The Effect of Corporate Governance in Islamic Banking on the Agility of Iraqi Banks
Bibliographic record
Abstract
The primary purpose of the research is to investigate the effect of the quality of corporate governance in Islamic banking on the agility of Iraqi banks. For this purpose, the structural-equation-modeling (SEM) method was used to investigate the effect of independent variables on the dependent variable. The statistical population of this study is all managers, employees, and customers of the public and private banks of Iraq, and a total of 70 questionnaires were included and analyzed to test the paper’s hypotheses. The research results indicate that corporate governance in Islamic banking has a positive impact on the agility of Iraqi banks, meaning that with an increase in corporate-governance mechanisms in Iraqi Islamic banking, the capability of banks to make timely reactions to potential changes is likely to increase. In this regard, the provision of various services in a flexible and snap manner to a wide range of customers, the acceptance of innovation and IT-related processes, the identification and application of environmental opportunities, and having a culture of learning and cooperating are expected to be realized by improving the quality of corporate-governance mechanisms. Our findings may apply to policymakers to improve market efficiency through designing regulations and bank managers to increase their general performance. The current paper is among the initial attempts to determine the influential factors on bank agility in emerging markets.
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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 | 0.002 | 0.011 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".