Tourists’ Satisfaction towards Bao Loc City, Vietnam
Bibliographic record
Abstract
Bao Loc City is the new tourism destination in Lam Dong province, Vietnam, where more and more tourists have been drawn to pay a visit. This study aims to test the correlative impact of tourism service quality factors on satisfaction of the tourists who have visited Bao Loc City. The key theory used in this study is SERVQUAL scale. The survey sample consists of 350 tourists who stayed overnight in Bao Loc City in the last quarter of 2019; 315 valid survey questionnaires could be used for the analysis. The research applied Cronbach's Alpha, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM), and bootstrap test. The results show that the satisfaction of the tourists who have visited Bao Loc City has been affected statistically by three factors: (1) Responsiveness; (2) Reliability; and (3) Empathy, which were ranked by descending importance. Surprisingly, the research found that Tangibles and Assurance do not have an impact on tourists' satisfaction towards Bao Loc City. The research formulates some suggestions to the city policy-makers and the tourism businesses management in Bao Loc City in order to enhance tourists' satisfaction through improving the tourism service quality at Bao Loc City.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".