Table 12 Inner model path coefficient

Hypothesis	Path	Path coefficient1)	T-statistics2)	P-value3)	F-squared4)	Decision
H1	PGSP → PVFP	0.620	6.545	0.000	0.45	Significant
H2	PGSP → PRGSP	0.375	3.939	0.000	0.167	Significant
H3	PGSP → NRGSP	- 0.224	1.386	0.166	0.0527	Not significant
H4	PGSP → PPVFP	0.409	4.876	0.000	0.2416	Significant
H5	PGSP → NPVFP	0.266	2.444	0.015	0.1214	Significant
H6	PRGSP → PVFP	- 0.158	1.850	0.065	0.323	Not significant
H7	PRGSP → PPVFP	0.364	4.928	0.000	0.2014	Significant
H8	PRGSP → NPVFP	0.221	2.925	0.004	0.0881	Significant
H9	NRGSP → PVFP	0.240	2.353	0.019	0.0491	Significant
H10	NRGSP → PPVFP	-0.103	1.282	0.201	0.0180	Not significant
H11	NRGSP → NPVFP	0.667	6.509	0.000	0.8897	Significant
H12	PPVFP → PVFP	0.290	3.112	0.002	0.0811	Significant
H13	NPVFP → PVFP	-0.188	1.906	0.057	0.0286	Not significant
Hypothesis	Path		Path Coefficient	T-Statistics	P-Value	Decisions
H14	PGSP → PRGSP → PVFP		- 0.059	1.457	0.145	Not significant
H15	PGSP → NRGSP → PVFP		- 0.053	1.089	0.276	Not significant
H16	PGSP → PPVFP → PVFP		0.118	2.592	0.009	Significant
H17	PGSP → NPVFP → PVFP		- 0.049	1.476	0.140	Not significant
H18	PGSP → PRGSP → PPVFP → PVFP		0.0396	1.952	0.051	Not significant
H19	PGSP → PRGSP → NPVFP → PVFP		0.015	1.338	0.181	Not significant
H20	PGSP → NRGSP → PPVFP → PVFP		0.006	0.715	0.474	Not significant
H21	PRGSP → NRGSP → NPVFP → PVFP		0.028	1.010	0.312	Not significant

Path coefficient: In PLS path analysis the significance of the path coefficients can be tested by the bootstrap algorithm. The number of bootstrap subsamples were 5,000 based on (Hair et al., 2011). It can be stated that all of the paths are significant.
T statistic: The value was to indicate the dependent variable (Endogen variable) significant (>1.96) or not significant (<1.96).
P value: P value test. To conduct a test of the hypothesis that β > 0, at the 0.05 significance level (i.e., 1-95%), we calculate the one-tailed P value associated with the path coefficient.
F square: is effect size (> = 0.02 is small; > = 0.15 is medium; > = 0.35 is large). f-square measured variance explain each exogenous variable in the models.