Impact of Female Executive Power on Corporate ESG Performance: The Mediating Role of Managerial Self‐Interest
Bibliographic record
Abstract
ABSTRACT The significance of the responsibility fulfillment capability for environmental, social, and governance (ESG) is increasing, with ESG performance becoming increasingly pivotal for firms seeking to bolster their competitive edge. This study empirically examines the correlation and mechanism between female executive power and corporate ESG performance, using regression analysis to focus on A‐share listed firms from 2012 to 2022. The results demonstrate that female executive power has a positive correlation with corporate ESG and ES performance. This positive correlation is ascribed to the mechanism by which female executive power diminishes managerial self‐interest and improves corporate ESG and ES performance. Furthermore, corporate digital transformation and regional digital finance development have a positive moderating effect on this relationship. This study expands prior scholarship on the determinants of corporate ESG performance by investigating the impact of executive gender diversity. Moreover, it elucidates how female executive power influences corporate ESG performance. These findings provide empirical evidence and theoretical insights for firms seeking to enhance their ESG performance for sustainable development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".