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Dark side of algorithmic management on platform worker behaviors: A mixed-method study

  • Ying Lu
  • , Miles M. Yang
  • , Jianhua Zhu
  • , Ying Wang*
  • *此作品的通讯作者
  • Macquarie University
  • School of Economics and Management, Harbin Institute of Technology Weihai

科研成果: 期刊稿件文章同行评审

摘要

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.

源语言英语
页(从-至)477-498
页数22
期刊Human Resource Management
63
3
DOI
出版状态已出版 - 1 5月 2024

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