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Record W2985796315 · doi:10.5539/ibr.v13n1p18

Corporate Social Responsibility and Brand Equity in Mexican Small Firms

2019· article· en· W2985796315 on OpenAlexvenueno aff
Gonzalo Maldonado Guzmán, Sandra Yesenia Pinzón Castro, Lucero Jazmín Cuevas‐Pichardo

Bibliographic record

VenueInternational Business Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsnot available
Fundersnot available
KeywordsBrand equityCorporate social responsibilityBusinessEquity (law)Social responsibilityMarketingAccountingSample (material)Equity capital marketsCorporate brandingEmpirical evidencePublic relationsPolitical science

Abstract

fetched live from OpenAlex

Corporate social responsibility is a topic that has generally been analyzed and discussed in large national and transnational companies, and relatively few studies have been oriented in small and medium-sized enterprises, even though theoretical and empirical evidence has been provided that small businesses also carry out social responsibility activities. Likewise, brand equity has been scarcely related to corporate social responsibility, and there are few studies published in the current marketing literature that relate these two important constructs. Therefore, using a sample of 300 small firms and applying a structural equations model of second order, which allows to know in greater depth the relationship between corporate social responsibility and brand equity, the essential objective of this empirical study is the analysis and discussion of the effects of corporate social responsibility on the level of brand equity of small firms. The results obtained show that corporate social responsibility has a significant positive effect on the level of brand equity of small firms.

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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.099
GPT teacher head0.366
Teacher spread0.267 · 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
Published2019
Admission routes1
Has abstractyes

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