The Effect of Partitioned Ticket Prices on Sport Consumer Perceptions and Enduring Attitudes
Bibliographic record
Abstract
The efficacy of partitioned pricing (PP) has been investigated in a range of industries. This work showed that the usefulness of PP is situational, with numerous contextual factors playing important roles. Ticket pricing scholarship has yet to devote adequate attention to PP as a focal variable, which is problematic given the industry’s reliance on ticket revenue and the “service” fees ubiquitous in the ticketing industry. In addition, there is a need to investigate the moderating factors unique to sport consumption, such as team identification and the entertainment value of live sport. Using a sample of 403 sport consumers, this study found that PP is associated with lower perceptions of fairness but not lower enduring attitudes about the platform. Thus, sport consumers are displeased by PP, but not enough to dissuade them from future purchases. The analysis found that team identification—the entertainment value of live sports entertainment value—can further offset negative perceptions of PP.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".