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Effect of Executives’ Vigilant Managerial Cognition on Enterprise Resilience: A Natural Language Processing and Machine Learning Analysis

Published online by Cambridge University Press:  15 July 2025

Chen Zhao ,
Chen Lin ,
Yonghong Liu  and
Zhonghua Gao Open the ORCID record for Zhonghua Gao [Opens in a new window]
Chen Zhao
Affiliation:
Beijing University of Posts and Telecommunications, China
Chen Lin
Affiliation:
Beijing University of Posts and Telecommunications, China
Yonghong Liu
Affiliation:
University of North Carolina at Greensboro, USA
Zhonghua Gao*
Affiliation:
Chinese Academy of Social Sciences, China
*
Corresponding author: Zhonghua Gao (gaozhh@cass.org.cn)
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Abstract

Resilient enterprises thrive under adverse conditions given their preparedness for crises. This study proposes that executives’ vigilant managerial cognition is essential for enhancing enterprise resilience. To measure this cognition, the study developed a textual index using machine learning methods and analyzed a sample of Chinese enterprises to assess the impact of executives’ vigilant managerial cognition on enterprise resilience. The findings indicate that this cognition is positively related to enterprise resilience, where the relationship is stronger in enterprises with robust internal controls. The primary contribution of this study is the conceptualization of vigilant managerial cognition and its established positive relationship with enterprise resilience. Furthermore, by introducing a novel quantitative measure of managerial cognition through textual analysis and machine learning, the study paves the way for future research on managerial cognition within firms.

摘要

摘要

具备韧性的企业通常能在危机前未雨绸缪,即便在逆境中也能维持发展势头。本研究表明,企业高管的忧患型管理认知对企业韧性的提升至关重要。我们首先通过机器学习方法,构造文本指标来衡量高管的忧患型管理认知。然后我们对中国上市公司的样本展开分析,检验高管忧患型管理认知对企业韧性的影响。结果发现高管的忧患型管理认知确实与企业韧性呈正相关系，而且对于内部控制较强的企业,该作用更强烈。本研究结合文本分析和机器学习构建了衡量管理认知的量化方法,为管理认知的后续研究提供了参考。

Keywords

enterprise resilienceinternal controlsmachine learningtextual analysisvigilant managerial cognition忧患型管理认知企业韧性内部控制机器学习文本分析

Information

Type
Article
Information
Management and Organization Review , Volume 21 , Issue 1 , February 2025 , pp. 102 - 130
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of International Association for Chinese Management Research.

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