Effectiveness of the board of directors' performance in Jordan: The moderating effect of enterprise risk management
Bibliographic record
Abstract
This study aims to investigate the moderating effect of enterprise risk management on the relationship between the board of directors’ effectiveness on accounting and market performance in Jordan. The current study uses panel data of 684 firm-year observations, employed regression analysis and analysis of annual reports of 76 listed companies on the Amman stock exchange (ASE) from 2009 to 2017 covering 9 years. The findings of the hierarchical regression analysis showed that the enterprise risk management has a significant positive moderating effect on the relationship between the board of directors’ effectiveness on accounting and market performance in Jordan. The findings reveal that enterprise risk management positively moderated the relationship between board of directors’ effectiveness on Return on Assets, Return on Equity, and Tobin’s Q. It also moderated the interaction of board of directors’ effectiveness intercept enterprise risk management on Return on Assets and Return on Equity, which were found positive and significant. The findings of this paper can provide crucial conclusions and recommendations that clarify the relationship between the board of directors’ effectiveness and the accounting and market performance in Jordan and the moderate impact of the enterprise risk management.
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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 | 0.004 | 0.009 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".