Perception of social prosperity in indigenous tourism destinations in Mexico: The mediator effect of competitiveness of the destinations

Figures & data

Figure 1. Research conceptual model.

CSC = Community Social Capital, PROSP = Social Prosperity, TDC = Tourism Destination Competitiveness.

Table 1. Sample location (communities) as indigenous tourism destinations

State	Indigenous tourism destination
Colima	La Becerrera El Carrizalillo
Estado de México	San Juan Teotihuacán
Guerrero	Grutas de Cacahuamilpa
Michoacán	San Juan Nuevo Cherán Isla Yunuén
Morelos	Amatlán de Quetzalcóatl Los Laureles
Oaxaca	Capulalpám
Puebla	Cuetzalan

Source. Self-made with data from RITA.

Table 2. Demographics data of the respondents

Gender	Total
Female	54
Male	49
Total	103
Marital Status
Married	71
Single	21
Other	10
Total	103
Education
High School/some college	28
Primary	26
Secondary	22
Bachelor’s Degree	17
Other	10
Total	103

Notes: Self-made with data from survey.

Figure 2. First reflective model without discriminating items.

*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001. Source: Self-made, results of SmartPLS 3.

Figure 3. Adjusted measurement model.

*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001. Source: Self-made, results of SmartPLS 3.

Table 3. Reliability and validity indexes

Latent variable	Internal Consistency Reliability		Convergent Validity		Average reliability of construct between Alpha and Pc
	Cronbach’s Alpha	rho_A	Ρс	AVE	%
CSC	0.719	0.725	0.842	0.639	0.791
PROSP	0.722	0.756	0.838	0.634	0.787
TDC	0.817	0.821	0.891	0.732	0.878

Notes: AVE (Average Variance Extracted), Ρс (Compound Reliability); rho_A,

% (average reliability).

Table 4. Crossed loads on the constructs with their observable variables

	CSC	PROSP	TDC
TRU	0.780
NRM	0.837
PoC	0.781
QoL		.854
DoW		.713
EVNP		.816
MoEVB			0.870
MoSCB			0.869
TDM			0.826

Notes: Self-made with results of SmartPLS analysis.

Table 5. Test of hypothetical relationship

Hypothetical Relationship	Β	t	f2	VIF	P-value	Hypotheses Supported
β1: CSC—TDC	0.676	2.957**	0.841	1.000	.003	Yes
β2: CSC—PROSP	−0.151	0.736ns	0.029	1.841	.4	No
β3: TDC—PROSP	0.849	2.846**	0.910	1.841	.005	Yes
Βind: CSC—TDC – PROSP	0.574	7.275**	-	-	.000	Yes

Notes: **p ≤ 0.01, ns: not significant, β- path coefficient, t- t value, p- p value, f2- effect size, VIF- variance inflation factor. Source: Self-made with results from SmartPLS 3.

Table 6. Values of Ǫ2 included

Total	SSO	SSE	Q2(1-SSE/SSO)
PROSP	166	98.838	0.404
TDC	249	167.547	0.327

Notes: Source: Self-made with results from the Blindfolding analysis with SmartPLS 3.

Table 7. Excluded Q 2 values

Total	SSO	SSE	1-SSE/SSO
TDC—PROSP	288	264.681338	0.080968
CSC—PROSP	255	161.64966	0.36608

Notes: Source: Self-made with results from the Blindfolding analysis with SmartPLS 3.

Table

Community Social Capital (CSC)		Tourism Destination Competitiveness (TDC)		Social Prosperity (PROSP)
Skewness	−0.630	−1.455 2.000		−0.944 0.510
Kurtosis	0.285
Media	7.575	7.92		7.656
Variance	1.246	1.347		1.687
TRUS	α = 0.837	NATR	α = 0.842	DoW	α = 0.840
λ1	0.555	λ36	0.446	λ76	0.801
λ2	0.812	λ37	0.652	λ77	0.794
λ3	0.530	λ38	0.767	λ78	0.602
λ4	0.734	λ39	0.82	λ79	0.512
λ5	0.794	λ40	0.768	QoL	α = 0.901
λ6	0.570	CULR	α = 0.672	λ80	0.547
λ7	0.524	λ41	0.475	λ81	0.546
λ8	0.440	λ42	0.698	λ82	0.684
λ9	0.451	λ43	0.656	λ83	0.742
NRMS	α = 0.845	λ44	0.384	λ84	0.783
λ10	0.670	λ45	0.493	λ85	0.373
λ11	0.633	DEVR	α = 0.791	λ86	0.658
λ12	0.762	λ46	0.378	λ87	0.729
λ13	0.718	λ47	0.507	λ88	0.479
λ14	0.604	λ48	0.480	EVNP	α = 0.792
λ15	0.599	λ49	0.548	λ89	0.568
λ16	0.690	λ50	0.701	λ90	0.655
SNW	α = 0.854	λ51	0.843	λ91	0.844
λ17	0.723	λ52	0.627	λ92	0.812
λ18	0.752	λ53	0.385
Community Social Capital (CSC)		Tourism Destination Competitiveness (TDC)
λ19	0.554	TDM	α = 0.893
λ20	0.569	λ54	0.708
λ21	0.356	λ55	0.687
λ22	0.771	λ56	0.619
λ23	0.772	λ57	0.773
λ24	0.360	λ58	0.691
λ25	0.593	λ59	0.772
λ26	0.517	λ60	0.791
λ27	0.276	λ61	0.698
PoC	α = 0.806	λ62	0.708
λ28	0.547	λ63	0.391
λ29	0.702	MoEVB	α = 0.775
λ30	0.509	λ64	0.238
λ31	0.653	λ65	0.384
λ32	0.317	λ66	0.403
Community Social Capital (CSC)		Tourism Destination Competitiveness (TDC)
λ33	0.661	λ67	0.784
λ34	0.053	λ68	0.749
λ35	0.361	λ69	0.621
		MoSCB	α = 0.834
		λ70	0.696
		λ71	0.611
		λ72	0.610
		λ73	0.753
		λ74	0.730
		λ75	0.739

Note: α= Cronbach´s alpha coefficient. Extraction Method: maximum likelihood; Rotation Method: Varimax with Kaiser Normalization. It used SPSS ver. 22.