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Record W2073679002 · doi:10.1108/bfj-07-2013-0174

Global brands or local heroes?: evidence from the Spanish beer market

2015· article· en· W2073679002 on OpenAlexaff
Cristina Calvo-Porral, Jean-Pierre Lévy-Mangín

Bibliographic record

VenueBritish Food Journal · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsBrand equityBusinessBrand loyaltyBrand managementOriginalityMarketingBrand awarenessBrand extensionLoyaltyValue (mathematics)Order (exchange)AdvertisingStructural equation modelingQuality (philosophy)SociologyQualitative research

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to investigate how consumers perceive and evaluate local and global brands – in a developed mature European market. Design/methodology/approach – For this purpose, four dimensions and two consequences of brand equity are evaluated, based on consumers’ standpoint. Structural equation modeling is carried out in order to analyze results obtained. Findings – The findings suggest that brand loyalty, brand image and perceived quality exert the higher influence on consumers’ brand value; while there are relevant differences in consumer’s assessment toward local and global brands. Originality/value – This study provides local and global brand marketers with further specific knowledge on how to market and enhance their brands’ value in a globalized increasingly competitive world.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.050
GPT teacher head0.243
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2015
Admission routes1
Has abstractyes

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