MétaCan
Menu
Back to cohort
Record W2048285454 · doi:10.5295/cdg.130408cc

Measuring the influence of customer-based store brand equity in the purchase intention

2014· article· en· W2048285454 on OpenAlexaff
Cristina Calvo-Porral, Valentín Alejandro Martínez, Óscar Juanatey Boga, Jean-Pierre Lévy Mangin

Bibliographic record

VenueCuadernos de Gestión · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Retail Behavior Studies
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsBrand equityBusinessBrand awarenessAdvertisingBrand loyaltyMarketingStructural equation modelingBrand managementStore brandConceptual modelBrand extensionSample (material)Perceived qualityQuality (philosophy)Order (exchange)Computer science

Abstract

fetched live from OpenAlex

Store brands account for and important market share in the Spain and a further increase in expected in the next years due to the downturn. However, there is lack of research on store brand customer-based Brand Equity. This study attempts to propose an integrated model of Brand Equity in store or retailer brands, based on Aaker’s well-known conceptual model. We propose a consumer-based model, including the main sources or dimensions of Brand Equity and considering the intention to purchase as a consequence. Based on a sample of 362 consumers and 5 store brands, structural equation modeling is used to test research hypotheses. The results obtained reveal that store brand awareness, loyalty along with store brand perceived quality have a significant influence on consumers’ intention to purchase store brands. Our study suggests that marketers and marketing managers from retailing companies should carefully consider the Brand Equity components when designing their brand strategies, and develop marketing activities in order to enhance their brands’ awareness.

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)0.006
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.289
Teacher spread0.226 · 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

Citations26
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCuadernos de GestiónSame topicConsumer Retail Behavior StudiesFrench-language works237,207