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Record W4407584129 · doi:10.1111/jifm.12234

Corporate Social Responsibility (CSR) and Firm Value: International Evidence on the Role of CSR Assurance

2025· article· en· W4407584129 on OpenAlexfundno aff
Ahrum Choi, Jin Lan, Zabihollah Rezaee, Gaoguang Zhou

Bibliographic record

VenueJournal of International Financial Management and Accounting · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
FundersHong Kong Baptist UniversityCanadian Academic Accounting Association
KeywordsCorporate social responsibilityBusinessAccountingValue (mathematics)Social responsibilityBusiness administrationPublic relationsPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT A growing number of companies around the world have started publishing corporate social responsibility (CSR) reports. However, the sustainability literature remains inconclusive as to whether CSR assurance enhances the credibility of these reports, improves stakeholder trust, and ultimately boosts firm value. Analyzing a global sample of 39,776 firm‐year observations from 2002 to 2019, we present robust evidence that CSR assurance positively influences investors' valuation of CSR efforts. Furthermore, auditor‐provided CSR assurance is found to have a greater impact on CSR valuation in countries where institutions are more conducive to opaque financial reporting. Our analysis further reveals that improved financial performance and better financial reporting quality are the main mechanisms behind this effect. Finally, the impact of CSR assurance is found to be more significant in countries with weaker legal institutions and CSR norms.

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)0.005
metaresearch head score (Gemma)0.025
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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.002
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.271
Teacher spread0.247 · 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

Citations9
Published2025
Admission routes1
Has abstractyes

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