Configurations of CEO Personality Characteristics, Power, and Board Fault Lines

This dissertation has two empirical essays that examine the impact of CEO personality on power, and the latter’s impact on board structure. I build upon past studies that have examined CEO personality and power as antecedents of firm-level outcomes to build and support the theoretical mechanisms that drive these relationships. Thus, this dissertation addresses a critical gap in personality, power, and governance research (see Hambrick, 2022; Ozgen, 2024). In essay 1, I draw upon research on upper echelons (Hambrick & Mason, 1984) literature, personality (Harrison et al., 2019), and CEO power (Finkelstein, 1992; Ozgen, 2024) to examine how configurations of personality characteristics impact CEO power. In essay 2, I draw upon self-verification (Swann, 1983; Zhu & Chen, 2015), resource complementarity theories (Barney, 1992; Pfeffer & Salancik, 1978; Wang et al., 2015), and board fault lines (Lau & Murnighan, 1998; Vandebeek, 2023) to examine how CEO power impacts board fault lines. I use machine learning to analyze CEO quarterly earnings calls and financial statements to generate a dataset that includes 9,284 CEO-year observations from S&P 1500 firms (from 2010 to 2019). The dissertation uses multiple methods, including fuzzy-set Qualitative Comparative Analysis, to examine how different configurations of personality traits lead to high power, followed by a statistical analysis of the impact of CEO personality under various power conditions on board fault lines. In essay 1, I show that distinct configurations of personality characteristics are pathways to high levels of CEO power. These personality configurations substitute for the expected findings based upon prior studies’ performance-based determinants of power. Essay 2 finds that CEO personality traits impact board fault lines in conjunction with CEO initial power and that the latter does not have a significant direct impact on its own. This dissertation makes several theoretical contributions. First, the findings of this dissertation advance upper echelons theory by identifying psychological mechanisms underlying executive power dynamics and challenging existing theoretical assumptions about the performance-power relationship. Second, it extends Finkelstein's (1992) power framework with support for how CEO personality and power influence board fault lines. Third, it integrates two competing theoretical perspectives that affect the CEO's influence on board composition. Finally, I contribute to governance research by showing the impact of CEO succession under conditions of varying initial power on board fault lines. The dissertation concludes with implications for governance practices and guidance for directors of firm boards.

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Publication Details

Journal
ODU Digital Commons (Old Dominion University)
Published
2025-09-18
DOI
https://doi.org/10.25777/9rp1-4j17
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Configurations of CEO Personality Characteristics, Power, and Board Fault Lines

ODU Digital Commons (Old Dominion University)
Geochemistry and Geologic Mapping
article

Configurations of CEO Personality Characteristics, Power, and Board Fault Lines

article en

Abstract

This dissertation has two empirical essays that examine the impact of CEO personality on power, and the latter’s impact on board structure. I build upon past studies that have examined CEO personality and power as antecedents of firm-level outcomes to build and support the theoretical mechanisms that drive these relationships. Thus, this dissertation addresses a critical gap in personality, power, and governance research (see Hambrick, 2022; Ozgen, 2024). In essay 1, I draw upon research on upper echelons (Hambrick & Mason, 1984) literature, personality (Harrison et al., 2019), and CEO power (Finkelstein, 1992; Ozgen, 2024) to examine how configurations of personality characteristics impact CEO power. In essay 2, I draw upon self-verification (Swann, 1983; Zhu & Chen, 2015), resource complementarity theories (Barney, 1992; Pfeffer & Salancik, 1978; Wang et al., 2015), and board fault lines (Lau & Murnighan, 1998; Vandebeek, 2023) to examine how CEO power impacts board fault lines. I use machine learning to analyze CEO quarterly earnings calls and financial statements to generate a dataset that includes 9,284 CEO-year observations from S&P 1500 firms (from 2010 to 2019). The dissertation uses multiple methods, including fuzzy-set Qualitative Comparative Analysis, to examine how different configurations of personality traits lead to high power, followed by a statistical analysis of the impact of CEO personality under various power conditions on board fault lines. In essay 1, I show that distinct configurations of personality characteristics are pathways to high levels of CEO power. These personality configurations substitute for the expected findings based upon prior studies’ performance-based determinants of power. Essay 2 finds that CEO personality traits impact board fault lines in conjunction with CEO initial power and that the latter does not have a significant direct impact on its own. This dissertation makes several theoretical contributions. First, the findings of this dissertation advance upper echelons theory by identifying psychological mechanisms underlying executive power dynamics and challenging existing theoretical assumptions about the performance-power relationship. Second, it extends Finkelstein's (1992) power framework with support for how CEO personality and power influence board fault lines. Third, it integrates two competing theoretical perspectives that affect the CEO's influence on board composition. Finally, I contribute to governance research by showing the impact of CEO succession under conditions of varying initial power on board fault lines. The dissertation concludes with implications for governance practices and guidance for directors of firm boards.

ODU Digital Commons (Old Dominion University)
Dominion University College (GH), Old Dominion University (US)
Openalex Percentile: Top 35%
Geochemistry and Geologic Mapping
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