Advancing Tourist Destination Image Theory: Formation Antecedents and Behavioral Consequences
Bibliographic record
Abstract
PurposeThe purpose of this thesis is three-fold:(1) To examine the effect of four personal factors (institutional trust (IT), consumer ethnocentrism tendency (CET), consumer cosmopolitanism (COS), and personality type (PT) on the formation of the domestic tourist destination image (DTDI), (2) To examine the effect of DTDI on the destination brand experience (DBE), tourist satisfaction (TS), behavioral intentions and the relationships among them, and(3) To assess the potential applicability of relative deprivation theory, the means-end approach, leisure constraints theory, freedom-seeking theory, and prestige-seeking theory on the tourist preference for international versus domestic tourism in Saudi Arabia. Design/methodology/approachA sample of 1,564 Saudi citizens was collected through an online questionnaire using established valid and reliable measures for each construct.A theoretical model that included the antecedents and consequences of DTDI was designed based on the latest status of the topic in the literature.The data were analyzed statistically using structural equation modeling (SEM) in order to test the model.The results are then discussed in the light of nine interviews with tourism officials, experts, and professionals.
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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 | 0.002 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".