Dubai as a First-Choice Destination for Saudi Tourists: Analysis of Socio-economic Characteristics, Travel Behaviour, and Perceptions of Saudi Visitors to Dubai
Bibliographic record
Abstract
This article examines the demand for Dubai tourism via a binary logit model, using its top source market, Saudi Arabia, as a case study. Saudi Arabia is a relatively mature tourism source market for Dubai, and the results produced should therefore be more representative than those of a sample drawn from any of Dubai’s other tourism markets. The explanatory variables in this model are socio-economic variables such as gender, age, marital status, number of children, income, employment, and education. A total of 1 111 tourists were selected via convenience sampling to participate in a survey. The results show that Saudis’ primary reasons for visiting Dubai are shopping, family entertainment, and youth entertainment. The survey results also indicate that most Saudis visiting Dubai are relatively young single men seeking an open-minded cosmopolitan context where they can enjoy the quality of place and the diversity, openness, and tolerance that Dubai offers. Gender and age are more significant factors for thos...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".