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| Managerial Characteristics and Corporate Innovation-evidence Based on SGBT Algorithm |
| LIU Shiqi1, XIE Tianmeng2
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1. School of Management and Economics, Tianjin University, Tianjin 300072, China;
2. School of Economics, Qingdao University, Qingdao 266061, China |
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Abstract The personal characteristics of top executives and corporate innovation have become a key research focus in corporate finance. While existing studies primarily examine causal relationships, few explore the predictive ability, mechanisms, and patterns of executive characteristics on innovation levels. This study employs the Stochastic Gradient Boosting Tree (SGBT) algorithm to analyze the predictive power of executive characteristics. Results show that executive characteristics, particularly compensation incentives, tenure, and overconfidence, strongly predict corporate innovation levels, with nonlinear (interval) effects. These findings highlight the importance of executive characteristics in forecasting innovation.
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Received: 19 November 2024
Published: 14 July 2026
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