Cronbach's Alpha Reliability Coefficient of Components of the Scale of Factors Affecting Investment Capital Attraction for Tourism in Ba Ria Vung Tau Province

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- Scale of components of factors affecting investment attraction for tourism

Results of Cronbach's alpha analysis of the components of the scale of influencing factors

The factors affecting the attraction of investment capital for tourism all have high Cronbach alpha coefficients of the scale (from 0.768 or higher) and the variables of this scale all have variable-total correlation coefficients greater than 0.3 (the smallest is 0.349). Therefore, the variables measuring these components are all used in the next EFA analysis.

Table 3.3 Cronbach's Alpha reliability coefficient of the components of the scale of factors affecting investment attraction for tourism in Ba Ria Vung Tau province

Scale Mean if Item Deleted	Scale Variance if Item Deleted	Corrected Item- Total Correlation	Cronbach's Alpha if Item Deleted
Institutional stability, investment laws and administrative reforms of the country (A)
A1 9.08 7.753 .505				.851
A2 10.43 6.609 .772				.728
A3 10.64 6.941 .747				.743
A4 9.63 7.358 .616				.801
Cronbach's Alpha 0.829
Macroeconomic stability and economic growth (B)
B1 6.63 3.616 .729				.734
B2 5.41 3.872 .592				.865
B3 6.13 3.352 .765				.694
Cronbach's Alpha 0.833
Policy to attract investment capital for tourism of Ba Ria - Vung Tau province (C)
C1 8.79 4.784 .726				.643
C2 9.46 6.076 .472				.777
C3 10.08 6.168 .438				.792
C4 8.47 4.658 .711				.650
Cronbach's Alpha 0.778
Advantages of natural resources and tourism resources of Ba Ria - Vung Tau province (D)
D1 10.03 6.161 .755				.730
D2 10.51 5.964 .768				.723
D3 11.39 7.922 .543				.827
D4 11.27 7.151 .559				.822
Cronbach's Alpha 0.826

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Infrastructure development of Ba Ria - Vung Tau province (E)

E1	9.30	5.124	.629	.679
E2	9.95	5,967	.502	.747
E3	10.29	5,956	.496	.750
E4	9.06	5,061	.654	.665
Cronbach's Alpha 0.768 Development of labor force, of science and technology level (F)
F1	9.97	7,893	.349	.859
F2	10.39	6.111	.771	.663
F3	10.29	5,640	.675	.710
F4	10.06	6.671	.680	.712

Cronbach's Alpha 0.795

Effectiveness of implemented tourism investment projects (G)

G1 G2 G3 G4

Cronbach's Alpha 0.806

9.63

10.22

9.65

9.35

5,773

7,305

8,652

7,143

.825

.551

.412

.742

.644

.793

.846

.705

3.2.3.4. Exploratory factor analysis EFA:

- Scale for evaluating investment attraction for tourism in Ba Ria Vung Tau province :

Through the data table below, we can see that only one factor was extracted at eigenvalue 2.463, the weighted variables are all greater than 0.50, so the observed variables are all important in the investment attraction factor. KMO coefficient = 0.770, the significance level of the test is 0 (sig = .000). The extracted variance is 61.572%, so EFA is appropriate. These observed variables all meet the requirements for the following analysis.

Table 3.4 Results of factor analysis of the assessment scale on attracting investment capital for tourism in Ba Ria Vung Tau province

Component Matrix a

Component
1
Impact on socio-economy (I1)	.859
Environmental impact (I2)	.629
Investment attraction results (I3)	.821
Investment Prospects (I4)	.809
KMO	.770
Eigenvalues	2,463
% of Variance	61,572
Cronbach's Alpha	.782

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- Scale of components of factors affecting investment attraction for tourism

EFA analysis results:

KMO and Bartlett's tests in factor analysis show that the KMO coefficient meets the requirements.

demand (0.854>0.5) with significance level of 0 (sig =.000) shows that EFA factor analysis is appropriate.

At Eigenvalues greater than 1 and with Principal components extraction method and Varimax rotation, factor analysis extracted 6 factors from 27 observed variables with extracted variance of 69.445% (greater than 50%) meeting the requirements.

Based on the analysis of the Rotated Component Matrix table(a), variable A1 is eliminated because it has a factor loading coefficient less than 0.5.

Table 3.5 Results of factor analysis of the components of the scale of influencing factors

impact on attracting investment capital for tourism in Ba Ria Vung Tau province

Rotated Component Matrix a

Component
1	2	3	4	5	6
Political security situation (A1)	.439	.490	.175	.294	.169	.225
Investment policy and law (A2)	.901	.191	.096	.054	.004	.026
Business Environment (A3)	.869	.113	.104	.120	.057	-.044
One-door cover (A4)	.669	.142	.044	.133	.046	.082
Microeconomic policy (B1)	.883	.084	.072	.047	.028	.058
GDP growth (B2)	.688	.066	-.024	.080	.120	.064
Economic management policy (B3)	.882	.116	.000	.078	.022	.038
Tourism planning (C1)	.010	.028	.009	.088	.887	.049
Investment promotion for tourism (C2)	.116	.094	.270	.112	.603	-.086
Surface Decompression Work (C3)	.093	.092	.046	.066	.619	.094
Flexibility in attracting investment (C4)	.015	.073	.028	.050	.886	.010
Marine tourism resources (D1)	.363	.746	.210	.142	.168	.177
Ecotourism Resources (D2)	.179	.819	.239	.082	.198	.029
Shopping mall and entertainment system (D3)	.147	.637	.087	.160	-.030	.156
Living environment (D4)	.208	.669	.153	.064	.066	-.066
Traffic system (E1)	.182	.169	.076	.766	.064	.143
Electrical and water systems (E2)	.027	.228	.104	.672	.085	.053
Waste treatment system (E3)	.226	.007	.097	.634	.065	.217

.048	.075	.235	.814	.124	-.026
General labor (F1)	-.090	.705	-.077	.087	.022	.299
High-quality work (F2)	.148	.315	.287	.212	.072	.784
Training base (F3)	.018	.233	.779	.174	.058	.417
Science and Technology Degree (F4)	.212	.221	.477	.262	.208	.548
Labor cost (G1)	-.002	.230	.812	.159	.067	.394
Infrastructure usage cost (G2)	.076	.036	.850	.122	.110	-.073
Industry Competition (G3)	.014	.102	.172	.070	-.036	.837
Business efficiency (G4)	.181	.235	.671	.258	.160	.413
KMO	.854
Eigenvalues	8,657	3,491	2.225	1,761	1,512	1.104
% of Variance	32,062	12,930	8,243	6,522	5.602	4,087

Palace of public finances (E4)

After eliminating variable A1, the results of the second EFA analysis are as follows:

KMO and Bartlett's tests in factor analysis showed that the KMO coefficient met the requirements (0.849>0.5) with a significance level of 0 (sig = .000), indicating that EFA factor analysis was appropriate.

At Eigenvalues greater than 1 and with Principal components extraction method and varimax rotation, factor analysis extracted 6 factors from 26 observed variables with extracted variance of 69.843% (greater than 50%) meeting the requirements.

Based on the analysis of the Rotated Component Matrix table (a), all variables have factor loading coefficients less than 0.5. So these observed variables all meet the requirements for the following analysis.

Table 3.6 Results of the second factor analysis of the components of the scale of factors affecting investment attraction for tourism in Ba Ria Vung Tau province

Rotated Component Matrix a

Component
1	2	3	4	5	6
Investment policy and law (A2)	.905
Microeconomic policy (B1)	.884
Economic management policy (B3)	.884
Business Environment (A3)	.869
GDP growth (B2)	.688
One-door cover (A4)	.671

	.845
	Labor cost (G1)	.816
	Training base (F3)	.784
	Business efficiency (G4)	.684
	Ecotourism Resources (D2)		.815
	Marine tourism resources (D1)		.726
	General labor (F1)		.718
	Living environment (D4)		.672
	Shopping mall and entertainment system (D3)		.641
	Tourism planning (C1)			.888
	Flexibility in attracting investment (C4)			.887
	Surface Decompression Work (C3)			.620
	Investment promotion for tourism (C2)			.603
	Palace of public finances (E4)				.815
	Traffic system (E1)				.768
	Electrical and water systems (E2)				.672
	Waste treatment system (E3)				.636
	Industry Competition (G3)					.837
	High-quality work (F2)					.783
	Science and Technology Degree (F4)					.543
KMO	.849
Eigenvalues	8.103	3,479	2.225	1,743	1,506	1.103
% of Variance	31,167	13,379	8,560	6,704	5,791	4,243

Infrastructure usage cost (G2)

Thus, the components of the factors attracting investment capital for tourism and the scale of measurement when performing EFA analysis have changed. The specific components of the scale are as follows:

Institutional, legal, investment and macroeconomic stability (A_B)

A2: Stable investment policies and laws A3: Transparent business environment

A4: One-stop mechanism facilitates investment activities B1: Stable macroeconomic policies

B2: Good GDP growth rate

B3: Economic management policy demonstrates fairness and non-discrimination

Policy to attract investment capital for tourism of Ba Ria - Vung Tau province (C)

C1: Clear and detailed tourism development planning

C2: Investment promotion for tourism is well implemented.

C3: The province has done a good job of compensation, site clearance and site clearance for investment projects.

private

C4: The Province's flexibility in investment attraction and implementation policies is high.

Advantages of natural resources and tourism resources of Ba Ria - Vung Tau province

Ship (Dn)

D1: Beautiful coastline, favorable for investing in beach tourism areas

D2: Rivers and primeval forests are favorable for investment in eco-tourism and resorts.

nourish

D3: The system of commercial centers and craft villages develops favorably for tourism investment.

MICE schedule

D4: Ecological environment is not polluted

F1: Many unskilled workers

Infrastructure development of Ba Ria - Vung Tau province (E)

E1: Modern transportation system

E2: Modern and complete electricity and water supply system

E3: Complete waste and wastewater treatment system E4: Financial institutions, development banks Business efficiency of tourism projects (Gn) G1: Low labor costs

G2 : Low infrastructure usage cost

G4: Investing in tourism brings high profits

F3: Training facilities in the province are capable of training human resources to serve development.

tourism development

Development of science and technology and competition (Fn)

F2: Highly skilled workers sufficient to meet tourism investment projects

F4: High level of science and technology, meeting the requirements of investors

G3: Competition in tourism is not too great

3.2.3.5. Calibrating the research model and hypotheses

Through testing Cronbach alpha reliability coefficient and EFA analysis, the theoretical model is adjusted to 6 components and is presented as follows:

H 1 '

H 3

H 4 ' H 5

H 6 '

H 7 '

Institutional, legal, investment and macroeconomic stability

Policy to attract investment capital for tourism of Ba Ria - Vung Tau province

Advantages of natural resources and tourism resources of Ba Ria - Vung Tau province

Attracting investment capital for tourism in Ba Ria - Vung Tau province

Infrastructure development

floor of Ba Ria - Vung Tau province

Effectiveness of tourism investment projects

Development of science and technology and competition

Figure 3.3 Research model of factors affecting investment attraction for development

Ba Ria - Vung Tau province tourism has been revised

Hypotheses:

Hypothesis H1' : When the stability of institutions, macroeconomics, investment laws and administrative reforms increases or decreases, the attraction of investment capital for tourism in Ba Ria - Vung Tau province also increases or decreases.

Hypothesis H3 : When the policy of attracting investment capital for tourism of Ba Ria - Vung Tau province increases or decreases, the attraction of investment capital for tourism of Ba Ria - Vung Tau province also increases or decreases.

Hypothesis H4' : When the advantages of natural resources and tourism resources of Ba Ria - Vung Tau province increase or decrease, the attraction of investment capital for tourism of Ba Ria - Vung Tau province also increases or decreases.

Hypothesis H5 : When the infrastructure development of Ba Ria - Vung Tau province increases or decreases, the attraction of investment capital for tourism of Ba Ria - Vung Tau province also increases or decreases.

Hypothesis H6' : When the effectiveness of tourism investment projects increases or decreases, the attraction of investment capital for tourism in Ba Ria - Vung Tau province also increases or decreases.

Hypothesis H7' : When the development of science and technology level and competition in tourism activities increases or decreases, the attraction of investment capital for tourism in Ba Ria - Vung Tau province also increases or decreases.

3.2.3.6. Results of testing the model and research hypothesis:

Regression analysis was performed using the general regression method of variables. The specific results are as follows:

The results of multiple linear regression analysis show that the model has an adjusted R 2 coefficient =

0.598 means that the constructed multiple linear regression model fits the data set 59.8%.

Table 3.7 Regression results using the enter method of the model

Model Summary b

Model

R Square

Adjusted R Square

Std. Error of the Estimate

Durbin-Watson

.779a

.607

.598

.63398942

1,881

a. Predictors: (Constant), Science and technology level and competition, Infrastructure, Local investment attraction policy, Tourism resources, Tourism business efficiency, Regime, law and microeconomics

b. Dependent Variable: Attracting investment capital for tourism

ANOVA analysis shows that the F parameter has a sig. value of 0.000, proving that the built regression model is suitable for the collected data set, and the variables included are all statistically significant. Thus, the independent variables in the model are related to the dependent variable Attracting investment capital for tourism in Ba Ria Vung Tau province.

Table 3.8 ANOVA analysis table

ANOVA b

Model

Sum of Squares	df	Mean Square	F	Sig.
1	Regression	160,897	6	26,816	66,716	.000 a
	Residual	104.103	259	.402
	Total	265,000	265
a. Predictors: (Constant), Science and technology level and competition, Infrastructure, Local investment attraction policy, Tourism resources, Tourism business efficiency, Regime, law and microeconomics b. Dependent Variable: Attracting investment capital for tourism

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