Purpose

Working as a freelancer in the gig economy has become an emerging trend in the contemporary working world. Specifically, the number of professionals offering their expertise to companies via freelancing platforms is increasing. Despite the “neutral” character of this new type of labor market, promoting a straightforward service-focused hiring process and emphasizing qualification-related and job-related criteria over personal criteria, there are mounting complaints of freelancers feeling unfairly treated and discriminated against on these platforms. Yet, research on discrimination on freelancing platforms is scarce, offering meaningful future research directions. The first research project within this cluster focuses on algorithmic HRM practices on freelancing platforms  . A second research project addresses (self-)discrimination of freelancers in the gig economy. The projects in this cluster aim to provide relevant implications for employers, freelancers, and policymakers seeking to reduce inequality.

Approach

The research projects within this cluster contain several studies utilizing different methodological approaches. For example, we conducted a field study with more than 44,000 freelancer profiles from one of the world’s largest online freelancing platforms. Furthermore, experimental studies will be conducted to gain insights into the mechanisms and behavioral patterns of the parties involved.

Keywords

Gig economy, discrimination, self-discrimination, AI, algorithmic HRM, algorithmic bias

Involved Persons

Yannik Trautwein, Dr. Ellen Weber, Felix Zechiel, Prof. Dr. Marion Büttgen, Prof. Dr. Kristof Coussement, Prof. Dr. Matthijs Meire