Accounting culture and the quality of financial reporting: Corporate governance as a moderator in Palestinian and Jordanian banking sectors
Bibliographic record
Abstract
This research presents a hypothesis suggesting that cultural values (conservatism, professionalism, confidentiality and consistency) affect the quality of financial reporting in Palestinian Jordanian banks. It also investigates the moderating role of corporate governance in such a relationship, a gap that is often mentioned in literature on how cultural values interplay with governance mechanisms in emerging markets. The study had an ex-post facto quantitative, cross-sectional plan on a sample of 380 high-ranking employees from the 33 banks in Palestine and Jordan that were chosen through proportionally stratified random sampling. Information was obtained through a validated questionnaire, and analysis was done using Stata software. Direct and moderating effects were tested using multiple linear regression analysis (MLR) and structural equation modeling (SEM). The results indicate that conservatism, professionalism, and consistency had a strong positive impact on financial reporting quality (p < 0.01), while confidentiality had an insignificant influence. Corporate governance strengthened professionalism and conservatism, verifying its moderating effect in transferring cultural values into better reporting quality. All these relationships were well supported in SEM Model fit, validating the stability of the hypothesized model both in theory and in data. This study enriches the cross-cultural accounting literature by empirically linking accounting cultural values with financial reporting quality through governance mechanisms in Arab banking contexts. It extends Institutional and Stakeholder theories, demonstrating that ethical culture and effective governance can jointly sustain transparency and accountability in emerging economies.
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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 | 0.011 |
| 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 | 0.002 |
| 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".