The impact of airlines' policies during COVID-19 on travellers' repurchase intentions: the case of Aegean Airlines
Bibliographic record
Abstract
The COVID-19 outbreak had a dramatic impact on the hospitality and air transport industries. After an international lockdown and mass flight cancellations in March 2020, airlines were required to issue full refunds to their customers or offer alternative options like credit vouchers for future flights. Aegean Airlines is one of the airlines that suspended any refund option and only offered vouchers to its customers. The purpose of this case study is to examine the likely impacts of an airline's crisis response during the COVID-19 pandemic on its customers' future decisions to use the same airline again, or to revisit their destination. A survey was created and disseminated online during the height of the crisis and the data were analysed through logistic regression models and qualitative, textual analyses. The findings of this exploratory study suggest that an airline's cancellation policy, combined with poor customer service communications and transparency, negatively influence passengers' re-purchase intentions, as well as their willingness to revisit the airline's host country in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".