Gig to the left, algorithms to the right: A case study of the dark sides in the gig economy

• Published in: Technological forecasting & social change Vol. 199; p. 123018
• Main Authors: Zhu, Guowei, Huang, Jing, Lu, Jinfeng, Luo, Yingyu, Zhu, Tingyu
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.02.2024
• Subjects: Algorithmic management; Gig economy; Multi-sided platform; The dark sides; Gig economy; The dark sides; Multi-sided platform; Algorithmic management
• ISSN: 0040-1625; 1873-5509
• DOI: 10.1016/j.techfore.2023.123018

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. •Platforms have transformed from two-sided to multi-sided platforms by increasing the supply side, upgrading transaction business, and introducing digital technologies in the gig economy.•Algorithmic management enables continuous optimization of the cost, efficiency, and experience of the gig economy platform through algorithmic match, algorithmic control, algorithmic incentive, and algorithmic feedback, but it has dark sides for multi-stakeholders in the process.•These dark sides manifest in various forms and act on diverse objects in different stages of algorithmic operations, concerning privacy, personal autonomy, digital discrimination, algorithmic bias, and etc.•These dark sides reflect an imbalance in the trade-offs between platform interests and stake-holder rights in the introduction of innovative business models for digital technologies by gig economy platforms.