Empirical Study of the Relationship between Ownership Structure and Firm Performance: Some Evidence of Listed Companies in Tehran Stock Exchange
Bibliographic record
Abstract
The study of effective factors seems essential since, the operation of profiting entities is very important in the decision of internal and external organization users. The effect of various factors on the assessment scale of operation was measured in different researches, e.g. the structure of ownership. In this study, the relationship between three kinds of various structures of ownership including the structure of shareholder's ownership and other firms and the structure of state ownership Q Tobin's operation scale of listed firms in TSE was considered. The effect of firm's age and size has considered as two control variables on the Q Tobin's operation scale. In this study, the statistical population is listed firms in Tehran Stock Exchange (TSE).Theories are tested by multilateral Regression on the basis of T and F statistics. Finding shows that Q Tobin operation scale has significant relationship with two kinds of investment organization's ownership scale and other companies and state ownership, but it does not have significant relationship with minor shareholder's scale. Age and size of firms do not effect on Q Tobin operation scale as two control variables.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".