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National Versus Regional Sports Marketing: An Interpretation of 'Think Globally, Act Locally'

2003· article· en· W171993802 on OpenAlexaffabout
Cheri L. Bradish, Julie Stevens, Anna H. Lathrop

Bibliographic record

VenueInternational Journal of Sports Marketing and Sponsorship · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsBrock University
Fundersnot available
KeywordsSports marketingMarketingGlobal marketingOptimal distinctiveness theoryGlobalizationMarketing managementMarketing mixSport managementMarketing strategyBusinessAdvertisingPublic relationsPolitical scienceRelationship marketingPsychology

Abstract

fetched live from OpenAlex

Few would question that one of the most significant determinants of growth in the sport industry — from a sport management, marketing, and sponsorship perspective — has been the inf luence of globalization. Product expansion and communication messages have targeted the 'global consumer,' and the recognition of a 'global brand' has come to epitomize successful sport marketing. Or, has it? Although global management practices present the possibility of expanded consumer markets, a number of marketing strategists have recently begun to question the use of standardized global marketing campaigns that lack national or regional distinctiveness. At issue, is the positioning of 'regionalism' within global sport marketing strategies. This paper will investigate the role of 'regionalism' in sport marketing through; a) an examination of the regional sport marketing strategy of a leading Canadian all-sports television cable network (Rogers Sportsnet) that targets four distinct regions across Canada, and b) a survey of Canadian Generation Y youth sport participation and spectatorship trends across four regions. Implications for regional positioning within sport marketing strategies will also be discussed.

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.

How this classification was reachedexpand

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)0.024
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.010
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.333
Teacher spread0.298 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2003
Admission routes2
Has abstractyes

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