Executive personality and sustainability: Do extraverted<scp>chief executive officers</scp>improve corporate social responsibility?
Bibliographic record
Abstract
Abstract We utilise IBM's Watson Personality Insights service to infer chief executive officers' (CEOs') Big Five personality traits and examine whether CEO extraversion, an important personality trait associated with assertive behaviour, decisive thinking, and desire for social engagement, is associated with firms' corporate social responsibility (CSR) practices. Using a longitudinal dataset of Standard & Poor 500 firms for 2008–2016, we find that firms led by extraverted CEOs' experience higher CSR performance (both environmental and social), even after controlling for other personality traits and other CEO‐ and firm‐specific characteristics. In addition, we find that the relationship between CEO extraversion and CSR performance is more pronounced among industries with higher environmental impact. Consistent with upper echelons theory, our results suggest that firms' strategic environmental and social decisions are significantly influenced by the personal characteristics of corporate executives.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".