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Record W1991166568 · doi:10.5539/ibr.v5n9p120

Does Board of Director’s Characteristics Affect Firm Performance? Evidence from Malaysian Public Listed Companies

2012· article· en· W1991166568 on OpenAlexvenueno aff
Siti Norwahida Shukeri, Ong Wei Shin, Mohd Shahidan Shaari

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingGender diversityReturn on equityBusinessIndependence (probability theory)Diversity (politics)Affect (linguistics)Equity (law)Corporate governanceFinancePolitical sciencePsychologyLawProfitability indexStatisticsMathematics

Abstract

fetched live from OpenAlex

The aim of this study is to answer the question: “do board characteristics affect firm performance?” There are six board of directors’ characteristics being studied, including managerial ownership, board size, board independence, CEO duality, gender diversity and ethnic diversity. Return on Equity (ROE) is used as a measurement for firm financial performance. There are 300 Malaysian public listed companies being randomly selected from each sector. The results show that board size and ethnic diversity have positive relationship with ROE while board independence has negative relationship. There is no significant relationship between managerial ownership, CEO duality and gender diversity on firm performance. The findings may provide some implications for future research regarding the effectiveness of board of directors towards firm performance.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.102
GPT teacher head0.324
Teacher spread0.223 · 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

Citations219
Published2012
Admission routes1
Has abstractyes

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