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Record W2461754896 · doi:10.1177/0149206316653804

Complementary or Substitutive Effects? Corporate Governance Mechanisms and Corporate Social Responsibility

2016· article· en· W2461754896 on OpenAlexaff
Won‐Yong Oh, Young Kyun Chang, Tae‐Yeol Kim

Bibliographic record

VenueJournal of Management · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCorporate governanceCorporate social responsibilityBusinessIncentiveMechanism (biology)Perspective (graphical)Principal–agent problemAccountingAffect (linguistics)Public relationsEconomicsMicroeconomicsPolitical sciencePsychologyFinance

Abstract

fetched live from OpenAlex

Management researchers have investigated how corporate governance mechanisms influence corporate social responsibility (CSR). The previous literature has been largely based on agency theory, which emphasizes the roles of effective monitoring and incentive alignment, but the empirical evidence has been mixed. This inconsistency may result from the assumption that each governance mechanism functions independently, even though they interact with one another to affect CSR. On the basis of a perspective of bundle of governance mechanisms, we examined whether multiple governance mechanisms act as complements or substitutes for each other in promoting CSR. Using a panel sample of U.S. firms for the years 2004 to 2010, we found that multiple governance mechanisms mainly act as substitutes to promote CSR. Our findings suggest that a similar level of CSR can be achieved with different combinations of governance mechanisms. Our study contributes to the fields of both corporate governance and CSR in theory and practice.

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)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0040.008
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.048
GPT teacher head0.266
Teacher spread0.218 · 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

Citations196
Published2016
Admission routes1
Has abstractyes

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