The Impact of Corporate Governance Practices on Financial Performance in Western Balkan Countries
Bibliographic record
Abstract
This study focuses on assessing the impact of the corporate governance practices of seven Western Balkan countries on their financial performance.Specifically, to investigate the specific relationship between them, we used measures of corporate governance such as the index of disclosure, liquidity and leverage, while to assess financial performance, we utilised return on assets and return on equity.We applied quantitative methods using secondary data.The data were extracted from the published reports of institutions such as the World Bank (WDI), the International Monetary Fund, and the central banks of the respective countries, as well as case studies and foreign literature in this field.Linear regression, fixed-effects, random effects and trend analysis were used to test the hypotheses, and this study will cover a period of five years.From the generated results of the models, we can conclude that the financial leverage and the index of financial disclosures positively influence the financial performance of the Western Balkan countries.We present real and consistent results regarding corporate governance practices' impact on Western Balkan countries' financial performance.Extracting data from the reports of WDI and CB and adhering to international literature allows us to draw competent conclusions and recommendations in this area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".