Low-Cost Carrier Passengers’ Willingness to Pay for the Seat Preselection Service: A Case Study on the Taiwan-Japan Route
Bibliographic record
Abstract
Due to the rising of consumer awareness, consumers not just pay more attention to leisure activities but also demand more on the related service quality. In recent years, low-cost carriers (LCCs) have continued to expand their routes, and traditional aviation is no longer the only choice for travel abroad. Different from the traditional way of operation, LCCs focus on reducing nonessential expenses. The concept of payment by service offers passengers the options for relatively low ticket price. To continuously operate in the highly competitive aviation industry, most airlines have introduced distinctive “value-added additional services” to attract air passengers. This study discusses the seat preselection, value-added service, and behavior of Taiwanese passengers who take low-cost flights to Japan. The results indicate that passengers who have experienced purchasing preselected seats are more willing to purchase this additional service and spend higher amount of money for that service. In addition, the result also indicates that younger people are more willing to accept novel services. These findings could be used as an importance reference for LCCs to guide managerial strategy in the future.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".