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Record W4294733407 · doi:10.1111/beer.12481

How does social trust affect corporate financial performance? The mediating role of corporate social responsibility

2022· article· en· W4294733407 on OpenAlexaff
Jae C. Jung, Junyon Im

Bibliographic record

VenueBusiness Ethics the Environment & Responsibility · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCorporate social responsibilityCommitEndogeneityBusinessAffect (linguistics)MediationLegitimacyStakeholderAccountingStakeholder theoryOrder (exchange)Public relationsPublic economicsFinanceEconomicsPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Abstract Prior studies assert that social trust may positively influence the economic performance of countries and firms (within those countries). This paper proposes a more nuanced mechanism whereby corporate social responsibility (CSR) mediates the relationship between country‐level social trust and firm‐level financial performance. Anchored in neo‐institutional theory, we theorize that social trust instills norms of trustworthiness and willingness to trust others guiding individual and corporate behaviors. In order to comply with such norms and gain legitimacy, firms in high‐trust society are more likely to commit to CSR activities that serve the interests of stakeholders. CSR activities, in turn, can positively influence financial performance by enabling firms to access stakeholders' resources and capabilities and to decrease transactions costs in the stakeholder relationships. We tested our theory by analyzing 9818 firm‐year observations across 34 countries, during the 2006 to 2015 period. Our analysis shows the expected CSR mediation in the relationship between social trust and firm‐level financial performance. Our findings are robust across different models addressing the concerns of endogeneity, alternative measures, and potential moderators.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0080.003
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.251
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes1
Has abstractyes

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