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Record W1538173246 · doi:10.1108/cg-05-2014-0056

CEO social capital and contingency pay: a test of two perspectives

2015· article· en· W1538173246 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCorporate Governance · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsExecutive compensationSocial capitalContingencyCorporate governanceBusinessShareholder valueOriginalityCost of capitalShareholderEquity (law)AccountingEconomicsFinanceMicroeconomicsIncentivePolitical scienceSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Purpose – This paper aims to provide greater understanding of how the composition of pay reduces agency cost to the shareholders by examining how firms pay their chief executive officers (CEOs). More specifically, this study examines the relationship between CEOs’ social capital, measured as external directorships, and their contingency pay, the proportion of their compensation that depends on achieving long-term performance goals. Design/methodology/approach – The authors use a panel sample of Standard & Poor 500 CEOs to test two contrasting theoretical perspectives. From a board perspective, boards attempt to retain executives with more social capital working longer for the firms to utilize executives’ social capital and pay them more in the form of contingency pay. The CEO power perspective argues that CEOs wield social capital as a form of power to lower contingency pay in an attempt at preserving wealth. Findings – CEO social capital does not exacerbate agency pressures. Boards reward the long-term benefits of social capital accumulated by CEOs through higher proportions of contingency pay. Research limitations/implications – The authors considered CEOs of well-capitalized, publicly-traded US-based firms. So the results may not generalizable to other contexts. Practical implications – Boards do recognize and reward CEOs for their social capital, and use higher levels of contingency pay to lock in CEOs with social capital. Originality/value – This is the first study to explicitly examine the impact of CEO social capital on both non-equity and equity compensation.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.142
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.226
Teacher spread0.192 · 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