Date of Award

2020

Document Type

Dissertation - Open Access

Degree Type

Dissertation

Degree Name

Doctor of Business Administration (DBA)

Advisor(s)

Robert C. Ford

Second Advisor

Henrique Correa

Third Advisor

James Johnson

Abstract

This study is aimed at investigating the relationship between conscious, social, and unconscious biases and the employment offer decision to add a new understanding of interviewer bias for or against military veterans by assessing the degree to which military service experience influences hiring managers’ selection decisions in U.S. organizations. The importance of this study is to add new practical and theoretical understanding to interviewer bias for this segment of the population. An experimental study was utilized for this research, which included a scenario-based experiment to investigate how different treatments, curriculum vitae (CV), influenced hiring managers’ employment offer outcomes. Specifically, this research sought to determine how CVs with the presence or absence of military service influenced a selection decision. ANOVA was utilized to test if the different treatment groups were statistically different from each other with regards to an employment offer decision (DV), and multi-group regression analysis was done using SEM PLS in the analyses of this study. Data revealed social biases were significant influences on hiring decisions where social peer pressure and conformity may result in participants offering socially desirable answers. Additionally, unconscious bias did not moderate the relationship between conscious and social bias, however, unconscious biases were discovered through the use of adapted conscious and social bias measurement scales for military veterans. Additional analysis of the conscious and social bias scales uncovered hidden biases that the IAT measure failed to reveal. It is anticipated that the results of this study will add new and fresh insights into the potential biases that military veterans encounter and will address an overarching issue of bias in the selection process.

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