‘Wild Your weekends' promotion and its effect on traffic recovery during COVID-19 pandemic
Bibliographic record
Abstract
China Eastern Airlines launched a ‘Wild Your Weekends' programme offering buyers an unlimited number of free trips during weekends, which is unprecedented in the Chinese airline market and also rare around the world. However, it is unclear whether such a promotion is effective in improving airlines’ liquidity. This study adopts the difference-in-differences (DID) method to empirically examine the impacts of this promotion programme on traffic volumes, ticket prices and revenues of China Eastern and its competitors. Our estimations suggest that this programme has overall helped China Eastern improve its liquidity. On one hand, the carrier was forced to lower prices on weekends, probably because passengers formed strong beliefs on China Eastern’s low price due to its promotion programme, and felt psychologically unfair by paying high prices as compared to the programme’s users. This decreased China Eastern’s revenue from non-programme passengers on weekends.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".