This study aims to examine how CEO gender expectancy violations, such as when a CEO is female rather than the expected male, affect investors’ judgments. Despite diversity initiatives, female CEOs remain rare in the corporate world. Based on the expectancy violation theory (Burgoon, 1993) and role incongruity theory (Eagly and Karau, 2002), we predict that when investors expect a male CEO but observe a female CEO instead, they are prompted to verify her legitimacy by examining the company’s performance more closely.
We conduct a 2 × 2 between-subjects experiment with online participants, where we manipulate the CEO’s gender (male vs female) and the company’s performance quality (high vs low).
We find that when the CEO is female and unexpected, investors analyze the company’s financial performance more carefully and are more likely to differentiate between high- and low-quality performance compared to when the CEO is male.
This study contributes to the accounting literature by showing a potential benefit of gender diversity in corporate leadership for enhancing investors’ ability to distinguish performance quality. As companies are recruiting increasingly diverse leadership, this can lead to improved investor decision-making during the transition phase.
We use AI-generated images to manipulate CEO gender while holding all other attributes constant across conditions. This study is among the earliest accounting studies to use this method, and future studies can use our manipulation. In addition, we introduce a novel method for measuring individuals’ expectations about a person’s gender.
