Influential Factors on Profitability of Islamic Banks: Evidence from Sudan
Bibliographic record
Abstract
Profitability of Islamic banks has a significant effect on banks current and future decisions that do not only associate with shareholders and management, but also for various types of stakeholders. Despite that, scholars are not yet in agreement on common determinants of profitability in banking industry. This study aims to investigate the effect of bank-specific and industry characteristics along with macroeconomic variable (the inflation) on the profitability of a sample of 10 Islamic banks in Sudan. The study applied descriptive statistics, Persons’ correlation and multiple regression analysis on secondary data in order to determine the relationships and degree of significant of the independent variables to profitability. The profitability has been measured by two models; as return on assets (ROA) and net profit margin (NMP). The results reveal that bank capitalization (EQTA), operational cost efficiency (OCOI), investment in short-term securities (SECA) and inflation (INF) variables are significantly affecting the profitability of Islamic banks in Sudan. In contrary, the deposit-size of the bank (as market share) is not a significant determinant of banks’ profitability. Furthermore, the results indicate that quality of credit loan (NPL) is highly significant to NPM, while it is insignificant to ROA.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".