The Relevance of the Souvenirs, Food, Experiences and Facilities of a Bordered Destination on the Key Relationship of Perceived Value, Attitudes and Satisfaction
Bibliographic record
Abstract
Borders are geographic areas with great potential for the development of tourism activity, and tourism can contribute to socioeconomic development and the conservation of resources, both cultural and natural. The study addresses the influence of aspects such as food, souvenirs, experiences and facilities on the perceived value, attitudes and satisfaction of visitors towards a border destination. A questionnaire was administered to a sample of 583 tourists visiting the northern border of the Dominican Republic and the Republic of Haiti. This geographical area being the main point of flow of visitors between both countries. Using variance-based structural equation modeling based on the partial least squares method, the food, experiences at the destination, and facilities of a border destination have a positive influence on their perceived value. It has also been verified a positive influence of tourist attitudes on the perceived value and satisfaction. Results are very useful for local stakeholders, for the improvement of elements such as souvenirs sale, which can increase tourist satisfaction and contribute to the sustainable development of the region, the creation of stores and/or local businesses.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".