Machine learning for predicting corporate violations: how do CEO characteristics matter?
Based on upper echelon theory, we employ machine learning to explore how CEO characteristics influence corporate violations using a large-scale dataset of listed firms in China for the period 2010-2020. Comparing ten machine learning methods, we find that eXtreme Gradient Boosting (XGBoost) outperfo...
| Authors: | ; ; ; ; |
|---|---|
| Format: | Electronic Article |
| Language: | English |
| Check availability: | HBZ Gateway |
| Interlibrary Loan: | Interlibrary Loan for the Fachinformationsdienste (Specialized Information Services in Germany) |
| Published: |
2024
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| In: |
Journal of business ethics
Year: 2024, Volume: 195, Issue: 1, Pages: 151-166 |
| Further subjects: | B
M48
B G30 B China B Aufsatz in Zeitschrift B K22 B Intentional violations B machine learning B CEO tenure B G38 B CEO characteristics B Violation severity B Corporate violations |
| Online Access: |
Volltext (lizenzpflichtig) Volltext (lizenzpflichtig) |
