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Record W3190460335 · doi:10.3390/jrfm14080353

The Effect of Dividend Payment on Firm’s Financial Performance: An Empirical Study of Vietnam

2021· article· en· W3190460335 on OpenAlexvenueno aff
Anh Huu Nguyen, Đức Cường Phạm, Nga Thanh Doan, Trang Thu Ta, Hieu Thanh Nguyen, Tu Van Truong

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
FundersĐại học Kinh tế Quốc dân
KeywordsVietnameseDividendDividend policyBusinessPaymentStock marketDividend yieldFinancial economicsStock (firearms)AccountingEconomicsEconometricsFinance

Abstract

fetched live from OpenAlex

This research aims to investigate the effects of dividend policies on a firms’ financial performance. The paper explores the research gap and then builds a research model using ROA, ROE, and Tobin’s Q as dependent variables, dividend rate and decision of dividend payment as independent variables. The paper collected data and financial statements of 450 firms that are listing on the stock market of Vietnam from 2008 to 2019. The analysis results indicate that the decision of dividend payment has negative impact to Vietnamese firms measured by accounting-based performance but this improve market expectation on firms. In addition, the paper finds that Vietnamese firms are offering low dividend rate which has a positive impact on accounting-based performance but a negative effect on market expectation. This paper proposes some instructive recommendations based on the findings, including a more appropriate model of dividend policies, a lower dividend rate, and clear decision of dividend payment.

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)0.003
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 score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.236
Teacher spread0.225 · 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

Citations56
Published2021
Admission routes1
Has abstractyes

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