other places in Vietnam. Next is the price with a fairly good average value of 3.9052 and a standard deviation of 0.64520, which is also rated quite well by tourists in terms of the price factor being reasonable and cheap compared to the standard of living in their country. In particular, the factor Culture, history and art has the lowest average value (2.7927) and a standard deviation of (0.57190) among the remaining 9 groups of factors, which explains that international tourists have not found anything attractive and interesting in culture, history and art, partly due to language barriers. In general, all of these groups of factors are rated quite well by international tourists.
4.4.1 Correlation analysis
The study applied Pearson's correlation analysis and linear regression analysis to investigate the relationships between independent variables and dependent variables. The correlation coefficient r has a value from -1 to +1, in which a positive sign is a positive correlation and a negative sign is a negative correlation. The meaning of the r value has been mentioned in chapter 3. When variables are found to be closely correlated with each other, it is necessary to pay attention to the problem of multicollinearity when analyzing regression.
Conducting correlation analysis on new groups of variables, the results are as follows:
Table 4.14: Correlation coefficients between variables Pearson's Correlations
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
1. TORETIN | 1.00 | |||||||||
2. CULHISART | .268 | 1.00 | ||||||||
3. SAFSEC | .190 | .195 | 1.00 | |||||||
4. NATENVI | .312 | .448 | .368 | 1.00 | ||||||
5. NEGAT | -.032 | -.060 | -.163 | -.256 | 1.00 | |||||
6. LOCUIS | .273 | .332 | .236 | .180 | .050 | 1.00 | ||||
7. TOSEFACI | .229 | .280 | .364 | .229 | -.037 | .317 | 1.00 | |||
8. ACCESS | .104 | .284 | .304 | .298 | -.181 | .284 | .404 | 1.00 | ||
9. PRICE | .235 | .271 | .217 | .162 | -.051 | .351 | .251 | .210 | 1.00 | |
10. ENTERPRISE | .332 | .444 | .203 | .254 | -.015 | .391 | .353 | .311 | .360 | 1.00 |
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The table above shows that all 8 independent variables have positive correlation with the dependent variable (TORENTIN), most of the independent variables have weak correlation with the dependent variable. Of which, 6 variables have weak correlation ENTERECRE (r = 0.332, P<.001), NATENVI (r = 0.312, P<.001), LOCUIS (r = 0.273, P<.001), CULHISART (r = 0.268, P<.05), PRICE (r = 0.235, P<.05), TOSEFACI (r = 0.229,
P<.05). And there are 2 independent variables that have very weak correlation with the dependent variable, which are SAFSEC (r = 0.190, P<.05), and ACCESS (r = 0.104, P<.05). In the significant correlations, Recreational and entertainment activities are the best, more than natural-social environment, local cuisine, culture, history and art, price, infrastructure, safety and security and accessibility. In contrast, the independent variable NEGAT has no correlation with the dependent variable TORENTIN (r = -0.032, p>0.05), which indicates that there is no correlation between the obstacle variables (NEGAT) and the variable (TORENTIN) of tourists' intention to return.
4.4.2 Model fit testing
Examining which of the independent variables has a significant impact on the intention to revisit the destination of Ho Chi Minh City will be done using linear regression equation.
Adjusted R 2 = 0.183 means that 9 independent variables explain 18.3% of tourists' intention to return to Ho Chi Minh City destination explained by the independent variables of the model.
Table 4.15: ANOVA a
Model
Total average direction | df | Medium square | F | Sig. | ||
Regression | 65,120 | 9 | 7,236 | 9,838 | .000 b | |
1 | Remainder | 253,744 | 345 | .735 | ||
Total | 318,864 | 354 |
a. Dependent variable: TORETIN: Tourists' intention to return
b. Independent variables: (constant), ENTERECRE: Recreational and entertainment activities, NEGAT: Barriers, SAFSEC: Safety and security, PRICE: price, ACCESS: Access, NATENVI: Natural-social environment, LOCUIS: local cuisine, TOSEFACI: Infrastructure, CULHISART: Culture, history and art.
The F-test used in the analysis of variance is a hypothesis test about the suitability of the overall linear regression model. The idea of this test is about the linear relationship between the dependent variable and the independent variables. In the ANOVA analysis table, we see that the sig. value is very small (sig. = 0.000), so the regression model fits the data set and can be used.
4.4.3 Regression analysis
To identify factors affecting international tourists' intention to return to Ho Chi Minh City, the overall correlation model has the form: TORETIN = f (CULHISART, SAFSEC, NATENVI, NEGAT, LOCUIS, TOSEFACI, ACCESS, PRICE, ENTERECRE)
In which: TORETIN: Dependent variable and CULHISART, SAFSEC, NATENVI, NEGAT, LOCUIS, TOSEFACI, ACCESS, PRICE, ENTERECRE:
independent variable
Examining which of the independent variables really affects international tourists' intention to return to Ho Chi Minh City will be done using the linear regression equation:
TORETIN = β 0 + β 1 CULHISART + β 2 SAFSEC+ β 3 NATENVI + β 4 NEGAT + β 5 LOCUIS + β 6 TOSEFACI + β 7 ACCESS + β 8 PRICE + β 9 ENTERECRE + ε
Table 4.16: Coefficients between independent variables and visitors' intention to return
Coefficients a
Model | Unstandardized coefficient | Standard coefficient chemical | T | Sig. | Multicollinearity statistics | ||
B | Error standard | Beta | Tolerance e | VIF | |||
(Constant) | .230 | .527 | .437 | .663 | |||
CULHISART | .044 | .099 | .027 | .450 | .653 | .652 | 1.53 5 |
SAFSEC | .032 | .072 | .025 | .449 | .654 | .751 | 1.33 2 |
NATENVI | .267 | .068 | .228 | 3.903 | .000 | .674 | 1.48 3 |
NEGAT | .020 | .073 | .014 | .274 | .784 | .894 | 1.11 9 |
LOCUIS | .206 | .094 | .123 | 2,188 | . 029 | .732 | 1.36 6 |
TOSEFACI | .114 | .078 | .084 | 1,468 | .143 | .710 | 1.40 8 |
ACCESS | -.172 | .080 | -.120 | -2.150 | . 032 | .735 | 1.36 1 |
PRICE | .117 | .079 | .080 | 1,484 | .139 | .796 | 1.25 6 |
ENTERECR E | .268 | .083 | .188 | 3.211 | .001 | .670 | 1.49 2 |
a. Dependent variable: TORETIN: Tourists' intention to return
- Based on the VIF variance inflation factor of the independent variables in the model, which are all very small (<2) (Table 4.15) , the independent variables do not have multicollinearity problems. This shows that the independent variables are closely related to each other, so multicollinearity does not occur.
The results of the multivariate regression (Table 4.15) show that 8 independent variables have a positive (positive) and direct impact on the dependent variable TORETIN. Of which, 3 variables have a significant impact on the intention to return, including: NATENVI (β = 0.267,sig. =. 000, T = 3.903), LOCUIS (β = 0.206,sig. =. 029, t = 2.188) and
ENTERECRE (β = 0.268,sig. =. 001, T = 3.211) has a significance level of p = sig. <0.05 equivalent to 95% confidence and |t| > 2 then that factor is accepted. It means that an increase in these three factors will lead to an increase in the intention to return of tourists. In other words, it means that each unit of deviation of NATENVI or LOCUIS or ENTERECRE changes, leading to an equivalent change in the intention to return to the destination of Ho Chi Minh City of international tourists with a coefficient of 0.267 or 0.206 or 0.268. On the contrary, ACCESS (β = -0.172,Sig =. 032, t = -2.150) has a significance level of p= sig.<0.05 equivalent to 95% confidence and |t| < 2 Therefore, the more difficult it is to access the city, the more tourists' intention to return to travel decreases because of poor access to information and tourism advertising, leading to international tourists not knowing much about Ho Chi Minh City.
PRICE (sig =. 139, t =1.484), NEGAT (sig =. 784, t =. 274), TOSEFACI (sig
=. 143, t = 1.468), SAFSEC (sig. =. 654, t = . 449), and CULHISART (sig. =. 653, t = .
450) has a significance level of p = sig. > 0.05 and |t| < 2 then the factor is not accepted, therefore increasing in these factors does not lead to an increase in the intention to return of tourists. For more clarity, a regression equation for TORENTIN's model is written using the coefficient (Beta):
Four variables were included in the analysis: NATENVI, LOCUIS, ENTERECRE, ACCESS, and the remaining variables were eliminated.
In summary, the regression equation meaningfully represents the relationship between international tourists' intention to return and four independent variables as follows:
TORETIN = .230 + .267(NATENVI) + .206 (LOCUIS) + .268 (ENTERECRE) -
.172 (ACCESS).
Good
Tourists' intention to return =. 230+. 267 (Natural-social environment) +.
206 (Local Cuisine) +.268 (Recreational Activities) -.172 (Accessibility).
In addition, the standardized beta coefficients are all > 0, indicating that eight independent variables have a positive impact on international tourists' intention to revisit Ho Chi Minh City. In particular, the accessibility variable (ACCESS) has a negative standardized beta (beta = -.120) and negatively impacts international tourists' intention to revisit Ho Chi Minh City.
Natural-social environment
0.267
Local cuisine
0.206
Tourists' intention to return
Fun activities
entertainment
0.268
-0.172
Accessibility
In summary, through the results of testing the theoretical model, specifically the results of multiple linear regression, we have the following new model:
Figure 4.8: Complete model Summary of chapter 4
In this chapter, specific research results are presented from actual survey data. Through supporting tools, data is processed, statistically evaluated to provide a complete model for the topic. The next chapter will summarize and provide recommendations and conclusions for the topic.
CHAPTER 5
CONCLUSION AND MANAGEMENT IMPLICATIONS
This chapter focuses on discussing the findings of chapter 4 to accept or reject the hypotheses and answer the research questions to understand the relationship between nine independent variables (natural-social environment, culture, history and art, local cuisine, infrastructure and access, entertainment activities, price and negative attributes, and the dependent variable visitor intention to revisit).
5. 1 Testing research hypotheses
The results of preliminary evaluation of the scales through Cronbach's alpha technique and EFA exploratory factor analysis showed that the theoretical research model had no change, with nine research hypotheses to explain the three research questions.
Research question
1) What factors influence international tourists' intention to return to Ho Chi Minh City?
H2 (+) : Local culinary factors positively affect tourists' intention to return.
H5 (+) : Infrastructure and accessibility factors positively affect tourists' intention to return.
H6 (+) : Natural and social environmental factors have a positive impact on tourists' intention to return.
H7 (+) : The factor of entertainment activities has a positive impact on tourists' intention to return.
The relationship and impact of nine independent variables on international tourists' intention to revisit Ho Chi Minh City. Each of the above hypotheses was used to test the relationships between the independent variables and the dependent variable, to determine which factors influence TORETIN's intention to revisit Ho Chi Minh City.
of international tourists and to find out the most influential factor among the dependent variables.
From Table 4.15: Regression results - Coefficients between independent variables and TORETIN of tourists' intention to return, it is clear that not all 9 factors have a significant impact on the dependent variable TORETIN of tourists' intention to return. Only 4 out of 9 independent factors have a significance level of p = sig. <0.05 equivalent to 95% confidence level, thus affecting TORETIN of tourists' intention to return. They are Natural-social environment (NATENVI), Local cuisine (LOCUIS), Entertainment activities (ENTERECRE), and Accessibility (ACCESS).
In addition to the Accessibility factor (ACCESS), the above three groups of factors possess positive beta values, which indicate a positive impact on (TORENTIN) the intention to return of tourists. This means that the number of international tourists increases if they perceive that the natural-social environment (NATENVI), entertainment activities (ENTERECRE), and local cuisine (LOCUIS) are in good condition. That is, when tourists perceive that the natural landscape, climate, weather are attractive, the people are friendly, the environment is favorable for the tour and the experiences of entertainment activities, enjoying unique and attractive local cuisine, their intention to return will be higher. This is also the conclusion of many previous studies on the intention to return (Chen & Tsai (2007) (Oppermann (2000), (Shoemaker & Lewis (1999), (Beerli and Martin, (2004), (Inskeep & Pelancongan, (1996), (Oxford dictionary, (2005), (Beerli and Martin, (2004),
(Mazanec (1997), (Hudman (1986), (Jones & Jenkins (2002).
The unstandardized coefficients (B) of the factors, 3 independent factors directly affect TORETIN. They are Natural Environment (NATENVI) with B = 0.267, p= sig<0.000, Local Cuisine (LOCUIS) with B = 0.206, p= sig<0.029, and Recreational Activities (ENTERECRE) with B = 0.268, p= sig<0.001. It illustrates that if Natural Environment (NATENVI), Local Cuisine (LOCUIS), Recreational Activities (ENTERECRE), are improved, the intention to revisit of international tourists will increase (positive influence).