Corporate governance, financial performance and sustainability disclosure: Evidence from Indonesian energy companies
Bibliographic record
Abstract
The research investigates the influence of corporate governance and financial performance on the disclosure of sustainability reports (DSR) in energy sector companies listed on the Indonesia Stock Exchange. The research population was 71 energy sector companies listed on the Indonesia Stock Exchange (IDX) for the 2017-2021 period, and 10 of the 71 companies that met the sample criteria were the unit of analysis. The data analysis method for the DSR determinant estimation model uses panel data regression analysis. The research results show that liquidity hurts DSR, while company size has a positive impact. Profitability, capital structure, foreign Ownership, and independent commissioners have yet to be proven to determine DSR. These findings demonstrate that corporate governance cannot encourage companies to carry out DSR according to stakeholder expectations as a legitimacy mechanism. Therefore, independent commissioners and foreign Owners can pressure companies to carry out DSR optimally by applicable regulations and achieve sustainable performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".