Revisiting the Relationship Between CEO Characteristics and Firm Internationalization: Evidence From a Machine Learning Approach

Cong Cheng, Yawen Lin and Jian Dai

Managerial and Decision Economics, 2025, vol. 46, issue 5, 2855-2868

Abstract: This study leverages machine learning (ML) techniques to assess the impact of CEO characteristics on the international performance of firms. Analyzing data from Chinese listed companies between 2008 and 2021, this study evaluates 14 ML algorithms and identifies the random forest model as the most effective. Additionally, the SHapley Additive exPlanations (SHAP) algorithm is employed for result interpretation and visualization. The findings indicate that most CEO traits can predict a firm's international success. Notably, international experience, age, and CEO duality emerge as the top predictors. Specifically, both international experience and CEO duality positively influence performance, while the CEO's age exhibits a complex, non‐linear relationship with performance. This study provides a nuanced perspective on how CEO characteristics influence a firm's international success.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/mde.4507

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:mgtdec:v:46:y:2025:i:5:p:2855-2868

Access Statistics for this article

Managerial and Decision Economics is currently edited by Antony Dnes

More articles in Managerial and Decision Economics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().