Determinants of Vietnamese Listed Firm Performance: Competition, Wage, CEO, Firm Size, Age, and International Trade
Bibliographic record
Abstract
This study investigates the relationship between firms’ competition, wage, CEOs’ characteristics, and firm performance (measured by net income per employee, return on assets (ROA) and return on equity (ROE)) of Vietnam’s 693 listed firms in 2015 using both the ordinary-least-square (OLS) and quantile regression methods. Triangulating the results coming from the analysis of three different measures of firm performance, this study consistently confirms that the sex of CEOs and chairman turns out to be insignificant in explaining firm performance and there is a negative association between capital intensity and firm performance. For financial firms, the age of a firm and average wage per employee are negatively associated with all types of firm performance. The quantile regression method shows that the age of a firm is negatively correlated with its net income per employee for small firms, while it is insignificant for medium-sized firms. Meanwhile, firm size is positively associated with firm performance. These results indicate Vietnam’s business activities are still concentrating on low labor cost, labor intensive, and low-tech production, thus, policies that promote innovation and high-tech applications should be encouraged.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".