This dissertation explores the impact of diversity, intersectionality, and diversity management on job satisfaction within the federal workforce. The three constituent studies use disaggregated ethnoracial data from the Federal Employee Viewpoint Survey (FEVS) to examine the effects of demographic congruence, demographic heterogeneity, and perceptions of diversity management practices on the outcome variable of job satisfaction.
The first study tests the effects of demographic congruence (representation) and heterogeneity (diversity) on job satisfaction across federal agencies for members of different ethnoraces by employing mixed-effects models to a combination of 2020 FEVS data and FedScope data on agency-level demographics. Findings from this study show that increased demographic congruence is positively associated with job satisfaction for all minority groups and that demographic heterogeneity, in contrast, presents a more complex relationship, where initial increases in diversity are linked to lower job satisfaction but later rebound past a certain threshold. The second study explores how intersectional identities—race and gender—influence job satisfaction and are mediated by perceptions of DEI management. By using mixed-effects models on 2022 FEVS data, the results show that minority status is generally associated with higher job satisfaction but that gender and perceptions of DEI Management moderate this relationship. For all ethnoracial groups and genders, perceptions of positive DEI management—especially equity and inclusion—are positively associated with job satisfaction. The third study employs Random Forest models on 2022 FEVS data to predict job satisfaction based on demographic and job-related factors. All models achieve high predictive accuracy across various racial and gender subgroups, with intrinsic work experience, job inspiration, satisfaction with pay, and personal attachment to the organization emerging as the most influential factors for all. Noticeable differences between ethnoracial and intersectional groups emerge. These results highlight the potential for AI techniques to enhance public administration by offering practical tools for HR managers to proactively address issues related to employee satisfaction, especially as it pertains to specific populations.
This dissertation advances the theoretical understanding of social identity and diversity management while offering practical guidance for improving job satisfaction in the federal workforce. All three studies show that targeted and effective DEI management practices can improve employees' job satisfaction. As public managers respond to policy changes and adjust their approach to diversity, this research can help improve data-driven strategies to better address their workforces’ needs.