Working Capital Management and Firms’ Profitability: Evidence from Vietnam’s Stock Exchange
Bibliographic record
Abstract
The paper investigates what effect Working Capital Management has on firms’ profitability by using the data from listed companies on Vietnamese Stock Exchange. The sample is collected from 127 public companies for the period of 9 years from 2006 to 2014. The research uses four variables to represent Working Capital Management, which are Day of Sales Outstanding (DSO), Day Sales of Inventories (DSI), Day of Payables Outstanding (DPO), and Cash Conversion Cycle (CCC). Moreover, in order to robust the result, the study also takes into the account the following variables: “Leverage, Growth, Tangibility, Size, Industrial Factors, and Macroeconomic Effects”, which were proven to have significant effects on firms’ profitability. The result implies that there is no correlation between Working Capital Management and firms’ profitability. Hence the conclusion is that Working Capital Management can help companies solve the short-term obligations and improve the efficiency by improving the supply chain and credit policies, however it has nothing to do with firms’ profitability of the companies in the sample.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".