What Drives the Value of Stadium Naming Rights? A Hedonic-Pricing Approach to the Valuation of Sporting Intangible Assets
Why this work is in the frame
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Bibliographic record
Abstract
This study adopts a multi-attribute hedonic-pricing benchmark valuation approach to the determination of the observed market value of stadium naming rights. Using a sample of 112 naming rights deals covering both major-league and nonmajor-league facilities in North America over the period of 1979-2002, a hedonic-pricing model is estimated using regression analysis. It is found that the value of stadium naming rights is highly systematic and information-efficient. Naming rights value is principally related to variables reflecting the size of potential target audiences including the economic size of the host city, the facility's capacity, the league status of the resident teams, and the diversity of the facility usage. It is also found that sponsors are prepared to pay a significant premium for virgin sites with no previous name associations.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it