Corporate Governance Quality and Cash Conversion Cycle: Evidence from Jordan
Bibliographic record
Abstract
This study aims at examining the impact of corporate governance quality on cash conversion cycle (CCC) in Jordan. Using OLS regression for a sample of all industrial companies listed on Amman Stock Exchange during the period (2009-2013). The results revealed that CCC is affected negatively by corporate governance quality, which provides an implication to industrial companies in Jordan to boost their compliance with corporate governance code in order to improve their working capital management efficiency. Furthermore, the outcomes showed a variation in corporate governance categories between sub-samples, which supports contingency theory that rejects the approach of “one size fits all”. The findings provide implications for future studies to deal with firm characteristics as context dependent rather than simply as control variables. The results also provide implications for regulatory bodies in Jordan that highlight the importance of “comply or explain” approach to some corporate governance rules embracing the “one size does not fit all” approach. This study fills a gap in the existing literature by studying the quality of corporate governance and by using the context dependent approach.
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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 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".