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Record W4404695168 · doi:10.3390/jrfm17120534

Do Long-Term Institutional Shareholders Always Vote in Favour of Board Recommendations? The Moderating Effect of Cash Holdings

2024· article· en· W4404695168 on OpenAlexvenueno aff
Abdulaziz Ahmed Alomran

Bibliographic record

VenueJournal of risk and financial management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsShareholderTerm (time)BusinessCashAccountingInstitutional investorMonetary economicsCorporate governanceFinanceEconomics

Abstract

fetched live from OpenAlex

This article aims to examine the voting behaviour of long-term institutional shareholders towards board recommendations on management proposals and resolutions and how the potential agency costs could moderate such voting behaviour. This study is conducted using all corporate capital proposals put to vote by management during the annual general meetings (AGM) of publicly listed firms on the London Stock Exchange over a period of 17 years from 2000 to 2016. Building on agency theory and the concept of the monitoring function of institutional shareholders, this study finds that long-term institutional shareholders do support board recommendations on management proposals, but potential agency concerns linked to excess cash holding can negatively moderate this relationship. Additional analysis reveals that this moderating effect is observed only for management proposals related to cash inflows, specifically after the 2007–2009 financial crisis. This study highlights the importance of long-term institutional shareholders actively monitoring firms’ cash holdings and using voting to address agency concerns while advising corporate managers to optimise cash management and stay attuned to shareholder preferences. For policymakers, the research suggests promoting transparency in corporate governance and strengthening shareholder engagement to reduce agency problems and improve governance. Several robustness tests are conducted, and the results support our predictions.

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)0.004
metaresearch head score (Gemma)0.032
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.232
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

Citations3
Published2024
Admission routes1
Has abstractyes

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