by factors (each variable is a polynomial of factors). Factor loading coefficients represent the correlation between variables and factors. This coefficient indicates that factors and variables are closely related to each other. The study uses the Number of factor analysis method with Varimax rotation, so factor loading coefficients must have a weight greater than >= 0.5 to have practical significance.
Building regression equations, testing hypotheses
After extracting factors from EFA, analyzing correlation matrix, multiple linear regression, checking the variance inflation factor (VIF). If the multicollinearity assumptions are not violated, the multiple linear regression model is built. And the adjusted R² coefficient (adjusted R square) shows how well the built regression model fits.
From the regression model, we proceed to evaluate the model's suitability and test the expected hypotheses.
CHAPTER 3 SUMMARY
Chapter 3 presents the research method used to construct and evaluate the measurement scale of research concepts and test the theoretical model.
The research method was carried out through group discussion technique with 8 people representing the Department of Culture, Sports and Tourism of Ben Tre province, representatives of ecotourism destinations of Ben Tre province, and 22 people representing domestic tourism areas. The result of the group discussion was to build an official scale to survey 350 samples. The official scale adopted by the group included 8 research factors on factors affecting the satisfaction of domestic tourism areas with ecotourism in Ben Tre province.
The next chapter will present the data analysis method and research results including scale evaluation using Cronbach's Alpha and EFA coefficients; testing the theoretical model using multivariate linear regression; Levene's test for the difference between a qualitative variable and a quantitative variable and One Way ANOVA analysis of variance.
CHAPTER 4: RESEARCH RESULTS
With the hypothetical model presented in chapter 2, after conducting an empirical survey, chapter 4 will re-verify the model. At the same time, quantitative analysis will be provided to better understand the research problem.
Chapter 4 revolves around 3 main contents: (1) Assessing the reliability of the scale, (2) Analyzing the exploratory factor and building a regression model, (3) Testing the impact of factors in the model.
4.1 Scale Evaluation
To evaluate the degree of coherence of the items in the scale in relation to each other, the study uses the Cronbach's alpha coefficient. The Cronbach's alpha coefficient varies from [0;1]. In theory, the higher the Cronbach's alpha coefficient, the better. However, when the Cronbach's alpha coefficient is too large, it will show that the variables do not have much difference from each other. Therefore, a scale has good reliability when it varies in the range of [0.7;0.8]. In addition, the total correlation coefficient of each variable and the total must be from 0.3 or higher. A scale with a Cronbach's alpha coefficient of 0.6 or higher can be used in the case of a new research concept (Nunnally, 1978; Peterson, 1994; Slater, 1995). Normally, a scale with Cronbach's alpha from 0.7 to 0.8 is good to use. In this case, the Cronbach's alpha coefficient used is from 0.7 or higher and the total item correlation coefficient is from 0.3 or higher. The results of testing the reliability of the scale of the variables are as follows:
4.1.1 Cronbach's alpha of the scale of tourist landscape factors Table 4.1: Assessment of the reliability of the scale of tourist landscape
Observation variable
Scale mean if variable excluded | Scale variance if variable is excluded | Variable-total correlation | Cronbach's Alpha if variable type | |
PC1 | 14,6758 | 10,465 | ,659 | ,833 |
PC2 | 14,7798 | 9,988 | ,711 | ,820 |
PC3 | 14,8410 | 10,453 | ,636 | ,839 |
PC4 | 14,7401 | 9,880 | ,715 | ,819 |
PC5 | 14,7737 | 10,709 | ,653 | ,835 |
Cronbach's Alpha = 0.859 | ||||
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Source: Data analysis – appendix 3
The tourism landscape scale has 5 observed variables. The result of Cronbach's alpha reliability coefficient analysis of this scale is 0.859 > 0.7. At the same time, the observed variables have variable-total correlation coefficients greater than 0.3. Therefore, the tourism landscape scale meets the reliability requirements, the variables in the tourism landscape scale are included in the EFA analysis in the next step.
4.1.2 Cronbach's alpha of the infrastructure factor scale
Table 4.2: Infrastructure scale reliability assessment
Observation variable
Scale mean if variable excluded | Scale variance if variable is excluded | Variable-total correlation | Cronbach's Alpha if variable type | |
CSHT1 | 14,4343 | 12,314 | ,729 | ,781 |
CSHT2 | 14,6330 | 12,423 | ,709 | ,787 |
CSHT3 | 14,4832 | 12,471 | ,719 | ,785 |
CSHT4 | 14,6361 | 15,116 | ,340 | ,883 |
CSHT5 | 14,5229 | 12,048 | ,741 | ,777 |
Cronbach's Alpha = 0.859 | ||||
CSHT1 | 10,8930 | 8,838 | ,749 | ,848 |
CSHT2 | 11,0917 | 8,857 | ,742 | ,851 |
CSHT3 | 10,9419 | 8,981 | ,737 | ,853 |
CSHT5 | 10,9817 | 8,662 | ,752 | ,847 |
Cronbach's Alpha = 0.883 | ||||
Source: Data analysis – appendix 3
The Infrastructure scale has 5 observed variables. The result of the first analysis of the Cronbach's alpha reliability coefficient of the scale is 0.859 > 0.7. However, the observed variable CSHT4 has the lowest item-total correlation coefficient and removing this variable will increase the reliability of the scale. Therefore, the author removes the variable CSHT4. After removing the variable, the Cronbach's alpha reliability coefficient of the scale is 0.883 > 0.7. At the same time, the observed variables have item-total correlation coefficients greater than 0.3. Therefore, the tourism landscape scale meets the reliability requirement, the remaining variables in the infrastructure scale are included in the EFA analysis in the next step.
4.1.3 Cronbach's alpha of the tour guide factor scale Table 4.3: Assessment of the reliability of the tour guide scale
Observation variable
Scale mean if variable excluded | Scale variance if variable is excluded | Variable-total correlation | Cronbach's Alpha if variable is excluded | |
HDV1 | 14,1223 | 11,592 | ,576 | ,822 |
HDV2 | 13,9358 | 9,711 | ,718 | ,782 |
HDV3 | 13,9480 | 10,270 | ,730 | ,781 |
HDV4 | 14,2446 | 9,891 | ,678 | ,794 |
HDV5 | 14,5382 | 11,071 | ,515 | ,839 |
Cronbach's Alpha = 0.837 | ||||
HDV1 | 10,9633 | 7,373 | ,620 | ,820 |
HDV2 | 10,7768 | 5,965 | ,736 | ,767 |
HDV3 | 10,7890 | 6,468 | ,737 | ,768 |
HDV4 | 11,0856 | 6,440 | ,615 | ,825 |
Cronbach's Alpha = 0.839 | ||||
Source: Data analysis – appendix 3
The tour guide scale has 5 observed variables. The result of the first analysis of the Cronbach's alpha reliability coefficient of the scale is 0.837 > 0.7. However, the observed variable HDV5 has the lowest item-total correlation coefficient and removing this variable will increase the reliability of the scale. Therefore, the author removes the variable HDV5. After removing the variable, the Cronbach's alpha reliability coefficient of the scale is 0.839 > 0.7. At the same time, the observed variables have item-total correlation coefficients greater than 0.3. Therefore, the tour guide scale meets the reliability requirement, the remaining variables in the tour guide scale are included in the EFA analysis in the next step.
4.1.4 Cronbach's alpha of the security and order factor scale
Table 4.4: Assessment of reliability of the safety and order scale
Observation variable
Scale mean if variable excluded | Scale variance if variable is excluded | Variable-total correlation | Cronbach's Alpha if variable type | |
ATTT1 | 13,8471 | 9,756 | ,637 | ,825 |
ATTT2 | 14,0917 | 9,715 | ,638 | ,825 |
ATTT3 | 13,9266 | 9,246 | ,702 | ,808 |
ATTT4 | 14,1988 | 9,092 | ,668 | ,817 |
ATTT5 | 13,9664 | 8,934 | ,661 | .820 |
Cronbach's Alpha = 0.850 | ||||
Source: Data analysis – appendix 3
The ATTT scale has 5 observed variables. The result of Cronbach's alpha reliability coefficient analysis of this scale is 0.850 > 0.7. At the same time, the observed variables have variable-total correlation coefficients greater than 0.3. Therefore, the ATTT scale meets the reliability requirements, the variables in the ATTT scale are included in the EFA analysis in the next step.
4.1.5 Cronbach's alpha of the shopping food service factor scale Table 4.5: Reliability assessment of the shopping food service scale
Observation variable
Scale mean if variable excluded | Scale variance if variable is excluded | Variable-total correlation | Cronbach's Alpha if variable is excluded | |
AUMS1 | 13,5291 | 13,710 | ,735 | ,795 |
AUMS2 | 13,4893 | 13,748 | ,723 | ,798 |
AUMS3 | 13,4557 | 16,825 | ,396 | ,877 |
AUMS4 | 13,7951 | 14,010 | ,726 | ,798 |
AUMS5 | 13,4985 | 13,116 | ,717 | ,800 |
Cronbach's Alpha = 0.848 | ||||
AUMS1 | 10,9633 | 7,373 | ,620 | ,820 |
AUMS2 | 10,7768 | 5,965 | ,736 | ,767 |
AUMS4 | 10,7890 | 6,468 | ,737 | ,768 |
AUMS5 | 11,0856 | 6,440 | ,615 | ,825 |
Cronbach's Alpha = 0.877 | ||||
Source: Data analysis – appendix 3
The shopping food service scale has 5 observed variables. The result of the first analysis of the Cronbach's alpha reliability coefficient of the scale is 0.848 > 0.7. However, the observed variable AUMS3 has the lowest item-total correlation coefficient and removing this variable will increase the reliability of the scale. Therefore, the author removes the AUMS3 variable. After removing the variable, the Cronbach's alpha reliability coefficient of the scale is 0.877 > 0.7. At the same time, the observed variables have item-total correlation coefficients greater than 0.3. Therefore, the shopping food service scale meets the reliability requirement, the remaining variables in the shopping food service scale are included in the EFA analysis in the next step.
4.1.6 Cronbach's alpha of the scale of factors of sightseeing, entertainment and recreation activities
Table 4.6: Assessment of reliability of the scale for sightseeing, entertainment and recreation activities
Observation variable
Scale mean if variable excluded | Scale variance if variable is excluded | Variable-total correlation | Cronbach's Alpha if variable type | |
TQVCGT1 | 14,4312 | 17,044 | ,397 | ,894 |
TQVCGT2 | 14,6850 | 13,167 | ,732 | ,823 |
TQVCGT3 | 14,6453 | 12,671 | ,793 | ,806 |
TQVCGT4 | 14,7645 | 12,849 | ,751 | ,817 |
TQVCGT5 | 14,4526 | 12,868 | ,750 | ,818 |
Cronbach's Alpha = 0.864 | ||||
TQVCGT2 | 10,8716 | 10,192 | ,736 | ,873 |
TQVCGT3 | 10,8318 | 9,674 | ,813 | ,845 |
TQVCGT4 | 10,9511 | 9,875 | ,762 | ,864 |
TQVCGT5 | 10,6391 | 9,968 | ,748 | ,869 |
Cronbach's Alpha = 0.894 | ||||
Source: Data analysis – appendix 3
The scale for measuring sightseeing, entertainment, and recreation activities has 5 observed variables. The result of the first analysis of the Cronbach's alpha reliability coefficient of the scale is 0.864 > 0.7. However, the observed variable TQVCGT1 has the lowest total item correlation coefficient and removing this variable will increase the reliability of the scale. Therefore, the author removes the variable TQVCGT1. After removing the variable, the Cronbach's alpha reliability coefficient of the scale is 0.894 > 0.7. At the same time, the observed variables have item-total correlation coefficients greater than 0.3. Therefore, the scale for sightseeing, entertainment, and recreation activities meets the reliability requirement, the remaining variables in the scale for sightseeing, entertainment, and recreation activities are included in the EFA analysis in the next step.