The relationship between market orientation, learning orientation and business results of hotel and restaurant enterprises: A case study in Ho Chi Minh City - 26

Pattern Matrix a

Component
1	2	3	4	5
BE4	.867
BE2	.861
BE6	.839
BE5	.822
BE7	.808
BE1	.753
BE3	.702
MO6		.800
MO1		.780
MO5		.729
MO4		.715
MO8		.710
MO7		.709
MO3		.708
MO2		.705
BP4			.900
BP6			.892
BP1			.851
BP3			.796
BP5			.793
BP2			.719
LO4				.892
LO1				.851
LO5				.847
LO2				.821
LO3				.811

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IN2

				.885
				IN3	.842
				IN4	.817
				IN1	.743
				IN5	.720

Structure Matrix

Component
1	2	3	4	5
BE4	.873
BE2	.844
BE6	.819
BE3	.803
BE5	.803
BE7	.790
BE1	.748
MO6		.822
MO1		.791
MO5		.719
MO7		.710
MO2		.704
MO3		.704
MO4		.702
MO8		.701
BP4			.914
BP6			.881
BP1			.844
BP3			.814

BP5

		.794
		BP2	.750
		LO4		.897
		LO5		.861
		LO1		.852
		LO2		.800
		LO3		.795
		IN2			.865
		IN3			.862
		IN4			.849
		IN1			.727
		IN5			.706

C. CFA RESULTS

Regression Weights: (Group number 1 - Default model)

Estimate	SE	CR	P	Label
BE1	<---	BEIGE	1,000
BE2	<---	BEIGE	1,283	.073	17,487	***
BE3	<---	BEIGE	1,227	.076	16,123	***
BE4	<---	BEIGE	1,408	.079	17,834	***
BE5	<---	BEIGE	1,219	.075	16,185	***
BE6	<---	BEIGE	1,144	.078	14,608	***
BE7	<---	BEIGE	1,079	.078	13,764	***
MO8	<---	MO	1,000
MO7	<---	MO	1,029	.082	12,516	***
MO6	<---	MO	1,499	.100	15,007	***
MO5	<---	MO	.959	.084	11,401	***

Estimate	SE	CR	P	Label
MO4	<---	MO	.813	.073	11,067	***
MO3	<---	MO	.870	.078	11,145	***
MO2	<---	MO	.823	.070	11,715	***
MO1	<---	MO	1,321	.090	14,654	***
LO5	<---	WORRY	1,000
LO4	<---	WORRY	.957	.036	26,387	***
LO3	<---	WORRY	.861	.050	17,122	***
LO2	<---	WORRY	.856	.052	16,554	***
LO1	<---	WORRY	.963	.052	18,679	***
BP1	<---	BP	1,000
BP2	<---	BP	.866	.062	13,911	***
BP3	<---	BP	.981	.056	17,462	***
BP4	<---	BP	1,403	.061	22,827	***
BP5	<---	BP	.913	.056	16,271	***
BP6	<---	BP	1,356	.062	21,883	***
IN5	<---	PRINT	1,000
IN4	<---	PRINT	1,254	.086	14,521	***
IN3	<---	PRINT	1,460	.100	14,640	***
IN2	<---	PRINT	1,284	.090	14,285	***
IN1	<---	PRINT	1,009	.084	12,027	***

Standardized Regression Weights: (Group number 1 - Default model)

Estimate
BE1	<---	BEIGE	.706
BE2	<---	BEIGE	.838
BE3	<---	BEIGE	.793

Estimate
BE4	<---	BEIGE	.882
BE5	<---	BEIGE	.776
BE6	<---	BEIGE	.697
BE7	<---	BEIGE	.654
MO8	<---	MO	.615
MO7	<---	MO	.673
MO6	<---	MO	.877
MO5	<---	MO	.597
MO4	<---	MO	.575
MO3	<---	MO	.580
MO2	<---	MO	.618
MO1	<---	MO	.842
LO5	<---	WORRY	.792
LO4	<---	WORRY	.839
LO3	<---	WORRY	.733
LO2	<---	WORRY	.766
LO1	<---	WORRY	.849
BP1	<---	BP	.742
BP2	<---	BP	.613
BP3	<---	BP	.755
BP4	<---	BP	.962
BP5	<---	BP	.708
BP6	<---	BP	.922
IN5	<---	PRINT	.620
IN4	<---	PRINT	.832
IN3	<---	PRINT	.843

Estimate
IN2	<---	PRINT	.811
IN1	<---	PRINT	.640

Covariances: (Group number 1 - Default model)

Estimate	SE	CR	P	Label
BEIGE	<-->	MO	.067	.019	3,569	***
BEIGE	<-->	WORRY	.164	.030	5,459	***
BEIGE	<-->	PRINT	.142	.023	6.234	***
BEIGE	<-->	BP	.210	.029	7,252	***
MO	<-->	WORRY	.090	.028	3.171	.002
MO	<-->	PRINT	.087	.021	4,186	***
WORRY	<-->	PRINT	.214	.034	6,291	***
WORRY	<-->	BP	.304	.043	7,130	***
BP	<-->	PRINT	.245	.033	7,440	***
MO	<-->	BP	.149	.027	5,487	***
e2	<-->	e1	-.005	.018	-.257	.797
e4	<-->	e3	.020	.018	1,091	.275
e6	<-->	e7	.403	.033	12,124	***
e5	<-->	e6	-.008	.014	-.583	.560
e21	<-->	e22	.158	.031	5,085	***
e24	<-->	e25	-.082	.027	-3.079	.002

Correlations: (Group number 1 - Default model)

Estimate
BEIGE	<-->	MO	.184
BEIGE	<-->	WORRY	.293

Estimate
BEIGE	<-->	PRINT	.367
BEIGE	<-->	BP	.414
MO	<-->	WORRY	.162
MO	<-->	PRINT	.227
WORRY	<-->	PRINT	.366
WORRY	<-->	BP	.396
BP	<-->	PRINT	.460
MO	<-->	BP	.297
e2	<-->	e1	-.015
e4	<-->	e3	.076
e6	<-->	e7	.744
e5	<-->	e6	-.019
e21	<-->	e22	.390
e24	<-->	e25	-.227

Variances: (Group number 1 - Default model)

Estimate	SE	CR	P	Label
BEIGE	.369	.042	8,692	***
MO	.363	.050	7,330	***
WORRY	.846	.084	10,041	***
BP	.699	.073	9,620	***
PRINT	.406	.055	7,358	***
e2	.258	.022	11,649	***
e4	.210	.022	9,631	***
e5	.363	.027	13,492	***
e6	.510	.036	14,295	***

Estimate	SE	CR	P	Label
e7	.575	.039	14,714	***
e8	.596	.040	14,814	***
e9	.465	.032	14,439	***
e10	.244	.024	10,052	***
e11	.603	.040	14,908	***
e12	.485	.032	15,008	***
e13	.541	.036	14,986	***
e14	.398	.027	14,800	***
e15	.261	.023	11,563	***
e21	.503	.043	11,659	***
e23	.539	.039	13,710	***
e24	.437	.038	11,466	***
e25	.303	.033	9,062	***
e1	.372	.027	13,891	***
e3	.328	.027	12,212	***
e22	.326	.032	10,245	***
e29	.570	.038	14,953	***
e30	.871	.056	15,416	***
e31	.506	.034	14,876	***
e32	.110	.017	6,519	***
e33	.578	.038	15,118	***
e34	.227	.021	10,915	***
e35	.648	.044	14,637	***
e36	.283	.025	11,366	***
e37	.351	.032	10,941	***
e38	.349	.029	12,041	***

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