数字经济
数据库事务
过程(计算)
零工经济
计算机科学
价值(数学)
交易成本
业务
经济
经济
万维网
数据库
财务
机器学习
服务经济
操作系统
作者
Guowei Zhu,Jing Huang,Jinfeng Lü,Yingyu Luo,Tingyu Zhu
标识
DOI:10.1016/j.techfore.2023.123018
摘要
In the current wave of digital technology that continues to innovate platform business models, an increasing number of gig economy platforms are deploying algorithms to optimize and reshape legacy transaction processes and create new value for multi-stakeholders. Nevertheless, algorithmic management also leads to many unforeseen dark sides for multiple participants in the practice, compromising their rights and interests (e.g., price discrimination, labor process control, and privacy concerns). Accordingly, this study aims to examine the negative implications of the introduction of digital technology in platform innovation within gig economy platforms, specifically focusing on the dark sides of algorithmic management, from a multi-sided platform perspective. Through a series of interviews with multi-stakeholders of Meituan Takeaway, the largest food-delivery platform in China, and secondary data analysis based on rooting theory, we develop a theoretical framework to deepen the understanding of the dark sides of algorithmic management and provide valuable insights for platforms seeking to optimize their operations management.
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