The effect of CEO’s social relational and moral capital on board process and performance of socially responsible company
Bibliographic record
Abstract
This study investigates the effects of stakeholder relations quality, and the social and moral capital of CEOs on the board processes and performance of socially and environmentally responsible companies. Data is collected from 40 companies listed on the Sri-Kehati Index of the Indonesia Stock Exchange and evaluated under the PROPER program by the Ministry of Environment Indonesia. Using GeSCA for analysis, results show that CEO’s relational and moral capital significantly impact board processes and performance. The quality of stakeholder relationships is more pronounced at the individual CEO level than the company level. Further analysis indicates that CEO’s relational capital strengthens the relationship between their moral capital and stakeholder relationship quality at the company level. Additionally, while the CEO’s relational capital significantly affects both board processes and performance, the CEO’s moral capital and the company’s responsible status only significantly impact board performance. Mediation analysis reveals that the CEO’s relational capital significantly mediates the relationship between the CEO’s moral capital and the company’s responsible status, affecting board processes. The findings underscore the importance of CEO’s relational capital at both individual and company levels for socially and environmentally responsible companies.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".