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Total Variance Explained


Comp

onent

Initial Eigenvalues

Extraction Sums of Squared

Loadings

Rotation Sums of

Squared Loadings


Total

% of

Variance

Cumulati

ve %

Total

% of

Variance

Cumulati

ve %

Total

% of

Variance

Cumulat

ive %

13

.445

1.647

87.329







14

.432

1.600

88.929

15

.373

1.381

90.310

16

.358

1.326

91.636

17

.309

1.146

92.782

18

.302

1.117

93.899

19

.263

.975

94.874

20

.244

.905

95.779

21

.232

.860

96.639

22

.188

.696

97.335

23

.173

.641

97.976

24

.166

.616

98.591

25

.140

.519

99.111

26

.123

.454

99.565

27

.117

.435

100.000

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Extraction Method: Principal Component Analysis.



Component Matrixa



Component

1

2

3

4

5

6

AN1

.601



-.501


.509



AN2

.650

AN3

.666

AN4

.657

AN5

.728

DU6

.569

DU7

.649

DU8

.683

DU9

.629

DU10

.608

NL11

.516


Component Matrixa



Component


1

2

3

4

5

6

NL12

.581


.552


.539



NL13

.648

.506


NL14

.566

.528


CSVC16

.561


.555

CSVC17

.599


.527

CSVC18

.627



CSVC19

.591



CLSP21

.519



CLSP22




CLSP23




CLSP24

.522



CLSP25




HLCP27

.738



HLCP29

.796



HLCP30

.789



HLCP31

.759



Extraction Method: Principal Component Analysis.

a. 6 components extracted.


Rotated Component Matrixa



Component

1

2

3

4

5

6

AN1

.800






AN2

.807




AN3

.717




AN4

.739




AN5

.730




DU6


.802



DU7


.768



DU8


.865



DU9


.846



DU10


.829



NL11




.808

NL12




.678

NL13




.792

NL14




.778

CSVC16



.804


CSVC17



.830



Rotated Component Matrixa



Component


1

2

3

4

5

6

CSVC18



.658




CSVC19

.670



CLSP21


.589


CLSP22


.642


CLSP23


.814


CLSP24


.838


CLSP25


.660


HLCP27



.568

HLCP29



.558

HLCP30



.563

HLCP31



.642

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 6 iterations.


KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.500


Approx. Chi-Square

70.602

Bartlett's Test of Sphericity

df

1


Sig.

.000


Communalities



Initial

Extraction

HL1

1.000

.774

HL2

1.000

.774

Extraction Method: Principal Component Analysis.


Total Variance Explained


Component

Initial Eigenvalues

Extraction Sums of Squared Loadings

Total

% of Variance

Cumulative %

Total

% of Variance

Cumulative %

1

1.548

77.412

77.412

1.548

77.412

77.412

2

.452

22.588

100.000

Extraction Method: Principal Component Analysis.


Correlations



HL

CSVC

NLPV

DU

HLCP

CLSP

AN


Pearson Correlation

1

.533**

.542**

.548**

.633**

.520**

.566**

HL

Sig. (2-tailed)


.000

.000

.000

.000

.000

.000


N

200

200

200

200

200

200

200


Pearson Correlation

.533**

1

.442**

.354**

.621**

.297**

.545**

CSVC

Sig. (2-tailed)

.000


.000

.000

.000

.000

.000


N

200

200

200

200

200

200

200


Pearson Correlation

.542**

.442**

1

.400**

.496**

.427**

.439**

NL

Sig. (2-tailed)

.000

.000


.000

.000

.000

.000


N

200

200

200

200

200

200

200


Pearson Correlation

.548**

.354**

.400**

1

.515**

.412**

.420**

DU

Sig. (2-tailed)

.000

.000

.000


.000

.000

.000


N

200

200

200

200

200

200

200


Pearson Correlation

.633**

.621**

.496**

.515**

1

.458**

.682**

HLCP

Sig. (2-tailed)

.000

.000

.000

.000


.000

.000


N

200

200

200

200

200

200

200


Pearson Correlation

.520**

.297**

.427**

.412**

.458**

1

.305**

CLSP

Sig. (2-tailed)

.000

.000

.000

.000

.000


.000


N

200

200

200

200

200

200

200


Pearson Correlation

.566**

.545**

.439**

.420**

.682**

.305**

1

AN

Sig. (2-tailed)

.000

.000

.000

.000

.000

.000



N

200

200

200

200

200

200

200

**. Correlation is significant at the 0.01 level (2-tailed).



Model Summaryb


Model

R

R

Squar e

Adjusted R Square

Std. Error of the Estimate

Change Statistics

R Square

Change

F Change

df1

df2

Sig. F

Change

1

.756a

.572

.558

.57024

.572

42.905

6

193

.000

a. Predictors: (Constant), AN, CLSP, DU, NL, CSVC, HLCP

b. Dependent Variable: HL


ANOVAa


Model

Sum of Squares

df

Mean Square

F

Sig.


Regression

83.710

6

13.952

42.905

.000b

1

Residual

62.759

193

.325


Total

146.469

199


a. Dependent Variable: HL

b. Predictors: (Constant), AN, CLSP, DU, NL, CSVC, HLCP


Coefficientsa


Model

Unstandardized

Coefficients

Standardized

Coefficients

t

Sig.

Collinearity Statistics

B

Std.

Error

Beta

Tolera

nce

VIF


(Constant)

-.211

.261


-.807

.421




AN

.166

.071

.145

2.326

.021

.570

1.755


DU

.178

.064

.162

2.787

.006

.654

1.530

1

NL

.188

.054

.200

3.482

.001

.675

1.480


CSVC

.162

.081

.153

1.989

.048

.375

2.669


CLSP

.206

.056

.205

3.665

.000

.706

1.416


HLCP

.198

.080

.164

2.456

.015

.497

2.010

a. Dependent Variable: HL


Collinearity Diagnosticsa


Model

Dimension

Eigenvalue

Condition Index

Variance Proportions



(Constant)

CSVC

NLPV

DU

HLCP

CLSP

AN


1

6.832

1.000

.00

.00

.00

.00

.00

.00

.00


2

.050

11.736

.04

.04

.01

.78

.00

.03

.02


3

.041

12.942

.00

.03

.01

.13

.02

.75

.03

1

4

.027

16.043

.01

.02

.80

.02

.10

.13

.03


5

.024

16.971

.59

.00

.17

.06

.19

.00

.00


6

.017

20.346

.03

.78

.00

.01

.01

.00

.37


7

.011

24.841

.33

.14

.00

.01

.68

.08

.55

a. Dependent Variable: HL


Residuals Statisticsa



Minimum

Maximum

Mean

Std. Deviation

N

Predicted Value

1.3037

5.2722

3.6375

.64858

200

Residual

-1.31965

2.26008

.00000

.56158

200

Std. Predicted Value

-3.598

2.520

.000

1.000

200

Std. Residual

-2.314

3.963

.000

.985

200

a. Dependent Variable: HL

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