2021 Funded Research

UTILIZING COMPUTER VISION AND MACHINE LEARNING TECHNOLOGIES TO REDUCE RACIAL HIRING INEQUALITY IN THE AMERICAN LABOR MARKET*

Organizations are increasingly engaged in diversity, equity, and inclusion initiatives. In response to social and political unrest, industry leaders are grappling with how to manage uncomfortable conversations and initiate necessary work in service of their underrepresented employees. With these initiatives comes reflection and revision around hiring and selection. It is within this space that my research calls attention. Implicit bias, microaggressions and other expressions of prejudice present themselves in selection decisions. Previous work addresses these biases at varying stages of the selection process, from application reviews to face-to-face job interviews. Yet, less attention has centered on the biases present in viewing applicant photos, particularly applicant attire in online job search platforms. In this work, I focus on job seeker attire in online job-seeking profile photos. I examine how varying signals of professionalism through attire in profile photos present unique challenges for minority applicants. For example, I consider the extent to which attire may positively or negatively impact the likelihood of employment. From this work, I hope to draw attention to hiring discrimination in a novel form by considering how decision makers examine online profile photos – an issue that is particularly relevant in the digital age of job selection.

Research conducted by Tiantian Yang, Assistant Professor, Department of Management, The Wharton School.

*This proposal was awarded funding from the new partnership with Deloitte and the Center for Leadership and Change Management 

WHAT DOES NOT KILL YOU MAKES YOU STRONGER: HOW DO PAST EXPERIENCE OF OVERCOMING ADVERSITY LEAD TO BETTER PERFORMANCE AT WORK INSTEAD OF BURNOUT?

Organizational leaders and followers alike gain skills and “toolkits” that they use to navigate organizational life from their past experiences in life (Martin & Cote, 2019). However, not everyone has the same past experiences. Whereas some organizational members may come from relatively adversity-free backgrounds, others may have overcome various forms of adversity in the past. How do these past experiences of overcoming adversity shape the ways organizational members effectively navigate and lead organizations? The limited organizational scholarship on past adversity has characterized it as something to cope with, positing that how past adversity is perceived is key to organizational member’s coping effectiveness (Stephens, Townsend, Hamedani, Destin, & Manzo, 2015; Vogel and Bolino, 2020). Yet artists, popular press, and lay theory have long professed German philosopher Frederick Nietzsche’s aphorism that “what does not kill you makes you stronger.” We will build on theories of work enrichment (Greenhaus & Powell, 2006; Rothbard, 2001) and post-traumatic growth (Vogel & Bolino, 2020) to empirically examine how overcoming adversity in the past can make employees “stronger” in organizations.This will be done via a series of experiments and field studies.

Research conducted by Arianna Beetz, Doctoral Candidate, The Wharton School, The University of Pennsylvania.

WHEN HELPING HURTS: ANTICIPATORY AND REACTIVE HELPING, RECIPIENT SELF-THREAT, AND HELPER OUTCOMES

Organizational research has documented how those who help receive positive treatment and outcomes in return (e.g., Podsakoff et al., 2009). However, because the literature suggests that most helping at work is reactive (i.e., employees give assistance after an explicit request), it has prevented thorough investigation of anticipatory helping—anticipating the needs of others and offering or providing assistance without being asked. We argue that such anticipatory helping may result in less positive outcomes for helpers. Through a series of experiments and field studies, we are examining why and when help recipients react more negatively toward helpers who engage in anticipatory helping. By doing so, we more precisely identify the distinct forms of helping at work (anticipatory vs. reactive) and when they lead to more (versus less) beneficial outcomes for helpers.

Research conducted by Michael Parke, Assistant Professor of Management, The Wharton School, University of Pennsylvania.