Bootstrap test results with sample size 2000 Model Fit Summary
CMIN
Model
NPAR | CMIN | DF | P | CMIN/DF | |
Default model | 49 | 262,838 | 161 | .000 | 1,633 |
Saturated model | 210 | .000 | 0 | ||
Independence model | 20 | 9501.916 | 190 | .000 | 50,010 |
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RMR, GFI
Model
RMR | GFI | AGFI | PGFI | |
Default model | .033 | .964 | .953 | .739 |
Saturated model | .000 | 1,000 | ||
Independence model | .272 | .271 | .194 | .245 |
Baseline Comparisons
Model
NFI Delta1 | RFI rho1 | IFI Delta2 | TLI rho2 | CFI | |
Default model | .972 | .967 | .989 | .987 | .989 |
Saturated model | 1,000 | 1,000 | 1,000 | ||
Independence model | .000 | .000 | .000 | .000 | .000 |
Parsimony-Adjusted Measures
Model
PRACTICE | PNFI | PCFI | |
Default model | .847 | .824 | .838 |
Saturated model | .000 | .000 | .000 |
Independence model | 1,000 | .000 | .000 |
NCP
Model
NCP | LO 90 | HI 90 | |
Default model | 101,838 | 61,323 | 150,259 |
Saturated model | .000 | .000 | .000 |
Independence model | 9311.916 | 8996.019 | 9634.134 |
FMIN
Model
FMIN | F0 | LO 90 | HI 90 | |
Default model | .371 | .144 | .086 | .212 |
Saturated model | .000 | .000 | .000 | .000 |
Independence model | 13,402 | 13,134 | 12,688 | 13,588 |
RMSEA
Model
RMSEA | LO 90 | HI 90 | PCLOSE | |
Default model | .030 | .023 | .036 | 1,000 |
Independence model | .263 | .258 | .267 | .000 |
AIC
Model
AIC | BCC | BIC | CAIC | |
Default model | 360,838 | 363,829 | 584,536 | 633,536 |
Saturated model | 420,000 | 432,820 | 1378.706 | 1588.706 |
Independence model | 9541.916 | 9543.137 | 9633.222 | 9653.222 |
ECVI
Model
ECVI | LO 90 | HI 90 | MECVI | |
Default model | .509 | .452 | .577 | .513 |
Saturated model | .592 | .592 | .592 | .610 |
Independence model | 13,458 | 13,013 | 13,913 | 13,460 |
HOELTER
Model
HOELTER HOELTER .05 .01 | |
Default model Independence model | 517 555 17 18 |
.046 | |
Miscellaneous: | 1,532 |
Bootstrap: | 4,977 |
Total: ESTIMATE | 6.555 |
Estimate | |||
NT | <--- | CB | -.356 |
HP | <--- | CB | .302 |
HP | <--- | NT | -.339 |
YD | <--- | NT | -.285 |
YD | <--- | HP | .309 |
YD3 | <--- | YD | .859 |
YD2 | <--- | YD | .833 |
YD4 | <--- | YD | .799 |
YD1 | <--- | YD | .838 |
YD5 | <--- | YD | .754 |
CB3 | <--- | CB | .895 |
Estimate | |||
CB4 | <--- | CB | .840 |
CB2 | <--- | CB | .838 |
CB5 | <--- | CB | .809 |
CB1 | <--- | CB | .766 |
HP4 | <--- | HP | .801 |
HP2 | <--- | HP | .782 |
HP3 | <--- | HP | .781 |
HP1 | <--- | HP | .738 |
HP5 | <--- | HP | .747 |
NT4 | <--- | NT | .846 |
NT3 | <--- | NT | .857 |
NT5 | <--- | NT | .799 |
NT2 | <--- | NT | .766 |
NT1 | <--- | NT | .705 |
BOOTSTRAP STANDARD ERROR
Parameter
SE | SE-SE | Mean | Bias | SE-Bias | |||
NT | <--- | CB | .037 | .001 | -.354 | .002 | .001 |
HP | <--- | CB | .039 | .001 | .301 | -.001 | .001 |
HP | <--- | NT | .038 | .001 | -.341 | -.002 | .001 |
YD | <--- | NT | .039 | .001 | -.284 | .002 | .001 |
YD | <--- | HP | .042 | .001 | .309 | .000 | .001 |
YD3 | <--- | YD | .013 | .000 | .859 | .000 | .000 |
YD2 | <--- | YD | .016 | .000 | .833 | .000 | .000 |
YD4 | <--- | YD | .017 | .000 | .799 | .000 | .000 |
YD1 | <--- | YD | .015 | .000 | .838 | .000 | .000 |
YD5 | <--- | YD | .021 | .000 | .754 | .000 | .000 |
CB3 | <--- | CB | .011 | .000 | .895 | .000 | .000 |
CB4 | <--- | CB | .015 | .000 | .839 | -.001 | .000 |
CB2 | <--- | CB | .015 | .000 | .838 | .000 | .000 |
CB5 | <--- | CB | .022 | .000 | .808 | -.001 | .000 |
CB1 | <--- | CB | .019 | .000 | .766 | .000 | .000 |
HP4 | <--- | HP | .017 | .000 | .801 | .000 | .000 |
HP2 | <--- | HP | .018 | .000 | .781 | -.001 | .000 |
HP3 | <--- | HP | .019 | .000 | .780 | .000 | .000 |
HP1 | <--- | HP | .021 | .000 | .738 | .000 | .000 |
HP5 | <--- | HP | .019 | .000 | .747 | .000 | .000 |
NT4 | <--- | NT | .014 | .000 | .846 | .000 | .000 |
NT3 | <--- | NT | .012 | .000 | .857 | .000 | .000 |
NT5 | <--- | NT | .015 | .000 | .799 | .000 | .000 |
NT2 | <--- | NT | .016 | .000 | .765 | -.001 | .000 |
NT1 | <--- | NT | .020 | .000 | .705 | .000 | .000 |
APPENDIX 11A: 3RD EXPERT INTERVIEW SCRIPT PART 1: INTRODUCTION
Hello everyone, my name is Le Thi Kieu Anh - a PhD student in Business Administration at Lac Hong University. I am currently conducting a research on the intention to return of tourists in Ho Chi Minh City. I look forward to your enthusiastic discussion. All your frank opinions will contribute to the success of this research topic. All your personal information and answers will be kept confidential, we will only publish the summary results. We sincerely thank you for your cooperation.
PART 2: INTERVIEW OBJECTIVES
The objective of the interview is to explain and evaluate the results obtained from data analysis in quantitative research through a questionnaire that was directly distributed to 710 international and domestic tourists at 10 tourist destinations in Ho Chi Minh City.
To best achieve this goal, the interviewees were experts who had undergone the first interview because these experts had a clear understanding of the concepts as well as the hypotheses and theoretical research models. At the same time, some experts were researchers or had a lot of experience in the tourism field. They would have both an academic and practical perspective to help contribute to the implications.
PART 3: CONTENT
A. Documents provided before interview:
To achieve the best interview results, the author provides relevant documents to help members review and evaluate the content in advance. Documents sent in advance to experts include:
- Official scales of factors such as intention to return, risk perception, subjective happiness, service fairness, culture;
- Descriptive statistics of the surveyed subjects;
- Results of testing theoretical models and research hypotheses.
B. Discussion questions:
To help the interview achieve its goals, some suggested questions are suggested:
1) What are your comments/evaluations about the results of testing the theoretical model and research hypotheses?
2) From those results, do you have any suggestions or recommendations?
THANK YOU VERY MUCH FOR YOUR HELP!
APPENDIX 11B: SUMMARY OF 3RD INTERVIEW RESULTS
After obtaining the quantitative research results, the study conducted interviews with 3 experts who have long-term research capabilities and many years of experience in the tourism sector in Ho Chi Minh City and participated in the first expert interview. The results of the interviews with the 3 experts were recorded and summarized as follows:
1. Experts' opinions on research results
Result
Expert opinion | ||
Number of experts agreeing to conclude fruit | Detailed content | |
1) The provision of a guaranteed service | ||
fairness will make customers happy | ||
satisfied and no longer feel defeated | ||
disadvantage compared to other customers. From there, receive | ||
It is obvious that their risk perception will decline. | ||
of course | ||
2) On the contrary, if the company only focuses on | ||
The increase of feeling | Provide good quality service without paying attention | |
get translation credit | Paying attention to fairness does not necessarily make | |
service will reduce the receipt | 3/3 experts | their customers are satisfied, at the same time, increasing |
customer risk awareness | fear of being treated unfairly | |
tourism. | equal. | |
3) Some employees/companies tend to | ||
"foreign-loving" should prioritize international guests | ||
than domestic guests. Or vice versa, for | ||
This statue has more priority for domestic guests. | ||
land due to national pride. From then on, in the past | ||
service provider, interaction or cost | ||
Unequal supply costs between two parties | ||
This phenomenon makes many customers feel very uncomfortable. If it happens repeatedly, it will make customers worry about continuing to use the service. 4) When providing services that do not ensure fairness in terms of cost/price, the perception of financial risk increases. Likewise, unclear/transparent procedures/information for each customer will make them feel that they are taking on policy risks. Or, uneven service among customers or providing incorrect information will sometimes cause accidents with serious consequences for health. That said, it is enough to see that the components of service fairness such as service delivery, interaction, procedures, information, price/cost also affect each component of risk perception. 5) The impact of service fairness on risk perception is considered very high (β= - 0.401). This shows that this relationship is considered very close. If customers do not feel fairness when using the service, their risk perception will increase significantly. | ||
An increase in perceived service fairness will increase subjective happiness | 3/3 experts | 1) Subjective happiness comes from satisfaction during the use of tourism services, as well as positive emotions. Therefore, in the process of providing tourism services |
fairness will increase satisfaction and positive emotions. In other words, increased service fairness will increase subjective well-being. 2) If the service delivery, the interaction of the staff or the information provided, the price, the procedures applied to all customers are not the same, there is bias or difference, then customers will immediately no longer feel satisfied. At the same time, that is also the cause of their physical and mental effects. From there, positive emotions are reduced and in many cases will last until after the end of the trip. 3) When Service Equity increases by one, it increases the subjective happiness of tourists by 0.316. Thus, businesses that make tourists feel service equity will have their happiness level increase significantly. | ||
Increased risk perception will decrease tourists' subjective well-being. | 3/3 experts | 1) When incidents occur frequently while traveling, tourists are likely to be dissatisfied. Since the probability and likelihood of incidents occurring increases, subjective well-being decreases. 2) The more serious the incident is, the lower the customer satisfaction level will be because it can affect the customer's mental and physical health. 3) Events related to finance, health |
of tourists.
Health, policies that occur during the travel process will make customers feel dissatisfied with the quality of the trip as well as the positive emotions are reduced. 4) Coefficient β = -0.316 is a high level of impact. It confirms a very close relationship between these two factors. | ||
1) Tourists encounter incidents | ||
frequent or severe | ||
or when financial risks occur, | ||
health, policy they will usually tend to | ||
insecure and completely dissatisfied | ||
with the trip. From there, there will be no thinking | ||
The increase of recognition | any thoughts or plans for the trip | |
risk awareness will do reduce the intention to turn | 3/3 experts | go next. In other words, increased risk perception will reduce the intention to return. |
of tourists. | tourist | |
2) The impact of risk perception on intention | ||
return intention is considered high (β= -0.261). | ||
This demonstrates the relationship between the two characters. | ||
This factor is very tight. This result is completely consistent. | ||
suitable for real situation | ||
1) Subjective happiness is only achieved through travel. | ||
An increase in subjective well-being will increase tourists' intention to revisit. | 3/3 experts | tourists have satisfaction and positive emotions during the travel experience. Satisfaction is also one of the components of the intention to return. Therefore, when tourists have a level of happiness Increased subjectivity will also increase the intention to return. |
increased again. |





