自治
抗性(生态学)
工作(物理)
透明度(行为)
托换
类型学
灵活性(工程)
知识管理
劳动力
公司治理
业务
公共关系
计算机科学
互联网隐私
社会学
工程类
计算机安全
政治学
管理
经济
机械工程
生态学
土木工程
人类学
法学
生物
财务
作者
Krishnan Vasudevan,Ngai Keung Chan
标识
DOI:10.1177/14614448221079028
摘要
In 2018, Uber released an overhauled mobile application for its independent contractor workforce, who had become increasingly dissatisfied by the lack of autonomy, transparency, and flexibility while working on the platform. Based on the gamification of work, the application linked individualized rewards with Uber’s need to maintain a frictionless marketplace. However, as recent studies of gig economy have revealed, workers resist gamified algorithmic management by developing work games. Our findings, based upon analysis of driver accounts of using Uber’s application, presents a typology of player modes and work games that drivers play. We identified two distinctive player modes, grinding and oppositional play, which, respectively, illustrate how drivers consent and resist gamification. We also describe several work games that Uber drivers play in resistance to Uber’s gamification. This study contributes to the understanding of how the (re)design of worker-facing apps shape the power dynamics underpinning platform-initiated algorithmic governance and worker-initiated games.
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