Corporate Governance and Accounting Performance: A Balanced Scorecard Approach
Bibliographic record
Abstract
This paper is motivated by the financial reform plan implemented in the Egyptian banking sector to enforce good corporate governance practices and improve performance. The study examines the association between governance quality and performance by estimating OLS regression models to test this relation. We measure governance as a multidimensional composite index comprised of board and ownership structure characteristics, while bank performance is measured using the Balanced Scorecard approach including financial and non-financial measures. Empirical evidence shows that governance has positive and significant impact on Egyptian bank performance. In particular, for the board structure, evidence shows that more executive directors on the board will enhance employee’s productivity. We find that board size is an insignificant determinant for bank performance; however, small board size is a significant determinant for better customer-related performance and improved employee productivity. CEO/Chairman duality is unrelated to bank performance, financial and non-financial performance. As for ownership structure, direct foreign investment in Egyptian banks should be encouraged, as there is evidence that foreign ownership has favorable impact on bank performance especially on employee productivity. Ownership concentration adversely affects bank performance index, and has unfavorable effect on employee productivity. Finally, institutional ownership is a marginal determinant of employee productivity.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".