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Record W4362731154 · doi:10.1080/23311975.2023.2194147

Moderation effects of multiple directorships on audit committee and firm performance: A middle eastern perspective

2023· article· en· W4362731154 on OpenAlexaff
Kamilah Kamaludin, Sheela Sundarasen, Izani Ibrahim

Bibliographic record

VenueCogent Business & Management · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsQuest University Canada
FundersPrince Sultan University
KeywordsAudit committeeModerationAttendanceAccountingBusinessAuditChief audit executiveCorporate governanceAudit evidenceJoint auditInternal auditPsychologyFinancePolitical scienceLaw

Abstract

fetched live from OpenAlex

This study examines the moderation effects of audit committee members’ multiple directorships on the association between the number of audit committee meetings, attendance in the audit committee meetings and firm performance. A panel generalized least square method is used as the analysis tool, on the selected listed firms in the Saudi Arabian Stock Market (Tadawul). Empirical evidence suggests an inverse relationship between the number of audit committee meetings, audit committee meetings’ attendance and firm performance. As for the moderation effects of multiple directorships, a positive effect is documented. The results indicate that the multiple directorships by the audit committee members play a significantly positive role on firm performance in the Kingdom of Saudi Arabia (KSA). This study underwrites a middle eastern perspective on the relationship between the number of audit committee meetings and its attendance and the moderation effects of audit committee members’ multiple directorships on firm performance. The findings of this study provide valuable insights to policymakers and practitioners. The results should provide support to regulatory authorities to legislate effective regulations to make internal governance mechanisms work more effectively in the country.

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)0.006
metaresearch head score (Gemma)0.010
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 score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.211
Teacher spread0.182 · 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

Citations15
Published2023
Admission routes1
Has abstractyes

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