The Relationship Between Responsible Tourism Practice, Destination Sustainability and Quality of Life: Perspective of Marine National Park Communities
Bibliographic record
Abstract
An ideal responsible tourism practice has become the most significant role and principle for modern sustainable tourism development concept. Responsible tourism practice promotes better for tourists visit and enhances the quality of life of host communities in the destination by encouraging ethical consumption and production in all stakeholders. This paper attempted to determine the impact of host communities’ perceived responsible tourism practice on perceived destination sustainability and their quality of life as well as the impact of host communities’ perceived destination sustainability on perceived quality of life. The study was conducted with 355 participants from host communities in Haad Chao Mai Marine National Park, Thailand. Self-administered questionnaires were used to collect the data. The collected data were analyzed by using structural equation modeling (SEM). The results revealed that perceived responsible tourism practice had a significant impact on perceived destination sustainability and perceived quality of life. Additionally, perceived destination sustainability influenced perceived quality of life. As such, embedding responsible tourism practice in destination development plan can enable destination sustainability and better quality of life of host communities and it might make the park successful ecotourism destination.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".