effects
------------------------------
 	Plan	Ejec	Control	Benefi


Control	0.069	
Benefi	0.090	0.073	


Effect sizes for sums of indirect effects
------------------------------
 	Plan	Ejec	Control	Benefi


Control	0.379	
Benefi	0.544	0.231	



Total effects
------------------------------
 	Plan	Ejec	Control	Benefi

Ejec	0.762	
Control	0.814	0.618	
Benefi	0.739	0.766	0.423	


Number of paths for total effects
------------------------------
 	Plan	Ejec	Control	Benefi

Ejec	1	
Control	2	1	
Benefi	4	2	1	


P values for total effects
------------------------------
 	Plan	Ejec	Control	Benefi

Ejec	<0.001	
Control	<0.001	<0.001	
Benefi	<0.001	<0.001	<0.001	


Standard errors for total effects
------------------------------
 	Plan	Ejec	Control	Benefi

Ejec	0.089	
Control	0.088	0.093	
Benefi	0.090	0.089	0.099	


Effect sizes for total effects
------------------------------
 	Plan	Ejec	Control	Benefi

Ejec	0.580	
Control	0.655	0.541	
Benefi	0.551	0.675	0.369	



*************************************
* Causality assessment coefficients *
*************************************

Path-correlation signs
----------------------

 	Plan	Ejec	Control	Benefi

Ejec	1	
Control	1	1	
Benefi	1	1	1	


Notes: path-correlation signs; negative sign (i.e., -1) = Simpson's paradox.

R-squared contributions
-----------------------

 	Plan	Ejec	Control	Benefi

Ejec	0.580	
Control	0.276	0.541	
Benefi	0.008	0.444	0.369	


Notes: R-squared contributions of predictor lat. vars.; columns = predictor lat. vars.; rows = criteria lat. vars.; negative sign = reduction in R-squared.

Path-correlation ratios
-----------------------

 	Plan	Ejec	Control	Benefi

Ejec	1.000	
Control	0.425	0.707	
Benefi	0.014	0.572	0.485	


Notes: absolute path-correlation ratios; ratio > 1 indicates statistical suppression; 1 < ratio <= 1.3: weak suppression; 1.3 < ratio <= 1.7: medium; 1.7 < ratio: strong.

Path-correlation differences
----------------------------

 	Plan	Ejec	Control	Benefi

Ejec	0.000	
Control	0.463	0.256	
Benefi	0.736	0.377	0.449	


Note: absolute path-correlation differences.

P values for path-correlation differences
-----------------------------------------

 	Plan	Ejec	Control	Benefi

Ejec	1.000	
Control	<0.001	0.008	
Benefi	<0.001	<0.001	<0.001	


Note: P values for absolute path-correlation differences.

Warp2 bivariate causal direction ratios
---------------------------------------

 	Plan	Ejec	Control	Benefi

Ejec	1.005	
Control	1.036	1.001	
Benefi	1.005	1.001	0.985	


Notes: Warp2 bivariate causal direction ratios; ratio > 1 supports reversed link; 1 < ratio <= 1.3: weak support; 1.3 < ratio <= 1.7: medium; 1.7 < ratio: strong.

Warp2 bivariate causal direction differences
--------------------------------------------

 	Plan	Ejec	Control	Benefi

Ejec	0.004	
Control	0.029	0.001	
Benefi	0.003	0.001	0.013	


Note: absolute Warp2 bivariate causal direction differences.

P values for Warp2 bivariate causal direction differences
---------------------------------------------------------

 	Plan	Ejec	Control	Benefi

Ejec	0.487	
Control	0.399	0.497	
Benefi	0.488	0.496	0.455	


Note: P values for absolute Warp2 bivariate causal direction differences.

Warp3 bivariate causal direction ratios
---------------------------------------

 	Plan	Ejec	Control	Benefi

Ejec	1.010	
Control	1.040	1.002	
Benefi	0.989	1.000	0.985	


Notes: Warp3 bivariate causal direction ratios; ratio > 1 supports reversed link; 1 < ratio <= 1.3: weak support; 1.3 < ratio <= 1.7: medium; 1.7 < ratio: strong.

Warp3 bivariate causal direction differences
--------------------------------------------

 	Plan	Ejec	Control	Benefi

Ejec	0.008	
Control	0.032	0.002	
Benefi	0.008	0.000	0.013	


Note: absolute Warp3 bivariate causal direction differences.

P values for Warp3 bivariate causal direction differences
---------------------------------------------------------

 	Plan	Ejec	Control	Benefi

Ejec	0.473	
Control	0.388	0.493	
Benefi	0.471	0.499	0.455	


Note: P values for absolute Warp3 bivariate causal direction differences.


