The role of corporate governance mechanisms, debt policy, profitability, and corporate social responsibility in strengthening company financial performance
Bibliographic record
Abstract
This research seeks to thoroughly examine the factors influencing the financial performance of firms listed on the SRI-KEHATI index of the Indonesia Stock Exchange from 2019 to 2023. This study employs a quantitative methodology utilizing the Ordinary Least Squares (OLS) technique to examine the impact of corporate governance mechanisms (specifically the presence of an audit committee and independent commissioners), profitability, corporate social responsibility (CSR) disclosure, and debt policy on financial performance of companies. The sample was chosen by purposive sampling to guarantee that the examined data aligned with the study's aims. The findings demonstrate that profitability, CSR disclosure, and debt policy have a favorable and substantial influence on firm financial performance. The presence of an audit committee has a substantial detrimental effect, while independent commissioners do not substantially influence financial performance. These results underscore the significance of agency theory, emphasizing the critical role of oversight measures and external openness in mitigating conflicts of interest between management and shareholders. In the realm of sustainability, these findings underscore the perspective that effective corporate governance and the incorporation of CSR initiatives transcend mere normative responsibilities. These techniques provide long-term methods for generating sustained economic benefit when executed correctly. This study's practical implications urge organizations to enhance internal supervision and strategically manage debt and CSR policies to foster responsibility and sustainably improve financial performance.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".