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Record W1507672391 · doi:10.1108/mf-05-2013-0123

Investment opportunity set, board independence, and firm performance

2014· article· en· W1507672391 on OpenAlexaff
Jerry Sun, George Lan, Zhenzhong Ma

Bibliographic record

VenueManagerial Finance · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCorporate governanceIndependence (probability theory)AccountingOriginalityBusinessInvestment (military)Sarbanes–Oxley ActSet (abstract data type)Enterprise valuePanel dataEconomicsFinanceEconometricsPolitical science

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to investigate the impact of Sarbanes-Oxley Act (SOX) on high growth firms’ corporate governance. Specially, the study examines whether there is a negative impact of SOX on the interactive effect of board independence and investment opportunity set on firm performance. Design/methodology/approach – Sample firms were selected from the Investor Responsibility Research Center Directors’ database. Both accounting- and market-based firm performance measures are used. Regressions are run to test the hypothesis. Findings – It was found that the impact of SOX on the interaction effect of board independence and investment opportunity set on firm performance is negative. Originality/value – The results suggest that the impact of SOX in corporate governance and regulatory environment mitigates the effect of board independence on the relationship between investment opportunity set and firm performance, consistent with the notion that the enactment of SOX increases monitoring costs of board governance especially for high-growth firms.

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)0.006
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.020
GPT teacher head0.200
Teacher spread0.180 · 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

Citations21
Published2014
Admission routes1
Has abstractyes

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