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Record W1554339485 · doi:10.1177/155862350700200102

What Drives the Value of Stadium Naming Rights? A Hedonic-Pricing Approach to the Valuation of Sporting Intangible Assets

2007· article· en· W1554339485 on OpenAlex
Bill Gerrard, Milena M. Parent

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Sport Finance · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of AlbertaUniversity of Ottawa
Fundersnot available
KeywordsStadiumValuation (finance)LeagueHedonic pricingValue (mathematics)Market valueBusinessEconomicsMicroeconomicsActuarial scienceEconometricsFinanceStatisticsMathematics

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.343
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it