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ESG And Firm Value in Vietnam: The Moderating Role of Profitability

2025· article· en· W4414355523 on OpenAlexvenueno aff
Thi Thu Trang La

Bibliographic record

VenueInternational Journal of Analysis and Applications · 2025
Typearticle
Languageen
FieldComputer Science
TopicEconomic Growth and Development
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexCorporate governanceEnterprise valueValue (mathematics)VietnameseHeteroscedasticityPanel dataSustainability

Abstract

fetched live from OpenAlex

This study examines the relationship between environmental, social, and governance (ESG) practices and firm value in Vietnam, with a specific focus on the moderating role of profitability. Using a panel dataset of publicly listed Vietnamese companies between 2014 and 2023, the study applies the Feasible Generalized Least Squares (FGLS) method to address potential heteroscedasticity and autocorrelation issues. The findings indicate that ESG engagement has a generally positive impact on firm value, measured by Tobin’s Q.; however, this effect varies significantly across firms depending on their profitability levels. Firms with higher profitability benefit more from ESG practices, while those with low profitability experience weaker or neutral effects. This suggests that financial health plays a critical role in shaping the outcomes of ESG adoptions. This study contributes to the growing ESG literature in emerging markets by highlighting how internal financial capacity affects the effectiveness of sustainability strategies. It also provides practical implications for managers and policymakers seeking to align ESG initiatives with value-creation goals.

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 score0.049
Threshold uncertainty score0.097

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.005
GPT teacher head0.248
Teacher spread0.243 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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