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Record W4416459662 · doi:10.1080/0965254x.2025.2586554

Beyond borders: how national culture and consumer ethnocentrism shape purchase intentions in Latin America

2025· article· en· W4416459662 on OpenAlexaff
Iliana E. Aguilar-Rodríguez, Leopoldo G. Arias‐Bolzmann, Luciano Barcellos de Paula, Geovanni F. Tapia-Andino, Ana Belén Tulcanaza-Prieto

Bibliographic record

VenueJournal of Strategic Marketing · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsConestoga College
Fundersnot available
KeywordsLatin AmericansConsumer ethnocentrismEthnocentrismConsumer CultureConsumer behaviour

Abstract

fetched live from OpenAlex

This study examines the impact of cultural dimensions and consumer ethnocentrism on purchase intentions toward domestic brands in Latin America – a region characterized by high levels of migration and cultural hybridity. Grounded in Hofstede’s cultural framework and the Theory of Planned Behavior, data from 535 respondents across six countries were analyzed using structural equation modeling. Results show that consumer ethnocentrism is a strong and consistent predictor of purchase intention, while Hofstede’s dimensions did not have significant direct effects. These findings highlight the importance of contextualizing cultural values within dynamic social environments and underscore the role of attitudinal factors, such as perceived behavioral control, in shaping consumer behavior. The study offers a more comprehensive understanding of how macro-level culture and micro-level psychology intersect in shaping consumer behavior. Practical implications include designing segmentation strategies and marketing messages that resonate with local identities and generational traits across diverse Latin American markets.

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)0.001
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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.039
GPT teacher head0.292
Teacher spread0.253 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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