Examining the Influence of Corporate Governance on Working Capital Management: Insights from Malaysian Public Listed Companies in Selangor
Bibliographic record
Abstract
Corporate governance and working capital management (WCM) are treated as essential subjects in financial management. Many researchers have studied the influence of corporate governance, but only a few of them have connected it with WCM efficiency. Particularly in Malaysia, there has been little concentration given to the relationship between corporate governance attributes and the WCM of the companies. Therefore, the present study intends to analyse the impact of corporate governance represented by CEO tenure, CEO Duality, Board size and Audit Committee on WCM represented by the current ratio of 35 Selangor-based companies which are listed under the FTSE Bursa Malaysia Top 100 Index.The results from this study show that CEO tenure has a significant negative impact on the current ratio, while CEO duality has a positive impact on the current ratio. Moreover, board size has no significant impact on the current ratio, and the audit committee has a significant positive impact on the current ratio. These findings imply that effective corporate governance mechanisms can significantly affect WCM. The result is expected to enable the owners of the firms to improve their corporate governance practices to enhance WCM efficiency and, furthermore, contribute to the enhancement of the profitability of the firms and maximise shareholders' wealth indirectly. Additionally, the findings from this study can also be a guide for good corporate governance' criteria that significantly affect the efficiency of WCM to be practised by other companies, including SMEs and other organisations.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".