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Record W4306678354 · doi:10.22146/gamaijb.65194

Insiders, Outsiders and Performance of Vietnamese Firms

2022· article· en· W4306678354 on OpenAlexaff
Richard Beason, Tu Thi Thanh Tran, Dong Phuong Dao, Hong Minh Nguyen

Bibliographic record

VenueGadjah Mada International Journal of Business · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVietnameseInsiderBusinessCreditorAccountingMonetary economicsStock (firearms)Stock marketState ownershipFinancial systemFinanceEmerging marketsEconomicsDebt

Abstract

fetched live from OpenAlex

The consensus in the finance literature is that a large proportion of inside ownership (defined as greater than 5% share ownership by non-institutional holders, managerial holdings, founding family holdings, cross-shareholdings by affiliated firms and ownership by creditors) tends to be associated with more unsatisfactory performance (as measured by ROE or ROA) when compared to firms with lower inside ownership, all else equal. However, this need not be the case if insiders act as monitors of the firm and have the same interest in returns as outsiders. Ownership structure and firm level financial performance have not been widely studied in Vietnam. Using data from 729 listed firms in Vietnam for 2018, we test the hypothesis that greater insider ownership has a negative impact on firm performance. We found that Vietnam's insiders play a monitoring role, exercising their relative power to ensure the firm's profitable functioning. These findings are inconsistent with research on Japanese groupings, as well as other findings. The Vietnamese stock market does not appear to be negatively affected by insider influence; indeed, insiders appear to act as positive monitors.

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 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 score0.046
Threshold uncertainty score0.436

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 head0.014
GPT teacher head0.203
Teacher spread0.189 · 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 teacher head, 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

Citations2
Published2022
Admission routes1
Has abstractyes

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