How do corporate social responsibility and sustainable development goals shape financial performance in Indonesia's mining industry?
Bibliographic record
Abstract
This study aims to investigate and scrutinize the financial performance, represented by the Return on Asset (ROA), considering the mediating roles of Corporate Social Responsibility (CSR) and Sustainable Development Goals (SDGs). The sample selection method used purposive sampling, which used several criteria with the research object being the Mining industry listed on the Indonesia Stock Exchange and the National Center for Sustainability Reporting (NCSR) in 2020-2021. The data were sourced from secondary materials derived from several mining companies. The research employed Structural Equation Modeling (SEM) for data analysis. The results of the study indicate that: (1) CSR has a significant positive effect on SDGs; (2) SDGs have a significant positive effect on financial performance; (3) CSR has a significant positive effect on financial performance; and (4) SDGs can mediate CSR and financial performance. Companies should consider enhancing their CSR disclosure, as it is positively related to SDG achievement and financial performance. Moreover, regulatory bodies may encourage firms to adopt SDGs as part of their CSR initiatives, which could lead to both societal and economic benefits.
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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 | 0.002 | 0.007 |
| 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 | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".