Integrated reporting, corporate governance, and financial sustainability in Islamic banking
Bibliographic record
Abstract
This research delves into the intricate nexus between integrated reporting, corporate governance, and financial sustainability in Islamic banking. The study scrutinized a collection of research spanning diverse geographies and periods, emphasizing factors like board dynamics, audit committee proficiency, sustainability disclosures, and the implementation of value-centric strategies. The distillation of insights from an initial pool of 173 studies, which was meticulously narrowed down to 30 through rigorous criteria, indicates a prevalent positive association between these determinants and the financial robustness of Islamic banks. Such findings accentuate the pivotal role of syncing banking operations with the intrinsically sustainable tenets of Islamic finance. This harmony can notably spur sustainable development, potentially drawing more investors and boosting the stature of the Islamic banking domain. Furthermore, this study sheds light on potential avenues for upcoming research, including the analysis of managerial competencies' influence on varying Corporate Social Responsibility (CSR) classifications and the examination of the ramifications of sustainability benchmarks, cultural variances, legal structures, and Islamic statutes in diverse nations. This investigation provides critical insights for professionals and decision-makers in Islamic banking, facilitating a deeper understanding of practices that strengthen financial sustainability.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".