The Immediate Impact of Coach Succession Events on Season Ticket Holder Attitudes
Bibliographic record
Abstract
This study is the first to examine the immediate impact that succession events (e.g., removal and hiring) involving head coaches have on season ticket holder (STH) attitudes like satisfaction and renewal intentions. Grounded within a customer equity framework, large-scale survey data from cases of two professional sport teams is presented showing STH attitudes directly before and after major succession events. The data shows that appointing a new coach was met with increases in positive attitudes toward almost every aspect of the STH experience, where the case of removing a coach had no meaningful impact on attitudes. The findings of these cases reaffirm the view that coach succession is a multiple-phase process including distinct stages of removal and replacement. While it is the desire for improved on-field performance that often motivates coach succession, our findings suggest the impact of succession activities on fans is more wide ranging, with significant implications for marketers who manage fan relationships. In guiding the management of a team's fans, coach removal alone should not be relied upon to change attitudes or intentions toward a club. Appointing new leaders completes the cycle, increasing positive STH attitudes and, most importantly, giving an immediate lift to renewal likelihood.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".