Comprendre les décisions d'achat dans les médias sociaux : le cas du e-tourisme
Bibliographic record
Abstract
L’évolution marquée des comportements d’achat en ligne oblige les dirigeants à mesurer l’impact des avis des consommateurs, émis dans les médias sociaux, sur le processus d’achat. Cet article vise à dégager les critères que les consommateurs prennent en compte au moment de la sélection d’un hôtel, ce qui permettra aux hôteliers d’optimiser les conditions d’achat de futurs clients. Nous basant sur une étude et sur la documentation, nous proposons des conseils à l’égard d’une stratégie de marketing intégrant les médias sociaux qui peuvent aider non seulement des dirigeants d’hôtels, mais des organisations de tous les secteurs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".