Carrie Zhang has been accepted for publication in the Journal of Organizational Behavior

Carrie Zhang, Associate Professor of Management at the Mike Ilitch School of Business, had her publication "Perceived algorithmic evaluation and app-worker's service performance. The role of flow experience and challenges of gig work," accepted in the Journal of Organizational Behavior.

The study explores the impact of perceived algorithmic evaluation (PAE) on service performance among app-workers. It introduces a new method for measuring PAE, investigates how flow experience mediates this relationship, and integrates conservation of resources theory and flow theory. Results show PAE positively influences flow experience and service performance but decreases when faced with viability challenges.

Abstract:

Algorithmic evaluation is becoming more common among app-workers. However, there's limited research on how app-workers' perceptions of these evaluations (perceived algorithmic evaluation, or PAE) affect their service performance. Our study fills this gap in three important ways. First, we introduce a new way to measure PAE among app-workers. Second, building on the flow theory, we explore how app-workers' flow experience mediates the relationship between PAE and service performance. Third, integrating the conservation of resources theory and flow theory, we examine how viability challenges might reduce the positive impact of PAE on app-workers' flow experience. Using both interviews and surveys, our research reveals that PAE positively influences app-workers' flow experience and, in turn, their service performance. Notably, we find that when app-workers face more viability challenges, the positive effects of PAE on app-workers' flow experience and service performance decrease. Our findings indicate the importance of algorithmic evaluation in shaping app-workers' work experience and outcomes in the gig economy and offer significant theoretical and practical implications.