Dark side of algorithmic management on platform worker behaviors: A mixed‐method study
基于1362名外卖骑手的实验和21名骑手的质性研究，发现高强度的算法管理会降低服务质量并抑制推荐行为，而高工作负荷能缓冲这种负面影响。
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.