Effect of working capital management in Toronto exchange on oil and gas sector profitability / Noor Syazwani Hayati Azman
Bibliographic record
Abstract
Working capital is a crucial element in order to manage the liquidity of the firms effectively. Working capital used to track the asset and liabilities of companies. It is also necessary which helping companies to make short-term decisions. The aim of carried out this research is to examine the factor affecting working capital management of oil and gas sector in Toronto Exchange that is cash conversion cycle (CCC), current ratio (CR), debt ratio (DR) and sales growth (SG) toward the return on total asset (OI) of the firms. A panel data of 10 firms selected based on its price to book value consists of five (5) from oil and gas companies and another five (5) from energy services companies. This research will be conduct in period of fifteen (15) years that is from year 2002 to 2016. This research use Ordinary Least Square (OLS) method of analysing the panel data. From this, it will be estimate that the variables of cash conversion cycle (CCC) and sales growth (SG) will have a positive relationship with profitability of firms. While variables of current ratio (CR) and debt ratio (DR) will have a negative relationship toward return on total asset. Thus, the length of period taken to liquid their asset and sales generated by companies related to improve the performance of the firms.
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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".