Women Executives and Off-the-Job Misconduct by High-Profile Employees:
A Study of National Football League Team Organizations
[Forthcoming, Journal of Organizational Behavior]
Chris Robinson, J.D., Tulane University
The risk of off-the-job misconduct by high-profile employees is a serious concern of top management in professional sport organizations, media and entertainment companies, and public-facing entities in the government and education sectors. Yet there is little research on how to prevent or mitigate this form of misconduct in organizations. Utilizing upper echelons theory and the literature on demographic composition, we examine the relationship between the gender composition of executives of team organizations in a men’s professional sport league, and subsequent misconduct by players on those teams. Specifically, we employed multilevel and logistic regression analyses to unique data on U.S. National Football League team organizations, and we found that firms with a critical mass of women executives experienced fewer player arrests. No support was found for executive power as a moderator of this relationship. We discuss the implications of our findings for the demographic composition literature. We also offer guidance for preventing and managing off-the-job misconduct by high-profile employees.
The authors would like to express their gratitude to Myrtle Bell, Alison Konrad, Shane Sanders, and Rick Welsh, who provided very helpful feedback on earlier drafts of the paper. They also thank Timothy Bryant and Justin Mattingly for their capable research assistance. The first two authors accessed the data on employer EEO-1 filings as unpaid researchers on temporary assignment with EEOC through an Intergovernmental Personnel Act (IPA) agreement. As part of this agreement, they entered into a confidentiality agreement which prohibits disclosure of any individual team organization data. The authors thank Ron Edwards, Patrick Davis, and Moriah Willow of the U.S. Equal Employment Opportunity Commission for assistance with this data.