Towards recreational travel modelling in non-western countries: An empirical study using a structural equation modeling approach
Bibliographic record
Abstract
Recreational tourism as a niche market has prompted researchers to take a variety of approaches to investigate the elements that influence travelers’ decisions to engage in leisure activities. The reasons why Muslim visitors select leisure-based travel are commonly discussed in the tourism literature, although little research has been done in this area. By analyzing the significance of travel motivation, emotional response, and satisfaction in determining attitudinal loyalty for Muslim leisure travelers, this study aims to bridge this knowledge gap. This study employed Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) using AMOS version 23 to answer the research questions. According to the findings, emotional experiences and extrinsic motives have a good direct impact on satisfaction and an indirect impact on the inclination to return. Having a deeper understanding of leisure-based travel from the perspective of Muslim tourists will benefit recreation managers.
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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 | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".