Dark side of algorithmic management on platform worker behaviors: A mixed-method study
Ying Lu, Miles M. Yang, Jianhua Zhu, Ying Wang
Human Resource Management · 2024 · Volume 63 · Issue 3
Abstract
This research investigates the impact of algorithmic management on worker behaviors, focusing on workers' commitment to service quality and referral tendencies. Drawing upon the job demands-resources model, we argue that high levels of algorithmic management could create hindrance demands that impede service quality and demotivate referral behaviors. We propose that high workload, as a challenge demand, buffers the negative effects of algorithmic management on worker outcomes. We find support for our proposed research model in an experiment with a sample of 1362 platform-based food-delivery riders. We also conduct a qualitative study with 21 riders, which provides a more nuanced understanding of how algorithmic management affects workers' attitudes, behaviors, and referral tendencies.
Keywords
algorithmic management, commitment to service quality, job demands-resources model, platform worker, referral tendencies
Enable JavaScript for citation tools and additional paper interactions.