2026年第52期(总第1196期)

演讲主题：Can customer ratings be discrimination amplifiers? Evidence from a gig economy platform

主讲人：滕菲 新加坡国立大学助理教授

主持人：关旭 教授、供应链管理与系统工程系主任

活动时间：2026年06月26日（周五）15:30-17:00

活动地址：管院大楼107教室

主讲人简介：

滕菲是新加坡国立大学商学院市场营销系助理教授。她在耶鲁大学取得量化市场营销博士学位，在约翰霍普金斯大学取得经济学和应用数学学士学位。她近期的研究重点是平台经济以及销售与组织设计。她的研究成果发表于《Management Science》。

活动简介：

This paper investigates whether rating systems generate discriminatory spillovers and act as “discrimination amplifiers.” When platforms display aggregated customer ratings, these “quality metrics” also serve as anchors for future evaluations. Because they embed ratings from biased customers, displayed averages memorialize past discrimination, transmitting it to otherwise unbiased customers and amplifying bias among discriminatory ones. We formalize this mechanism using a stylized analytical model and test it with data from an online labor platform. Allowing for unobserved heterogeneity, we identify three customer segments: a neutral segment, and two biased segments, one that cancels more minority-accepted jobs and another that both cancels more and rates minorities lower. All segments are impacted strongly by displayed ratings. Customer discrimination generates a rating gap of 36.1% and an earnings gap of 5.2% between minority and majority workers. Notably, the unbiased segment produces discriminatory outcomes through spillovers. Adjusting displayed ratings reduces the gaps by mitigating the spillovers to the unbiased segment and amplification of the biased segment, but aggregate rating and earnings disparities persist because biased segments constitute a large share of the market.