Service Quality on Online Platforms: Empirical Evidence about Driving Quality at Uber
Social Science Research Network(2021)
摘要
Online marketplaces have adopted new mechanisms for quality control that can accommodate a flexible pool of providers, with unclear effects on overall service quality. We focus on ride-hailing: pre-screening, which prevailed in taxi markets, has been diminished in favor of automated quality measurement, incentives, and nudges. Using telemetry data, an objective measure of quality, we show that UberX drivers perform better than UberTaxi drivers. We then explore whether the difference is driven by incentives, nudges, and information. Drivers respond to user preferences and to nudges, such as notifications due to low ratings. Informing drivers about their past behavior improves quality, especially for low-performing drivers.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要