The impact of firm characteristics on dividends in Jordan: Institutional ownership as moderating variable
Bibliographic record
Abstract
The objective of this research was to look at how firm attributes like age, size, as well as profitability affected the number of dividends paid. It also looked at how institutional ownership affected the connection between all these corporate characteristics as well as dividend payments as a moderating factor. A sample of forty publicly traded industrial businesses that were listed between 2016 and 2020 on the stock exchange in Amman were included in the research. The research analyzed the variables utilizing acceptable descriptive statistical techniques and used a model of multiple regression to test its predictions. The study's conclusions demonstrated that a company's size, years of existence, and income all positively affect dividend payments. Additionally, it found that corporate ownership had a strong correlation with dividend influence, as did both firm size as well as profitability. On the other hand, it discovered a negative correlation between the age of the firm as well as institutional ownership in terms of dividend effect. The research concludes with a proposal that Jordanian industrial enterprises should take size, years of operation, and profitability into account when determining how much dividend to pay out, acknowledging their important roles as well as effects on dividend distribution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".